Study reference

Study characteristics

Patient characteristics

Intervention (I)

control (C)

Follow-up

Outcome measures and effect size

Comments

Kebede, 2018

SR and meta-analysis of RCTs

Literature search up to June 2017

A: Agboola, 2016

B: Arora, 2014

C: Capozza, 2015

D: Fortmann, 2017

E: Cho, 2011

F: Cho, 2017

G: Egede, 2017

H: Holmen, 2014

I: Kim, 2016

J: Kleinmann, 2017

K: Ralston, 2009

L: Tang, 2013

M: Tildesley, 2011

N: Trobjohnsen, 2014

O: Wang, 2017

P: Welch, 2015

Q: Wild, 2016

R: Dario, 2017

S: Hansen, 2017

T: Khanna, 2014

U: Liou, 2014

V: Wakefield, 2014

Study design: RCT parallel or cross-over

Setting and Country: Academic hospital, Germany

Source of funding and conflicts of interest:

No competing interests; information on funding not disclosed

Inclusion criteria SR:

(1) study design (cluster) RCT; (2) patients with poorly controlled type 2 diabetes (HbA1c >7.0%); (3) interventions were technology-based; (4) HbA1c was reported as outcome; (5) control group received usual care; (6) English ublication

Exclusion criteria SR:

(1) Studies targeting either persons with type 1 or both type 1 and 2 diabetes; (2) studies including control groups receiving interventions

22 studies included, 21 studies included in meta-analysis (not C)

Important patient characteristics at baseline:

Not reported per study.

3787 subjects; with 52.6% randomized to intervention groups and 47.4% to control groups.

Groups comparable at baseline?

Cannot be judged.

A: text message to move

B: text message (twice daily) for education, medication reminders and healthier living

C: Text message for education, medication adherence, glucose control, weight and exercise

D: text messages

E: Internet diabetes management

F: health-care provider mediated remote coaching via glucometer and internet

G: telehealth and clinical decision support system

H: diabetes diary app with or without health counselling

I: Internet based glucose monitoring system

J: smartphone app for patients and app + web-based portal for providers

K: web-based care management

L: Online disease management system

M: Internet-based glucose monitoring system

N: diabetes diary app with or without health counselling

O: monitoring via computer/web/mobile phone connected to glucometer via cable

P: internet-based integrated diabetes management system

Q: monitoring through computer/ web-based/mobile phone connected to glucometer via modem

R: videoconferencing

S: Videoconferencing

T: automated telephone support with dialogic telephone card

U: web-based and videoconferencing

V: tele-monitoring

Usual care, standard care, or existing care

End-point of follow-up:

A: 6 months

B: 6 months

C: 6 months

D: 6 months

E: 3 months

F: 6 months

G: 6 months

H: 12 months

I: 6 months

J: 3 months

K: 12 months

L: 12 months

M: 12 months

N: 4 months

O: 6 months

P: 6 months

Q: 9 months

R: 12 months

S: 8 months

T: 3 months

U: 6 months

V: 6 months

For how many participants were no complete outcome data available?

Not reported

Outcome measure

Defined as glycosylated hemoglobin (HbA1c, %). mean difference [95% CI]:

A: -0.07 (-2.04 to 1.90)

B: -0.25 (-0.56 to 0.06)

C: not included in meta-analysis

D: -0.84 (-1.13 to -0.55)

E: -0.30 (-0.50 to -0.10)

F: -0.17 (-0.25 to -0.10)

G: -0.90 (-1.54 to -0.26)

H: -0.30 (-0.81 to 0.21)

I: -0.71 (-0.92 to -0.50)

J: -0.41 (-0.78 to -0.07)

K: -0.81 (-1.50 to -0.12)

L: -0.24 (-0.41 to -0.07)

M: -0.42 (-1.24 to 0.39)

N: -0.20 (-0.66 to 0.26)

O: -0.63 (-0.82 to -0.44)

P: -0.79 (-1.00 to -0.58)

Q: -0.51 (-1.12 to 0.09)

R: 0.0 (-0.18 to 0.19)

S: -0.65 (-0.90 to -0.39)

T: 0.45 (0.02 to 0.88)

U: -0.61 (-0.92 to -0.29)

V: -0.16 (-2.70 to 2.38)

Pooled effect (random effects model):

-0.39 [95% CI -0.51 to -0.26] favoring digital interventions

Heterogeneity (I²): 80.8%

Author’s conclusion:

Participation in digital interventions, particularly web-based interventions, favourably influences HbA1c levels among patients with poorly controlled type 2 diabetes.

Michaud, 2021

SR and meta-analysis of RCTs

Literature search up to October 2018

A: Whitlock, 2000

B: Kim, 2008

C: Yoo, 2009

D: Stone, 2010

E: Castelnuovo, 2011

F: Luley, 2011

G: Orsama, 2013

H: Karhula, 2015

I: Wayne, 2015

J: Agboola, 2016

K: Bentley, 2016

L: Lim, 2016

M: Wild, 2016

N: Cho, 2017

O: Kempf, 2017

P: Hansen, 2017

Q: Hansel, 2017

Study design: RCT [parallel / cross-over]

Setting and Country:

Academic hospital, United States of America

Source of funding and conflicts of interest:

Non-commercial grant, authors report no competing financial interest (information about other conflicts of interest not disclosed)

Inclusion criteria SR:

(1) patients ≥18 years with type 2 diabetes, (2) transmission of physiological or physical data to a health care professional as intervention, (3) usual care with or without additional conventional disease self-management education as comparator, (4) diabetes-related outcomes (weight, HbA1c, lipids, complications)

Exclusion criteria SR:

Not reported

17 studies included

Important patient characteristics at baseline:

N – mean age – %male

A: 28 – 63 y – 83%

B: 40 – 46.7 ±8.4 y – 48%

C: 123 – 58.0 ±8.7 y – 59%

D: 148 – NR – 99%

E: 34 – 53.3 ±8.4 y – 69%

F: 70 – 57.5 ±8.0 y – 50%

G: 56 – 61.8 ±8.2 y – 54%

H: 287 – 66.2 ±8.6 y – 56%

I: 131 – 53.2 ±11.3 y – 28%

J: 126 – 51.4 ±11.6 y – 49%

K: 18 – 52.9 ±8.6 y – 44%

L: 100 – 65.1 ±4.9 y – 75%

M: 321 – 60.9 ±9.8 y – 67%

N: 484 – 53.3 ±8.9 y – 53%

O: 202 – 59.0 ±8.7 y – 37%

P: 165 – 58.1 ±9.3 y – 53%

Q: 120 – 56.5 ±9.4 y – 33%

Groups comparable at baseline?

