Methode voorscreening

Beoordeeld: 08-07-2024

Uitgangsvraag

Welke van de volgende methoden van voorscreening te weten flowcytometrie, microscopie (urinesediment en/of grampreparaat) of urinesticks, heeft een hoge voorspellende waarde en kan in het microbiologisch laboratorium of klinisch chemisch laboratorium worden gebruikt om een urineweginfectie uit te sluiten?

Aanbeveling

Gebruik een methode van voorscreening om alleen urines met een hoge kans op relevante groei voor kweek te selecteren.

Om een urineweginfectie uit te sluiten kunnen urinesticks (conform de NHG-standaard urineweginfecties) of flowcytometrie (na lokale validatie) worden gebruikt, tenzij deze technieken op het laboratorium niet beschikbaar zijn of gebruik hiervan tot vertraging in de uitslagen leidt.

Indien bij het laboratorium bekend is dat een aanvrager zelf voorscreent is het niet nodig om deze voorscreening binnen het laboratorium te herhalen.

Het gebruik van sediment (microscopie) als methode van voorscreening wordt gelet op de lage diagnostische waarde niet aanbevolen om een urineweginfectie uit te sluiten.

Er bestaan indicaties om hiervan af te wijken in specifieke situaties, zoals persisterend hoge verdenking op uwi ondanks negatieve voorscreening.

Overwegingen

Voor- en nadelen van de interventie en de kwaliteit van het bewijs

Voor deze module zijn literatuuranalyses verricht om de diagnostische waarde van verschillende methoden van voorscreening in het microbiologisch laboratorium te bepalen, waaronder flowcytometrie, microscopie (urinesediment en/of grampreparaat) en urinesticks. Sensitiviteit en de negatief voorspellende waarde ten opzichte van urinekweek als referentie zijn benoemd als cruciale diagnostische uitkomstmaten. Deze uitkomstmaten zijn proxy’s voor de uitkomstmaat waar men idealiter in geïnteresseerd is, de klinische uitkomst voor de patiënt.

Met betrekking tot flowcytometrie als voorscreenings methode om de aanwezigheid van bacteriën in urine te bepalen werd in de systematische literatuuranalyse geconcludeerd dat de sensitiviteit (89,50%-95,70%) van flowcytometrie matig tot hoog was. De NPV was echter hoog (94,5%-100%). Dit betekent dat er een kleine kans bestaat op fout-negatieve bevindingen. De specificiteit (39,20%-91,89%) en PPV (40,00%-86,15%) worden in de verschillende studies laag tot hoog ingeschat. Concluderend lijkt flowcytometrie beter in staat om urineweginfecties uit te sluiten dan aan te tonen.

De GRADE-beoordeling is laag voor het gebruik van een flowcytometrie als voorscreenings methode om een urineweginfectie uit te sluiten. Dit houdt in dat er met lage zekerheid gezegd kan worden dat de daadwerkelijke sensitiviteit en de negatief voorspellende waarde overeenkomt met de waarden gevonden in de studies.

Met betrekking tot microscopie als voorscreenings methode werd in de systematische literatuuranalyse geconcludeerd dat de sensitiviteit (47%-97%) en de NPV (41%-97%) van microscopie laag tot hoog waren. Dit betekent dat er in sommige gevallen een reële kans bestaat op fout-negatieve bevindingen. De specificiteit (27%-100%) en PPV (55%-100%) worden in de verschillende studies laag tot hoog ingeschat. Concluderend lijkt microscopie beperkt in staat om urineweginfecties uit te sluiten dan wel aan te tonen.

De GRADE-beoordeling is laag voor het gebruik van een microscopie als voorscreeningsmethode om een urineweginfectie uit te sluiten. Dit houdt in dat er met lage zekerheid gezegd kan worden dat de daadwerkelijke sensitiviteit en de negatief voorspellende waarde overeenkomt met de waarden gevonden in de studies.

Flowcytometrie

Het gebruik van flowcytometrie als voorscreeningsmethode om de aanwezigheid van bacteriën in urine te bepalen is alleen beschikbaar in laboratoria. Wanneer laboratoria deze voorscreening inzetten kan dit door een hoge NPV (lokaal te bepalen) goed gebruikt worden om een urineweginfectie uit te sluiten waardoor de urine niet verder op kweek hoeft te worden gezet. Aanvullend op de bepaling van de aanwezigheid van bacteriën kan bij flowcytometrie ook een bepaling van het aantal leucocyten worden uitgevoerd om de kwaliteit van het urinemonster te beoordelen. Russcher (2016) heeft een prospectieve studie uitgevoerd met als doel om negatieve kweken te voorspellen met behulp van een screeningsalgoritme op basis van flowcytometrie. Daarnaast is het gebruik van flowcytometrie vergeleken met gramkleuring. De auteurs hebben middels flowcytometrie 1442 urinemonsters gescreend die waren ingediend voor bacteriële kweek van deze monsters had 357 (24,8%) een positief kweekresultaat. Opvallend is dat in deze studie niet het kiemgetal van de microbiologische kweek, maar de Q score (verhouding leucocyten en eptiheelcellen) als gouden standaard is gebruikt, wat afwijkt van van de geincludeerde studies in de systematische literatuursamenvatting. De afwezigheid van micro-organismen werd geidentificeerd als de sterkste voorspeller voor een negatieve kweek, met een sensitiviteit van 90,5% (323/357). Het algoritme werd verder verbeterd door logistieke regressie uit te voeren op leukocytenaantallen, wat een drempelwaarde van 65 leukocyten/μl opleverde om de gewenste sensitiviteit van >95% (95,2%; 95% betrouwbaarheidsinterval [BI], 92,5 tot 97,0) en een negatieve voorspellende waarde van 97,3% (95% BI, 95,7 tot 98,3). De overeenkomst tussen monsterkwaliteit op basis van Gram-kleuring en flowcytometrie was slechts 72%, wat waarschijnlijk het gevolg was van het interbeoordelaarseffect bij de beoordeling van de Gram-kleuring (en daarmee dus ook de Q score). Ook andere studies zijn niet eenduidig over de toegevoegde waarde van het gebruik van het gebruik van flowcytometrie voor de bepaling van leucocyten en epitheelcellen om de monsterkwaliteit te bepalen (Garcia-Coca, 2016; Maher, 2020; Mohr, 2016). Er zijn meer studies noodzakelijk om te vast te stellen wat de toegevoegde waarde is van bepaling van van het aantal leucocyten als aanvullende parameter te gebruiken. Het leucocytengetal in urine kan niet gebruikt worden als aanvullende parameter in geval van leucopenie.

Microscopie: urinesediment

Microscopie is een eenvoudige manier om urine te beoordelen. Het is daarentegen wel arbeidsintensief en minder geschikt voor grote aantallen. Het kan laagdrempelig worden ingezet, maar vereist wel getrainde beoordelaars en juist gebruikte apparatuur. De sensitiviteit en specificiteit zijn matig. Microscopie lijkt daardoor beperkte waarde te hebben als voorscreening, maar het is wel nuttig voor de beoordeling van cellen (zie module ‘uitwerken urinekweek’). Het leucocytengetal in urine kan niet gebruikt worden als aanvullende parameter in geval van leucopenie

Urinesticks

De NHG-standaard urineweginfecties beschrijft richtlijnen voor diagnostiek bij verdenking op een urineweginfectie op basis van anamnese en zo nodig lichamelijk onderzoek. Het stroomschema begint met het uitvoeren van een urinestick. Daarbij wordt gekeken naar de resultaten van de testvelden voor nitriet en leukocyten. Een urinesticktest is beter in staat om de kans op aanwezigheid van een urineweginfectie in te schatten dan op basis van anamnese en lichamelijk onderzoek alleen. Het NHG heeft in de recente NHG-standaard urineweginfecties uitgebreide systematische searches uitgevoerd naar de meerwaarde van urinesticks t.o.v. een urinekweek voor het diagnosticeren van urineweginfecties bij gezonde (niet zwangere) vrouwen en kinderen. Daarnaast is uitgezocht wat de meerwaarde is voor het gebruik van urinesticks op het voorspellen van een verhoogd risico op een gecompliceerd beloop. Hierbij is alle literatuur gescreend tot en met januari 2018. Voor deze module is eveneens breed gezocht op de diagnostische waarde van een urinestick t.o.v. urinekweek voor het diagnosticeren van urineweginfecties. Hierbij zijn 5 studies gevonden die sinds het verschijnen van de NHG-standaard zijn gepubliceerd (zie Tabel 4). Onderstaande studies leiden echter niet tot andere inzichten of hogere dan wel lagere kwaliteit van het bewijs zoals in de NHG-standaard urineweginfecties is gerapporteerd. Omdat urinesticks in principe alleen bij de huisarts worden gebruikt en recente literatuur niet tot andere inzichten leidt wordt voor het gebruik van een urinestick verwezen naar de NHG-standaard urineweginfecties.

Table 4. Samenvattingen van studies die rapporteren over de diagnostische waarde van urinesticks in vergelijking met urinekweek

Studie	Populatie	Prevalentie	Sensitiviteit	Specificiteit	NPV	PPV
Bellazeg (2019)	Volwassen mannen en vrouwen verdacht van een urineweginfectie	139/436 (39%)	95%	87%	92%	85%
Chernaya (2021)	Volwassen mannen en vrouwen die de spoedeisendehulp bezochten.	177/500 (35,4%)	NR*	NR*	81%	90%
Dadzie (2019)	Volwassen mannen en vrouwen verdacht van een urineweginfectie	65/429 (15,2%)	72%	73%	32%	94%
Mohana (2021)	Volwassen mannen en vrouwen verdacht van een urineweginfectie	250/350 (71,4%)	94%	30%	NR*	NR*

* niet gerapporteerd

Het is goed om te benoemen dat de huisarts een voorscreening kan gebruiken middels een urinestick, maar dat deze uitslagen in het laboratorium niet worden gebruikt. Het laboratorium kan daarna nogmaals overwegen een voorscreening uit te voeren. Er is geen literatuur gevonden die iets beschrijft over deze in de praktijk voorkomende situatie. Het is mogelijk dat hierdoor een matig tot grote selectiebias ontstaat als in de huisartsenpraktijk reeds een voorscreening met een urinestick is uitgevoerd. Dat betekent dat de meerwaarde van de voorscreening op het laboratorium middels flowcytometrie of microscopie minder wordt. De voorafkans dat een ingestuurde urine werkelijk zal leiden tot een terecht positief kweekresultaat is dan namelijk hoger dan die in de huisartsenpraktijk. De commissie vindt geen bewijs dat in de situatie waarbij het van een aanvrager bekend is dat hij/zij voorscreeningen verricht, het nuttig is om bij monsters van deze aanvrager nogmaals een voorscreening te doen. Het specifieke voorscreeningsresultaat van het betreffende monster hoeft daarbij niet op het laboratorium bekend te zijn.

Waarden en voorkeuren van patiënten (en evt. hun verzorgers)

Patiënten willen graag een duidelijke uitspraak over of zij wel of geen urineweginfectie hebben en in geval van een urineweginfectie met welke antibiotica deze dient te worden behandeld. Patiënten hebben naar verwachting geen specifieke voorkeur of deze diagnostiek met of zonder voorscreening plaats zou moeten vinden.

Kosten (middelenbeslag)

Er is niet specifiek gezocht op kosten. Het is echter aannemelijk dat wanneer geen gebruik gemaakt wordt van een voorscreening dit betekent dat alle aanvragen op kweek gezet worden. Kostentechnisch is dit niet de optimale werkwijze en kweken van alle monsters is daarnaast erg arbeidsintensief. Door op het laboratorium gebruik te maken van flowcytometrie kan een groot deel van de aanvragen zonder kweek afgehandeld worden. De verwachting is dat de kosten van het gebruik van flowcytometrie opwegen tegen het uitvoeren van extra kweken.

Aanvaardbaarheid, haalbaarheid en implementatie

De aanvaardbaarheid en haalbaarheid van de verschillende methodes van voorscreening zijn niet kwalitatief of kwantitatief onderzocht. Er worden geen problemen voorzien met de aanvaardbaarheid van deze module, aangezien de aanbevelingen niet afwijken van de huidige praktijk.

Rationale van de aanbeveling

Flowcytometrie is alleen beschikbaar op laboratoria, maar kan door de hoge NPV goed gebruikt worden om een urineweginfectie uit te sluiten en voorkomt daarmee dat een urine onnodig op kweek wordt gezet. Microscopie is een eenvoudige manier om urine te beoordelen, maar heeft gelet op de matige diagnostische waarde slechts beperkte waarde als methode voor voorscreening.

Onderbouwing

Achtergrond

Er bestaan verschillende manieren om vast te stellen of een urineweginfectie aanwezig is, dan wel om deze uit te sluiten is. Deze methoden zijn de urinestick (leukocyten en nitriet), microscopie voor beoordeling van het urinesediment (aanwezigheid van leukocyten en bacteriën) en flowcytometrie (tellen van leukocyten en bacteriën en eventueel epitheel). Op een laboratorium zijn alle mogelijkheden in principe beschikbaar. Het is op dit moment onvoldoende duidelijk welke methode de hoogst negatief voorspellende waarde heeft (en dus potentieel het best in staat is een urineweginfectie uit te sluiten). Voor deze module wordt uitgegaan van een voorscreening uitgevoerd op een laboratorium. Met de resultaten van deze voorscreening kan besloten worden welke urines verder onderzocht worden middels een conventionele kweek.

Conclusies / Summary of Findings

Low

GRADE

Flow cytometry

The sensitivity of flow cytometry to detect bacteria may be moderate to high (range 89,50% to 100,00%) for the screening of urinary tract infections in adults when compared to conventional culture as reference test.

Source: Shang, 2013; Fritzenwalker, 2022; Le, 2016; Martín-Guitiérrez, 2014, Stefanovic, 2017; Monsen, 2017; Boonen, 2013; de Boer, 2018; Tavenier, 2017; Moshaver, 2016.

Low

GRADE

The NPV of flow cytometry to detect bacteria may be high (range 94.50% to 100,00%) for the screening of urinary tract infections in adults when compared to conventional culture as reference test.

