Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 3 appraisals
BMJ paediatrics open
Impact of flash glucose monitoring versus capillary blood glucose monitoring on glycaemia in Indian youth with type 1 diabetes: a randomised crossover study
BACKGROUND: Data relating to flash glucose monitoring (FGM) use in low-resource settings are limited. Our study investigated the impact of FGM versus self-monitoring of blood glucose (SMBG) on glycaemia in Ahmedabad, India. METHODS: A randomised crossover study of FGM versus SMBG was undertaken. Participants aged 10-25 years (type 1 diabetes (T1D)>1 year) were randomised 1:1 to either Freestyle Libre 1 FGM use (intervention) for 6 months, followed by SMBG≥4 times/day (local care standard) for 6 months; or SMBG≥4 times/day, followed by FGM. After 12 months, everyone entered a 6-month observation period using the monitoring method choice. Insulin and dietary adjustments were undertaken as per local care standards. Glycated haemoglobin (HbA1c) was measured at 0, 3 and 6 months (period 1) and 9 and 12 months (period 2). Analyses included use of linear mixed-effects analysis of covariance, a paired Wilcoxon signed-rank test, and cumulative link mixed tests and model. RESULTS: Of 106 participants, 91 (86%) completed 12 months follow-up (47.3% female). At baseline, mean±SD age was 17.8±3.8 years, diabetes duration 9.9±5.0 years and HbA1c 8.6±1.9% (70±21 mmol/mol).HbA1c decreased when using FGM versus SMBG (difference -0.44% (4.8 mmol/mol); p=0.006), with greater reduction in those with higher baseline HbA1c (p=0.003). In the FGM→SMBG group, HbA1c initially decreased from 8.6±2.2% (70±24 mmol/mol) to 7.9±1.1% (62±12 mmol/mol) at 3 and 6 months (both p<0.05). After SMBG crossover, HbA1c was unchanged (7.9±1.1% (63±12 mmol/mol) at 9 months and 8.1±1.3% (65±14 mmol/mol) at 12 months). In the SMBG→FGM group, HbA1c was initially stable (8.6±1.4% (70±15 mmol/mol) at baseline; 8.8±1.7% (73±19 mmol/mol) at 6 months), but decreased after crossover to FGM (8.4±1.4% (68±15 mmol/mol) at 9 months; 8.3±0.9% (67±10 mmol/mol) at 12 months; p=0.023). CONCLUSION: This study provides evidence of improvement in glycaemic outcomes while using FGM in youth living with T1D in India. TRIAL REGISTRATION NUMBER: Clinical Trial Registry of India (CTRI/2022/02/020175).
1 June 2026
Read appraisal →JMIR formative research
Complication Risk Classification in Children and Adolescents With Type 1 Diabetes: Interpretable Machine Learning Study Based on Saudi Clinical Guidelines
BACKGROUND: Complication risks in children and adolescents with type 1 diabetes (T1D) can lead to serious health outcomes if not detected early. Despite the availability of clinical data, there remains a gap in interpretable tools that support risk stratification in this age group, particularly in alignment with local clinical guidelines. OBJECTIVE: The purpose of this study is to develop a clinically interpretable model that classifies the risk levels of T1D complications-acute, chronic, and low-using real-world data and expert clinical rules derived from the Saudi Diabetes Clinical Practice Guidelines. METHODS: A pediatric T1D dataset comprising of 306 patients was preprocessed through structured cleaning and feature engineering. Risk labels were constructed using Saudi Diabetes Clinical Practice Guidelines-derived rules. Feature selection was performed using a hybrid approach that combined the SHAP (Shapley Additive Explanations) analysis with exhaustive feature selection. A decision tree model was trained and optimized via cross-validation, using the F1-score as the primary performance metric. RESULTS: The final model achieved a high mean F1-score of 0.9876 with a low variance of 0.0189, using only 5 clinical features: BMI, hypoglycemia, disease duration, hemoglobin A1c, and impaired glucose metabolism. These features were consistently ranked as the most influential. The resulting decision tree offered a transparent logic path, enhancing its clinical interpretability and usability. CONCLUSIONS: This study demonstrates that a simple and interpretable model, guided by national clinical guidelines, can effectively predict the risk levels of T1D complications in children and adolescents. Its strong performance, clarity, and reliance on a small number of clinically meaningful features make it a promising candidate for integration into clinical decision support systems. This supports a shift toward predictive and personalized diabetes care.
17 May 2026
Read appraisal →BMJ open
Regular human insulins versus rapid-acting insulin analogues in children and adolescents with type 1 diabetes: a systematic review with meta-analysis and trial sequential analysis
OBJECTIVES: To assess the beneficial and harmful effects of regular human insulins versus rapid-acting insulin analogues in children and adolescents with type 1 diabetes. DESIGN: Systematic review of randomised clinical trials with meta-analysis and trial sequential analysis. DATA SOURCES: CENTRAL, MEDLINE, Embase, LILACS and other sources from inception to 30 January 2026. STUDY SELECTION: Randomised clinical trials comparing regular human insulins versus rapid-acting insulin analogues (insulin aspart, lispro, glulisine) in children and adolescents with type 1 diabetes. ANALYSES: Data were analysed using meta-analysis and trial sequential analysis. Risk of bias was assessed using the Cochrane Risk of Bias tool, V.2, and the certainty of the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. PRIMARY OUTCOMES: Severe hypoglycaemia, ketoacidosis and serious adverse events. RESULTS: 10 trials randomising 1107 participants were included. The certainty of evidence was very low mainly due to high risk of bias and small sample sizes. Meta-analysis showed no evidence of a difference between regular human insulins and rapid-acting insulin analogues on severe hypoglycaemia (risk ratio (RR) 1.28, 95% CI 0.81 to 2.03; I2=0.0%; p=0.2851; nine trials), ketoacidosis (RR 0.88, 95% CI 0.26 to 2.93; I2=0.0%; p=0.8593; two trials) and serious adverse events (RR 1.00, 95% CI 0.44 to 2.25; I2=0.0%; p=0.9958; two trials). Trial sequential analysis showed that all meta-analyses of primary outcomes were underpowered. CONCLUSIONS: Current research shows no differential effects between regular human insulins and rapid-acting insulin analogues for children and adolescents with type 1 diabetes, but the evidence is very uncertain. PROSPERO REGISTRATION NUMBER: CRD42024508625.
16 May 2026
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