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Introduction: Fluid overload is a known complication in patients with diabetes mellitus, particularly those with cardiovascular and/or chronic kidney disease (CKD). This study investigates the impact of fluid overload on healthcare utilisation and its association with diabetes-related complications. Method: Electronic medical records from the SingHealth Diabetes Registry (2013-2022) were analysed. Hospitalisations due to fluid overload were identified using International Classification of Diseases, 10th Revision (ICD-10) discharge codes. Trends were examined using Joinpoint regression, and associations were assessed with generalised estimating equation models. Results: Over a period of 10 years, 259,607 individuals treated at primary care clinics and tertiary hospitals were studied. The incidence of fluid overload-related hospitalisations decreased from 2.99% (n=2778) in 2013 to 2.18% (n=2617) in 2017. However, this incidence increased from 2.42% (n=3091) in 2018 to 3.71% (n=5103) in 2022. The strongest associations for fluid overload-related hospitalisation were found with CKD stages G5 (odds ratio [OR] 6.61, 95% confidence interval [CI] 6.26-6.99), G4 (OR 5.55, 95% CI 5.26-5.86) and G3b (OR 3.18, 95% CI 3.02-3.35), as well as with ischaemic heart disease (OR 3.97, 95% CI 3.84-4.11), acute myocardial infarction (OR 3.07, 95% CI 2.97-3.18) and hypertension (OR 3.90, 95% CI 3.45-4.41). Additionally, the prevalence of stage G5 CKD among patients with fluid overload increased between 2018 and 2022. Conclusion: Our study revealed a significant increase in fluid overload-related hospitalisations and extended lengths of stay, likely driven by severe CKD. This underscores an urgent need for initiatives aimed at slowing CKD progression and reducing fluid overload-related hospitalisations in diabetes patients.

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Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise care for people with diabetes and adapt treatments for complex presentations. However, the rapid advancement of AI also introduces challenges such as potential biases, ethical considerations, and implementation challenges in ensuring that its deployment is equitable. Ensuring inclusive and ethical developments of AI technology can empower both health-care providers and people with diabetes in managing the condition. In this Review, we explore and summarise the current and future prospects of AI across the diabetes care continuum, from enhancing screening and diagnosis to optimising treatment and predicting and managing complications.

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BACKGROUND: The clinical management of type 2 diabetes mellitus (T2DM) presents a significant challenge due to the constantly evolving clinical practice guidelines and growing array of drug classes available. Evidence suggests that artificial intelligence (AI)-enabled clinical decision support systems (CDSSs) have proven to be effective in assisting clinicians with informed decision-making. Despite the merits of AI-driven CDSSs, a significant research gap exists concerning the early-stage implementation and adoption of AI-enabled CDSSs in T2DM management. OBJECTIVE: This study aimed to explore the perspectives of clinicians on the use and impact of the AI-enabled Prescription Advisory (APA) tool, developed using a multi-institution diabetes registry and implemented in specialist endocrinology clinics, and the challenges to its adoption and application. METHODS: We conducted focus group discussions using a semistructured interview guide with purposively selected endocrinologists from a tertiary hospital. The focus group discussions were audio-recorded and transcribed verbatim. Data were thematically analyzed. RESULTS: A total of 13 clinicians participated in 4 focus group discussions. Our findings suggest that the APA tool offered several useful features to assist clinicians in effectively managing T2DM. Specifically, clinicians viewed the AI-generated medication alterations as a good knowledge resource in supporting the clinician's decision-making on drug modifications at the point of care, particularly for patients with comorbidities. The complication risk prediction was seen as positively impacting patient care by facilitating early doctor-patient communication and initiating prompt clinical responses. However, the interpretability of the risk scores, concerns about overreliance and automation bias, and issues surrounding accountability and liability hindered the adoption of the APA tool in clinical practice. CONCLUSIONS: Although the APA tool holds great potential as a valuable resource for improving patient care, further efforts are required to address clinicians' concerns and improve the tool's acceptance and applicability in relevant contexts.