Source: Fritzenwalker, 2022; Le, 2016; Martín-Guitiérrez, 2014, Stefanovic, 2017; Monsen, 2017; Boonen, 2013; de Boer, 2018; Moshaver, 2016.

Low

GRADE

The specificity of flow cytometry to detect bacteria may be moderate to high (range 39.20% to 91.89%) for the screening of urinary tract infections in adults when compared to conventional culture as reference test.

Source: Shang, 2013; Fritzenwalker, 2022; Le, 2016; Martín-Guitiérrez, 2014, Stefanovic, 2017; Monsen, 2017; Boonen, 2013; de Boer, 2018; Tavenier, 2017; Moshaver, 2016.

Low

GRADE

The PPV of flow cytometry to detect bacteria may be moderate to high (range 40,00% to 86.15%) for the screening of urinary tract infections in adults when compared to conventional culture as reference test.

Source: Fritzenwalker, 2022; Le, 2016; Martín-Guitiérrez, 2014, Stefanovic, 2017; Monsen, 2017; Boonen, 2013; de Boer, 2018;

Low

GRADE

Microscopy

The sensitivity of microscopy may be moderate to high (range 47% to 97%) for the screening of urinary tract infections in adults when compared to conventional culture as reference test.

Source: Beyer, 2019

Low

GRADE

The NPV of microscopy may be moderate to high (range 41% to 97%) for the screening of urinary tract infections in adults when compared to conventional culture as reference test.

Source: Beyer, 2019

Low

GRADE

The specificity of microscopy may be low to high (range 27% to 100%) for the screening of urinary tract infections in adults when compared to conventional culture as reference test.

Source: Beyer, 2019

Low

GRADE

The PPV of microscopy may be moderate to high (range 55% to 100%) for the screening of urinary tract infections in adults when compared to conventional culture as reference test.

Source: Beyer, 2019

Samenvatting literatuur

Description of studies

Flow cytometry

Shang (2013) conducted a systematic review and meta-analysis screening or diagnostic performance of flow cytometry for urinary tract infections (UTIs). Shang (2013) covers the literature until December 2012 and literature searches were conducted in Medline (using Pubmed as the search engine), EMBASE, and Web of Science. Shang (2013) included studies focusing on the screening or diagnostic performance of flow cytometry that reported both sensitivity and specificity and had a total samples size >40 patients with a number of UTI patients >10. Conference abstract, animal studies and letters to the editor were excluded. In total, 19 studies were included containing 22,305 samples. All studies used urine culture as the reference standards, but cutoffs were different (see Table 1). Assessment of article quality was assessed using The Quality Assessment for Studies of Diagnostic Accuracy (QUADAS) Tool. Outcomes were sensitivity and specificity for bacteria and white blood cells.

Fritzenwanker (2022) conducted a prospective study evaluating urine flow cytometry as a tool to screen urine samples of urological patients for bacteriuria compared to urine culture. Included were consecutive urine samples from patients of the urological department of a university hospital. Samples were analysed using the UF-1000i flow cytometer and culture for bacterial growth was performed. Species identification was determined by MALDI-TOF analysis and supplemented using biochemical methods following MiQ standards. Outcomes were sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for urine flow cytometry compared to urine culture.

Le (2016) conducted a prospective study systematically exploring the performance of UF-1000i as a method for diagnosing bacterial or fungal UTIs. Included were 1016 urine samples from inpatients with suspected urinary infections. Samples were analysed using the UF-1000i flow cytometer and cultured. Culture was conducted with a 1-mL calibrated loop onto Columbia blood agar plates and with a 10-mL calibrated loop onto selective eosin-methylene

blue plates. All of the plates were incubated at 37 °C for 18-24 h, and the numbers of colonies were counted and multiplied by 10³ for the Columbia blood agar plates and 10² for the selective eosin-methylene blue plates to determine the number of organisms per millilitre. The culture was considered positive if bacterial counts reached 10⁴ CFU/mL or yeast counts were more than 10³ CFU/mL. The VITKE2-Compact automated system was applied for bacterial identification. Samples showing the growth of 3 or more types of colonies without a dominant species were classified as mixed flora; these samples were considered culture positive but contaminated and were not subjected to the identification procedure. Outcomes were sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for urine flow cytometry compared to urine culture.

Martín-Gutiérrez (2015) conducted a prospective study evaluating and optimizing the use of the Sysmex UF-1000i as a screening method for urine samples obtained from an in community-dwelling elderly population older than 65 year. Included were 346 randomly selected urine samples from elderly outpatients (≥65 years old), Samples were analysed using the UF-1000i flow cytometer and cultured. Ten microlitres of the urine specimen were quantitatively cultured onto Brilliance UTI Clarity Agar plates. All plates were aerobically incubated for 18–24 h at 37 °C, and the results were expressed as the number of colony-forming units (CFUs) per millilitre. A threshold of ≥10⁵ CFUs/mL for women and ≥10⁴ CFUs/mL for men was established for positive cultures. The presence of two or more different isolates as well as the growth of one or more non-pathogens was defined as contamination of the specimen. Identification of the isolates was performed by conventional biochemical tests (biochemical testing, pigment production, growth, and colony characteristics) and MicroScan WalkAway® plus System. When the identification was uncertain, it was confirmed by Bruker Biotyper MALDI-TOF MS system. Outcomes were sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for urine flow cytometry compared to urine culture.

Monsen (2017) conducted a prospective study assessing flow cytometry to identify and rule out culture negative urine specimens in patients with suspected UTI prior to culture. Included were consecutive samples from in- and outpatients. In total 1312 samples were included. All Samples were analysed using the UF-1000i flow cytometer and cultured. Gram-negative and Gram-positive uropathogens were identified by Brilliance™ UTI agar. Isolates were identified in specimens with presence of ≥10⁶ colony forming units/L (CFU/L) and those with mixed flora

(with both gram negative and gram positive bacteria) with a dominating pathogen (i.e. bacterial count at least 10 times higher than any other species). Significant bacteriuria was defined in accordance with European guidelines (at ≥10⁶ CFU/L of an uropathogen with acute uncomplicated cystitis). Outcomes were sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for urine flow cytometry compared to urine culture.

Stefanovic (2017) conducted a prospective study determine whether flow cytometry as a screening method can predict which urine samples will subsequently grow in culture. Included were specimens submitted for urine culture over the period of 22 July 2015 to 17 February 2016. A total of 15 046 urine samples were requested for urine culture during the study period. Samples were analysed using the UF-1000i flow cytometer and cultured. Urine culture was performed by inoculating urine onto a 5% sheep’s blood agar plate and a MacConkey plate using a 0.01 ml quantitative inoculation loop. After overnight incubation at 35 °C in ambient air, the colony count (cfu) was measured semi-quantitatively. Pinpoint growth plates were incubated for 48 h. Colony identification was performed using MALDI-TOF Biotyper

3.1 Outcomes were sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for urine flow cytometry compared to urine culture.

Boonen (2013) conducted a prospective study evaluate the performance of the Sysmex UF500i and to define a cut-off value to be used in routine practice in the urology outpatient clinic of our hospital. Included were 281 urine samples from a general population of adult outpatients visiting the urology department. Samples were analysed using the UF-500i flow cytometer and cultured. Culture was performed by plating 10 µL was plated on a Brilliance UTI Clarity Agar and a blood agar plate containing 5 µg/ml colistin and 2 µg/ml aztreonam. Both plates were examined for growth after 18–24 h of incubation at 35 °C. Grown colonies were identified by color or VITEK2® if necessary. A culture result of >10⁴ colony forming units (CFU) per mL urine was considered positive, independent of the species and number of species of bacteria found. Outcomes were sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for urine flow cytometry compared to urine culture.

de Boer (2017) conducted a prospective cohort study investigating whether flow cytometry could be a fast and accurate diagnostic method for counting the number of bacteria in urine compared to culture as a gold standard. Included were consecutive patients older than 18 years who were admitted to the ED for internal medicine and had fever 38.0 °C (at admission or at home <24 h) or who had at least two SIRS-criteria (systematic inflammatory response syndrome) over a period of 10 weeks. In total, 165 consecutive samples were included. All urine samples were analyzed for bacteria by the Accuri C6 in the clinical chemical laboratory. Culture was performed by placing 10 µl urine was placed on two different Agars (a chromogenic agar and a sheep blood agar for urine cultures). Growth was determined after overnight incubation at 37 °C, by semi quantitatively counting of CFU/mL per isolated organism. A specimen that grew >10⁵ CFU/mL of one or two uropathogens was defined as a positive urine culture. Identification and determination of antibiotic susceptibility of relevant bacteria was performed with the Vitek-II. Outcomes were sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for urine flow cytometry compared to urine culture.

Tavenier (2018) conducted a prospective cohort study investigating the reliability of counting viable bacteria by flow cytometry to predict the outcome of urinary culture. Included were 135 consecutive adult patients admitted to the ED with a temperature 38.0 °C in the last 24 h measured at home or at the emergency department, or 2 SIRS (systemic inflammatory response syndrome)-criteria and suspected infection. SIRS was defined by the presence of at least 2 of the following symptoms: body temperature >38.5 °C, heart rate- >90 beats/minute, respiratory rate >20 breaths/minute, an arterial partial pressure or carbon dioxide <4.3 kPa or white blood cell count >12 x 10⁹ cells/L. All urine samples were analyzed for bacteria by the Accuri C6 in the clinical chemical laboratory. Culture was performed by placing 10 µl urine was placed on two different Agars (a chromogenic agar and a sheep blood agar for urine cultures). Growth was determined after overnight incubation at 37 °C, by semi quantitatively counting of CFU/mL per isolated organism. A specimen that grew >10⁵ CFU/mL of one or two uropathogens was defined as a positive urine culture. Identification and determination of antibiotic susceptibility of relevant bacteria was performed with the Vitek-II. Outcomes were sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for urine flow cytometry compared to urine culture.

Moshaver (2016) conducted a prospective cohort study investigating the reliability flow cytometry to predict the outcome of urinary culture. Included were randomly selected urine samples from patients with suspected UTI from general practitioners, outpatient and clinical departments. In total, 209 patients were included. All urine samples were analyzed for bacteria by the Accuri C6 in the clinical chemical laboratory. Culture was performed by placing 10 µl urine was placed on two different Agars (a chromogenic agar and a sheep blood agar for urine cultures). Growth was determined after overnight incubation at 37 °C, by semi quantitatively counting of CFU/mL per isolated organism. A specimen that grew >10⁵ CFU/mL of one or two uropathogens was defined as a positive urine culture. Identification and determination of antibiotic susceptibility of relevant bacteria was performed with the Vitek-II. Outcomes were sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for urine flow cytometry compared to urine culture.

As shown in Table 1, the reference methods differed between studies. There were also differences observed in the prevalence of positive cases (see Table 1), this affects the comparability of NPV and PPV between studies.

Table 1. Study characteristics of included flow cytometry studies

Study (year)	Sample size	Reference test	UTI (with/without/ contaminated samples)
Pieretti (2010)	703	10⁴ CFU/ml	186/486/31
Broeren (2011)	1577	10⁴CFU/ml	619/785/173
Wang (2010)	313	10⁴CFU/ml	NA
Kim (2007)	330	10³ CFU/ml	66/259/5
Van der Zwet (2010)	358	10⁴CFU/ml	93/265/NA
De Rosa (2010)	1349	10⁴CFU/ml	346/1003/NA
Lunn (2009)	186	10⁴CFU/ml	19/167/NA
Koken (2002)	260	10⁴CFU/ml	48/212/NA
Kadkhoda (2011)	2496	10⁴CFU/ml	653/935/672
Manoni (2009)	1463	10⁵ CFU/ml	546/917/NA
Grosso (2008)	1047	10⁵CFU/ml	247/800/NA
Brilha (2010)	5356	10³CFU/ml	706/4650/NA
Manini (2002)	2010	10⁵CFU/ml	529/1481/NA
Evans (2006)	1005	10⁴CFU/ml	306/699/NA
Marschal (2012)	5513	10² CFU/ml	163/223/127
Gutierrez-Fernandez	1198	10⁵CFU/ml	228/970/NA
Dos Santos (2007)	675	10³CFU/ml	108/550/17
Krongvorakul (2012)	372	10⁵CFU/ml	118/254/NA
Jolkkonen (2010)	1094	10⁴CFU/ml	184/910/NA
Fritzenwalker (2022)	662	10⁵CFU/ml	NA/NA/NA
Le (2016)	1016	10⁴CFU/ml	441/604/NA
Martín-Guitiérrez (2015)	346	10⁴CFU/ml for women and 10⁵ CFU/ml for men	346/135/214/19
Stefanovic (2017)	15046	10⁴CFU/ml	5359/9549/NA
Monsen (2017)	1312	10⁶ CFU/ml	472/741/NA
Boonen (2013)	281	10⁴CFU/ml	75/206/NA
de Boer (2018)	165	10⁴CFU/ml	38/127/NA
Tavenier (2017)	135	10⁴CFU/ml	19/116/NA
Moshaver (2016)	209	10⁵CFU/ml	79/129/NA

NA: Not available; CFU: colony forming units. UTI: urinary tract infection

Microscopie: urinesediment

Beyer (2019) conducted a systematic review determining the clinical validity, i.e. sensitivity and specificity, of microscopy performed in general practice on urine samples from patients with symptoms of UTI, using urine culture as a reference standard. Beyer (2019) covers the literature until August 2017 and searches were conducted in Medline. Beyer (2019) included diagnostic studies, in which the accuracy/validity of urine microscopy on urine from patients with symptoms of urinary tract infections performed in general practice, outpatient clinics or a similar setting by the GP or general practice staff with urine culture at the microbiological department as reference standard. All studies used microscopy but differed in which technique of microscopy was used, and in what cut-offs they used for measuring infection. In total, 8 studies were included containing 4582 patients (see table 2). Assessment of article quality was assessed using The Quality Assessment for Studies of Diagnostic Accuracy (QUADAS) Tool. Outcomes were pooled sensitivity, specificity, PPV, and NPV for microscopy compared to urine culture as a reference.