Large differences in % males, but ages are similar

A: Telemonitoring device, voice and videoconsults

B: Monitoring + feedback through website and cell phone

C: Text messaging, physiological and physical activity monitoring

D: Physiological telemonitoring, telephone calls

E: Weight-loss website on phone, teleconference

F: remote monitoring, weekly reports mailed

G: diabetes self-management promotion program with remote reporting and automated feedback

H: mobile phone health coaching and remote health monitoring

I: health coaching and smartphone interaction

J: text messages in addition to usual care

K: diet and exercise advice and smart wearable with or without email motivational support

L: electronic reporting and monitoring of health values and text message response

M: remote monitoring + feedback

N: internet-based monitoring device (automatic recording and relayed information from care providers)

O: automatic reporting sale, step counter and glucometer + personalized online portal

P: videoconferencing, remote monitoring of physiological data

Q: web-based nutritional support tool; feedback provided based on the input step count

Usual care with or without additional conventional disease self-management education.

End-point of follow-up:

A: 3 months

B: 6 months

C: 3 months

D: 6 months

E: 12 months

F: 6 months

G: 10 months

H: 12 months

I:6 months

J: 6 months

K: 4 months

L: 6 months

M: 9 monhts

N: 6 months

O: 12 months

P: 8 months

Q: 4 months

For how many participants were no complete outcome data available?

A: 0%

B: 15%

C: 10%

D: 9%

E: 62%

F: 3%

G: 18%

H: 10%

I: 26%

J: 0%

K: 26%

L: 15%

M: 11%

N: 8%

O: 17%

P: 16%

Q: 11%

Outcome measure-1

Defined as glycosylated hemoglobin (HbA1c, %).

mean difference [95% CI]:

A: -0.40 (-1.47 to 0.67)

B: -1.09 (-1.34 to -0.84)

C: -0.70 (-0.76 to -0.64)

D: -0.70 (-0.77 to -0.63)

E: not included in meta-analysis

F: -1.0 (-1.27 to -0.73)

G: -0.41 (-0.89 to 0.07)

H: -0.14 (-0.38 to 0.10)

I: -0.05 (-0.13 to 0.03)

J: -0.22 (-0.32 to -0.12)

K: -2.10 (-3.96 to -0.24)

L: -0.50 (-0.57 to -0.43)

M: -0.60 (-0.63 to -0.57)

N: -0.20 (-0.21 to -0.19)

O: -0.80 (-0.85 to -0.75)

P: not included in meta-analysis

Q: -0.50 (-0.80 to -0.20)

Pooled effect (fixed/random effects not reported):

-0.30 [95% CI -0.31 to -0.29] favoring telemonitoring

Heterogeneity (I²): 99.1%

Authors’ conclusion:

inform telemonitoring design for future diabetes management to enhance access to care, ease of use, and to improve patient engagement

Verma, 2021

SR and meta-analysis of  RCTs and clinical trials

Literature search up to August 2020

A: Cheng, 2017

B: Vinitha, 2019

C: Kusnanto, 2019

D: Adikusuma, 2018

E: Dong, 2018

F: Goodarzi, 2012

G: Gunawardena, 2019

H: Kumar, 2018

I: Kim, 2006

J: Jarab, 2012

K: Jain, 2018

L: Kleinman, 2017

M: Lee, 2018

N: Sun, 2019

O: Oh, 2003

P: Patnaik, 2014

Q: Sadanshiv, 2020

R: Islam, 2015

Study design: RCT [parallel / cross-over]

Setting and Country: Public Health department, India

Source of funding and conflicts of interest:

None.

Inclusion criteria SR:

RCT or clinical trial; (2) reporting on outcomes after mHealth interventions (mHealth app, text message or phone calls); (3) targeting patients with diabetes type 2; (4) study conducted in Asian population and published in English language

Exclusion criteria SR:

(1) diabetes patients wit severe complications (e.g. diabetic foot, heart disease); (2) mixed population of type 1 and 2 diabetes; (3) pregnant patients with type 2 diabetes

18 studies included (13 for quantitative analysis of main outcome; not H, J, M, P, R)

Important patient characteristics at baseline:

Not reported per study.

Groups comparable at baseline?

Cannot be judged.

A: Phone calls

B: text message

C: mobile application

D: text message

E: mobile application

F: text message

G: mobile application

H: text message

I: text message

J: phone calls

K: phone calls

L: mobile application

M: mobile application

N: mobile application

O: phone calls

P: text message +phone calls

Q: text message

R: text message

Usual or conventional care

End-point of follow-up:

A: 5 months

B: 24 months

C: 3 months

D: 6 months

E: 12 months

F: 3 months

G: 6 months

H: 12 months

I: 6 months

J: 6 months

K: 6 months

L: 6 months

M: 12 months

N: 6 months

O: 3 months

P: 3 months

Q: 6 months

R: 6 months

For how many participants were no complete outcome data available?

A: 41 (16.9%)

B: 30 (12.1%)

C: -

D: -

E: 1 (0.8%)

F: 18 (18%)

G: 15 (22.4%)

H: 103 (10.8%)

I: 9 (15%)

J: 15 (8.8%)

K: 9 (3%)

L: 11 (12.1%)

M: 43 (29.1%)

N: -

O: 12 24%)

P: 45 (45%)

Q: 18 (5.6%)

R: 6 (2.5%)

Outcome measure-1

Defined as glycosylated haemoglobin (HbA1c, %). mean difference [95% CI]:

A: -0.60 (-1.17 to -0.03)

B: -0.40 (-0.77 to -0.03)

C: -0.30 (-1.03 to 0.43)

D: -1.10 (-1.54 to -0.66)

E: -1.70 (-2.22 to -1.18)

F: -0.40 (-0.88 to 0.08)

G: 0.90 (0.49 to 1.31)

H: not included in meta-analysis

I:-0.70 (-1.32 to -0.08)

J: not included in meta-analysis

K: 0.0 (-0.43 to 0.43)

L: -0.30 (-0.84 to 0.24)

M: not included in meta-analysis

N: 0.0 (-0.29 to 0.29)

O: -1.30 (-1.91 to -0.69)

P: not included in meta-analysis

Q: -0.10 (-0.35 to 0.15)

R: not included in meta-analysis

Pooled effect (random effects model):

-0.44 [95% CI -0.79 to-0.10] favoring mHealth.

Heterogeneity (I²): 87%

Authors’ conclusion:

mHealth interventions can be seen as a suitable medium to improve the glycemic index among diabetic patients. The available literature about assessing the use of mHealth is limited and inconsistent to draw any robust conclusions.

Yaminne, 2022

SR and meta-analysis of  studies with comparative design

Literature search up to March 2020

A: Wilbright, 2004 (n = 140)

B: Rasmussen, 2015 (n = 374)

C: Smith-Strøm, 2018 (n = 182)

D: Jafary, 2020 (n = 120)

Study design:

RCTs (parallel design) and clinical trials

Setting and Country:

Academic hospital, Lebanon

Source of funding and conflicts of interest:

None.

NB: study D will not be analyzed as it does not compare remote healthcare delivery with regular healthcare activities; rather it compares home-based care to hospital-based care.