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We have developed a digital twin-based CKD identification and prediction model that leverages generalized metabolic fluxes (GMF) for patients with Type 2 Diabetes Mellitus (T2DM). GMF digital twins utilized basic clinical and physiological biomarkers as inputs for identification and prediction of CKD. We employed four diverse multi-ethnic cohorts (n = 7072): a Singaporean cohort (EVAS, n = 289) and a North American cohort (NHANES, n = 1044) for baseline CKD identification, and two multi-center Singaporean cohorts (CDMD, n = 2119 and SDR, n = 3627) for 3-year CKD prediction and risk stratification. We subsequently conducted a comprehensive study utilizing a single dataset to evaluate the clinical utility of GMF for CKD prediction. The GMF-based identification model performed strongly, achieving an AUC between 0.80 and 0.82. In prediction, the GMF generated with complete parameters attained high performance with an AUC of 0.86, while with incomplete parameters, it achieved an AUC of 0.75. The GMF-based prediction model utilizing complete inputs is the standard implementation of our algorithm: HealthVector Diabetes®. We have established the GMF digital twin-based model as a robust clinical tool capable of predicting and stratifying the risk of future CKD within a 3-year time horizon. We report the correlation of GMF with basic input parameters, their ability to differentiate between future health states and medication status at baseline, and their capability to quantify CKD progression rates. This holistic methodology provides insights into patients' health states and CKD progression rates based on GMF metabolic profile differences, enabling personalized care plans.

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AIMS: Hospital readmissions due to recurrent fluid overload in diabetes and diabetic kidney disease can be avoided with evidence-based interventions. We aimed to identify at-risk patients who can benefit from these interventions by developing risk prediction models for readmissions for fluid overload in people living with diabetes and diabetic kidney disease. METHODS: This was a single-center retrospective cohort study of 1,531 adults with diabetes and diabetic kidney disease hospitalized for fluid overload, congestive heart failure, pulmonary edema, and generalized edema between 2015 and 2017. The multivariable regression models for 30-day and 90-day readmission for fluid overload were compared with the LACE score for discrimination, calibration, sensitivity, specificity, and net reclassification index (NRI). RESULTS: Readmissions for fluid overload within 30 days and 90 days occurred in 8.6% and 17.2% of patients with diabetes, and 8.2% and 18.3% of patients with diabetic kidney disease, respectively. After adjusting for demographics, comorbidities, clinical parameters, and medications, a history of alcoholism (HR 3.85, 95% CI: 1.41-10.55) and prior hospitalization for fluid overload (HR 2.50, 95% CI: 1.26-4.96) were independently associated with 30-day readmission in patients with diabetic kidney disease, as well as in individuals with diabetes. Additionally, current smoking, absence of hypertension, and high-dose intravenous furosemide were also associated with 30-day readmission in individuals with diabetes. Prior hospitalization for fluid overload (HR 2.43, 95% CI: 1.50-3.94), cardiovascular disease (HR 1.44, 95% CI: 1.03-2.02), eGFR ≤45 mL/min/1.73 m2 (HR 1.39, 95% CI: 1.003-1.93) was independently associated with 90-day readmissions in individuals with diabetic kidney disease. Additionally, thiazide prescription at discharge reduced 90-day readmission in diabetic kidney disease, while the need for high-dose intravenous furosemide predicted 90-day readmission in diabetes. The clinical and clinico-psychological models for 90-day readmission in individuals with diabetes and diabetic kidney disease had better discrimination and calibration than the LACE score. The NRI for the clinico-psychosocial models to predict 30- and 90-day readmissions in diabetes was 22.4% and 28.9%, respectively. The NRI for the clinico-psychosocial models to predict 30- and 90-day readmissions in diabetic kidney disease was 5.6% and 38.9%, respectively. CONCLUSION: The risk models can potentially be used to identify patients at risk of readmission for fluid overload for evidence-based interventions, such as patient education or transitional care programs to reduce preventable hospitalizations.