Table 2. Characteristics of included microscopy studies

Study (year)	Patients	Magnification	Staining	Measure of infection
Dornfest (1979)	109	x1000	No	>35 organisms in total over 5 fields
Wilks (1979)	100	x110 x490	No	1 white blood cell per LPF 1 motile bacillus per HPF
Ditchburn (1990)	237	94.9	NA	>18 leukocytes per LPF
Balslev (1980)	1663	85.7	NA	Pyuria or bacteria
Hallander (1986)	776	74.0 60.0	NA	Moderate or abundant bacterial finding per field >20 white blood cells per field
Winkens (1995)	1311	91.9 47.0	Yes	>5 leukocytes >20 bacteria
Ferry (1990)	201	97.0	Yes	>5 leukocytes per HPF or 100-300 bacteria per HPF
Chalmers (2015)	108	57.1	Yes	>10 white blood cells per HPF and >1 bacteria per HPF

LPF: Low power field; HPF: High power field; NA: Not avaliable.

Results

Flow cytometry

In total, 28 studies reported on the diagnostic value of flow cytometry. Nineteen of these studies were published after the systematic review by Shang (2013) and were used to update the meta-analysis.

Shang (2013) included 19 studies that reported on the diagnostic value of flow cytometry compared to urine culture. For detecting bacteria, the overall pooled sensitivity was 92% (95% CI 91 to 93%, I²=95.6%), specificity was 60% (95% CI 59% to 61%, I²=99.7%). However, there was significant heterogeneity among included studies.

Fritzenwalker (2022) found that, using a cut-off of bacteria >142, sensitivity of flow cytometry was 93.1% compared to conventional culture as reference standard. Specificity for flow cytometry was 91.9% and PPV and NPV were 52.4% and 99.28% respectively.

Le (2016) found that, using a cut-off of bacteria >38.7, sensitivity of flow cytometry was a sensitivity of flow cytometry was 90.5% compared to conventional culture as reference standard. Specificity for flow cytometry was 67.4% and PPV and NPV were 51.7% and 94.5% respectively.

Martin-Gutiérrez (2015) found that, using a cut-off of bacteria >200, sensitivity of flow cytometry was 99.1% compared to conventional culture as reference standard. Specificity for flow cytometry was 91.6% and PPV and NPV were 86.2% and 99.5% respectively.

Monsen (2017) found that screening with FCA-LDA at 95% sensitivity identified 42% (552/1312) as culture negative specimens when UTI was defined according to European guidelines. Overall, this resulted in a sensitivity of flow cytometry of 95% compared to conventional culture as reference standard. Specificity for flow cytometry was 65% and PPV and NPV were 63% and 95% respectively.

Stefanovic (2017) found that, using a cut-off of bacteria >20, sensitivity of flow cytometry was 96.0% (95% CI 95.7 to 96.3%) compared to conventional culture as reference standard. Specificity for flow cytometry was 39.2% (95% CI 38.4 to 40.0%) and PPV and NPV were 47.0% (95% CI 46.2 to 47.8%) and 94.5% (95% CI 94.1 to 94.9%) respectively.

Boonen (2013) found that, using a cut-off of bacteria >60, sensitivity of flow cytometry was 100.0% compared to conventional culture as reference standard. Specificity for flow cytometry was 62% and PPV and NPV were 40% and 100% respectively.

De Boer (2017) found that, using a cut-off of bacteria >10⁶, sensitivity of flow cytometry was 100.0 compared to conventional culture as reference standard. Specificity for flow cytometry was 64.7% and PPV and NPV were 51.4% and 100.0% respectively.

Tavenier (2018) found that, using a cut-off of bacteria >10⁶, sensitivity of flow cytometry was 89.5% (17/19) compared to conventional culture as reference standard. Specificity for flow cytometry was 83.6% (97/116).

Gehringer (2021) found that, using a cut-off of bacteria >106, sensitivity of flow cytometry of 99% compared to conventional culture as reference standard. Specificity for flow cytometry was 68% and PPV and NPV were 59% and 99% respectively.

Microscopie: urinesediment

Beyer (2019) included 8 studies that reported on the diagnostic value of microscopy compared to urine culture. Table 3 provides an overview of sensitivity, specificity, PPV and NPV reported in each individual study.

Table 3. Accuracy summaries of included studies

Study (year)	Prevalence (%)	Specificity (%)	Sensitivity (%)	PPV (%)	NPV (%)
Dornfest (1979)	28	93.6	93.5	85	97
Wilks (1979)	68 33	100 67.2	48.5 81.8	100 55	48 88
Ditchburn (1990)	41	76.3	94.9	74	95
Balslev (1980)	48	73.7	85.7	75	85
Hallander (1986)	17 17	97.0 93.0	74.0 60.0	87 65	95 92
Winkens (1995)	69	27.0 81.0	91.9 47.0	73 85	58 41
Ferry (1990)	82	38.9	97.0	88	74
Chalmers (2015)	41	88.9	57.1	79	74

Level of evidence of the literature

Diagnostic performance (sensitivity, specificity, PPV and NPV) of flow cytometry

The level of evidence regarding the outcome measures sensitivity, specificity, NPV and PPV for flow cytometry was downgraded with one level because of heterogeneity (execution of studies, differences in reference cut-off) and one level because of risk of bias (unclear if reference without knowledge of the index test and vice versa). The level of evidence is graded as ‘low’.

Diagnostic performance (sensitivity, specificity, PPV and NPV) of microscopy

Zoeken en selecteren

A systematic review of the literature was performed to answer the following question:

What is the diagnostic value of each method of pre-screening versus urine culture to screen patients suspected of having a urinary tract infection?

P:	Urine of adults with suspected urinary tract infection
I:	Flow cytometry, microscopy (sediment), urine stick
C:	Microbiological culture
O:	Diagnostic performance (sensitivity, specificity, Negative Predictive Value (NPV), Positive Predictive Value (PPV))

Relevant outcome measures

The guideline development group considered sensitivity and NPV as critical outcomes measure for decision making; and specificity, PPV as important outcome measures for decision making

A priori, the working group did not define the outcome measures listed above but used the definitions used in the studies.

Search and select (Methods)

The databases Medline (via OVID) and Embase (via Embase.com) were searched with relevant search terms. For flow from 1 January 2000 until 20 December 2022. For urine sticks and sediment the ‘NHG-standaard urineweginfecties’ was used as the basis covering literature until 2018 and observational studies on urine sticks and sediment from 2019 onwards were included. At first, we selected for systematic reviews and after this we performed an additional selection to supplement the systematic review(s) with RCT’s or observational studies that were published after the search date of the included systematic review(s). The detailed search strategy is depicted under the tab Methods. The systematic literature search resulted in 708 hits. In total, 103 studies were selected based on the following criteria: systematic reviews, randomized controlled trials, or comparative observational studies answering the research question. Studies were initially selected based on title and abstract screening. After reading the full text 93 studies were excluded (see the table with reasons for exclusion under the tab Methods), and ten studies were included.

Results

Ten studies were included in the analysis of the literature. Important study characteristics and results are summarized in the evidence tables. The assessment of the risk of bias is summarized in the risk of bias tables. The summary of literature, results and evidence tables are included in 'Samenvatting literatuur'.

Referenties

Beyer AK, Currea GCC, Holm A. Validity of microscopy for diagnosing urinary tract infection in general practice - a systematic review. Scand J Prim Health Care. 2019 Sep;37(3):373-379. doi: 10.1080/02813432.2019.1639935. Epub 2019 Jul 14. PMID: 31304845; PMCID: PMC6713105.
Boonen KJ, Koldewijn EL, Arents NL, Raaymakers PA, Scharnhorst V. Urine flow cytometry as a primary screening method to exclude urinary tract infections. World J Urol. 2013 Jun;31(3):547-51. doi: 10.1007/s00345-012-0883-4. Epub 2012 May 16. PMID: 22588552.
de Boer FJ, Gieteling E, van Egmond-Kreileman H, Moshaver B, van der Leur SJ, Stegeman CA, Groeneveld PH. Accurate and fast urinalysis in febrile patients by flow cytometry. Infect Dis (Lond). 2017 May;49(5):380-387. doi: 10.1080/23744235.2016.1274048. Epub 2017 Jan 11. PMID: 28077007.
García-Coca M, Gadea I, Esteban J. Relationship between conventional culture and flow cytometry for the diagnosis of urinary tract infection. J Microbiol Methods. 2017 Jun;137:14-18. doi: 10.1016/j.mimet.2017.03.010. Epub 2017 Mar 19. PMID: 28330780.
Maher PJ, Jablonowski KD, Richardson LD. Squamous epithelial cell presence reduces accuracy of urinalysis for prediction of positive urine cultures. Am J Emerg Med. 2020 Jul;38(7):1384-1388. doi: 10.1016/j.ajem.2019.11.024. Epub 2019 Nov 28. PMID: 31843330.
Martín-Gutiérrez G, Porras-González A, Martín-Pérez C, Lepe JA, Aznar J. Evaluation and optimization of the Sysmex UF1000i system for the screening of urinary tract infection in primary health care elderly patients. Enferm Infecc Microbiol Clin. 2015 May;33(5):320-3. doi: 10.1016/j.eimc.2014.07.010. Epub 2014 Oct 18. PMID: 25444045.
Monsen T, Ryden P. A new concept and a comprehensive evaluation of SYSMEX UF-1000i flow cytometer to identify culture-negative urine specimens in patients with UTI. Eur J Clin Microbiol Infect Dis. 2017 Sep;36(9):1691-1703. doi: 10.1007/s10096-017-2964-1. Epub 2017 Apr 6. Erratum in: Eur J Clin Microbiol Infect Dis. 2017 Jul 15;: PMID: 28386705; PMCID: PMC5554267.
Mohr NM, Harland KK, Crabb V, Mutnick R, Baumgartner D, Spinosi S, Haarstad M, Ahmed A, Schweizer M, Faine B. Urinary Squamous Epithelial Cells Do Not Accurately Predict Urine Culture Contamination, but May Predict Urinalysis Performance in Predicting Bacteriuria. Acad Emerg Med. 2016 Mar;23(3):323-30. doi: 10.1111/acem.12894. Epub 2016 Feb 17. PMID: 26782662.
Moshaver B, de Boer F, van Egmond-Kreileman H, Kramer E, Stegeman C, Groeneveld P. Fast and accurate prediction of positive and negative urine cultures by flow cytometry. BMC Infect Dis. 2016 May 17;16:211. doi: 10.1186/s12879-016-1557-4. PMID: 27189024; PMCID: PMC4869392.
Le Z, Li F, Fei C, Ye A, Xie X, Zhang J. Performance of the Sysmex UF-1000i urine analyser in the rapid diagnosis of urinary tract infections in hospitalized patients. J Infect Chemother. 2016 Jun;22(6):377-82. doi: 10.1016/j.jiac.2016.02.009. Epub 2016 Mar 19. PMID: 27006323.
Russcher A, Kusters E, Wolterbeek R, Kuijper EJ, Cobbaert CM, van der Beek MT. Interlaboratory Collaboration for Optimized Screening for Urinary Tract Infection. J Clin Microbiol. 2016 Jan;54(1):93-8. doi: 10.1128/JCM.01943-15. Epub 2015 Oct 21. PMID: 26491183; PMCID: PMC4702725.
Shang YJ, Wang QQ, Zhang JR, Xu YL, Zhang WW, Chen Y, Gu ML, Hu ZD, Deng AM. Systematic review and meta-analysis of flow cytometry in urinary tract infection screening. Clin Chim Acta. 2013 Sep 23;424:90-5. doi: 10.1016/j.cca.2013.05.014. Epub 2013 May 28. PMID: 23721948.
Stefanovic A, Roscoe D, Ranasinghe R, Wong T, Bryce E, Porter C, Lim A, Grant J, Ng K, Pudek M. Performance assessment of urine flow cytometry (UFC) to screen urines to reflex to culture in immunocompetent and immunosuppressed hosts. J Med Microbiol. 2017 Sep;66(9):1308-1315. doi: 10.1099/jmm.0.000572. Epub 2017 Sep 4. PMID: 28869004.
Tavenier AH, de Boer FJ, Moshaver B, van der Leur SJCM, Stegeman CA, Groeneveld PHP. Flow cytometric analysis of viable bacteria in urine samples of febrile patients at the emergency department. Cytometry B Clin Cytom. 2018 Sep;94(5):689-695. doi: 10.1002/cyto.b.21548. Epub 2017 Aug 23. PMID: 28815948.

