SynthesisBMJ open2019
Predicting the risk of stroke among patients with type 2 diabetes: a systematic review and meta-analysis of C-statistics.
Synthesis in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 4 of them syntheses that pooled it.
What it found
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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
11 citing papers in PubMed, 4 syntheses or guidelines pooled it, 28 citations in OpenAlex.
- Machine learning based prediction models for first stroke in community primary care: a systematic review and meta-analysis.BMC medical informatics and decision making · 2026Pooled it
- Pooled it
- Evaluation of Machine Learning Methods Developed for Prediction of Diabetes Complications: A Systematic Review.Journal of diabetes science and technology · 2023Pooled it
- Prediction of hypertension using traditional regression and machine learning models: A systematic review and meta-analysis.PloS one · 2022Pooled it
- A Review of Emerging Biomarkers Connecting Diabetes and Ischemic Stroke: Implications for Early Detection and Risk Stratification.Journal of diabetes research · 2026Review
- CVD incidence and mortality among people with diabetes and/or hypertension: Results from the English longitudinal study of ageing.PloS one · 2024Article
- DNA methylation age acceleration is associated with risk of diabetes complications.Communications medicine · 2023Article
- Precision prognostics for the development of complications in diabetes.Diabetologia · 2022Review
- Development and validation of a hypertension risk prediction model and construction of a risk score in a Canadian population.Scientific reports · 2022Article
- Development and validation of resource-driven risk prediction models for incident chronic kidney disease in type 2 diabetes.Scientific reports · 2021Observational
- Use of Machine Learning Approaches in Clinical Epidemiological Research of Diabetes.Current diabetes reports · 2020Review
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 at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveStroke is a major cause of disability and death worldwide. People with diabetes are at a twofold to fivefold increased risk for stroke compared with people without diabetes. This study systematically reviews the literature on available stroke prediction models specifically developed or validated in patients with diabetes and assesses their predictive performance through meta-analysis.
designSystematic review and meta-analysis. DATA SOURCES: A detailed search was performed in MEDLINE, PubMed and EMBASE (from inception to 22 April 2019) to identify studies describing stroke prediction models. ELIGIBILITY CRITERIA: All studies that developed stroke prediction models in populations with diabetes were included. DATA EXTRACTION AND SYNTHESIS: Two reviewers independently identified eligible articles and extracted data. Random effects meta-analysis was used to obtain a pooled C-statistic.
resultsOur search retrieved 26 202 relevant papers and finally yielded 38 stroke prediction models, of which 34 were specifically developed for patients with diabetes and 4 were developed in general populations but validated in patients with diabetes. Among the models developed in those with diabetes, 9 reported their outcome as stroke, 23 reported their outcome as composite cardiovascular disease (CVD) where stroke was a component of the outcome and 2 did not report stroke initially as their outcome but later were validated for stroke as the outcome in other studies. C-statistics varied from 0.60 to 0.92 with a median C-statistic of 0.71 (for stroke as the outcome) and 0.70 (for stroke as part of a composite CVD outcome). Seventeen models were externally validated in diabetes populations with a pooled C-statistic of 0.68.
conclusionsOverall, the performance of these diabetes-specific stroke prediction models was not satisfactory. Research is needed to identify and incorporate new risk factors into the model to improve models' predictive ability and further external validation of the existing models in diverse population to improve generalisability.
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What OpenQuestion 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 OpenQuestion graph.