ArticleInternational journal of general medicine2026
Risk Factors for Cardiac Rupture After Acute Myocardial Infarction and Development of a Risk Prediction Model.
Article in International journal of general 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: To investigate the influencing factors for acute myocardial infarction (AMI) complicated by cardiac rupture (CR),evaluate the predictive value of the systemic inflammation response index (SIRI), and construct a clinically practical risk prediction model. Methods: A total of 53 AMI patients complicated with CR admitted to Tianshui First People's Hospital from January 2013 to December 2023 were enrolled as the CR group.During the same period, 159 AMI patients without CR were selected as the control group at a 1:3 ratio, matched for age and sex.Baseline data, clinical indicators, and laboratory test results of patients in both groups were collected, and SIRI was calculated. Lasso regression was used to screen core variables, multivariate Logistic regression analysis was performed to identify independent influencing factors, a nomogram prediction model was constructed based on key variables, and the receiver operating characteristic (ROC) curve was used to evaluate the model's efficacy. Results: Multivariate Logistic regression analysis showed that admission heart rate (OR = 1.050,95% CI = 1.024-1.075, P < 0.001), Killip classification (OR = 2.092,95% CI = 1.460-2.997, P < 0.001) and SIRI (OR = 1.105,95% CI = 1.022-1.196, P = 0.012) were independent risk factors for CR in AMI patients. Primary PCI (OR = 0.239,95% CI = 0.097-0.589, P = 0.002) and taking ACEI / ARB drugs within 24 hours (OR = 0.173,95% CI = 0.060-0.500, P = 0.001) were protective factors. The ROC curve model constructed based on the above five indicators has an area under the curve (AUC) of 0.885. Conclusion: Admission heart rate, Killip classification, and systemic inflammatory response index are independent risk factors for AMI with CR. Primary PCI and the administration of ACEI/ARB within 24 hours of admission were identified as protective factors against CR. The nomogram model demonstrated good predictive value for the occurrence of cardiac rupture in patients with AMI.
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.