Evidence tabellen

Evidence table for diagnostic test accuracy studies

Study reference	Study characteristics	Patient characteristics	Index test (test of interest)	Reference test	Follow-up	Outcome measures and effect size	Comments
Fritzenwalker (2022)	Type of study: Observational study Setting and country: Hospital Germany Funding and conflicts of interest: Study was non-commercially funded but authors do report conflicts of interest and declared personal fees and advisor board attendance.	Inclusion criteria: consecutive urine samples from patients of the urological department of a university hospital Exclusion criteria: Non-reported N=662 Prevalence: Not reported Median age (SD): 58.25+17.21 years Sex: 75.2% M / 24.8% F	Describe index test: UF5000 flow cytometry Cut-off point(s): Bacteria > 142/µl	Describe reference test: Urine culture Cut-off point(s): CFU > 10⁵ was considered positive	Time between the index test and reference test: No time difference For how many participants were no complete outcome data available? All had complete outcome data available.	Outcome measures and effect size: Sensitivity: 93.1% Specificity 91.89% PPV 52.43% NPV 99.28%	The authors conclude that counting bacteria with UFC is an accurate and rapid method to determine significant bacteriuria in urological patients.
Le (2016)	Type of study: observational study Setting and country: Hospital, China Funding and conflicts of interest: Study was non-commercially funded and de authores reported to have no conflicts of interest	Inclusion criteria: consecutive urine samples from patients Exclusion criteria: Non-reported N=1016 Prevalence: 40.4% UTI	Describe index test: UF1000i flow cytometry Cut-off point(s): Bacteria > 38.7/µl	Describe reference test: Urine culture Cut-off point(s): CFU > 10⁴ was considered positive	Time between the index test and reference test: No time difference For how many participants were no complete outcome data available? All had complete outcome data available.	Outcome measures and effect size: Sensitivity: 90.5% Specificity 67.4% PPV 51,7% NPV 94.5%	The authors conclude that the BACT count determined with the UF-1000i analyser would be a reliable platform for ruling out bacterial UTIs in hospitalized patients with or without urinary catheters
Martín-Guitiérrez (2015)	Type of study: observational study Setting and country: Hospital, Spain Funding and conflicts of interest: Study was non-commercially funded and thee authors reported to have no conflicts of interest	Inclusion criteria: consecutive urine samples from patients Exclusion criteria: Non-reported N=346 Prevalence: 32.65% UTI Median age (SD): 76.70 ± 0.75 years Sex: 56% M / 43% F	Describe index test: UF1000i flow cytometry Cut-off point(s): Bacteria > 200/µl	Describe reference test: Urine culture Cut-off point(s): CFU > 10⁴ was considered positive	Time between the index test and reference test: No time difference For how many participants were no complete outcome data available? All had complete outcome data available.	Outcome measures and effect size: Sensitivity: 99.11% (95% CI 95.15-99.84) Specificity 91.59% (95% CI 87.09-94.61) PPV 86.15% (95% CI 79.17-91.06%) NPV 99.49% (95% CI 97.18-99.91)	The authors conclude that the stratification of age groups helps in selecting a more adjusted Sysmex UF1000i cut-off limit, leading to an improvement diagnostic performance for ruling out UTI.
Stefanovic (2017)	Type of study: observational study Setting and country: Hospital, Canada Funding and conflicts of interest: No specific funding was received, and the authors reported to have no conflicts of interest	Inclusion criteria: Consecutive urine samples from patients Exclusion criteria: Non-reported N=15046 Prevalence: 35.9% UTI Median age (SD): 62.29 ± 20.4 years Sex: 46.6% M / 53.3% F	Describe index test: UF1000i flow cytometry Cut-off point(s): Bacteria > 20/µl	Describe reference test: Urine culture Cut-off point(s): CFU > 10⁴ was considered positive	Time between the index test and reference test: No time difference For how many participants were no complete outcome data available? All had complete outcome data available.	Outcome measures and effect size: Sensitivity: 96.0% (95% CI 95.7–96.3) Specificity 39.2% (95% CI 38.4–40.0) PPV 47.0% (95% CI 46.2–47.8) NPV 94.5% (95% CI 94.1–94.9)	The authors conclude that flow cytometry is a rapid and sensitive method to screen out urine samples that will subsequently be negative and to reflex urines to culture that will subsequently grow
Boonen (2013)	Type of study: observational study Setting and country: Hospital, Netherlands Funding and conflicts of interest: None reported	Inclusion criteria: urine samples from patients Exclusion criteria: Non-reported N=281 Prevalence: 35.9% UTI Sex: 57% M / 43% F	Describe index test: UF500i flow cytometry Cut-off point(s): Bacteria > 60/µl	Describe reference test: Urine culture Cut-off point(s): CFU > 10⁴ was considered positive	Time between the index test and reference test: No time difference For how many participants were no complete outcome data available? All had complete outcome data available.	Outcome measures and effect size: Sensitivity: 100% Specificity 62% PPV 40% NPV 100%	The authors conclude that Flow cytometry is a reliable screening method to exclude urinary tract infections. With a cutoff value of 60 bacteria/ L urine, negative predictive value is 100 % and the calculated percentage of false negatives is 0 % (95 % confidence interval 0–3.3 %).
de Boer (2018)	Type of study: observational study Setting and country: Hospital, Netherlands Funding and conflicts of interest: No specific funding was received, and the authors reported to have no conflicts of interest	Inclusion criteria: Consecutive Included were consecutive patients older than 18 years who were admitted to the ED for internal medicine and had fever 38.0 °C (at admission or at home <24 h) or who had at least two SIRS-criteria (systematic inflammatory response syndrome) over a period of 10 weeks Exclusion criteria: Non-reported N=165 Prevalence: 23% UTI Median age (range): Sex: 54% M / 46% F	Describe index test: Acury C6 flow cytometry Cut-off point(s): Bacteria > 10⁶/µl	Describe reference test: Urine culture Cut-off point(s): CFU > 10⁵ was considered positive	Time between the index test and reference test: No time difference For how many participants were no complete outcome data available? 25 patients	Outcome measures and effect size: Sensitivity: 100.0% Specificity 64.7% PPV 51.4% NPV 100.0%	The authors conclude that counting bacteria by flow cytometry has the highest diagnostic accuracy and is superior to other methods in urinalysis in febrile patients in the ED when using urine culture as the gold standard
Tavenier (2017)	Type of study: observational study Setting and country: Hospital, Netherlands Funding and conflicts of interest: No specific funding was received, and the authors reported to have no conflicts of interest	Inclusion criteria: Consecutive Included were consecutive patients older than 18 years who were admitted to the ED for internal medicine and had fever 38.0 °C (at admission or at home <24 h) or who had at least two SIRS-criteria (systematic inflammatory response syndrome) over a period of 10 weeks Exclusion criteria: Non-reported N=166 Prevalence: 11.4% UTI Sex: 51% M / 49% F	Describe index test: Acury C6 flow cytometry Cut-off point(s): Bacteria > 10⁶/µl	Describe reference test: Urine culture Cut-off point(s): CFU > 10⁵ was considered positive	Time between the index test and reference test: No time difference For how many participants were no complete outcome data available? 25 patients	Outcome measures and effect size: Sensitivity: 89.5% Specificity 83.6%	The authors conclude that counting bacteria by flow cytometry can predict quickly and reliably positive and negative urine cultures in febrile patients admitted tot the ED.
Moshaver (2016)	Type of study: observational study Setting and country: Hospital, Netherlands Funding and conflicts of interest: No specific funding was received, and the authors reported to have no conflicts of interest	Inclusion criteria: Consecutive Randomly selected urine samples of patients with suspected UTI from general practitioners, outpatient and clinical departments Exclusion criteria: Non-reported N=209 Prevalence: 37.8% UTI	Describe index test: Acury C6 flow cytometry Cut-off point(s): Bacteria > 10⁶/µl	Describe reference test: Urine culture Cut-off point(s): CFU > 10⁵ was considered positive	Time between the index test and reference test: No time difference For how many participants were no complete outcome data available? 25 patients	Outcome measures and effect size: Sensitivity: 99% Specificity 58% PPV 59% NPV 99%	The authors conclude that flow cytometry is able to rule out UTI, which can lead to a substantial reduction (36 %) of urine cultures.

Risk of bias assessment diagnostic accuracy studies (QUADAS II, 2011)

Study reference	Patient selection	Index test	Reference standard	Flow and timing	Comments with respect to applicability
Fritzenwalker (2022)	Was a consecutive or random sample of patients enrolled? Yes, a consecutive sample of patients was enrolled. Was a case-control design avoided? Yes Did the study avoid inappropriate exclusions? No exclusion criteria were mentioned	Were the index test results interpreted without knowledge of the results of the reference standard? Unclear If a threshold was used, was it pre-specified? Yes	Is the reference standard likely to correctly classify the target condition? Yes Were the reference standard results interpreted without knowledge of the results of the index test? Unclear	Was there an appropriate interval between index test(s) and reference standard? Yes Did all patients receive a reference standard? Yes Did patients receive the same reference standard? Yes Were all patients included in the analysis? Yes	Are there concerns that the included patients do not match the review question? No Are there concerns that the index test, its conduct, or interpretation differ from the review question? No Are there concerns that the target condition as defined by the reference standard does not match the review question? No
Fritzenwalker (2022)	CONCLUSION: Could the selection of patients have introduced bias? RISK: LOW	CONCLUSION: Could the conduct or interpretation of the index test have introduced bias? RISK: UNCLEAR	CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias? RISK: UNCLEAR	CONCLUSION Could the patient flow have introduced bias? RISK: LOW
Le (2016)	Was a consecutive or random sample of patients enrolled? Yes, a consecutive sample of patients was enrolled. Was a case-control design avoided? Yes Did the study avoid inappropriate exclusions? No exclusion criteria were mentioned	Were the index test results interpreted without knowledge of the results of the reference standard? Unclear If a threshold was used, was it pre-specified? Yes	Is the reference standard likely to correctly classify the target condition? Yes Were the reference standard results interpreted without knowledge of the results of the index test? Unclear	Was there an appropriate interval between index test(s) and reference standard? Yes Did all patients receive a reference standard? Yes Did patients receive the same reference standard? Yes Were all patients included in the analysis? Yes	Are there concerns that the included patients do not match the review question? No Are there concerns that the index test, its conduct, or interpretation differ from the review question? No Are there concerns that the target condition as defined by the reference standard does not match the review question? No
Le (2016)	CONCLUSION: Could the selection of patients have introduced bias? RISK: LOW	CONCLUSION: Could the conduct or interpretation of the index test have introduced bias? RISK: UNCLEAR	CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias? RISK: UNCLEAR	CONCLUSION Could the patient flow have introduced bias? RISK: LOW
Martín-Guitiérrez (2015)	Was a consecutive or random sample of patients enrolled? Yes, a random sample of patients was enrolled. Was a case-control design avoided? Yes Did the study avoid inappropriate exclusions? No exclusion criteria were mentioned	Were the index test results interpreted without knowledge of the results of the reference standard? Unclear If a threshold was used, was it pre-specified? Yes	Is the reference standard likely to correctly classify the target condition? Yes Were the reference standard results interpreted without knowledge of the results of the index test? Unclear	Was there an appropriate interval between index test(s) and reference standard? Yes Did all patients receive a reference standard? Yes Did patients receive the same reference standard? Yes Were all patients included in the analysis? Yes	Are there concerns that the included patients do not match the review question? No Are there concerns that the index test, its conduct, or interpretation differ from the review question? No Are there concerns that the target condition as defined by the reference standard does not match the review question? No
Martín-Guitiérrez (2015)	CONCLUSION: Could the selection of patients have introduced bias? RISK: LOW	CONCLUSION: Could the conduct or interpretation of the index test have introduced bias? RISK: UNCLEAR	CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias? RISK: UNCLEAR	CONCLUSION Could the patient flow have introduced bias? RISK: LOW
Stefanovic (2017)	Was a consecutive or random sample of patients enrolled? Yes, all specimence over the period of 22 July 2015 to 17 February 2016 were included Was a case-control design avoided? Yes Did the study avoid inappropriate exclusions? No exclusion criteria were mentioned	Were the index test results interpreted without knowledge of the results of the reference standard? Unclear If a threshold was used, was it pre-specified? Yes	Is the reference standard likely to correctly classify the target condition? Yes Were the reference standard results interpreted without knowledge of the results of the index test? Unclear	Was there an appropriate interval between index test(s) and reference standard? Yes Did all patients receive a reference standard? Yes Did patients receive the same reference standard? Yes Were all patients included in the analysis? Yes	Are there concerns that the included patients do not match the review question? No Are there concerns that the index test, its conduct, or interpretation differ from the review question? No Are there concerns that the target condition as defined by the reference standard does not match the review question? No
Stefanovic (2017)	CONCLUSION: Could the selection of patients have introduced bias? RISK: LOW	CONCLUSION: Could the conduct or interpretation of the index test have introduced bias? RISK: UNCLEAR	CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias? RISK: UNCLEAR	CONCLUSION Could the patient flow have introduced bias? RISK: LOW
Boonen (2013)	Was a consecutive or random sample of patients enrolled? Unclear. Was a case-control design avoided? Yes Did the study avoid inappropriate exclusions? No exclusion criteria were mentioned	Were the index test results interpreted without knowledge of the results of the reference standard? Unclear If a threshold was used, was it pre-specified? Yes	Is the reference standard likely to correctly classify the target condition? Yes Were the reference standard results interpreted without knowledge of the results of the index test? Unclear	Was there an appropriate interval between index test(s) and reference standard? Yes Did all patients receive a reference standard? Yes Did patients receive the same reference standard? Yes Were all patients included in the analysis? Yes	Are there concerns that the included patients do not match the review question? No Are there concerns that the index test, its conduct, or interpretation differ from the review question? No Are there concerns that the target condition as defined by the reference standard does not match the review question? No
Boonen (2013)	CONCLUSION: Could the selection of patients have introduced bias? RISK: UNCLEAR	CONCLUSION: Could the conduct or interpretation of the index test have introduced bias? RISK: UNCLEAR	CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias? RISK: UNCLEAR	CONCLUSION Could the patient flow have introduced bias? RISK: LOW

