Trial reportJournal of diabetes2023
Developing a prediction model for all-cause mortality risk among patients with type 2 diabetes mellitus in Shanghai, China.
Trial report in Journal of diabetes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prognostic models for all-cause and cardiovascular mortality in type 2 diabetes: Systematic review.Diabetic medicine : a journal of the British Diabetic Association · 2026Pooled it
- Developing a prediction model for all-cause mortality risk among patients with type 2 diabetes mellitus in Shanghai, China.Journal of diabetes · 2023Trial
- Therapeutic Effects of Lavender Oil on Streptozotocin-Induced Diabetes Mellitus and Experimental Thrombosis.Antioxidants (Basel, Switzerland) · 2025Article
- Explainable artificial intelligence model predicting the risk of all-cause mortality in patients with type 2 diabetes mellitus.Frontiers in endocrinology · 2025Article
- Development and validation of a nomogram of all-cause mortality in adult Americans with diabetes.Scientific reports · 2024Article
- Influence of Lemongrass Essential Oil (Life (Basel, Switzerland) · 2024Article
- Comparisons of clinical outcomes between newly diagnosed early- and late-onset T2DM: a real-world study from the Shanghai Hospital Link Database.Endocrine connections · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundAll-cause mortality risk prediction models for patients with type 2 diabetes mellitus (T2DM) in mainland China have not been established. This study aimed to fill this gap.
methodsBased on the Shanghai Link Healthcare Database, patients diagnosed with T2DM and aged 40-99 years were identified between January 1, 2013 and December 31, 2016 and followed until December 31, 2021. All the patients were randomly allocated into training and validation sets at a 2:1 ratio. Cox proportional hazards models were used to develop the all-cause mortality risk prediction model. The model performance was evaluated by discrimination (Harrell C-index) and calibration (calibration plots).
resultsA total of 399 784 patients with T2DM were eventually enrolled, with 68 318 deaths over a median follow-up of 6.93 years. The final prediction model included age, sex, heart failure, cerebrovascular disease, moderate or severe kidney disease, moderate or severe liver disease, cancer, insulin use, glycosylated hemoglobin, and high-density lipoprotein cholesterol. The model showed good discrimination and calibration in the validation sets: the mean C-index value was 0.8113 (range 0.8110-0.8115) and the predicted risks closely matched the observed risks in the calibration plots.
conclusionsThis study constructed the first 5-year all-cause mortality risk prediction model for patients with T2DM in south China, with good predictive performance.
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