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CONTEXT: Diabetes mellitus is associated with morbid complications such as diabetic foot ulcers (DFUs) that may lead to amputations or mortality if not managed adequately. OBJECTIVE: New adjunctive interventions to treat diabetic wounds include topical biologics and growth factors. This study aims to evaluate their efficacy in improving wound-healing outcomes and safety. METHODS: Comprehensive database searches of MEDLINE via PubMed, EMBASE, and Cochrane were performed from inception to December 2022. Three independent researchers selected the studies. Randomized controlled trials that compared the use of a topical biologic growth factor-containing regimen to other biologics or standard of care (SOC) were included. This review followed PRISMA guidelines. Risk of bias analysis was performed using the Jadad scale. Network meta-analysis was performed. Treatments were grouped into common nodes based on the type of biologic agent. Primary outcomes of interest were healing rate and time to wound closure. Secondary outcomes included wound infection, serious adverse events (AEs), and amputation rate. RESULTS: Human umbilical cord (HUC) was associated with the highest cure, followed by recombinant human epidermal growth factor (hEGF). A significantly greater reduction in the time to cure DFUs was seen in HUC, hEGF, and fibroblast growth factor (FGF). There was a significantly lower risk of AEs when platelet-rich plasma (PRP) was administered. CONCLUSION: HUC, hEGF, and FGF are promising topical biologics with statistically significant primary outcomes compared to SOC, while PRP is effective in reducing ulcer-related AEs. HUC has been found to be the most effective in terms of cure rate and a reduction in time to cure.

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BACKGROUND: We aimed to explore the three-way interaction among age, gender, and kidney function on the risk of all-cause mortality and cardiovascular mortality among patients with type 2 diabetes (T2D). METHODS: In a retrospective cohort study, patients aged > 40 years with T2D with serum creatinine and urine albumin measured from 2013 to 2019 were included from a multi-institutional diabetes registry. The exposure was estimated glomerular filtration rate (eGFR), outcomes were all-cause mortality (primary outcome) and cardiovascular disease (CVD) mortality (secondary outcome). We applied multivariable cox proportional hazards regression analysis to compute the association between eGFR and mortality. RESULTS: A total of 36,556 patients were followed for up to 6 years during which 2492 (6.82%) died from all causes, and 690 (1.9%) died from CVD. We observed a significant three-way interaction (p = 0.021) among age (younger, < 65; older, ≥65 years), gender and eGFR for the risk of all-cause mortality. Using age- and gender-specific eGFR of 90 ml/min/1.73m2 as the reference point, the adjusted hazard rate (HR) (95% CI) for all-cause mortality at eGFR of 40 ml/min/1.73m2 was 3.70 (2.29 to 5.99) in younger women and 1.86 (1.08 to 3.19) in younger men. The corresponding adjusted HRs in older women and older men were 2.38 (2.02 to 2.82) and 2.18 (1.85 to 2.57), respectively. Similar results were observed for CVD deaths, although the three-way interaction was not statistically significant. Sensitivity analysis yielded similar results. CONCLUSIONS: In this T2D population, younger women with reduced kidney function might be more susceptible to higher risks of all-cause mortality and CVD mortality than younger men.

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BACKGROUND: We examined the trajectory of estimated glomerular filtrate rate (eGFR), associated risk factors, and its relationship with end-stage kidney disease (ESKD) among a multiethnic patient population with type 2 diabetes in Singapore. METHODS: A follow-up study included 62 080 individuals with type 2 diabetes aged ≥18 years in a multi-institutional SingHealth Diabetes Registry between 2013 and 2019. eGFR trajectories were analyzed using latent class linear mixed models. Factors associated with eGFR trajectories were evaluated using multinomial logistic regression. The association of eGFR trajectories with ESKD was assessed via competing risk models. RESULTS: Trajectory of kidney function, determined by eGFR, was nonlinear. The trajectory pattern was classified as stable initially then gradual decline (75%), progressive decline (21.9%), and rapid decline (3.1%). Younger age, female sex, Malay ethnicity, lower-income housing type, current smoking, higher glycated hemoglobin, lower low-density lipoprotein, higher triglyceride, uncontrolled blood pressure, albuminuria, cardiovascular disease, hypertension, and higher eGFR levels each were associated with progressive or rapid decline. Compared with the trajectory of stable initially then gradual eGFR decline, progressive decline increased the hazard of ESKD by 6.14-fold (95% confidence interval [CI]: 4.96-7.61)) and rapid decline by 82.55 folds (95% CI: 55.90-121.89). CONCLUSIONS: Three nonlinear trajectory classes of kidney function were identified among multiethnic individuals with type 2 diabetes in Singapore. About one in four individuals had a progressive or rapid decline in eGFR. Our results suggest that eGFR trajectories are correlated with multiple social and modifiable risk factors and inform the risk of ESKD.

