Dataset Information

Risk Factors Associated With Major Cardiovascular Events 1 Year After Acute Myocardial Infarction.

ABSTRACT:

Importance

Patients 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.

Objectives

To identify risk factors and develop and evaluate a risk model that predicts 1-year cardiovascular events after AMI.

Design, setting, and participants

Prospective 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 measures

Major cardiovascular events, including recurrent AMI, stroke, heart failure, and death, within 1 year after discharge for the index AMI hospitalization.

Results

The 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 relevance

Nineteen 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.

SUBMITTER: Wang Y

PROVIDER: S-EPMC6324290 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Publications

Risk Factors Associated With Major Cardiovascular Events 1 Year After Acute Myocardial Infarction.

Wang Yun Y Li Jing J Zheng Xin X Jiang Zihan Z Hu Shuang S Wadhera Rishi K RK Bai Xueke X Lu Jiapeng J Wang Qianying Q Li Yetong Y Wu Chaoqun C Xing Chao C Normand Sharon-Lise SL Krumholz Harlan M HM Jiang Lixin L

JAMA network open 20180803 4

<h4>Importance</h4>Patients 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.<h4>Objectives</h4>To identify risk factors and develop and evaluate a risk model that predicts 1-year cardiovascular events after AMI.<h4>Design, setting, and participants</h4>Prospective cohort study. Patients with AMI (n = 4227), aged 18 year ...[more]

PMID: 30646102

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Project description:ObjectivesPatients 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.DesignData 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.Setting161 nationally representative hospitals, and 53 and 157 other hospitals were involved in the above three studies, respectively.Participants8010 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 measuresThe in-hospital major adverse cardiovascular events (MACE) was defined as death from any cause, recurrent AMI, or ischaemic stroke.ResultsThe 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.ConclusionsA 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.

Project description:BACKGROUND:Among patients undergoing noncardiac surgery, major vascular surgery is associated with a high risk of perioperative myocardial infarction (MI). Currently, there are no perioperative MI risk calculators accounting for intraoperative and postoperative risk factors in vascular surgery patients. We aimed to investigate specific risk factors for perioperative MI after major open vascular surgery to determine which patients are at highest risk of MI and the association of perioperative MI with perioperative transfusion. METHODS:This statewide, retrospective cohort study analyzed risk factors for perioperative MI in major open vascular surgery between July 2012 and December 2015 using the Michigan Surgical Quality Collaborative, a multicenter quality collaborative. Patients were identified using current procedure terminology codes including open abdominal aortic aneurysm repairs (oAAA), aortobifemoral bypasses (AFB), and lower extremity bypasses (LEB). Rates of myocardial infarction were described for each procedure. A priori, preoperative, intraoperative, and postoperative variables were evaluated using univariate and multivariable statistics after adjusting for intraoperative factors including anesthesia type, intraoperative blood loss, intraoperative transfusion, and intraoperative vasopressor medications. RESULTS:A total of 3,689 patients underwent major open vascular surgery, including 375 oAAA, 392 AFB, and 2,922 LEB procedures. The overall incidence of MI was 2.4%, varying from 1.8% for aortobifemoral bypass, 2.4% for lower extremity bypass, and 3.7% for open abdominal aortic aneurysm repair. Although preoperative risk factors for myocardial infarction included age, American Society of Anesthesiologists score, diabetes, coronary artery disease, congestive heart failure, use of beta blocker, lower preoperative hematocrit, and surgical priority (urgent/emergent cases), after adjusting for intraoperative risk factors, all preoperative risk factors were not significant with the exception of surgical priority. After adjusting for intraoperative factors, only surgical priority (odds ratio [OR] = 1.70, 95% confidence interval [CI] [1.01-2.85], P < 0.001) and postoperative transfusion (OR = 2.65, 95% CI [1.59-4.44], P < 0.001) was associated with myocardial infarction, and higher nadir hematocrit was inversely associated with myocardial infarction (OR = 0.89, 95% CI [0.85-0.94], P < 0.001). CONCLUSIONS:Among vascular surgery patients undergoing major open vascular surgery, surgical priority was the only preoperative risk factors independently associated with MI, and only postoperative variables such as nadir hematocrit and postoperative transfusion were associated with MI. This suggests minimizing intraoperative blood loss and prioritizing early intraoperative transfusion may be the potential targets for process improvement.

Dataset Information

Risk Factors Associated With Major Cardiovascular Events 1 Year After Acute Myocardial Infarction.

Importance

Objectives

Design, setting, and participants

Main outcomes and measures

Results

Conclusions and relevance

Publications

Risk Factors Associated With Major Cardiovascular Events 1 Year After Acute Myocardial Infarction.

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