SynthesisPloS one2019
Cardiovascular risk prediction models for women in the general population: A systematic review.
Synthesis in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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
32 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Electronic health record-based prediction models for in-hospital adverse drug event diagnosis or prognosis: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2023Pooled it
- Pooled it
- Cardiovascular disease risk prediction models in the Chinese population- a systematic review and meta-analysis.BMC public health · 2022Pooled it
- Association between the reproductive health of young women and cardiovascular disease in later life: umbrella review.BMJ (Clinical research ed.) · 2020Pooled it
- Review of breast arterial calcifications for cardiovascular disease risk prediction.NPJ cardiovascular health · 2026Review
- A Review of Traditional and Non-Traditional Cardiovascular Risk Factors in Women.International journal of women's health · 2026Review
- Cardiovascular risk prediction in women: rethinking traditional approaches through precision medicine.Frontiers in global women's health · 2026Review
- A pipeline for developing deep learning prognostic prediction models in cardiac magnetic resonance image analysis.European heart journal. Digital health · 2026Article
- The value of pregnancy-related factors in the prediction of cardiovascular disease: a systematic review.International journal of cardiology. Cardiovascular risk and prevention · 2025Review
- Beyond one-size-fits-all: addressing sex differences and promoting inclusive leadership in cardiovascular research and healthcare.BMC medicine · 2025Review
- Reproductive history, menopause and cardiometabolic health in women: a multicountry analysis.Journal of epidemiology and community health · 2025Article
- Development and validation of a postpartum cardiovascular disease risk prediction model in women incorporating reproductive and pregnancy-related predictors.BMC medicine · 2025Article
- Article
- Transforming Cardiovascular Risk Prediction: A Review of Machine Learning and Artificial Intelligence Innovations.Life (Basel, Switzerland) · 2025Review
- Superior aortic strain and ventriculoarterial coupling in older women are moderately correlated with Framingham 10-year risk.European heart journal. Imaging methods and practice · 2025Article
- Prevalence of Cardiometabolic Risk Factors in Women: Insights From the Houston HeartReach Study.Texas Heart Institute journal · 2024Article
- Article
- Incorporating reproductive system history data into cardiovascular nursing research to advance women's health.European journal of cardiovascular nursing · 2024Article
- The menopausal transition period and cardiovascular risk.Nature reviews. Cardiology · 2024Review
- Major Limitations of Cardiovascular Risk Scores.Cardiovascular therapeutics · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo provide a comprehensive overview of cardiovascular disease (CVD) risk prediction models for women and models that include female-specific predictors.
methodsWe performed a systematic review of CVD risk prediction models for women in the general population by updating a previous review. We searched Medline and Embase up to July 2017 and included studies in which; (a) a new model was developed, (b) an existing model was validated, or (c) a predictor was added to an existing model.
resultsA total of 285 prediction models for women have been developed, of these 160 (56%) were female-specific models, in which a separate model was developed solely in women and 125 (44%) were sex-predictor models. Out of the 160 female-specific models, 2 (1.3%) included one or more female-specific predictors (mostly reproductive risk factors). A total of 591 validations of sex-predictor or female-specific models were identified in 206 papers. Of these, 333 (56%) validations concerned nine models (five versions of Framingham, SCORE, Pooled Cohort Equations and QRISK). The median and pooled C statistics were comparable for sex-predictor and female-specific models. In 260 articles the added value of new predictors to an existing model was described, however in only 3 of these female-specific predictors (reproductive risk factors) were added.
conclusionsThere is an abundance of models for women in the general population. Female-specific and sex-predictor models have similar predictors and performance. Female-specific predictors are rarely included. Further research is needed to assess the added value of female-specific predictors to CVD models for women and provide physicians with a well-performing prediction model for women.
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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.