Inclusion criteria SR:

(1) intervention including any type of remote consultation, (2) comparison including any type of face-to-face consultation (e.g. home care or hospital/medical center care)

Exclusion criteria SR:

(1) wounds not being diabetic foot ulcers

4 studies included

Important patient characteristics at baseline:

816 patients total

I: 387 (47.4%)

C: 429 (52.6%)

Mean age

A: I: 55.1 | C: 56.5

B: I: 66.8 | C: 66.7

C:I: 67.2 | C: 65.5

Sex (% male):

A: I: 45% | C: 55%

B: I: 78.2% | C: 71.3%

C: I: 74.5% | C: 73.9%

Groups comparable at baseline?

Yes, though participants from study A are younger and have less males

A: Telemedicine consultation

B: Telemedical monitoring (2 consultations at patient’s home) and 1 at outpatient clinic

C: telemedicine follow-up care

A: face-to-face care at diabetes foot program

B: 3 outpatient clinic visits

C: standard outpatient care

End-point of follow-up:

A: 3 months

B: 3 months

C: 12 months

For how many participants were no complete outcome data available?

Not reported

Healing rate

Effect measure: RR [95% CI]:

A: 0.93 [0.71 to 1.21]

B: 0.97 [0.86 to 1.10]

C: 1.05 [0.90 to 1.22]

Pooled effect (random effects model): 0.99 [95% CI 0.91 to 1.09]

Favoring telemedicine.

Heterogeneity (I²): 0%

Time to heal

A: I: 34 ±29.3 | C: 45.5 ± 43.4

B: I: 74 | C: 91

C: I: 102 | C: 114

Overall mean:

I: 73 ± 24.1 days

C: 83.5 ± 28.4 days

Amputation rate

Effect measure: RR [95% CI]:

B: 0.76 [0.44 to 1.30]

C: 0.36 [0.13 to 0.97]

Pooled effect (random effects model): 0.59 [95% CI 0.29 to 1.18]

Favoring telemedicine.

Heterogeneity (I²): 41%

Mortality rate

Effect measure: RR [95% CI]:

B: 7.50 [0.95 to 59.39]

C: 0.94 [0.28 to 3.12]

Pooled effect (random effects model): 2.25 [95% CI 0.28 to 18.13]

Favoring face-to-face care delivery.

Heterogeneity (I²): 68%

Authors’ conclusion:

treating DFU via TM could be at least as effective as to face-to-face attendance.

Not researched (selective reporting?): ulcer recurrence rate, ulcer transfer rate, infection rate

Kebede, 2018

Yes, objective stated with selection criteria for the parts of the PICO

No, search strategy not presented, search date to June 2017

No, only PRISMA flowchart presented

Partly, table 1 provides study characteristics, but not of the population in the studies

Not applicable

Yes, figure 2 risk of bias table (Cochrane tool)

Unclear, as population characteristics are poorly presented

Yes, supplementary figure 1 and tests.

No, declaration of no competing interests for review, but not reported for individual RCTs

Michaud, 2021

Yes, clear objectives stated with clear PICO

Yes, search period (to October 2018) and strategy reported

Partly, only PRISMA flowchart and overview of included studies

Yes, Table 1 characteristics of included studies

Not applicable

Yes, using the Jadad scale (presented in table 1)

Unclear, I² results in 99.1%, possible clinical heterogeneity

Yes, funnel plot and Egger’s model

No, declaration of no competing financial interests for review, but not reported for individual RCTs

Verma, 2021

Yes, objective stated with selection criteria for the parts of the PICO

Yes, search period (to August 2020) and strategy reported

Yes, in annexure 1.

Partly, table 2 provides study characteristics, but not of the population in the studies

Not applicable

Yes, figure 1 risk of bias table (Cochrane tool)

Unclear, I² results in 87%, possible clinical heterogeneity

Partly, visual inspection of funnel plot only

No, declaration of no conflicts of interests for review, but not reported for individual RCTs

Yammine, 2022

Partly, research question clear but broad subparts of PICO.

No, search strategy insufficient, search date to March 2020

No, only PRISMA flowchart presented

Yes, Table 1 characteristics of included studies

Not applicable

Yes, Joanna Briggs Institute critical appraisal tool

No, last study different intervention group; and I² 72.2% for first outcome.

No, no funnel plots and no tests.

No, declaration of no conflicts of interests for review, but not reported for individual RCTs

Study reference

Study characteristics

Patient characteristics

Intervention (I)

Comparison / control (C)

Follow-up

Outcome measures and effect size

Direction of effect

Comments

Leong, 2022

Type of study: Open-label RCT

Setting and country: Taiwan

Funding:

Reported

Conflicts of interest:

Reported

Inclusion criteria:

(1) Patients ≥20 years, (2) at least one HbA1c measurement ≥6% in the past 6 months, (3) possessed smartphone with LINE app

Exclusion criteria:

(1) Gestational diabetes, (2) cognitive impairment, (3) controlled diabetes through dietary control without medication

N total at baseline:

Intervention (I): 91

Control (C): 90

Important prognostic factors:

Age ± SD:

I: 59.0 ± 11.4

C: 58.1 ± 11.9

Sex (% male):

I: 73.6% | C: 63.3%

Groups comparable at baseline? Yes

TMU-LOVE program in addition to usual care. The program consisted of educational videos, frequently asked questions, one-on-one chat room, graphic messages, and the ability to direct patients to certain websites. Physicians could send educational videos and communicate with patients by text message, voice, or video call. The program was designed to last for a study duration of 3 months (i.e., 12 weeks), with two or three videos sent every week and a care message sent every 2 weeks to the patients in the intervention group.

Usual care, including patient consultations with physicians, access to nurses in the outpatient services, as well as medication consultations with pharmacists upon receiving prescriptions. Physicians also referred patients for consultations with certified diabetes educators (CDEs) when necessary.

Length of follow-up:

3 months

Loss-to-follow-up:

I: 9 | C: 8

Did not return to clinics (n=3 for I, n = 4 for C); Unwilling to complete post-test (n=6 for I, n = 4 for C)

Incomplete outcome data:

No incomplete outcome data, 91 patients in the IG and 90 patients in the CG were analysed.

Effectiveness

HbA1c (mean % ± SD)

Intervention: 7.0 ± 0.9

Control: 6.7 ± 0.7

Knowledge (measured using the Simplified Diabetes Knowledge Scale (SDKS)) (mean % correctness ± SD)

Intervention: 76.7 ± 11.7

Control: 73.2 ± 12.6

Patient focus

Patient attitude towards diabetes (mean score ± SD)

(measured using the Chinese version of the Diabetes Care Profile-Attitudes Toward Diabetes Scales (DCP-ATDS))

Intervention: 3.8 ± 0.5

Control: 3.7 ± 0.5

Self-care activities (mean score ± SD)

(measured using the Chinese version of the Summary of Diabetes Self-Care Activities (SDSCA))

Intervention: 3.97 ± 1.18

Control: 3.86 ± 1.46

HbA1c: no difference.

Knowledge: no difference.

