ArticleBMJ open2025
Development and validation of a simple risk score model for predicting 3-year major adverse cardiovascular events in patients with coronary artery disease: a retrospective cohort study.
Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo develop and validate a simple risk score for predicting major adverse cardiovascular events (MACE) in coronary artery disease (CAD) patients using routinely available clinical variables.
designThis was a cohort study with retrospective analysis of prospectively collected data.
settingThis study was conducted at a tertiary care centre in China.
participantsThis cohort study included 7182 CAD patients, randomly divided into training dataset and testing dataset in a ratio of 3:1. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was a composite of MACE (cardiovascular death, non-fatal MI, stroke and revascularisation). A Cox regression model was developed on a training set to identify independent predictors. Variables were assigned points based on their β-coefficients to construct a risk score. The model was validated on a testing set. Discrimination was assessed using the concordance index (C-index) and area under the receiver operating characteristic (ROC) curve (AUC). Risk groups were defined according to the total score.
resultsOver a median follow-up of 27.3 months, 487 (6.8%) MACE events occurred. Six independent predictors were identified and included in the score: age ≥65 years (three points), NT-proBNP ≥125 pg/mL (four points), HbA1c ≥7% (3 points), elevated serum creatinine (>106 µmol/L for male or >97 µmol/L for female, 4 points), low-density lipoprotein-cholesterol (LDL-C) ≥1.8 mmol/L (two points), and cardiac troponin T (cTnT) ≥0.15 ng/mL (four points). The score stratified patients into low- (0-4 points), middle- (5-9 points), and high-risk (10-14 points) groups. In the testing set, the middle- and high-risk groups had significantly increased MACE risk compared with the low-risk group (HR 1.54, 95% CI 1.03 to 2.29; HR 2.70, 95% CI 1.78 to 4.08, respectively). The model showed consistent discrimination in both training (C-index = 0.726, AUC = 0.728) and testing sets (C-index = 0.702, AUC = 0.705).
conclusionA simple risk score comprising six clinical variables effectively stratified CAD patients into distinct MACE risk categories. This tool may aid in clinical decision-making and resource prioritisation in secondary prevention, pending external validation.
Indexed as
Identifiers
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.