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AIMS: Fluid overload is a common manifestation of cardiovascular and kidney disease and a leading cause of hospitalizations. To identify patients at risk of recurrent severe fluid overload, we evaluated the incidence and risk factors associated with early repeat hospitalization for fluid overload among individuals with cardiovascular disease and risks. METHODS: Single-center retrospective cohort study of 3423 consecutive adults with an index hospitalization for fluid overload between January 2015 and December 2017 and had cardiovascular risks (older age, diabetes mellitus, hypertension, dyslipidemia, kidney disease, known cardiovascular disease), but excluded if lost to follow-up or eGFR < 15 ml/min/1.73 m2. The outcome was early repeat hospitalization for fluid overload within 30 days of discharge. RESULTS: The mean age was 73.9 ± 11.6 years and eGFR was 54.1 ± 24.6 ml/min/1.73 m2 at index hospitalization. Early repeat hospitalization for fluid overload occurred in 291 patients (8.5%). After adjusting for demographics, comorbidities, clinical parameters during index hospitalization and medications at discharge, cardiovascular disease (adjusted odds ratio, OR 1.66, 95% CI 1.27-2.17), prior hospitalization for fluid overload within 3 months (OR 2.52, 95% CI 1.17-5.44), prior hospitalization for any cause in within 6 months (OR 1.33, 95% CI 1.02-1.73) and intravenous furosemide use (OR 1.58, 95% CI 1.10-2.28) were associated with early repeat hospitalization for fluid overload. Higher systolic BP on admission (OR 0.992, 95% 0.986-0.998) and diuretic at discharge (OR 0.50, 95% CI 0.26-0.98) reduced early hospitalization for fluid overload. CONCLUSION: Patients at-risk of early repeat hospitalization for fluid overload may be identified using these risk factors for targeted interventions.

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BACKGROUND: Type 2 diabetes (T2D), a major risk factor for cardiovascular disease and other adverse health conditions, is on the rise in Singapore. TRIPOD is a randomized controlled trial aimed to determine whether complementing usual care with an evidence-based diabetes management package (DMP) -comprising access to an evidence-based app, health coaching, pedometer, glucometer and weighing scale, with or without a financial rewards scheme (M-POWER rewards), can improve mean HbA1c levels at months 6 and 12. METHODS: The protocol was published in Trials, accessible via https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-019-3749-x 1. This manuscript updates the protocol with changes to the study design due to challenges with recruitment and presents baseline characteristics. Key updates include changing the arm allocation ratio from 1:1:1 (Arm 1-Usual Care: Arm 2-DMP: Arm 3-DMP+M-POWER rewards) to 10:1:10, the sample size from 339 to 269, the intervention period from two to one year, and the primary hypothesis to focus solely on differences between Usual Care and DMP+M-POWER rewards. Recruitment for the study began on 19 October 2019 and ended on 4 June 2022. RESULTS: The average age of participants was 55.0 (SD9.7) years old and 64.2% were male. The majority of participants (76.8%) were Chinese, 4.9% Malay and 18.3% Indian and of other ethnicities. 67.0% had a monthly household income of SGD$4000 or more. The mean baseline HbA1c was 8.10% (SD 0.95) and the mean body mass index was 26.8 kg/m2 (SD 5.3). DISCUSSION: The final participant completed month 12 follow-up data collection on 8 June 2023. All pre-planned analyses will be conducted and final results reported. TRIAL REGISTRATION: ClinicalTrials.gov NCT03800680 . Registered on 11 January 2019.