Patient attitude: significant increase in IG compared with baseline (no comparison made between IG and CG)

Self-care activities: significant increase in IG compared with baseline (no comparison made between IG and CG)

Study also reports utility rates of the educational videos and performed a subgroup analysis to measure the effects of health literacy. These data were not reported here.

Di Molfetta, 2022

Type of study: Prospective RCT

Setting and country: Three tertiary referral centres for diabetes in Italy

Funding:

Reported

Conflicts of interest:

Reported

Inclusion criteria:

(1) Age 18-70 years; (2) Insulin-treated diabetes, (3) diagnosis of diabetes for at least 1 year, (4) inadequate glycaemic control, (5) ability and willingness to carry out standard self-monitoring blood glucose

Exclusion criteria:

(1) complications of diabetes, (2) comorbidities, (3) diagnosis of active neoplasia within the last 5 years, (4) pregnancy or intervention to become pregnant

N total at baseline:

Intervention (I): 62

Control (C): 61

Important prognostic factors:

Age ± SD:

I: 47.15 ± 14.54

C: 45.21 ± 14.76

Sex (% male):

I: 53.2 % | C: 55.7 %

Groups comparable at baseline? Yes

Patients received prompt feedback about their blood glucose levels and therapy suggestions from the study staff via phone/SMS, when appropriate.

Standard self-monitoring blood glucose, reported on paper daily, without remote assistance.

Length of follow-up:

6 months

Loss-to-follow-up:

I: 7 | C: 19

Withdrew from the trial (Article: Most common reasons for declining participation in the trial were poor compliance with self-testing of blood glucose and/or unwillingness to be engaged in an intensive monitoring program involving use of smartphone and device.)

Incomplete outcome data:

138 patients were randomised. 15 were excluded because on CSII, resulting in 123 patients included in the final analysis.

Effectiveness

HbA1c (% change)

Intervention: -0.38%

Control: +0.08%

Mean blood glucose

Blood glucose

Fasting blood glucose

Postprandial blood glucose

Postprandial blood glucose excursion

No difference over time in IG (14 days following first visit, 14 days preceding 3 months, and 14 days preceding 6 months).

Body weight change

No difference between baseline and six months in either IG or CG patients.

Waist circumference

No difference between baseline and six months in either IG or CG patients.

Hypoglycemia

Not reported.

HbA1c: significant reduction in IG between baseline and six months.

No difference in other parameters.

No comments.

Yang, 2022

Type of study: RCT

Setting and country: Community health centre, China

Funding:

Reported

Conflicts of interest:

Reported

Inclusion criteria:

(1) Newly diagnosed type 2 diabetes mellitus within the past 3 months; (2) HbA1c of 6.5-7.5%; (3) age 40-60 years, (4) systolic blood pressure of 90-120 mmHg and diastolic blood pressure of 60-90 mmHg

Exclusion criteria:

(1) type 1 diabetes, (2) comorbidities, (3) inability to understand or comply with instructions, (4) lactating, pregnant, or planning to be pregnant, (5) serious disease resulting in loss to follow-up, (6) smoking, (7) alcoholism, (8) attending another clinical trial

N total at baseline:

Intervention (I): 50

Control (C): 50

Important prognostic factors²:

Age ± SD:

I: 65.09 ± 6.06

C: 67.34 ± 5.33

Sex (% male):

I: 38.30% | C: 42.00%

Groups comparable at baseline? Yes

Telemedicine management, using a mobile phone to manage patients’ health condition remotely. Patients would get reminders for recording and uploading all daily meals and snacks, weight, fasting glucose, blood pressure and medication every day via WeChat, and the nutrition platform would check the data automatically and give an immediate warning message or feedback if the patient ate too much high glycemic index (GI) value food or saturated fat. A 40-minute phone visit was conducted every month to educate patients about diet or exercise, such as eating low GI value food, moderate aerobic physical activity, or resistance exercise to increase mass of muscle and received a dietary guideline.

Regularly routine intervention; patients came to see the outpatient doctor per standard of care during the study period and received simple dietary advise or exercise recommendation each visit.

Length of follow-up:

12 months

Loss-to-follow-up:

I: 3 | C: 0

Did not upload data or return to outpatient department

Incomplete outcome data:

No incomplete outcome data

HbA1c (mean % ± SD)

Intervention: 6.18 ± 0.73

Control: 7.34 ± 1.68

Fasting blood glucose (mean mmol/L ± SD)

Intervention: 6.10 ± 0.83

Control: 7.07 ± 1.43

Biochemical parameters

Total cholesterol (mean mmol/L ± SD)

I: 4.61 ± 0.95 | C: 5.02 ± 1.03

Physical and body composition parameters

Weight (mean kg ± SD)

I: 58.25 ± 8.23 | C: 59.43 ± 9.91

BMI (mean kg/m2 ± SD)

I: 23.66 ± 2.86 | C 24.69 ± 3.51

Waist circumference (mean cm ± SD)

I: 86.22 ± 4.80 |C: 90.92 ± 5.11

Diastolic BP (mean mmHg ± SD)

I: 75.85 ± 7.30 | C: 75.22 ± 7.59

Systolic BP (mean mmHg ± SD)

I: 123.21 ± 12.61 | C: 128.88 ± 10.28

Adverse events

There were no adverse events reported during the study.

Quality of life (SF-36)

Intervention: 71.38 ± 14.68

Control: 69.96 ± 13.92

Costs

Total costs 1 month (mean ¥ ± SD)

Intervention: 193.48 ± 21.71

Control: 331.67 ± 56.37

Physical and body composition parameters: significant improvement in IG, except lean body mass change and muscle mass change. (body fat percentage, body fat mass, lean body mass, body water and muscle mass not reported in this table)

Biochemical parameters: all significant improvement in IG. (Triglicerides, LDL, and HDL not reported in this table)

Quality of life:

no significant difference.

Costs:

Significant lower in IG.

Patients had to be between 40 and 60 years but the mean age is above 60. Protocol states inclusion of patients 30 to 75 years à risk of bias.

Study also performed correlation analysis, these data is not presented here.

Li, 2021

Type of study:

Cost-effectiveness analysis, random

Setting and country: Tertiary care hospital specific to diabetes in China

Funding:

Reported

Conflicts of interest:

Reported

Inclusion criteria:

(1) Patients ≥18 years, (2) type 2 diabetes, (3) registered in the clinical database for enrolment and follow-up of patients with DM living in the territories served by Community Health Care

Exclusion criteria:

(1) No interest, (2) no smartphone

N total at baseline:

Intervention (I): 130

Control (C): 85

Important prognostic factors:

Age ± SD:

I: 47.5 ± 9.88

C: 46.7 ± 10.11

Sex (% male):

I: 67.7% | C: 63.5% M

Groups comparable at baseline? Yes

Mobile-based intervention, extending medical services from hospitals to families. The functions of the app include authentication, appointment registration, electronic medical record access, medication reminders, results checks, blood glucose monitoring and threshold alarms, diet and exercise monitoring and suggestions, health education, telephone follow-up, real-time communication with the management team, and peer support and communication.