De Boer (2017)	Was a consecutive or random sample of patients enrolled? Yes, a consecutive sample of patients was enrolled. Was a case-control design avoided? Yes Did the study avoid inappropriate exclusions? No exclusion criteria were mentioned	Were the index test results interpreted without knowledge of the results of the reference standard? Unclear If a threshold was used, was it pre-specified? Yes	Is the reference standard likely to correctly classify the target condition? Yes Were the reference standard results interpreted without knowledge of the results of the index test? Unclear	Was there an appropriate interval between index test(s) and reference standard? Yes Did all patients receive a reference standard? Yes Did patients receive the same reference standard? Yes Were all patients included in the analysis? Yes	Are there concerns that the included patients do not match the review question? No Are there concerns that the index test, its conduct, or interpretation differ from the review question? No Are there concerns that the target condition as defined by the reference standard does not match the review question? No
De Boer (2017)	CONCLUSION: Could the selection of patients have introduced bias? RISK: HIGH	CONCLUSION: Could the conduct or interpretation of the index test have introduced bias? RISK: UNCLEAR	CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias? RISK: UNCLEAR	CONCLUSION Could the patient flow have introduced bias? RISK: LOW
Tavenier (2018)	Was a consecutive or random sample of patients enrolled? Yes, a consecutive sample of patients was enrolled. Was a case-control design avoided? Yes Did the study avoid inappropriate exclusions? No exclusion criteria were mentioned	Were the index test results interpreted without knowledge of the results of the reference standard? Unclear If a threshold was used, was it pre-specified? Yes	Is the reference standard likely to correctly classify the target condition? Yes Were the reference standard results interpreted without knowledge of the results of the index test? Unclear	Was there an appropriate interval between index test(s) and reference standard? Yes Did all patients receive a reference standard? Yes Did patients receive the same reference standard? Yes Were all patients included in the analysis? Yes	Are there concerns that the included patients do not match the review question? No Are there concerns that the index test, its conduct, or interpretation differ from the review question? No Are there concerns that the target condition as defined by the reference standard does not match the review question? No
Tavenier (2018)	CONCLUSION: Could the selection of patients have introduced bias? RISK: HIGH	CONCLUSION: Could the conduct or interpretation of the index test have introduced bias? RISK: UNCLEAR	CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias? RISK: UNCLEAR	CONCLUSION Could the patient flow have introduced bias? RISK: LOW
Moshaver (2016)	Was a consecutive or random sample of patients enrolled? Yes, a consecutive sample of patients was enrolled. Was a case-control design avoided? Yes Did the study avoid inappropriate exclusions? No exclusion criteria were mentioned	Were the index test results interpreted without knowledge of the results of the reference standard? Unclear If a threshold was used, was it pre-specified? Yes	Is the reference standard likely to correctly classify the target condition? Yes Were the reference standard results interpreted without knowledge of the results of the index test? Unclear	Was there an appropriate interval between index test(s) and reference standard? Yes Did all patients receive a reference standard? Yes Did patients receive the same reference standard? Yes Were all patients included in the analysis? Yes	Are there concerns that the included patients do not match the review question? No Are there concerns that the index test, its conduct, or interpretation differ from the review question? No Are there concerns that the target condition as defined by the reference standard does not match the review question? No
Moshaver (2016)	CONCLUSION: Could the selection of patients have introduced bias? RISK: HIGH	CONCLUSION: Could the conduct or interpretation of the index test have introduced bias? RISK: UNCLEAR	CONCLUSION: Could the reference standard, its conduct, or its interpretation have introduced bias? RISK: UNCLEAR	CONCLUSION Could the patient flow have introduced bias? RISK: LOW