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BACKGROUND: Elevated blood pressure (BP) is associated with increased risk of cardiovascular mortality. However, there is ongoing debate whether intensive BP lowering may paradoxically increase the risk of cardiovascular disease (CVD), especially in patients with type 2 diabetes (T2D). We investigated the association of BP with risk of CVD mortality in patients with T2D. METHODS AND RESULTS: We used data on 83 721 patients with T2D from a multi-institutional diabetes registry in Singapore from 2013 to 2019. BP was analyzed as categories and restricted cubic splines using Cox multivariable regression analysis stratified by preexisting CVD and age (<65 years versus ≥65 years). The primary outcome was CVD mortality, determined via linkage with the national registry. Among 83 721 patients with T2D (mean age 65.3 years, 50.6% women, 78.9% taking antihypertensive medications), 7.6 per 1000 person-years experienced the primary outcome. Systolic BP had a graded relationship with a significant increase in CVD mortality at levels >120 to 129 mm Hg. Diastolic BP levels >90 mm Hg were significantly associated with CVD mortality in those aged ≥65 years. In addition, diastolic BP <70 mm Hg was associated with a significantly higher risk of CVD mortality in all patients. CONCLUSIONS: In patients with T2D, clinic systolic BP levels ≥130 mm Hg or diastolic BP levels ≥90 mm Hg are associated with higher risk of CVD mortality. Diastolic BP <70 mm Hg is also associated with the risk of adverse CVD outcomes, although reverse causality cannot be ruled out.

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AIMS: We aim to compare and correlate Gold and Clarke questionnaire scores with hypoglycaemic symptomatic responses between insulin-treated type 2 diabetes participants with and without IAH in a real-life study. METHODS: Insulin-treated type 2 diabetes participants attending an outpatient diabetes clinic in Singapore were asked to complete the Gold and Clarke questionnaires, record capillary blood glucose (CBG) and hypoglycaemic symptoms for 4 weeks. RESULTS: Data were collected from 153 participants (M:F = 98:55) with mean age 61.0 ± 9.4 years, duration of diabetes 19.5 ± 8.8 years and HbA1c 68 ± 17 mmol/mol (8.4 ± 1.5%). Gold and Clarke methods classified 19.6% and 26.8% of participants with IAH, respectively. Using CBG threshold of <3 mmol/L, significantly greater proportion of participants with intact awareness were experiencing autonomic symptoms than those with IAH with either method (Gold: 69% vs. 18%, p = 0.006; Clarke: 85% vs. 46%, p = 0.010). Significantly greater proportion of participants with IAH experienced no hypoglycaemia symptoms than those with intact awareness (Gold: 3.4% vs. 36%, p = 0.015; Clarke: 3.7% vs. 31%, p = 0.031). Participants with IAH had significantly higher rates of severe hypoglycaemia in the preceding year compared to those without (Gold: 17% vs. 3.3%; Clarke: 15% vs. 2.7%, p = 0.012). CONCLUSIONS: Gold and Clarke questionnaires are appropriate tools in ascertaining IAH status in insulin-treated type 2 diabetes participants. This is the first time whereby the hypoglycaemia symptomology has robustly validated the Gold and Clarke questionnaire in insulin-treated type 2 diabetes participants.

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Background: Technological advances make it possible to use device-supported, automated algorithms to aid basal insulin (BI) dosing titration in patients with type 2 diabetes. Methods: A systematic review and meta-analysis of randomized controlled trials were performed to evaluate the efficacy, safety, and quality of life of automated BI titration versus conventional care. The literature in Medline, Embase, Web of Science, and the Cochrane databases from January 2000 to February 2022 were searched to identify relevant studies. Risk ratios (RRs), mean differences (MDs), and their 95% confidence intervals (CIs) were calculated using random-effect meta-analyses. Certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. Findings: Six of the 7 eligible studies (889 patients) were included in meta-analyses. Low- to moderate-quality evidence suggests that patients who use automated BI titration versus conventional care may have a higher probability of reaching a target of HbA1c <7.0% (RR, 1.82 [95% CI, 1.16-2.86]); and a lower level of HbA1c (MD, -0.25% [95% CI, -0.43 to -0.06%]). No statistically significant differences were detected between the two groups in fasting glucose results, incidences of hypoglycemia, severe or nocturnal hypoglycemia, and quality of life, with low to very low certainty for all the evidence. Interpretation: Automated BI titration is associated with small benefits in reducing HbA1c without increasing the risk of hypoglycemia. Future studies should explore patient attitudes and the cost-effectiveness of this approach. Funding: Sponsored by the Chinese Geriatric Endocrine Society.

