Dataset Information

Development and validation of a risk prediction model for in-hospital major cardiovascular events in patients hospitalised for acute myocardial infarction.

ABSTRACT:

Objectives

Patients admitted to hospital with acute myocardial infarction (AMI) have considerable variability in in-hospital risks, resulting in higher demands on healthcare resources. Simple risk-assessment tools are important for the identification of patients with higher risk to inform clinical decisions. However, few risk assessment tools have been built that are suitable for populations with AMI in China. We aim to develop and validate a risk prediction model, and further build a risk scoring system.

Design

Data from a nationally representative retrospective study was used to develop the model. Patients from a prospective study and another nationally representative retrospective study were both used for external validation.

Setting

161 nationally representative hospitals, and 53 and 157 other hospitals were involved in the above three studies, respectively.

Participants

8010 patients hospitalised for AMI were included as development sample, and 4485 and 11 223 other patients were included as validation samples in their corresponding studies.

Primary and secondary outcome measures

The in-hospital major adverse cardiovascular events (MACE) was defined as death from any cause, recurrent AMI, or ischaemic stroke.

Results

The proportion of in-hospital MACE was 11.7%, 8.8% and 11.4% among the development sample and two external-validation samples, respectively. Nine predictors (ie, age, sex, left ventricular ejection fraction, Killip class, systolic blood pressure, creatinine, white blood cell count, heart rate and blood glucose) were independently associated with in-hospital MACE. The model performed well on both discrimination and calibration capability, with areas under the Receiver Operating Characteristic Curve (ROC) curve of 0.85, 0.74 and 0.80, and calibration slopes of 0.98, 0.84 and 0.97 in the development sample and two external validation samples, respectively. A point-based risk scoring system was built with good discrimination and reclassification ability.

Conclusions

A prediction model using readily available clinical parameters was developed and externally validated to estimate risks of in-hospital MACE among patients with AMI, thereby better informing decision-making in improving clinical care.

SUBMITTER: Wu C

PROVIDER: S-EPMC8162080 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportancePatients who survive acute myocardial infarction (AMI) have a high risk of subsequent major cardiovascular events. Efforts to identify risk factors for recurrence have primarily focused on the period immediately following AMI admission.ObjectivesTo identify risk factors and develop and evaluate a risk model that predicts 1-year cardiovascular events after AMI.Design, setting, and participantsProspective cohort study. Patients with AMI (n?=?4227), aged 18 years or older, discharged alive from 53 acute-care hospitals across China from January 1, 2013, to July 17, 2014. Patients were randomly divided into samples: training (50% [2113 patients]), test (25% [1057 patients]), and validation (25% [1057 patients]). Risk factors were identified by a Cox model with Markov chain Monte Carlo simulation and further evaluated by latent class analysis. Analyses were conducted from May 1, 2017, to January 21, 2018.Main outcomes and measuresMajor cardiovascular events, including recurrent AMI, stroke, heart failure, and death, within 1 year after discharge for the index AMI hospitalization.ResultsThe mean (SD) age of the cohort was 60.8 (11.8) years and 994 of 4227 patients (23.5%) were female. Common comorbidities included hypertension (2358 patients [55.8%]), coronary heart disease (1798 patients [42.5%]), and dyslipidemia (1290 patients [30.5%]). One-year event rates were 8.1% (95% CI, 6.91%-9.24%), 9.0% (95% CI, 7.22%-10.70%), and 6.4% (95% CI, 4.89%-7.85%) for the training, test, and validation samples, respectively. Nineteen risk factors comprising 15 unique variables (age, education, prior AMI, prior ventricular tachycardia or fibrillation, hypertension, angina, prearrival medical assistance, >4 hours from onset of symptoms to admission, ejection fraction, renal dysfunction, heart rate, systolic blood pressure, white blood cell count, blood glucose, and in-hospital complications) were identified. In the training, test, and validation samples, respectively, the risk model had C statistics of 0.79 (95% CI, 0.75-0.83), 0.73 (95% CI, 0.68-0.78), and 0.77 (95% CI, 0.70-0.83) and a predictive range of 1.2% to 33.9%, 1.2% to 37.9%, and 1.3% to 34.3%. The C statistic was 0.69 (95% CI, 0.65-0.74) for the latent class model in the training data. The risk model stratified 11.3%, 81.0%, and 7.7% of patients to high-, average-, and low-risk groups, with respective probabilities of 0.32, 0.06, and 0.01 for 1-year events.Conclusions and relevanceNineteen risk factors were identified, and a model was developed and evaluated to predict risk of 1-year cardiovascular events after AMI. This may aid clinicians in identifying high-risk patients who would benefit most from intensive follow-up and aggressive risk factor reduction.

Project description:Background:Risk stratification models with incorporation of biochemical markers have received attention recently. In acute myocardial infarction (AMI) one such marker is lipoprotein(a) (Lp(a)). Lp(a) has prothrombotic and proinflammatory properties. High levels of Lp(a) probably contribute to the additional adverse effects in AMI, as it enhances the damaging effect of acute thrombosis. This study aimed to evaluate serum Lp(a) as a predictor of major adverse cardiovascular events (MACE) in hospitalized-acute myocardial infarction patients. Methods:A prospective cohort study was conducted at Sanglah Hospital, Denpasar, during June-August 2018, among 66 people by consecutive sampling. Samples that met the inclusion and exclusion criteria were examined for serum Lp(a) at the time of admission and the occurrence of MACE during hospitalization was observed. Data regarding serum Lp(a), demography, smoking history, dyslipidemia, hypertension, diabetes mellitus, and MACE were collected. Log rank test and Cox proportional hazards regression were conducted with SPSS version 20 for Windows. Results:During observation, MACE occurred in 25 (38%) patients, including cardiogenic shock in 7 (10.6%) patients, heart failure in 20 (30.3%) patients, cardiovascular death in 5 (7, 6%) patients, malignant arrhythmias in 5 (7.6%) patients, and postinfarction angina in 5 (7.6%) patients. After the Log rank test, a significant difference in survival was observed (p = 0.001) between groups of high Lp(a) (survival rate of 60.6 hours; 95% CI 43.3-77.9) and low Lp(a) (average survival of 104.3 hours, 95% CI 91.4-117.2). The hazard ratio of high Lp(a) against MACE was 4.63 (p=0.002), and it increased to 4.69 in multivariate analysis with Cox proportional hazards regression test (p=0.003). Conclusion:The high level of Lp(a) in AMI patients was a risk factor for the occurrence of MACE during hospitalization. Patients with high Lp(a) also had worse survival compared to patients with low Lp(a).