Table of excluded studies

Reference	Reason for exclusion
Abdelrheem, S. S. and Aly, H. M. and Diab, F. and Maebed, A. and Osman, A. O. B. and Mhsb, A. H. and Alaswad, N. K. and Darwish, T. M. and Gabri, M. F. Prediction of Urinary Tract Infection in Neonates with Unexplained Indirect Hyperbilirubinemia. Open Access Macedonian Journal of Medical Sciences. 2022; 10 :1153-1160	P does not meet PICO
Alenkaer, L. K. and Pedersen, L. and Szecsi, P. B. and Bjerrum, P. J. Evaluation of the sysmex UF-5000 fluorescence flow cytometer as a screening platform for ruling out urinary tract infections in elderly patients presenting at the Emergency Department. Scandinavian Journal of Clinical and Laboratory Investigation. 2021; 81 (5) :379-384	P does not meet PICO
Andersen ES, Østergaard C, Röttger R, Christensen AF, Brandslund I, Brasen CL. POCT urine dipstick versus central laboratory analyses: Diagnostic performance and logistics in the medical emergency department. Clin Biochem. 2023 Jan;111:17-25. doi: 10.1016/j.clinbiochem.2022.10.010. Epub 2022 Oct 21. PMID: 36279905.	C does not meet PICO
Bafna P, Deepanjali S, Mandal J, Balamurugan N, Swaminathan RP, Kadhiravan T. Reevaluating the true diagnostic accuracy of dipstick tests to diagnose urinary tract infection using Bayesian latent class analysis. PLoS One. 2020 Dec 31;15(12):e0244870. doi: 10.1371/journal.pone.0244870. PMID: 33382863; PMCID: PMC7774958.	C does not meet PICO
Boon HA, Verbakel JY, De Burghgraeve T, Bruel AVD. Clinical prediction rules for childhood urinary tract infections: a cross-sectional study in ambulatory care. BJGP Open. 2022 Aug 30;6(2):BJGPO.2021.0171. doi: 10.3399/BJGPO.2021.0171. PMID: 35031560; PMCID: PMC9447316.	P does not meet PICO
Boon, H. A. and De Burghgraeve, T. and Verbakel, J. Y. and Van Den Bruel, A. Point-of-care tests for pediatric urinary tract infections in general practice: A diagnostic accuracy study. Family Practice. 2022; 39 (4) :616-622	P does not meet PICO
Breinbjerg, A. and Mohamed, L. and Yde Nielsen, S. and Rittig, S. and Tullus, K. and Kamperis, K. Pitfalls in Diagnosing Urinary Tract Infection in Children below the Age of 2: Suprapubic Aspiration vs Clean-Catch Urine Sampling. The Journal of urology. 2021; 206 (6) :1482-1489	P does not meet PICO
Broeren, M. A. C. and Bahçeci, S. and Vader, H. L. and Arents, N. L. A. Screening for urinary tract infection with the sysmex UF-1000i urine flow cytometer. Journal of Clinical Microbiology. 2011; 49 (3) :1025-1029	Included in Shang (2013)
Broeren, M. and Nowacki, R. and Halbertsma, F. and Arents, N. and Zegers, S. Urine flow cytometry is an adequate screening tool for urinary tract infections in children. European Journal of Pediatrics. 2019; 178 (3) :363-368	P does not meet PICO
Chambliss, A. B. and Mason, H. M. and Van, T. T. Correlation of Chemical Urinalysis to Microscopic Urinalysis and Urine Culture: Implications for Reflex Urinalysis Workflows. The journal of applied laboratory medicine. 2020; 5 (4) :724-731	P does not meet PICO
Chambliss, A. B. and Van, T. T. Revisiting approaches to and considerations for urinalysis and urine culture reflexive testing. Critical Reviews in Clinical Laboratory Sciences. 2022; 59 (2) :112-124	Wrong publication type (narrative review)
Chaudhari, P. P. and Monuteaux, M. C. and Bachur, R. G. Microscopic Bacteriuria Detected by Automated Urinalysis for the Diagnosis of Urinary Tract Infection. Journal of Pediatrics. 2018; 202 :238-244.e1	P does not meet PICO
Cheng, B. and Zaman, M. and Cox, W. Correlation of Pyuria and Bacteriuria in Acute Care. American Journal of Medicine. 2022; 135 (9) :e353-e358	O does not meet PICO
Chotiprasitsakul, D. and Kijnithikul, A. and Uamkhayan, A. and Santanirand, P. Predictive Value of Urinalysis and Recent Antibiotic Exposure to Distinguish Between Bacteriuria, Candiduria, and No-Growth Urine. Infection and Drug Resistance. 2021; 14 :5699-5709	O does not meet PICO
Christy P, Sidjabat HE, Lumban Toruan AA, Moses EJ, Mohd Yussof N, Puspitasari Y, Fuadi MR, Aryati, Marpaung FR. Comparison of Laboratory Diagnosis of Urinary Tract Infections Based on Leukocyte and Bacterial Parameters Using Standardized Microscopic and Flow Cytometry Methods. Int J Nephrol. 2022 May 27;2022:9555121. doi: 10.1155/2022/9555121. PMID: 35669495; PMCID: PMC9167024.	O does not meet PICO
Chun TTS, Ruan X, Ng SL, Wong HL, Ho BSH, Tsang CF, Lai TCT, Ng ATL, Ma WK, Lam WP, Na R, Tsu JHL. The diagnostic value of rapid urine test platform UF-5000 for suspected urinary tract infection at the emergency department. Front Cell Infect Microbiol. 2022 Sep 27;12:936854. doi: 10.3389/fcimb.2022.936854. PMID: 36237433; PMCID: PMC9551190.	I and C do not meet PICO
Conkar, S. and Mir, S. Urine Flow Cytometry in the Diagnosis of Urinary Tract Infection. Indian Journal of Pediatrics. 2018; 85 (11) :995-999	P does not meet PICO
Coudert, M. and Pépin, M. and de Thezy, A. and Fercot, E. and Laycuras, M. and Coudert, A. L. and Duran, C. and Bouchand, F. and Davido, B. and Le Crane, M. and Denis, B. and Muller, F. and Gourdon, M. and Peng, C. L. and Mahamdia, R. and Mekerta, Z. and Seridi, Z. and Gaillard, J. L. and Leichowski, L. and Moulias, S. and Rottman, M. and Sivadon-Tardy, V. and Teillet, L. and Dinh, A. Clinical presentation and performance of urine dipstick for diagnosis of urinary infection in geriatric population. Revue de Medecine Interne. 2019; 40 (11) :714-721	Wrong language (French)
Dai, Q. and Jiang, Y. and Shi, H. and Zhou, W. and Zhou, S. and Yang, H. Evaluation of the automated urine particle analyzer UF-1000i screening for urinary tract infection in nonpregnant women. Clinical Laboratory. 2014; 60 (2) :275-280	Wrong language (Spanish)
De Rosa, R. and Grosso, S. and Bruschetta, G. and Avolio, M. and Stano, P. and Modolo, M. L. and Camporese, A. Evaluation of the Sysmex UF1000i flow cytometer for ruling out bacterial urinary tract infection. Clinica Chimica Acta. 2010; 411 (1) :1137-1142	Included in Shang (2013)
Delanghe, J. New screening diagnostic techniques in urinalysis. Acta Clinica Belgica. 2007; 62 (3) :155-161	Wrong publication type (narrative review)
Diviney J, Jaswon MS. Urine collection methods and dipstick testing in non-toilet-trained children. Pediatr Nephrol. 2021 Jul;36(7):1697-1708. doi: 10.1007/s00467-020-04742-w. Epub 2020 Sep 12. Erratum in: Pediatr Nephrol. 2020 Nov 23;: PMID: 32918601; PMCID: PMC8172492.	P does not meet PICO
dos Santos, J. C. and Weber, L. P. and Perez, L. R. R. Evaluation of urinalysis parameters to predict urinary-tract infection. Brazilian Journal of Infectious Diseases. 2007; 11 (5) :479-481	Included in Shang (2013)
Edelbauer, M. and Kshirsagar, S. and Riedl, M. and Billing, H. and Tönshoff, B. and Haffner, D. and Cortina, G. and Amon, O. and Ross, S. and Dötsch, J. and Wechselberger, G. and Weber, L. T. and Dablander, M. and Anliker, M. and Griesmacher, A. and Steichen-Gersdorf, E. Activity of childhood lupus nephritis is linked to altered T cell and cytokine homeostasis. Journal of Clinical Immunology. 2012; 32 (3) :477-487	P does not meet PICO
El Kettani A, Housbane S, Wakit F, Mikou KA, Belabbes H, Zerouali K. Evaluation of the Sysmex UF-4000i urine analyzer as a screening test to rule out urinary tract infection and reduce urine cultures. Ann Biol Clin (Paris). 2021 Apr 9. doi: 10.1684/abc.2021.1634. Epub ahead of print. PMID: 33840645.	Wrong language (French)
Erdman, Patrick and Anderson, Brian and Zacko, J. Christopher and Taylor, Kirk and Donaldson, Keri The Accuracy of the Sysmex UF-1000i in Urine Bacterial Detection Compared With the Standard Urine Analysis and Culture. Archives of pathology & laboratory medicine. 2017; 141 (11) :1540-1543	P does not meet PICO
Evans, R. and Davidson, M. M. and Sim, L. R. W. and Hay, A. J. Testing by Sysmex UF-100 flow cytometer and with bacterial culture in a diagnostic laboratory: A comparison. Journal of Clinical Pathology. 2006; 59 (6) :661-662	Included in Shang (2013)
Foudraine DE, Bauer MP, Russcher A, Kusters E, Cobbaert CM, van der Beek MT, Stalenhoef JE. Use of Automated Urine Microscopy Analysis in Clinical Diagnosis of Urinary Tract Infection: Defining an Optimal Diagnostic Score in an Academic Medical Center Population. J Clin Microbiol. 2018 May 25;56(6):e02030-17. doi: 10.1128/JCM.02030-17. PMID: 29643200; PMCID: PMC5971551.	I does not meet PICO
Gallego Anguí, P. and Cuadros González, J. and Romanyk, J. and Gómez Herruz, P. and González, R. and Arroyo, T. and Saz, J. V. Efficacy and optimisation of flow cytometry in the universal screening of urinary tract infection. Revista del Laboratorio Clinico. 2019; 12 (2) :78-83	Wrong language (Spanish)
Garcia-Coca, Marta and Gadea, Ignacio and Esteban, Jaime Relationship between conventional culture and flow cytometry for the diagnosis of urinary tract infection. Journal of microbiological methods. 2017; 137 :14-18	P and I do not meet PICO
Gatt, D. and Lendner, I. and Ben-Shimol, S. Catheter-obtained, Enterococcus and Proteus positive urine cultures may represent mostly contamination or asymptomatic bacteriuria in infants <90 days. Infectious Diseases. 2021; 53 (5) :332-339	P does not meet PICO
Gehringer C, Regeniter A, Rentsch K, Tschudin-Sutter S, Bassetti S, Egli A. Accuracy of urine flow cytometry and urine test strip in predicting relevant bacteriuria in different patient populations. BMC Infect Dis. 2021 Feb 25;21(1):209. doi: 10.1186/s12879-021-05893-3. PMID: 33632129; PMCID: PMC7908726.	P does not meet PICO
Gessoni, G. and Saccani, G. and Valverde, S. and Manoni, F. and Caputo, M. Does flow cytometry have a role in preliminary differentiation between urinary tract infections sustained by gram positive and gram negative bacteria? An Italian polycentric study. Clinica Chimica Acta. 2015; 440 :152-156	I does not meet PICO
Gilboe HM, Reiakvam OM, Aasen L, Tjade T, Bjerner J, Ranheim TE, Gaustad P. Rapid diagnosis and reduced workload for urinary tract infection using flowcytometry combined with direct antibiotic susceptibility testing. PLoS One. 2021 Jul 6;16(7):e0254064. doi: 10.1371/journal.pone.0254064. PMID: 34228764; PMCID: PMC8259986.	P does not meet PICO
Grossmann, N. C. and Schuettfort, V. M. and Betschart, J. and Becker, A. S. and Hermanns, T. and Keller, E. X. and Fankhauser, C. D. and Kranzbühler, B. Risk factors for concomitant positive midstream urine culture in patients presenting with symptomatic ureterolithiasis. Urolithiasis. 2022; 50 (3) :293-302	I does not meet PICO
Gutiérrez-Fernández, J. and Lara, A. and Bautista, M. F. and de Dios Luna, J. and Polo, P. and Miranda, C. and Navarro, J. M. Performance of the Sysmex UF1000i system in screening for significant bacteriuria before quantitative culture of aerobic/facultative fast-growth bacteria in a reference hospital. Journal of Applied Microbiology. 2012; 113 (3) :609-614	Included in Shang (2013)
Han YQ, Zhang L, Wang JR, Xu SC, Hu ZD. Net benefit of routine urine parameters for urinary tract infection screening: a decision curve analysis. Ann Transl Med. 2020 May;8(9):601. doi: 10.21037/atm.2019.09.52. PMID: 32566627; PMCID: PMC7290540.	I and C do not meet PICO
Harris, M. and Fasolino, T. New and emerging technologies for the diagnosis of urinary tract infections. Journal of Laboratory Medicine. 2022; 46 (1) :3-15	Wrong publication type (narrative review)
Haugum K, Haugan MS, Skage J, Tetik M, Jakovljev A, Nilsen HS, Afset JE. Use of Sysmex UF-5000 flow cytometry in rapid diagnosis of urinary tract infection and the importance of validating carryover rates against bacterial count cut-off. J Med Microbiol. 2021 Dec;70(12):001472. doi: 10.1099/jmm.0.001472. PMID: 34898416; PMCID: PMC8744275.	P does not meet PICO
He, H. and Wang, Z. and Zuo, L. and Zhang, L. and Liu, C. and Dai, C. and Shi, W. and Li, J. and Wang, R. and Yongjun, F. and Li, J. Establishment of the Risk Prediction Model for Significant Bacteriuria in Adult Patients with Automated Urine Analysis. Urologia Internationalis. 2021; 105 (9) :786-791	I and C do not meet PICO
Herráez, O. and Asencio, M. A. and Carranza, R. and Jarabo, M. M. and Huertas, M. and Redondo, O. and Arias-Arias, A. and Jiménez-Álvarez, S. and Solís, S. and Zamarrón, P. and Illescas, M. S. and Galán, M. A. Sysmex UF-1000i flow cytometer to screen urinary tract infections: the URISCAM multicentre study. Letters in Applied Microbiology. 2018; 66 (3) :175-181	P does not meet PICO
Herreros, M. L. and Tagarro, A. and García-Pose, A. and Sánchez, A. and Cañete, A. and Gili, P. Performing a urine dipstick test with a clean-catch urine sample is an accurate screening method for urinary tract infections in young infants. Acta Paediatrica, International Journal of Paediatrics. 2018; 107 (1) :145-150	P does not meet PICO
Hitzeman, Nathan and Greer, Dineen M. D. M. P. H. and Carpio, Erik Office-Based Urinalysis: A Comprehensive Review. American family physician. 2022; 106 (1) :27-35B	Wrong publication type (narrative review)
Holthaus, E. A. and Ferrando, C. A. and Jelovsek, J. E. and Barber, M. D. Reliability of Symptoms and Dipstick for Postoperative Catheter-Associated Urinary Tract Infections. Female Pelvic Medicine and Reconstructive Surgery. 2021; 27 (6) :398-402	P does not meet PICO
Hsu, Y. L. and Chang, S. N. and Lin, C. C. and Lin, H. C. and Lai, H. C. and Kuo, C. C. and Hwang, K. P. and Chiang, H. Y. Clinical characteristics and prediction analysis of pediatric urinary tract infections caused by gram-positive bacteria. Scientific reports. 2021; 11 (1) :11010	P does not meet PICO
Íñigo, M. and Coello, A. and Fernández-Rivas, G. and Carrasco, M. and Marcó, C. and Fernández, A. and Casamajor, T. and Ausina, V. Evaluation of the SediMax automated microscopy sediment analyzer and the Sysmex UF-1000i flow cytometer as screening tools to rule out negative urinary tract infections. Clinica Chimica Acta. 2016; 456 :31-35	P does not meet PICO
Ippoliti, Roberto and Allievi, Isabella and Rocchetti, Andrea UF-5000 flow cytometer: A new technology to support microbiologists' interpretation of suspected urinary tract infections. MicrobiologyOpen. 2020; 9 (3) :e987	O does not meet PICO
Janes, Victoria A. and Matamoros, Sebastien and Munk, Patrick and Clausen, Philip T. L. C. and Koekkoek, Sylvie M. and Koster, Linda A. M. and Jakobs, Marja E. and de Wever, Bob and Visser, Caroline E. and Aarestrup, Frank M. and Lund, Ole and de Jong, Menno D. and Bossuyt, Patrick M. M. and Mende, Daniel R. and Schultsz, Constance Metagenomic Dsequencing for semi-quantitative pathogen detection from urine: a prospective, laboratory-based, proof-of-concept study. The Lancet. Microbe. 2022; 3 (8) :e588-e597	I does not meet PICO
Jiménez-Guerra, G. and Heras-Cañas, V. and Valera-Arcas, M. D. and Rodríguez-Grangér, J. and Navarro, J. M. and Gutiérrez-Fernández, J. Comparison between urine culture profile and morphology classification using fluorescence parameters of the Sysmex UF-1000i urine flow cytometer. Journal of Applied Microbiology. 2017; 122 (2) :473-480	P does not meet PICO
Jolkkonen, S. and Paattiniemi, E. L. and Kärpänoja, P. and Sarkkinen, H. Screening of urine samples by flow cytometry reduces the need for culture. Journal of Clinical Microbiology. 2010; 48 (9) :3117-3121	Included in Shang (2013)
Kanegaye, J. T. and Jacob, J. M. and Malicki, D. Automated urinalysis and urine dipstick in the emergency evaluation of young febrile children. Pediatrics. 2014; 134 (3) :523-529	P does not meet PICO
Kim, H. and Kim, H. R. and Kim, T. H. and Lee, M. K. Age-Specific Cutoffs of the Sysmex UF-1000i Automated Urine Analyzer for Rapid Screening of Urinary Tract Infections in Outpatients. Annals of laboratory medicine. 2019; 39 (3) :322-326	Wrong publication type (communication) and P does not meet PICO
Koken, T. and Aktepe, O. C. and Serteser, M. and Samli, M. and Kahraman, A. and Dogan, N. Determination of cut-off values for leucocytes and bacteria for urine flow cytometer (UF-100) in urinary tract infections. International Urology and Nephrology. 2002; 34 (2) :175-178	Included in Shang (2013)
Kolodziej LM, Kuil SD, de Jong MD, Schneeberger C. Resident-Related Factors Influencing Antibiotic Treatment Decisions for Urinary Tract Infections in Dutch Nursing Homes. Antibiotics (Basel). 2022 Jan 21;11(2):140. doi: 10.3390/antibiotics11020140. PMID: 35203742; PMCID: PMC8868192.	I and C do not meet PICO
Krongvorakul, J. and Phundhusuwannakul, S. and Santanirand, P. and Kunakorn, M. A flow cytometric urine analyzer for bacteria and white blood cell counts plus urine dipstick test for rapid screening of bacterial urinary tract infection. Asian Biomedicine. 2012; 6 (4) :601-608	Included in Shang (2013)
Lee KS, Lim HJ, Kim K, Park YG, Yoo JW, Yong D. Rapid Bacterial Detection in Urine Using Laser Scattering and Deep Learning Analysis. Microbiol Spectr. 2022 Apr 27;10(2):e0176921. doi: 10.1128/spectrum.01769-21. Epub 2022 Mar 2. PMID: 35234514; PMCID: PMC8941854.	I and C do not meet PICO
Lendner, Idan and Justman, Naphtali and Givon-Lavi, Noga and Maimon, Michal S. and Kestenbaum, Inbal and Ben-Shimol, Shalom Urine dipstick low sensitivity for UTI diagnosis in febrile infants *. Infectious diseases (London, England). 2019; 51 (10) :764-771	P does not meet PICO
Lubell, T. R. and Barasch, J. M. and King, B. and Ochs, J. and Fan, W. and Duong, J. and Chitre, M. and Dayan, P. Urinary tract infections in children: Testing a novel, noninvasive, point-of-care diagnostic marker. Academic Emergency Medicine. 2022; 29 (3) :326-333	P does not meet PICO
Lunn, A. and Holden, S. and Boswell, T. and Watson, A. R. Automated microscopy, dipsticks and the diagnosis of urinary tract infection. Archives of Disease in Childhood. 2010; 95 (3) :193-197	Included in Shang (2013)
Ma, Yu-Cheng and Jian, Zhong-Yu and Li, Hong and Wang, Kun-Jie Preoperative urine nitrite versus urine culture for predicting postoperative fever following flexible ureteroscopic lithotripsy: a propensity score matching analysis. World journal of urology. 2021; 39 (3) :897-905	P does not meet PICO
Maduemem, Kene Ebuka and Rodriguez, Yurelis Diaz and Fraser, Brian How Sensitive are Dipstick Urinalysis and Microscopy in Making Diagnosis of Urinary Tract Infection in Children?. International journal of preventive medicine. 2019; 10 :62	P does not meet PICO
Malia, L. and Strumph, K. and Smith, S. and Brancato, J. and Johnson, S. T. and Chicaiza, H. Fast and Sensitive: Automated Point-of-Care Urine Dips. Pediatric Emergency Care. 2020; 36 (10) :486-488	P does not meet PICO
Manoni, F. and Fornasiero, L. and Ercolin, M. and Tinello, A. and Ferrian, M. and Hoffer, P. and Valverde, S. and Gessoni, G. Cutoff values for bacteria and leukocytes for urine flow cytometer Sysmex UF-1000i in urinary tract infections. Diagnostic Microbiology and Infectious Disease. 2009; 65 (2) :103-107	Included in Shang (2013)
Manoni, F. and Valverde, S. and Antico, F. and Giacomini, A. and Salvadego, M. and Gessoni, G. Measurement of urine leukocytes by a second generation flow cytometer; application in the diagnosis of acute urinary tract infections in adult patients. Rivista di Medicina di Laboratorio. 2001; 2 (3) :19-27	Included in Shang (2013)
Manoni, F. and Valverde, S. and Antico, F. and Salvadego, M. M. and Giacomini, A. and Gessoni, G. Field evaluation of a second-generation cytometer UF-100 in diagnosis of acute urinary tract infections in adult patients. Clinical Microbiology and Infection. 2002; 8 (10) :662-668	Included in Shang (2013)
Martín-Gutiérrez G, Martín-Pérez C, Toledo H, Sánchez-Cantalejo E, Lepe JA. FlowUTI: An interactive web-application for optimizing the use of flow cytometry as a screening tool in urinary tract infections. PLoS One. 2022 Nov 8;17(11):e0277340. doi: 10.1371/journal.pone.0277340. PMID: 36346782; PMCID: PMC9642874.	I and C do not meet PICO
Middelkoop, S. J. M. and van Pelt, L. J. and Kampinga, G. A. and ter Maaten, J. C. and Stegeman, C. A. Influence of gender on the performance of urine dipstick and automated urinalysis in the diagnosis of urinary tract infections at the emergency department. European Journal of Internal Medicine. 2021; 87 :44-50	C does not meet PICO
Middelkoop, S. J. M. and van Pelt, L. J. and Kampinga, G. A. and ter Maaten, J. C. and Stegeman, C. A. Routine tests and automated urinalysis in patients with suspected urinary tract infection at the ED. American Journal of Emergency Medicine. 2016; 34 (8) :1528-1534	C does not meet PICO
Müller M, Sägesser N, Keller PM, Arampatzis S, Steffens B, Ehrhard S, Leichtle AB. Urine Flow Cytometry Parameter Cannot Safely Predict Contamination of Urine-A Cohort Study of a Swiss Emergency Department Using Machine Learning Techniques. Diagnostics (Basel). 2022 Apr 16;12(4):1008. doi: 10.3390/diagnostics12041008. PMID: 35454055; PMCID: PMC9025120.	P does not meet PICO
Nadeem S, Badawy M, Oke OK, Filkins LM, Park JY, Hennes HM. Pyuria and Urine Concentration for Identifying Urinary Tract Infection in Young Children. Pediatrics. 2021 Feb;147(2):e2020014068. doi: 10.1542/peds.2020-014068. PMID: 33514634.	P does not meet PICO
Nakamura A, Kohno A, Noguchi N, Kawa K, Ohno Y, Komatsu M, Yamanishi H. Prediction of Uropathogens by Flow Cytometry and Dip-stick Test Results of Urine Through Multivariable Logistic Regression Analysis. PLoS One. 2020 Jan 7;15(1):e0227257. doi: 10.1371/journal.pone.0227257. PMID: 31910242; PMCID: PMC6946154.	I does not meet PICO
Naseem, M. and Tariq, A. and Saeed, S. and Ghuncha, M. R. and Jabeen, N. and Raza, M. The diagnostic accuracy of urine dipstick in early detection of uti in children keeping urine culture as a gold standard. Medical Forum Monthly. 2020; 31 (11) :12-15	P does not meet PICO
O'Leary, B. D. and Armstrong, F. M. and Byrne, S. and Talento, A. F. and O'Coigligh, S. The prevalence of positive urine dipstick testing and urine culture in the asymptomatic pregnant woman: A cross-sectional study. European Journal of Obstetrics and Gynecology and Reproductive Biology. 2020; 253 :103-107	P does not meet PICO
Ohnishi, T. and Asada, N. and Furuichi, M. and Sekiguchi, S. and Awazu, M. and Hori, N. and Kamimaki, I. A novel screening method for pediatric urinary tract infection using ordinary diapers. Scientific reports. 2020; 10 (1) :19342	P does not meet PICO
Okada, H. and Sakai, Y. and Miyazaki, S. and Arakawa, S. and Hamaguchi, Y. and Kamidono, S. Detection of significant bacteriuria by automated urinalysis using flow cytometry. Journal of Clinical Microbiology. 2000; 38 (8) :2870-2872	Included in Shang (2013)
Ourani, M. and Honda, N. S. and MacDonald, W. and Roberts, J. Evaluation of evidence-based urinalysis reflex to culture criteria: Impact on reducing antimicrobial usage. International Journal of Infectious Diseases. 2021; 102 :40-44	I does not meet PICO
Paalanne N, Wikstedt L, Pokka T, Salo J, Uhari M, Renko M, Tapiainen T. Diaper-embedded urine test device for the screening of urinary tract infections in children: a cohort study. BMC Pediatr. 2020 Aug 11;20(1):378. doi: 10.1186/s12887-020-02277-5. PMID: 32781982; PMCID: PMC7419204.	P does not meet PICO
Penders, J. and Fiers, T. and Everaert, K. and Barth, J. and Dhondt, A. W. and Delanghe, J. R. Diagnostic performance of combined specific urinary proteins and urinary flow cytometry in urinary tract pathology. Clinical Chemistry and Laboratory Medicine. 2007; 45 (4) :499-504	C does not meet PICO
Pieretti, B. and Brunati, P. and Pini, B. and Colzani, C. and Congedo, P. and Rocchi, M. and Terramocci, R. Diagnosis of bacteriuria and leukocyturia by automated flow cytometry compared with urine culture. Journal of Clinical Microbiology. 2010; 48 (11) :3990-3996	Included in Shang (2013)
Ramesh, S. and Sumana, B. S. Dipstick screening for urinary tract infection in adolescent school girls: Evaluation of self screening ability. Journal of Clinical and Diagnostic Research. 2019; 13 (12) :EC06-EC10	P does not meet PICO
Safdar, O. and Marouf, A. and Sait, R. and Bayazeed, L. and Silawi, R. and Mustafa, L. H. and Habiballah, A. and Maqboul, A. and Bawahab, N. and Habib, M. and Alsomali, A. Urine analysis sensitivity and specificity for paediatric urinary tract infections. Australasian Medical Journal. 2020; 13 (12) :330-337	P does not meet PICO
Saini, P. and Singh, V. A. and Shinu, P. Clinical evaluation of pyuria, bacteriuria and culture for diagnosis of urinary tract infection. Indian Journal of Public Health Research and Development. 2020; 11 (2) :828-833	full tekst not available
Schuh SK, Seidenberg R, Arampatzis S, Leichtle AB, Hautz WE, Exadaktylos AK, Schechter CB, Müller M. Diagnosis of Urinary Tract Infections by Urine Flow Cytometry: Adjusted Cut-Off Values in Different Clinical Presentations. Dis Markers. 2019 Mar 3;2019:5853486. doi: 10.1155/2019/5853486. PMID: 30944667; PMCID: PMC6421762.	I does not meet PICO
Shaikh, N. and Liu, H. and Kurs-Lasky, M. and Forster, C. S. Biomarkers for febrile urinary tract infection in children. Pediatric Nephrology. 2022; 37 (1) :171-177	P does not meet PICO
Shine, Y. K. and Young, J. K. and Sun, M. L. and Sang, H. H. and Hyung, H. K. and Han, C. S. and Lee, E. Y. Evaluation of the Sysmex UF-100 urine cell analyzer as a screening test to reduce the need for urine cultures for community-acquired urinary tract infection. American Journal of Clinical Pathology. 2007; 128 (6) :922-925	Included in Shang (2013)
Suresh, J. and Krishnamurthy, S. and Mandal, J. and Mondal, N. and Sivamurukan, P. Diagnostic Accuracy of Point-of-care Nitrite and Leukocyte Esterase Dipstick Test for the Screening of Pediatric Urinary Tract Infections. Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia. 2021; 32 (3) :703-710	P does not meet PICO
Szmulik M, Trześniewska-Ofiara Z, Mendrycka M, Woźniak-Kosek A. A novel approach to screening and managing the urinary tract infections suspected sample in the general human population. Front Cell Infect Microbiol. 2022 Aug 25;12:915288. doi: 10.3389/fcimb.2022.915288. PMID: 36093203; PMCID: PMC9455924.	P does not meet PICO
Van Der Zwet, W. C. and Hessels, J. and Canbolat, F. and Deckers, M. M. L. Evaluation of the Sysmex UF-1000i® urine flow cytometer in the diagnostic work-up of suspected urinary tract infection in a Dutch general hospital. Clinical Chemistry and Laboratory Medicine. 2010; 48 (12) :1765-1771	Included in Shang (2013)
Wang, J. and Zhang, Y. and Xu, D. and Shao, W. and Lu, Y. Evaluation of the sysmex UF-1000i for the diagnosis of urinary tract infection. American Journal of Clinical Pathology. 2010; 133 (4) :577-582	Included in Shang (2013)
Waterfield, T. and Foster, S. and Platt, R. and Barrett, M. J. and Durnin, S. and Maney, J. A. and Roland, D. and McFetridge, L. and Mitchell, H. and Umana, E. and Lyttle, M. D. Diagnostic test accuracy of dipstick urinalysis for diagnosing urinary tract infection in febrile infants attending the emergency department. Archives of Disease in Childhood. 2022; 107 (12) :1095-1099	P does not meet PICO
Xie, R. and Li, X. and Li, G. and Fu, R. Diagnostic value of different urine tests for urinary tract infection: a systematic review and meta-analysis. Translational Andrology and Urology. 2022; 11 (3) :325-335	I does not meet PICO
Yang SS, Yang CC, Chen YS, Chang SJ. A performance comparison of the fully automated urine particle analyzer UF-5000 with UF-1000i and Gram staining in predicting bacterial growth patterns in women with uncomplicated urinary tract infections. BMC Urol. 2021 Feb 12;21(1):24. doi: 10.1186/s12894-021-00791-x. PMID: 33579236; PMCID: PMC7881468.	O does not meet PICO
Yavaş, D. P. and Arslansoyu Çamlar, S. and Soylu, A. and Kavukçu, S. Clinical predictive value of the urine leukocyte esterase test positivity in childhood. Pediatrics International. 2021; 63 (11) :1334-1338	P does not meet PICO