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Background: Bariatric surgery is the most effective treatment for morbid obesity and reduces the severity of nonalcoholic fatty liver disease (NAFLD) in the long term. Less is known about the effects of bariatric surgery on liver fat, inflammation, and fibrosis during the early stages following bariatric surgery. Aims: This exploratory study utilises advanced imaging methods to investigate NAFLD and fibrosis changes during the early metabolic transitional period following bariatric surgery. Methods: Nine participants with morbid obesity underwent sleeve gastrectomy. Multiparametric MRI (mpMRI) and magnetic resonance elastography (MRE) were performed at baseline, during the immediate (1 month), and late (6 months) postsurgery period. Liver fat was measured using proton density fat fraction (PDFF), disease activity using iron-correct T1 (cT1), and liver stiffness using MRE. Repeated measured ANOVA was used to assess longitudinal changes and Dunnett's method for multiple comparisons. Results: All participants (Age 45.1 ± 9.0 years, BMI 39.7 ± 5.3 kg/m2) had elevated hepatic steatosis at baseline (PDFF >5%). In the immediate postsurgery period, PDFF decreased significantly from 14.1 ± 7.4% to 8.9 ± 4.4% (p = 0.016) and cT1 from 826.9 ± 80.6 ms to 768.4 ± 50.9 ms (p = 0.047). These improvements continued to the later postsurgery period. Bariatric surgery did not reduce liver stiffness measurements. Conclusion: Our findings support using MRI as a noninvasive tool to monitor NAFLD in patient with morbid obesity during the early stages following bariatric surgery.

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Diabetes Technology Society assembled a panel of clinician experts in diabetology, cardiology, clinical chemistry, nephrology, and primary care to review the current evidence on biomarker screening of people with diabetes (PWD) for heart failure (HF), who are, by definition, at risk for HF (Stage A HF). This consensus report reviews features of HF in PWD from the perspectives of 1) epidemiology, 2) classification of stages, 3) pathophysiology, 4) biomarkers for diagnosing, 5) biomarker assays, 6) diagnostic accuracy of biomarkers, 7) benefits of biomarker screening, 8) consensus recommendations for biomarker screening, 9) stratification of Stage B HF, 10) echocardiographic screening, 11) management of Stage A and Stage B HF, and 12) future directions. The Diabetes Technology Society panel recommends 1) biomarker screening with one of two circulating natriuretic peptides (B-type natriuretic peptide or N-terminal prohormone of B-type natriuretic peptide), 2) beginning screening five years following diagnosis of type 1 diabetes (T1D) and at the diagnosis of type 2 diabetes (T2D), 3) beginning routine screening no earlier than at age 30 years for T1D (irrespective of age of diagnosis) and at any age for T2D, 4) screening annually, and 5) testing any time of day. The panel also recommends that an abnormal biomarker test defines asymptomatic preclinical HF (Stage B HF). This diagnosis requires follow-up using transthoracic echocardiography for classification into one of four subcategories of Stage B HF, corresponding to risk of progression to symptomatic clinical HF (Stage C HF). These recommendations will allow identification and management of Stage A and Stage B HF in PWD to prevent progression to Stage C HF or advanced HF (Stage D HF).