Standard medical care every three months.

Length of follow-up:

12 months

Loss-to-follow-up:

No loss to follow-up

Incomplete outcome data:

NR

Effectiveness

HbA1c (% control rates)

Intervention: 74.6%

Control: 47.1%

Costs

Costs at 12-month follow-up (mean ¥ ± SD)

Intervention: 7754.03 ± 7118.53

Control: 12428.06 ± 11122.32

Incremental costs

-605.68 ¥ per patient/year

ICER

-22.02 ¥  per patient/year

No differences between controlled and uncontrolled HbA1c.

HbA1c: significant improvement in IG

Costs: significant less costs in IG

María Gómez, 2022

Type of study:

Open non-blinded RCT

Setting and country: Tertiary referral hospital, Colombia

Funding:

Not reported

Conflicts of interest:

Reported

Inclusion criteria:

(1) adults with type 2 diabetes mellitus, (2) using insulin, (3) HbA1c ≥ 6.5%, (4) access to technology used

Exclusion criteria:

(1) patients admitted for acute diabetes decompensation or acute coronary syndrome, (2) under glucocorticoid treatment within the last 3 months, (3) using real-time or intermittent continuous glucose monitoring, (4) visual impairment, (5) pregnant, (6) psychiatric illness or cognitive impairment limiting the likelihood of device use

N total at baseline:

Intervention (I): 42

Control (C) : 45

Important prognostic factors:

Age ± SD:

I: 58.6 ± 10.6

C: 60.5 ± 12.8

Sex (% male):

I: 55.0% | C: 54.2% M

Groups comparable at baseline? Yes, except for the proportion of patients with obesity (IG 46% vs CG 29%).

Patients were assessed by nutrition service and a telemedicine platform (ClouDi) was used to record and adjusted insulin doses. The platform consists of a web version, a version for mobile devices, and a desktop application. This allowed glucose measurements to be uploaded, and these were reviewed weekly by the members of the research group who were responsible for adjusting the therapy. Patients received pop-up notifications about changes.

Standard care of the institution and assessment by nutrition service. They also received education in the management of diabetes medications and diet by nutrition and nursing before discharge from the hospital.

Length of follow-up:

3 months

Loss-to-follow-up:

I: 3 | C 3

Died before treatment (n = 1 for I); died during follow-up (n = 2 for I, n = 3 for C)

Incomplete outcome data:

I: 14 | C: 20

• Communication was lost (n=3 for I; n = 4 for C)
• Discontinued intervention (n=7 for I; n = 8 for C)
• Patient request (n=2 for I; n = 5 for C)
• Death (n=2 for I; n = 3 for C)

Effectiveness

HbA1c (%), means and mean difference in change

Intervention: 7.16

Control: 8.81

MD: -2.03% (95%CI -3.39 to -0.68)

Hypoglycaemia (≥1 episodes) (%)

Level 1 (<3.0 mmol/L [<70 mg/dL])

Intervention: 52.5

Control: 52.3

RR 1.01 [0.67; 1.51]

Level 2 (<3.8 mmol/L [<54 mg/dL])

Intervention: 75.0

Control: 72.3

RR 1.03 [0.80; 1.33]

Level 3 or severe hypoglycaemia

Intervention: 15.0

Control: 25.6

RR 0.59 [0.24; 1.44]

Weight reduction (MD kg [95%CI])

I: 3.63 [1.28 to 5.97]

C: 1.64 [-0.28 to 3.56]

BMI change (MD kg/m2 [95%CI]

Intervention: 1.20 [0.41 to 1.98]

Control: 0.53 [-0.26 to 1.32]

Patient focus

Satisfaction

(measured using the ITSQ questionnaire)

I: 73.8 ± 11.1| C: 42.8 ± 16.7

HbA1c: significant reduction in IG

Hypoglycaemia: no difference

Weight: significant decrease in IG

BMI:

significant decrease in IG

Patient satisfaction: significant higher in IG

Turnin, 2021

Type of study:

Open-label RCT

Setting and country:

16 investigation sites in France

Funding: Reported

Conflicts of interest: Reported

Inclusion criteria:

(1) 18 years or above, (2) documented medical history of type 2 diabetes, with or without insulin treatment, (3) recent HbA1c value >6.5% and ≤10%, (4) active internet connection at home

Exclusion criteria:

(1) severe or active comorbidities, (2) reduced mobility, (3) serious eating disorders, (4) who had undergone bariatric surgery

N total at baseline:

Intervention (I): 141

Control (C): 141

Important prognostic factors:

Age ± SD:

I: 59.8 ± 9.2

C: 59.3 ± 10.0

Sex (% male):

I: 64.1% | C: 62.2% M

Groups comparable at baseline? Yes

Home telemonitoring device, that combined biomedical data sensors with educational software. Participants received three tele-educational software programs: (1) Nutri-Kiosk (set of self-learning quizzes for formative assessment based on nutritional knowledge); (2) Acti-Kiosk (support in starting physical activity (assessment, information and videos)); (3) Nutri-Educ (personalized nutritional educational software application that meets international clinical recommendations). Patients in the IG sent the data to a platform weekly and had free access to this information and their monitoring summary. Physicians could see the data, received alerts about certain events, and could communicate with the patient. No face-to-face consultations were scheduled in advance.

Face-to-face consultations in accordance with standard practices.

Length of follow-up:

12 months

Loss-to-follow-up:

I: 13 | C: 6

• Refusal to continue (n = 8 for I; n = 1 for C)
• Lost to follow-up (n = 2 for I
• Withdrawal of consent (n = 2 for I; n = 1 for C)
• Unknown reason (n = 1 for both I and C)
• Protocol violations (n = 2 for C
• Emergence of an exclusion criteria (n = 1 for C)

Incomplete outcome data:

No incomplete outcome data

Effectiveness

HbA1c (mean % ± SD)

Intervention: 7.4 ± 1.0

Control: 7.6 ± 1.0%

BMI change (mean kg/m2 ± SD)

Intervention: -0.30 ± 1.9

Control: 0.06 ± 1.3

Waist circumference

Adjusted intergroup difference -1.67 cm [-3.27; -0.06] in favour of the IG

Patient focus

Satisfaction (measured using an ad hoc questionnaire)

97.4% was completely satisfied or rather satisfied with device use and telemonitoring data synthesis.

Device-generated assistance was deemed positive by 88.2% of subjects for the daily management of diabetes.

Health professional focus

Satisfaction (measured using an ad hoc questionnaire)

85% of the investigators reported having completely integrated the web application functions and over 80% found it easy to very easy to use, in terms of both patient records and telemonitoring synthesis reports. 82.3% were keen to continue using the device.

HbA1c: no difference

BMI: no difference

Waist circumference: significant reduction in IG

Satisfaction: patients in IG were satisfied (no comparison made with CG)

Satisfaction: HCPs in IG were satisfied (no comparison made with CG)

Study performed baseline HbA1c level stratification before patients were randomly assigned.