Verantwoording

Beoordelingsdatum en geldigheid

Laatst beoordeeld : 08-07-2024

Initiatief en autorisatie

Initiatief:

Nederlandse Vereniging voor Medische Microbiologie
Nederlandse Vereniging voor Urologie

Geautoriseerd door:

Nederlands Huisartsen Genootschap
Nederlandse Vereniging voor Medische Microbiologie
Nederlandse Vereniging voor Urologie
Nederlandse Vereniging voor Klinische Chemie en Laboratoriumgeneeskunde
Nierpatiënten Vereniging Nederland

Algemene gegevens

De ontwikkeling/herziening van deze richtlijnmodule werd ondersteund door het Kennisinstituut van de Federatie Medisch Specialisten (www.demedischspecialist.nl/kennisinstituut) en werd gefinancierd uit de Kwaliteitsgelden Medisch Specialisten (SKMS). De financier heeft geen enkele invloed gehad op de inhoud van de richtlijnmodule.

Samenstelling werkgroep

Voor het ontwikkelen van de richtlijnmodule is in 2022 een multidisciplinaire werkgroep ingesteld, bestaande uit vertegenwoordigers van alle relevante specialismen (zie hiervoor de Samenstelling van de werkgroep).

Werkgroep

Dr. A.T. Bernards (voorzitter), arts-microbioloog, Nederlandse Vereniging voor Medische Microbiologie (NVMM)
Drs. I.O Lede MBA, arts-microbioloog, Nederlandse Vereniging voor Medische Microbiologie (NVMM)
Dr. A.P. van Dam, arts-microbioloog, Nederlandse Vereniging voor Medische Microbiologie (NVMM)
Dr. E.M de Koff, Arts in opleiding tot arts-microbioloog (onder begeleiding van Dr. A.P. van Dam)
Dr. E.C.H.J. Michielsen, Laboratoriumspecialist klinische chemie, Nederlandse Vereniging voor Klinische Chemie (NVKC)
Dr. T.N. Platteel, Huisarts, Nederlands Huisartsen Genootschap (NHG) (tot 1 september 2023 en vanaf 1 januari 2024)
Dr. L. Boelman, Huisarts, Nederlands Huisartsen Genootschap (NHG) (vanaf 1 september 2023 tot 1 januari 2024)
Drs. J.H. Wolterbeek, uroloog, Nederlandse Vereniging voor Urologie (NVU)

Klankbordgroep:

Dr. P.D.J. Sturm, arts-microbioloog, Nederlandse Vereniging voor Medische Microbiologie (NVMM)
Dr. M.T. van der Beek, arts-microbioloog, Nederlandse Vereniging voor Medische Microbiologie (NVMM)
Drs. S.C.M. Tops arts in opleiding tot arts-microbioloog, Nederlandse Vereniging voor Medische Microbiologie (NVMM)
Drs. K. Prantl, Nierpatiëntenvereniging Nederland (NVN)

Met ondersteuning van:

M. van der Maten, literatuurspecialist, Kennisinstituut van de Medisch Specialisten
A. van der Wal, literatuurspecialist, Kennisinstituut van de Medisch Specialisten
A. Eikelenboom-Boskamp, adviseur, Kennisinstituut van de Federatie Medisch Specialisten
Dr. A.J Versteeg, senior adviseur, Kennisinstituut van de Federatie Medisch Specialisten

Belangenverklaringen

De Code ter voorkoming van oneigenlijke beïnvloeding door belangenverstrengeling is gevolgd. Alle werkgroepleden hebben schriftelijk verklaard of zij in de laatste drie jaar directe financiële belangen (betrekking bij een commercieel bedrijf, persoonlijke financiële belangen, onderzoeksfinanciering) of indirecte belangen (persoonlijke relaties, reputatiemanagement) hebben gehad. Gedurende de ontwikkeling of herziening van een module worden wijzigingen in belangen aan de voorzitter doorgegeven. De belangenverklaring wordt opnieuw bevestigd tijdens de commentaarfase.

Een overzicht van de belangen van werkgroepleden en het oordeel over het omgaan met eventuele belangen vindt u in onderstaande tabel. De ondertekende belangenverklaringen zijn op te vragen bij het secretariaat van het Kennisinstituut van de Federatie Medisch Specialisten.

Werkgroeplid	Functie	Nevenfuncties	Gemelde belangen	Ondernomen actie
Dr. A.T. Bernards	Voorzitter werkgroep	Geen	Geen	Geen
Drs. I.O Lede MBA	Arts-microbioloog Tergooi MC betaald	Aspirant bestuurslid Stichting Pensioenfonds Medisch Specialisten (SPMS) (bezoldigd)	Geen	Geen
Dr. A.P. van Dam	Arts-microbioloog Amsterdam UMC (0,9 FTE) waarbij detachering naar - GGD Amsterdam, Streeklaboratorium, (0,2 FTE) - RIVM, consulent openbare gezondheidszorg/microbiologie (COMmer) (0,2 FTE)	Vanuit Amsterdam UMC: lid redactieraad Tijdschrift voor Infectieziekten (onbetaald) - Vanuit GGD: laboratoriumvertegenwoordiger NL voor SOA-European Center of Disease Control ECDC (onbetaald)	Onderzoek naar effectiviteit van zolidoflacin voor behandeling van gonorroe, opdrachtgever GARDP Onderzoek naar belang van Mycoplasma genitalium bij PID, financier OLVG research fonds Onderzoek naar diagnostische waarde geautomatiseerde moleculaire test voor Treponema pallidum, Hologic financiert hierbij alleen kits, geen personele kosten en geen honoraria	Geen
Dr. E.M. de Koff	Arts in opleiding tot arts-microbioloog bij Amsterdam Universitair Medisch Centrum	Geen	Geen	Geen
Dr. E.C.H.J. Michielsen	Laboratoriumspecialist klinische chemie - Diagnostiek voor U (betaald) Technical assessor Raad voor Accreditatie (betaald)	NHG LESA commissie NHG werkgroep diagnostische bepalingen	Geen	Geen
Dr. T.N. Platteel	Waarnemend huisarts Assistant professor Julius centrum, UMC Utrecht	Lid regionaal coördinatieteam ABR zorgnetwerk Gain. afgevaardigd als werkgroeplid namens NHG	Geen	Geen
Dr. L. Boelman	Huisarts, Huisartsenpraktijk de Brink, Werkhoven (0,3 FTE) Wetenschappelijk medewerker, cluster Richtlijnontwikkeling, NHG (0,6 FTE)	Geen	Geen	Geen
Drs. J.H. Wolterbeek	Uroloog Franciscus Rotterdam	Commissie kwaliteitsvisitatie Urologie vanuit de NVU	Geen	Geen

Inbreng patiëntenperspectief

Er werd aandacht besteed aan het patiëntenperspectief door uitnodigen van Patiëntfederatie Nederland (PFNL) en de Nierpatiëntenvereniging Nederland voor de schriftelijke knelpuntenanalyse. De verkregen input is meegenomen bij het opstellen van de uitgangsvragen, de keuze voor de uitkomstmaten en bij het opstellen van de overwegingen. De conceptrichtlijn is tevens voor commentaar voorgelegd aan PFNL en de eventueel aangeleverde commentaren zijn bekeken en verwerkt.

Kwalitatieve raming van mogelijke financiële gevolgen in het kader van de Wkkgz

Bij de richtlijn is conform de Wet kwaliteit, klachten en geschillen zorg (Wkkgz) een kwalitatieve raming uitgevoerd of de aanbevelingen mogelijk leiden tot substantiële financiële gevolgen. Bij het uitvoeren van deze beoordeling zijn richtlijnmodules op verschillende domeinen getoetst (zie het stroomschema op de Richtlijnendatabase).

Uit de kwalitatieve raming blijkt dat er geen substantiële financiële gevolgen zijn, zie onderstaande tabel.

Module	Uitkomst raming	Toelichting
Module methode voorscreening	Geen financiële gevolgen	Hoewel uit de toetsing volgt dat de aanbeveling(en) breed toepasbaar zijn (>40.000 patiënten), volgt uit de toetsing dat [het overgrote deel (±90%) van de zorgaanbieders en zorgverleners al aan de norm voldoet

Werkwijze

AGREE

Deze richtlijnmodule is opgesteld conform de eisen vermeld in het rapport Medisch Specialistische Richtlijnen 3.0 van de adviescommissie Richtlijnen van de Raad Kwaliteit. Dit rapport is gebaseerd op het AGREE II instrument (Appraisal of Guidelines for Research & Evaluation II; Brouwers, 2010).