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The objective of this study was to provide recommendations regarding effectiveness, safety, optimal starting dose, optimal maintenance dose range, and target fasting plasma glucose of five basal insulins (glargine U-300, degludec U-100, glargine U-100, detemir, and insulin protamine Hagedorn) in insulin-naïve adult patients with type 2 diabetes in the Asia-Pacific region. Based on evidence from a systematic review, we developed an Asia-Pacific clinical practice guideline through comprehensive internal review and external review processes. We set up and used clinical thresholds of trivial, small, moderate, and large effects for different critical and important outcomes in the overall certainty of evidence assessment and balancing the magnitude of intervention effects when making recommendations, following GRADE methods (Grading of Recommendations, Assessment, Development, and Evaluation). The AGREE (Appraisal of Guidelines, Research and Evaluation) and RIGHT (Reporting Items for practice Guidelines in HealThcare) guideline reporting checklists were complied with. After the second-round vote by the working group members, all the recommendations and qualifying statements reached over 75% agreement rates. Among 44 contacted external reviewers, we received 33 clinicians' and one patient's comments. The overall response rate was 77%. To solve the four research questions, we made two strong recommendations, six conditional recommendations, and two qualifying statements. Although the intended users of this guideline focused on clinicians in the Asia-Pacific region, the eligible evidence was based on recent English publications. We believe that the recommendations and the clinical thresholds set up in the guideline can be references for clinicians who take care of patients with type 2 diabetes worldwide.

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AIMS: To investigate the effectiveness, safety, optimal starting dose, optimal maintenance dose range, and target fasting plasma glucose of five basal insulins in insulin-naïve patients with type 2 diabetes mellitus. METHODS: MEDLINE, EMBASE, Web of Science, and the Cochrane Library were searched from January 2000 to February 2022. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed and the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach was adopted. The registration ID is CRD42022319078 in PROSPERO. RESULTS: Among 11 163 citations retrieved, 35 publications met the planned criteria. From meta-analyses and network meta-analyses, we found that when injecting basal insulin regimens at bedtime, the optimal choice in order of most to least effective might be glargine U-300 or degludec U-100, glargine U-100 or detemir, followed by neutral protamine hagedorn (NPH). Injecting glargine U-100 in the morning may be more effective (ie, more patients archiving glycated hemoglobin < 7.0%) and lead to fewer hypoglycemic events than injecting it at bedtime. The optimal starting dose for the initiation of any basal insulins can be 0.10-0.20 U/kg/day. There is no eligible evidence to investigate the optimal maintenance dose for basal insulins. CONCLUSIONS: The five basal insulins are effective for the target population. Glargine U-300, degludec U-100, glargine U-100, and detemir lead to fewer hypoglycemic events than NPH without compromising glycemic control.

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BACKGROUND: Delayed initiation and inadequate titration remain critical challenges to optimizing insulin therapy in type 2 diabetes (T2D). We aimed to study whether hemoglobin A1c (HbA1c) can be lowered in people with insulin-treated T2D using telemonitoring. METHODS: This single-center study recruited adults with greater than or equal to six months of diabetes, greater than or equal to three months of insulin therapy, HbA1c ≥8.5% and ≤12.5%, and body mass index (BMI) ≤40 kg/m2. All participants received a connected glucose meter and the accompanying smartphone application. Participants sent weekly blood glucose (BG) diary to their primary endocrinologist via email. Adjustments in insulin doses were communicated to the participants. HbA1c, proportion of BG readings in range (70-180 mg/dL, PIR), below range (<70 mg/dL, PBR) and above range (>180 mg/dL, PAR), and glycemic variability as the coefficient of variation (% CV) were measured at baseline, week 12, and week 24 and compared using repeated-measures analysis of variance (ANOVA) or Friedman's ANOVA. RESULTS: We recruited 40 people (55% women). Mean age was 57.9 years, BMI 27.8 kg/m2, and baseline HbA1c 9.8% (83.7 mmol/mol). Mean HbA1c improved by 1.7%, % CV reduced from 32.9% to 30.7%, PIR increased from 58.8% to 67.1% (all P <.01) by week 24, without any change in PBR. This was achieved with a 0.04 U/kg/d median increase in total daily dose of insulin and 0.9 kg weight gain over 24 weeks. CONCLUSION: Telemonitoring and titration of insulin using a connected glucose meter resulted in significant improvements in glycemia, characterized by a reduction in HbA1c, increase in PIR, and reduction in glycemic variability without any increase in hypoglycemia.

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