SynthesisSystematic reviews2021
Prognostic models of diabetic microvascular complications: a systematic review and meta-analysis.
Synthesis in Systematic reviews, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Opportunities and Challenges of Cardiovascular Disease Risk Prediction for Primary Prevention Using Machine Learning and Electronic Health Records: A Systematic Review.Reviews in cardiovascular medicine · 2025Pooled it
- Machine learning-based risk predictive models for diabetic kidney disease in type 2 diabetes mellitus patients: a systematic review and meta-analysis.Frontiers in endocrinology · 2025Pooled it
- Machine Learning Models for Prediction of Diabetic Microvascular Complications.Journal of diabetes science and technology · 2024Pooled it
- The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Diabetic retinopathy in Greenland and Denmark-Can differences in risk factors explain the lower prevalence in Greenland?Acta ophthalmologica · 2026Article
- A clinically interpretable machine learning model for early detection of diabetic retinopathy in multiple community health centers.Frontiers in endocrinology · 2026Article
- Hemodynamic phenotypes defined by arterial stiffness index and pulse pressure with risk of diabetic microvascular complications in type 2 diabetes.Frontiers in endocrinology · 2026Article
- A SuperLearner approach for predicting diabetic kidney disease upon the initial diagnosis of T2DM in hospital.BMC medical informatics and decision making · 2025Article
- Predictive ability of visit-to-visit glucose variability on diabetes complications.BMC medical informatics and decision making · 2025Article
- Approaches to predict future type 2 diabetes mellitus and chronic kidney disease: A scoping review.PloS one · 2025Article
- Development and Validation of a Literature Screening Tool: Few-Shot Learning Approach in Systematic Reviews.Journal of medical Internet research · 2024Article
- Predicting 1, 2 and 3 year emergent referable diabetic retinopathy and maculopathy using deep learning.Communications medicine · 2024Article
- Fasting pancreatic polypeptide predicts incident microvascular and macrovascular complications of type 2 diabetes: An observational study.Diabetes/metabolism research and reviews · 2024Observational
- Diabetes-Related Macrovascular Complications Are Associated With an Increased Risk of Diabetic Microvascular Complications: A Prospective Study of 1518 Patients With Type 1 Diabetes and 20 802 Patients With Type 2 Diabetes in the UK Biobank.Journal of the American Heart Association · 2024Article
- DNA methylation age acceleration is associated with risk of diabetes complications.Communications medicine · 2023Article
- Role of ADMA in the pathogenesis of microvascular complications in type 2 diabetes mellitus.Frontiers in endocrinology · 2023Review
- Environmental exposures in machine learning and data mining approaches to diabetes etiology: A scoping review.Artificial intelligence in medicine · 2023Article
- Article
- Pharmacological Treatment of Diabetic and Non-Diabetic Patients With Coronary Artery Disease in the Real World of General Practice.Frontiers in pharmacology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMany prognostic models of diabetic microvascular complications have been developed, but their performances still varies. Therefore, we conducted a systematic review and meta-analysis to summarise the performances of the existing models.
methodsPrognostic models of diabetic microvascular complications were retrieved from PubMed and Scopus up to 31 December 2020. Studies were selected, if they developed or internally/externally validated models of any microvascular complication in type 2 diabetes (T2D).
resultsIn total, 71 studies were eligible, of which 32, 30 and 18 studies initially developed prognostic model for diabetic retinopathy (DR), chronic kidney disease (CKD) and end stage renal disease (ESRD) with the number of derived equations of 84, 96 and 51, respectively. Most models were derived-phases, some were internal and external validations. Common predictors were age, sex, HbA1c, diabetic duration, SBP and BMI. Traditional statistical models (i.e. Cox and logit regression) were mostly applied, otherwise machine learning. In cohorts, the discriminative performance in derived-logit was pooled with C statistics of 0.82 (0.73‑0.92) for DR and 0.78 (0.74‑0.83) for CKD. Pooled Cox regression yielded 0.75 (0.74‑0.77), 0.78 (0.74‑0.82) and 0.87 (0.84‑0.89) for DR, CKD and ESRD, respectively. External validation performances were sufficiently pooled with 0.81 (0.78‑0.83), 0.75 (0.67‑0.84) and 0.87 (0.85‑0.88) for DR, CKD and ESRD, respectively.
conclusionsSeveral prognostic models were developed, but less were externally validated. A few studies derived the models by using appropriate methods and were satisfactory reported. More external validations and impact analyses are required before applying these models in clinical practice. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42018105287.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.