Knelpuntenanalyse en uitgangsvragen

Tijdens de voorbereidende fase inventariseerde de werkgroep de knelpunten met betrekking tot de technische uitwerking van urinekweken. Tevens zijn er knelpunten aangedragen door ZiNL, NVZ, NVN, NVMM, NVKC, NVKG, NVU, V&VN, ZKN, NVOG, VIG via een schriftelijke knelpuntenanalyse. Een verslag hiervan is opgenomen onder aanverwante producten.

Op basis van de uitkomsten van de knelpuntenanalyse zijn door de werkgroep concept-uitgangsvragen opgesteld en definitief vastgesteld.

Uitkomstmaten

Na het opstellen van de zoekvraag behorende bij de uitgangsvraag inventariseerde de werkgroep welke uitkomstmaten voor de patiënt relevant zijn, waarbij zowel naar gewenste als ongewenste effecten werd gekeken. Hierbij werd een maximum van acht uitkomstmaten gehanteerd. De werkgroep waardeerde deze uitkomstmaten volgens hun relatieve belang bij de besluitvorming rondom aanbevelingen, als cruciaal (kritiek voor de besluitvorming), belangrijk (maar niet cruciaal) en onbelangrijk. Tevens definieerde de werkgroep tenminste voor de cruciale uitkomstmaten welke verschillen zij klinisch (patiënt) relevant vonden.

Methode literatuursamenvatting

Een uitgebreide beschrijving van de strategie voor zoeken en selecteren van literatuur is te vinden onder ‘Zoeken en selecteren’ onder Onderbouwing. Indien mogelijk werd de data uit verschillende studies gepoold in een random-effects model. Review Manager 5.4 werd gebruikt voor de statistische analyses. De beoordeling van de kracht van het wetenschappelijke bewijs wordt hieronder toegelicht.

Beoordelen van de kracht van het wetenschappelijke bewijs

De kracht van het wetenschappelijke bewijs werd bepaald volgens de GRADE-methode. GRADE staat voor ‘Grading Recommendations Assessment, Development and Evaluation’ (zie http://www.gradeworkinggroup.org/). De basisprincipes van de GRADE-methodiek zijn: het benoemen en prioriteren van de klinisch (patiënt) relevante uitkomstmaten, een systematische review per uitkomstmaat, en een beoordeling van de bewijskracht per uitkomstmaat op basis van de acht GRADE-domeinen (domeinen voor downgraden: risk of bias, inconsistentie, indirectheid, imprecisie, en publicatiebias; domeinen voor upgraden: dosis-effect relatie, groot effect, en residuele plausibele confounding).

GRADE onderscheidt vier gradaties voor de kwaliteit van het wetenschappelijk bewijs: hoog, redelijk, laag en zeer laag. Deze gradaties verwijzen naar de mate van zekerheid die er bestaat over de literatuurconclusie, in het bijzonder de mate van zekerheid dat de literatuurconclusie de aanbeveling adequaat ondersteunt (Schünemann, 2013; Hultcrantz, 2017).

GRADE	Definitie
Hoog	er is hoge zekerheid dat het ware effect van behandeling dichtbij het geschatte effect van behandeling ligt; het is zeer onwaarschijnlijk dat de literatuurconclusie klinisch relevant verandert wanneer er resultaten van nieuw grootschalig onderzoek aan de literatuuranalyse worden toegevoegd.
Redelijk	er is redelijke zekerheid dat het ware effect van behandeling dichtbij het geschatte effect van behandeling ligt; het is mogelijk dat de conclusie klinisch relevant verandert wanneer er resultaten van nieuw grootschalig onderzoek aan de literatuuranalyse worden toegevoegd.
Laag	er is lage zekerheid dat het ware effect van behandeling dichtbij het geschatte effect van behandeling ligt; er is een reële kans dat de conclusie klinisch relevant verandert wanneer er resultaten van nieuw grootschalig onderzoek aan de literatuuranalyse worden toegevoegd.
Zeer laag	er is zeer lage zekerheid dat het ware effect van behandeling dichtbij het geschatte effect van behandeling ligt; de literatuurconclusie is zeer onzeker.

Bij het beoordelen (graderen) van de kracht van het wetenschappelijk bewijs in richtlijnen volgens de GRADE-methodiek spelen grenzen voor klinische besluitvorming een belangrijke rol (Hultcrantz, 2017). Dit zijn de grenzen die bij overschrijding aanleiding zouden geven tot een aanpassing van de aanbeveling. Om de grenzen voor klinische besluitvorming te bepalen moeten alle relevante uitkomstmaten en overwegingen worden meegewogen. De grenzen voor klinische besluitvorming zijn daarmee niet één op één vergelijkbaar met het minimaal klinisch relevant verschil (Minimal Clinically Important Difference, MCID). Met name in situaties waarin een interventie geen belangrijke nadelen heeft en de kosten relatief laag zijn, kan de grens voor klinische besluitvorming met betrekking tot de effectiviteit van de interventie bij een lagere waarde (dichter bij het nuleffect) liggen dan de MCID (Hultcrantz, 2017).

Overwegingen (van bewijs naar aanbeveling)

Om te komen tot een aanbeveling zijn naast (de kwaliteit van) het wetenschappelijke bewijs ook andere aspecten belangrijk en worden meegewogen, zoals aanvullende argumenten uit bijvoorbeeld de biomechanica of fysiologie, waarden en voorkeuren van patiënten, kosten (middelenbeslag), aanvaardbaarheid, haalbaarheid en implementatie. Deze aspecten zijn systematisch vermeld en beoordeeld (gewogen) onder het kopje ‘Overwegingen’ en kunnen (mede) gebaseerd zijn op expert opinion. Hierbij is gebruik gemaakt van een gestructureerd format gebaseerd op het evidence-to-decision framework van de internationale GRADE Working Group (Alonso-Coello, 2016a; Alonso-Coello 2016b). Dit evidence-to-decision framework is een integraal onderdeel van de GRADE methodiek.

Formuleren van aanbevelingen

De aanbevelingen geven antwoord op de uitgangsvraag en zijn gebaseerd op het beschikbare wetenschappelijke bewijs en de belangrijkste overwegingen, en een weging van de gunstige en ongunstige effecten van de relevante interventies. De kracht van het wetenschappelijk bewijs en het gewicht dat door de werkgroep wordt toegekend aan de overwegingen, bepalen samen de sterkte van de aanbeveling. Conform de GRADE-methodiek sluit een lage bewijskracht van conclusies in de systematische literatuuranalyse een sterke aanbeveling niet a priori uit, en zijn bij een hoge bewijskracht ook zwakke aanbevelingen mogelijk (Agoritsas, 2017; Neumann, 2016). De sterkte van de aanbeveling wordt altijd bepaald door weging van alle relevante argumenten tezamen. De werkgroep heeft bij elke aanbeveling opgenomen hoe zij tot de richting en sterkte van de aanbeveling zijn gekomen.

In de GRADE-methodiek wordt onderscheid gemaakt tussen sterke en zwakke (of conditionele) aanbevelingen. De sterkte van een aanbeveling verwijst naar de mate van zekerheid dat de voordelen van de interventie opwegen tegen de nadelen (of vice versa), gezien over het hele spectrum van patiënten waarvoor de aanbeveling is bedoeld. De sterkte van een aanbeveling heeft duidelijke implicaties voor patiënten, behandelaars en beleidsmakers (zie onderstaande tabel). Een aanbeveling is geen dictaat, zelfs een sterke aanbeveling gebaseerd op bewijs van hoge kwaliteit (GRADE gradering HOOG) zal niet altijd van toepassing zijn, onder alle mogelijke omstandigheden en voor elke individuele patiënt.

Implicaties van sterke en zwakke aanbevelingen voor verschillende richtlijngebruikers

	Sterke aanbeveling	Zwakke (conditionele) aanbeveling
Voor patiënten	De meeste patiënten zouden de aanbevolen interventie of aanpak kiezen en slechts een klein aantal niet.	Een aanzienlijk deel van de patiënten zouden de aanbevolen interventie of aanpak kiezen, maar veel patiënten ook niet.
Voor behandelaars	De meeste patiënten zouden de aanbevolen interventie of aanpak moeten ontvangen.	Er zijn meerdere geschikte interventies of aanpakken. De patiënt moet worden ondersteund bij de keuze voor de interventie of aanpak die het beste aansluit bij zijn of haar waarden en voorkeuren.
Voor beleidsmakers	De aanbevolen interventie of aanpak kan worden gezien als standaardbeleid.	Beleidsbepaling vereist uitvoerige discussie met betrokkenheid van veel stakeholders. Er is een grotere kans op lokale beleidsverschillen.

Organisatie van zorg

In de knelpuntenanalyse en bij de ontwikkeling van de richtlijnmodule is expliciet aandacht geweest voor de organisatie van zorg: alle aspecten die randvoorwaardelijk zijn voor het verlenen van zorg (zoals coördinatie, communicatie, (financiële) middelen, mankracht en infrastructuur). Randvoorwaarden die relevant zijn voor het beantwoorden van deze specifieke uitgangsvraag zijn genoemd bij de overwegingen. Meer algemene, overkoepelende, of bijkomende aspecten van de organisatie van zorg worden behandeld in de module Organisatie van zorg.

Commentaar- en autorisatiefase

De conceptrichtlijnmodule werd aan de betrokken (wetenschappelijke) verenigingen en (patiënt) organisaties voorgelegd ter commentaar. De commentaren werden verzameld en besproken met de werkgroep. Naar aanleiding van de commentaren werd de conceptrichtlijnmodule aangepast en definitief vastgesteld door de werkgroep. De definitieve richtlijnmodule werd aan de deelnemende (wetenschappelijke) verenigingen en (patiënt) organisaties voorgelegd voor autorisatie en door hen geautoriseerd dan wel geaccordeerd.

Literatuur

Agoritsas T, Merglen A, Heen AF, Kristiansen A, Neumann I, Brito JP, Brignardello-Petersen R, Alexander PE, Rind DM, Vandvik PO, Guyatt GH. UpToDate adherence to GRADE criteria for strong recommendations: an analytical survey. BMJ Open. 2017 Nov 16;7(11):e018593. doi: 10.1136/bmjopen-2017-018593. PubMed PMID: 29150475; PubMed Central PMCID: PMC5701989.

Alonso-Coello P, Schünemann HJ, Moberg J, Brignardello-Petersen R, Akl EA, Davoli M, Treweek S, Mustafa RA, Rada G, Rosenbaum S, Morelli A, Guyatt GH, Oxman AD; GRADE Working Group. GRADE Evidence to Decision (EtD) frameworks: a systematic and transparent approach to making well informed healthcare choices. 1: Introduction. BMJ. 2016 Jun 28;353:i2016. doi: 10.1136/bmj.i2016. PubMed PMID: 27353417.

Alonso-Coello P, Oxman AD, Moberg J, Brignardello-Petersen R, Akl EA, Davoli M, Treweek S, Mustafa RA, Vandvik PO, Meerpohl J, Guyatt GH, Schünemann HJ; GRADE Working Group. GRADE Evidence to Decision (EtD) frameworks: a systematic and transparent approach to making well informed healthcare choices. 2: Clinical practice guidelines. BMJ. 2016 Jun 30;353:i2089. doi: 10.1136/bmj.i2089. PubMed PMID: 27365494.

Brouwers MC, Kho ME, Browman GP, Burgers JS, Cluzeau F, Feder G, Fervers B, Graham ID, Grimshaw J, Hanna SE, Littlejohns P, Makarski J, Zitzelsberger L; AGREE Next Steps Consortium. AGREE II: advancing guideline development, reporting and evaluation in health care. CMAJ. 2010 Dec 14;182(18):E839-42. doi: 10.1503/cmaj.090449. Epub 2010 Jul 5. Review. PubMed PMID: 20603348; PubMed Central PMCID: PMC3001530.

Hultcrantz M, Rind D, Akl EA, Treweek S, Mustafa RA, Iorio A, Alper BS, Meerpohl JJ, Murad MH, Ansari MT, Katikireddi SV, Östlund P, Tranæus S, Christensen R, Gartlehner G, Brozek J, Izcovich A, Schünemann H, Guyatt G. The GRADE Working Group clarifies the construct of certainty of evidence. J Clin Epidemiol. 2017 Jul;87:4-13. doi: 10.1016/j.jclinepi.2017.05.006. Epub 2017 May 18. PubMed PMID: 28529184; PubMed Central PMCID: PMC6542664.

Medisch Specialistische Richtlijnen 2.0 (2012). Adviescommissie Richtlijnen van de Raad Kwalitieit. http://richtlijnendatabase.nl/over_deze_site/over_richtlijnontwikkeling.html

Neumann I, Santesso N, Akl EA, Rind DM, Vandvik PO, Alonso-Coello P, Agoritsas T, Mustafa RA, Alexander PE, Schünemann H, Guyatt GH. A guide for health professionals to interpret and use recommendations in guidelines developed with the GRADE approach. J Clin Epidemiol. 2016 Apr;72:45-55. doi: 10.1016/j.jclinepi.2015.11.017. Epub 2016 Jan 6. Review. PubMed PMID: 26772609.

Schünemann H, Brożek J, Guyatt G, et al. GRADE handbook for grading quality of evidence and strength of recommendations. Updated October 2013. The GRADE Working Group, 2013. Available from http://gdt.guidelinedevelopment.org/central_prod/_design/client/handbook/handbook.html .

Richtlijnendatabase

Urineweginfecties (UWI) bij volwassenen

Urineweginfecties (UWI) bij volwassenen

Methode voorscreening

Uitgangsvraag

Aanbeveling

Overwegingen

Onderbouwing

Achtergrond

Conclusies / Summary of Findings

Samenvatting literatuur

Zoeken en selecteren

Referenties

Evidence tabellen

Verantwoording

Beoordelingsdatum en geldigheid

Initiatief en autorisatie

Algemene gegevens

Samenstelling werkgroep

Belangenverklaringen

Inbreng patiëntenperspectief

Module

Werkwijze

Bijlagen