Study is funded by SANOFI laboratory for provision of blood glucose monitors, and some of the authors received congress invitations and consultancy fees from the company.

Hu, 2021

Type of study: RCT

Setting and country: Single hospital in China

Funding:

Reported

Conflicts of interest:

Not reported

Inclusion criteria:

(1) diagnosis of T2DM more than 3 months prior, (2) age 18-70 years, (3) ability to use a smartphone and blood-glucose meter, (4) voluntary participation

Exclusion criteria:

(1) severe heart, liver, or renal insufficiency, (2) history of cancer, coronary heart disease, or cerebral infarction, (3) hyper- or hypothyroidism, (4) severe infection, (5) current treatment with drugs that affect blood-glucose levels, (6) mental illness, communication disorder, or blindness, (6) major trauma, major surgery, or any severe illness

N total at baseline:

Intervention (I): 74

Control (C): 74

Important prognostic factors:

Age ± SD:

I: 50.04 ± 5.76

C: 52.21 ± 8.38

Sex (% male):

I: 71% | C: 61% M

Groups comparable at baseline? Yes

Monthly diabetes education from a diabetes specialist nurse pertaining to self-monitoring of blood-glucose levels, dietary habits, importance

of medication timing, and physical activity.

Telemedicine, including a wireless intelligent blood-glucose meter for monitoring blood-glucose levels, transmit data, and upload information on diet, exercise frequency, and oral medications. It was possible to communicate between the hospital and patient. Blood-glucose, exercise frequency, and dietary were uploaded to the telemedicine platform each week. This was transmitted to a telemedicine system. This allowed the researchers to view the patients’ blood-glucose levels, insulin dosage, physical activity frequency, and meal data. The researchers contacted the patients, if necessary, via WeChat (Tencent), telephone, or other online connections.

Monthly diabetes education from a diabetes specialist nurse pertaining to self-monitoring of blood-glucose levels, dietary habits, importance

of medication timing, and physical activity.

Patients used an intelligent blood-glucose meter that did no upload blood-glucose data via the network. These patients received conventional outpatient treatment once a month

from department endocrinologists and nurses. Blood-glucose levels were uploaded once a month by the doctors and nurses.

Length of follow-up:

6 months

Loss-to-follow-up:

Intervention: 2

• 1 withdrew because glucometer failed to upload blood-glucose data
• 1 unable to return to hospital on time

Control: 4

• 1 developed nasopharynhea; carcinoma
• 1 had liver transplantation
• 2 required a difference blood glucose meter due to finger pain

Incomplete outcome data:

No incomplete outcome data

Effectiveness

HbA1c (mean % ± SD)

Intervention: 7.38 ± 1.67

Control: 8.22 ± 2.04

Hypoglycaemia (n patients (%))

Intervention: 18 (25%)

Control: 29 (41.4%)

UACR (mean mg/mmol ± SD)

Intervention: 4.36 ± 1.45

Control: 4.56 ± 1.11

Carotid plaque (n patients (%))

Intervention: 27 (37.5%)

Control: 27 (38.6%)

HbA1c: significant reduction in IG

Hypoglycaemia: significant reduction in IG

Urinary albumin to creatinine ratio: no difference

Carotid plaque: no difference

Data after 3 months also described in the article, not reported here.

Conflicts of interest not reported.

Timurtas, 2022

Type of study:

Stratified, randomized, assessor-blind, controlled, pragmatic trial, with three arms.

Setting and country: Single centre trial in Turkey

Funding:

Reported

Conflicts of interest:

Reported

Inclusion criteria:

(1) between 30 and 65 years, (2) type 2 diabetes diagnosed by an endocrinologist, (3) possess a smartphone

Exclusion criteria:

(1) participation in an exercise program before, (2) unable to use a smartphone or wearable smartwatch independently, (3) health condition other than T2D associated with disordered glucose metabolism, (4) diagnosed cognitive, mental health, neurological, or orthopaedic condition

N total at baseline:

Intervention (I): 60

Control (C): 30

Important prognostic factors:

Age ± SD:

I-SP: 51.6 ± 7.8

I-SW: 51.4 ± 8.1

C: 51.8 ± 8.0

Sex (% male): Not reported

Groups comparable at baseline? Not reported by the authors, but probably yes.

As control group, plus:

An online platform to support the delivery, tracking, and adaption of exercise programs.

IG SP: three one-on-one training sessions; after that push exercise reminders (for which participants decided the frequency). Message feature of the app for communication between participants and physiotherapists as needed. Step count in smartphone. Extra notifications when participants did not check in exercises. Possibility for viewing progress daily, weekly, and monthly.

IG SW: three one-on-one training sessions. After that participants accessed their DIABETEX account through smartwatch and could view their personal exercise program. This permitted real-time remote tracking. Automatic push notifications when the sensors did not detect sufficient heart rate elevation or acceleration.

Prescribed exercise training composed of aerobic, strengthening, balance, and stretching exercises to 3x/week, starting with a 30-minute session building up to a one-hour session for a duration of 12 weeks. The programs were designed by physiotherapists as per the needs of each individual. Each exercise session included a warm-up, aerobic exercises with treadmill or cycling, resistance exercises with elastic band and dumbbell, balance and flexibility exercises, and a cool down. The intensity of aerobic exercise was determined by the target heart rate, measured with an oximeter, according to the Karvonen method.

Length of follow-up:

12 weeks

Loss-to-follow-up:

Intervention SP: 3

• familial reasons
• surgery

Intervention SW: 4

• holiday
• familial reasons
• another city

Control: 2

• holiday
• busy with work

Incomplete outcome data:

Dropped out after randomization but before the intervention started for reasons unrelated to the study group assigned.

à 2 in each group

Efficiency

HbA1c (mean % ± SD)

Intervention (n=49): 7.1 ± 1.5

Control (n=26): 6.5 ± 0.7

Patient focus

Self-efficacy

Intervention:

• 36% improved
• 48% unchanged
• 16% declined

Control:

• 36% improved
• 39% unchanged
• 25% declined

HbA1c: Significance level not provided

Self-efficacy: significance level not provided

Stratification by age (3 categories) and sex yielded 6 strata and randomization in blocks of

6 was used to assign people to groups.

Gender of participants is not reported.

Avdal, 2020

Type of study:

RCT

Setting and country: Single centre university hospital in Turkey

Funding:

Not reported

Conflicts of interest:

Reported

Inclusion criteria:

(1) diagnosed with type 2 diabetes at least 6 months prior (having had diabetes education, (2) taking oral antidiabetic drugs (OADs) and insulin, (3) 18 years of age or older. (4) BMI > 29.0, (5) LDL > 130 mg/dl, (6) HDL > 35 mg/dl, (7) Systolic blood pressure > 130 mmHg, (8) Diastolic blood pressure > 110 mg/dl, (9) fasting blood glucose > 140 mg/dl, (10) postprandial blood glucose > 160 mg/dl, (11) agreeing to receive continuing diabetes education, (12) participating voluntarily, (13) able to use computers and the internet.

