ArticleFrontiers in cardiovascular medicine2026
Early prediction model for in-hospital all-cause death in patients with acute ST-elevation myocardial infarction after primary coronary artery stenting.
Article in Frontiers in cardiovascular medicine, 2026. 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
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The in-hospital mortality for acute ST-segment elevation myocardial infarction (STEMI) patients remains high. This study aims to establish an early prediction model for in-hospital all-cause death in patients with STEMI after primary coronary artery stenting. Methods: This retrospective study analyzed 3,916 STEMI patients undergoing primary coronary stenting within 24 h of symptom onset at TEDA International Cardiovascular Hospital (2014-2022). We collected demographic, clinical, and procedural data, along with 48-h laboratory results (including echocardiography and Holter monitoring). The primary outcome was in-hospital all-cause mortality. Eighty clinical parameters were compared between survivors and non-survivors to identify risk factors and develop an early prediction model. Results: In a cohort of 3,916 patients, 54 experienced in-hospital all-cause death. Comparison of 80 clinical variables between groups, followed by univariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression, identified nine risk factors. Multicollinearity analysis confirmed no significant interactions. Multivariate logistic regression revealed six independent predictors: B-type natriuretic peptide (BNP) (per 200 pg/mL), creatine kinase-MB isoenzyme (CK-MB) (per 100 ng/mL), blood urea nitrogen (BUN) (per 1 mmol/L), lactate (LAC) (per 1 mmol/L), Holter mean heart rate (MHR) (per 10 bpm), and Holter total atrial beats (TAB) (per 1,000 times). Receiver operating characteristic (ROC) curve, calibration slope, decision curve analysis (DCA) demonstrated superior net benefit of the combined model over individual predictors. Twenty-five cross-validations confirmed excellent performance of this prediction model, with mean AUC of 0.911 and good stability. Bootstrap internal validation confirmed the good stability (optimism-corrected AUC = 0.873, optimism = 0.019) and calibration (calibration slope = 1.061) of the model, indicating that despite a borderline events per variable (EPV) of 9, the model can reliably predict in-hospital mortality risk in STEMI patients. Conclusion: The combination of BNP, CK-MB, BUN, LAC, Holter MHR, and Holter TAB can effectively predict in-hospital all-cause death in STEMI patients undergoing primary coronary artery stenting, offering potential clinical utility.
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.