Exclusion criteria:

(1) severe retinopathy, (2) severe neuropathy

N total at baseline:

Intervention (I): 40

Control (C): 40

Important prognostic factors:

Age ± SD: Not reported

Sex (% male): Not reported

Groups comparable at baseline? Yes according to study authors

2-h course on how to use the internet program. After, every participant was tracked weekly to assess usage of program. A second course was given by the researchers to those who could not use the program.

Diabetes diagnosis forms were sent online to all the participants in the experimental group. Participants saved their data and sent it to the researcher. Using this information, the researcher sent each participant a unique slideshow or media component that included information on how to meet their self-care needs. An FAQ section was available. Participants saved their daily or weekly blood glucose levels on the online data entry screen and were monitored and frequently advised which LDL, HDL, and systolic and diastolic blood pressure levels were recommended by the doctors.

2-h course on how to use the internet program. After, every participant was tracked weekly to assess usage of program. A second course was given by the researchers to those who could not use the program.

Training and monitoring of control group continued at the outpatient clinic, receiving education by diabetes nurses and training materials were prepared. Monitoring of patients in the control group was conducted by the researcher by using patients’ medical records from the Endocrinology Outpatient Clinic every 3 months.

Length of follow-up:

12 months

Loss-to-follow-up:

Not reported

Incomplete outcome data:

Not reported

Effectiveness

BMI (mean kg/m2 ± SD)

Intervention: 24.8 ± 0.231

Control: 28.6 ± 1.621

LDL (mean mg/dl ± SD)

Intervention: 95 ± 10

Control: 130 ± 12

HDL (mean mg/dl ± SD)

Intervention: 50 ± 10

Control: 39 ± 13

Systolic blood pressure (mean mmHg ± SD)

Intervention: 80 ± 9

Control: 120 ± 10

Diastolic blood pressure (mean mmHg ± SD)

Intervention: 80 ± 5

Control: 95 ± 5

Fasting blood glucose (mean mg/dl ± SD)

Intervention: 120 ± 10

Control: 138 ± 12

Postprandial blood glucose (mean mg/dl ± SD)

Intervention: 148 ± 10

Control: 168 ± 11

BMI: significant reduction in IG.

LDL: significant reduction in IG.

HDL: significant reduction in IG.

SBP: significant reduction in IG.

DBP: significant reduction in IG.

FBG: significant reduction in IG.

PPBG: significant reduction in IG.

Data from the experimental group were collected online while data belonging to the control group were collected by the researcher from patients’ medical records in the Endocrinology Outpatient Clinic.

No table 1 with patient characteristics.

Loss to follow-up and incomplete outcome data not reported -> not applicable or just not reported?

Funding not reported.

Molavy-nejad, 2020

Type of study:

3-arm RCT

Setting and country:

University hospital in Iran

Funding:

Reported

Conflicts of interest:

Reported

Inclusion criteria:

(1) T2DM at least for one year, (2) age > 18 years, (3) no other chronic conditions, (4) receiving no official education on self-care or attending other educational program before or during the study, (5) not being pregnant or under breastfeeding

Exclusion criteria:

(1) absent in two educational sessions, (2) worsening health condition, (3) no longer interested in participation in the study, (4) hospitalized during the study, (5) changed therapeutic regimen

N total at baseline:

Video (VTE): 126

In-person (IPE): 125

Pamphlets (P): 126

Important prognostic factors:

Age ± SD:

VTE: 45.88 ± 9.09

IPE: 47.37 ± 7.07

Sex (% male):

VTE: 54.2% | IPE: 50.4%

Groups comparable at baseline? Yes

Video tele-education (VTE):

An educational movie (2 hours) was displayed in the clinic for all subgroups with opportunity to ask questions. The educational movie divided into several episodes was provided to the participants in the form of DVDs or Cell phone formats for home use (distance learning) during study process. During the study, research assistants

reminded participants via regular text messages to watch the video education again and contact if they had any questions.

Pamphlets (P): Participants received an education by staff nurses via pamphlets including education about lifestyle management of T2DM.

à not assessed for this literature analysis

In-person education (IPE):

An educational movie (2 hours) was displayed in the clinic for all subgroups with opportunity to ask questions. The patients received 4 in-person educational sessions (45 minutes + discussion opportunity) by clinical nurses during a two-week period, then they received monthly in-person education at the clinic. Also an abstract of the educational content was provided in writing to the patients.

Length of follow-up:

3 months

Loss-to-follow-up:

VTE: 3 | IPE: 4

• unwilling to continue study (n = 2 for VTE, n = 1 for IPE)
• failure to attend two educational sessions (n = 1 for VTE, n = 2 for IPE)
• hospital admission during intervention (n = 1 for IPE)

Incomplete outcome data:

No incomplete outcome data

Effectiveness

Triglyceride (mean mg/dl ± SD)

Video tele-education: 168.02 ± 67.19

In-person education: 174.60 ± 58.83

HDL (mean mg/dl ± SD)

Video tele-education: 43.42 ± 6.91

In-person education: 44.01 ± 6.67

LDL (mean mg/dl ± SD)

Video tele-education: 104.86 ± 28.26

In-person education: 111.28 ± 38.71

V-LDL (mean mg/dl ± SD)

Video tele-education: 30.99 ± 13.24

In-person education: 31.69 ± 12.90

Total cholesterol (mean mg/dl ± SD)

Video tele-education: 180.24 ± 34.69

In-person education: 190.70 ± 47.99

Fasting blood sugar (mean mg/dl ± SD)

Video tele-education: 162.67 ± 61.06

In-person education: 159.02 ± 59.13

HbA1c (mean % ± SD)

Video tele-education: 6.99 ± 1.59

In-person education: 6.78 ± 1.34

Weight (mean kg ± SD)

Video tele-education: 91.23 ± 14.77

In-person education: 87.74 ± 14.76

Patient focus

Satisfaction with educational programs

(scale from 0 to 10)

Video tele-education: 7.13 ± 1.80

In-person education: 5.91 ± 1.7

Triglyceride, HDL, LDL: no significant difference

V-LDL, total cholesterol: significant reduction in IG

Fasting blood sugar: no significant difference

HbA1c: significant reduction in IGs

Weight: no significant difference

Satisfaction: significant higher satisfaction with VTE compared with IPE.

Study describes in text that there are no difference in baseline characteristics, but occupation status and marital status differ significantly between groups (table 1)

Study reference

Was the allocation sequence adequately generated?

Was the allocation adequately concealed?

Blinding: Was knowledge of the allocated interventions adequately prevented?

• Were patients blinded?
• Were healthcare providers blinded?
• Were data collectors blinded?
• Were outcome assessors blinded?
• Were data analysts blinded?

Was loss to follow-up (missing outcome data) infrequent?

Are reports of the study free of selective outcome reporting?

Was the study apparently free of other problems that could put it at a risk of bias?

Overall risk of bias

If applicable/necessary, per outcome measure

Definitely yes

Probably yes

Probably no

Definitely no

Definitely yes

Probably yes

Probably no

Definitely no

Definitely yes

Probably yes

Probably no

Definitely no

Definitely yes

Probably yes

Probably no

Definitely no

Definitely yes

Probably yes

Probably no

Definitely no

Definitely yes

Probably yes

Probably no

Definitely no

LOW

Some concerns

HIGH

Leong, 2022

Probably yes;

Reason: random sequence generated by a digital program before start of study

Unclear;

Reason: Pharmacists allocated participants according to the random sequence.

Definitely no,

Reason: open-label RCT (blinding of data analysts not reported)

Probably yes;

Reason: Loss to follow-up was infrequent in intervention and control group. Adequate imputation methods (multiple imputation) were used.

Definitely yes;

Reason: All relevant outcomes were reported (conform pre-registered protocol)

Probably no;

Reason: use of self-reported outcome measures leading to possible recall bias

Some concerns:

• Unclear if allocation concealment was adequate
• No blinding with self-reported outcome measures

Di Molfetta, 2022

Probably yes;

Reason: randomization was carried out using a web-based application, stratified by age, sex, type of diabetes, HbA1c level

No information;

Reason: using web-based application; no further information supplied.

Definitely no,

Reason: patients and physicians not blinded (blinding of outcome assessors, data collectors and analysts not reported)

Definitely no

Reason: Loss to follow-up was more frequent in control group (nearly 30%). No imputation methods were used

Probably no

Reason: set of secondary (subgroup) outcomes from protocol not reported

Probably no;

Reason: Unclear sample size calculation (clinical difference in HbA1c)

High:

• unclear allocation concealment
• No blinding
• Frequent loss to follow-up
• Possible selective outcome reporting
• Imprecise

Yang, 2022

Probably yes;

Reason: randomized using a computer-generated randomization number

No information;

Reason: no further information supplied.

Probably no,

Reason: no information on blinding provided

Definitely yes

Reason: Loss to follow-up was infrequent. No imputation methods were used

Probably yes

Reason: protocol very brief, in article all outcomes reported

Definitely no;

Reason: Patients had to be between 40 and 60 years but the mean age is above 60. Protocol states 30 to 75 years

Some concerns:

• unclear allocation concealment
• no information on blinding
• Selection of patients unclear

Li, 2021

Insufficient information;

Reason: drawing lots

Insufficient information;

Reason: drawing lots (unclear how and if sufficiently concealed)

Definitely no;

Reason: patients and physicians not blinded (blinding of outcome assessors, data collectors and analysts not reported)

Insufficient information

Reason: No information on loss to follow-up reported.

Probably yes

Reason: no protocol registered. All relevant outcomes from methods are reported.

Definitely yes;

Reason: Not all possible costs taken into account.

High:

• Possible risk of bias in randomization procedure
• no blinding
• no information on follow-up provided

Maria Gomez, 2022

Insufficient information;

Reason: reported: “the selected patients were randomized”

Insufficient information;

Reason: reported: “the selected patients were randomized”

Definitely no

Reason: Open-label trial (patients, outcome assessors and health care providers not blinded). Blinding of data collectors not reported. Data analysts were blinded.

Probably yes

Reason: Loss to follow-up was infrequent in intervention and control group. No imputation methods were used

Probably yes

Reason: no protocol registered. Outcomes stated in objective are reported.

Probably yes;

Reason: Patients with more than 80% compliance were selected for the study (limited generalizability)

Some concerns

• Possible risk of bias in randomization
• no blinding
• limited generalizability

Turnin, 2021

Definitely yes;

Reason: Random block sizes stratified by HbA1c level

Insufficient information;

Reason: allocation concealment not described.

Definitely no

Reason: Open-label trial (patients, health care providers, outcome assessors and data collectors not blinded). Blinding of data analysts not reported.

Probably yes

Reason: Loss to follow-up was infrequent (<10% )in both groups. Mixed model for repeated measurements used.

Probably yes

Reason: Not all outcomes from protocol reported; relevant outcomes for objective are.

Definitely no;

Reason: Study is funded by SANOFI, some authors received consultancy fees

Some concerns:

• unclear allocation concealment
• no blinding
• industrial funding

Hu, 2021

Probably yes;

Reason: random number table for odd and even numbers, put in envelopes randomly drawn.

Definitely yes;

Reason: Doctors who were not part of the study prepared opaque, sealed envelopes which patients drew.

Definitely no

Reason: Patients, health care providers, outcome assessors and data collectors not blinded. Blinding of data analysts not reported.

Probably yes

Reason: Loss to follow-up was infrequent (<10%) in both groups. No imputation methods were used.

Probably yes

Reason: no protocol registered. All relevant outcomes from methods are reported

No information

Reason: Conflicts of interest not reported.

Low

• no blinding causes risk of bias
• Conflict of interest not reported by authors

Timurtas, 2022

Probably yes;

Reason: Randomization in blocks of 6 with 6 strata.

Insufficient information;

Reason: allocation concealment not described.

Probably no

Reason: Patients and health care providers not blinded. Data collectors and outcome assessors blinded (not for self-reported outcomes). Blinding of data analysts not reported.

Probably no

Reason: Loss to follow-up was frequent (>10%) in all groups. Inadequate imputation method (last observation carried forward) used.

Probably no

Reason: Biochemical measurements from protocol not reported in study.

Probably no

Reason: Underpowered due to randomization in 6 strata. No gender reported.

High

• unclear allocation concealment
• partial blinding
• frequent loss to follow up
• possible selective outcome reporting

Avdal, 2020

Unclear;

Reason: Experimental and control groups were determined with the basic random array

Definitely no;

Reason: composition of groups was determined before the trial

Definitely no

Reason: Patients, health care providers, outcome assessors and data collectors not blinded. Blinding of data analysts not reported.

No information

Reason: Loss to follow-up was not reported

Probably yes

Reason: no protocol registered. All relevant outcomes from methods are reported

Probably no

Reason: no baseline characteristics provided. Funding information and ethical approval not reported.

High

• Unclear randomization method and no allocation concealment
• no blinding
• no information on loss to follow-up
• unclear if baseline characteristics similar between groups

Molavynejad, 2020

Definitely yes;

Reason: Statistician generated random allocation sequence with permuted block randomization.

Probably yes;

Reason: Research assistant enrolled and assigned participants

Probably yes;

Reason: Patients blinded to existence of other study arms. Healthcare providers not blinded. Data collectors, outcome assessors and data analysts blinded to group assignment.

Probably yes

Reason: Loss to follow-up was infrequent (<10%) in both groups. No imputation methods were used.

Probably yes

Reason: no protocol registered. All relevant outcomes from methods are reported

Probably yes

Reason: Marital status and occupation differed at baseline. 

High

• healthcare providers not blinded