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Simple risk score based on the China Acute Myocardial Infarction registry for predicting in-hospital mortality among patients with non-ST-segment elevation myocardial infarction: results of a prospective observational cohort study.

ABSTRACT: OBJECTIVES:To simplify our previous risk score for predicting the in-hospital mortality risk in patients with non-ST-segment elevation myocardial infarction (NSTEMI) by dropping laboratory data. DESIGN:Prospective cohort. SETTING:Multicentre, 108 hospitals across three levels in China. PARTICIPANTS:A total of 5775 patients with NSTEMI enrolled in the China Acute Myocardial Infarction (CAMI) registry. PRIMARY OUTCOME MEASURES:In-hospital mortality. RESULTS:The simplified CAMI-NSTEMI (SCAMI-NSTEMI) score includes the following nine variables: age, body mass index, systolic blood pressure, Killip classification, cardiac arrest, ST-segment depression on ECG, smoking status, previous angina and previous percutaneous coronary intervention. Within both the derivation and validation cohorts, the SCAMI-NSTEMI score showed a good discrimination ability (C-statistics: 0.76 and 0.83, respectively); further, the SCAMI-NSTEMI score had a diagnostic performance superior to that of the Global Registry of Acute Coronary Events risk score (C-statistics: 0.78 and 0.73, respectively; p<0.0001 for comparison). The in-hospital mortality increased significantly across the different risk groups. CONCLUSIONS:The SCAMI-NSTEMI score can serve as a useful tool facilitating rapid risk assessment among a broader spectrum of patients admitted owing to NSTEMI. TRIAL REGISTRATION NUMBER:NCT01874691.

SUBMITTER: Song C

PROVIDER: S-EPMC6747644 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Simple risk score based on the China Acute Myocardial Infarction registry for predicting in-hospital mortality among patients with non-ST-segment elevation myocardial infarction: results of a prospective observational cohort study.

Song Chenxi C Fu Rui R Li Sidong S Yang Jingang J Wang Yan Y Xu Haiyan H Gao Xiaojin X Liu Jia J Liu Qianqian Q Wang Chunyue C Dou Kefei K Yang Yuejin Y

BMJ open 20190912 9

<h4>Objectives</h4>To simplify our previous risk score for predicting the in-hospital mortality risk in patients with non-ST-segment elevation myocardial infarction (NSTEMI) by dropping laboratory data.<h4>Design</h4>Prospective cohort.<h4>Setting</h4>Multicentre, 108 hospitals across three levels in China.<h4>Participants</h4>A total of 5775 patients with NSTEMI enrolled in the China Acute Myocardial Infarction (CAMI) registry.<h4>Primary outcome measures</h4>In-hospital mortality.<h4>Results</ ...[more]

PMID: 31515430

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Project description:BackgroundMachine learning (ML) risk prediction models, although much more accurate than traditional statistical methods, are inconvenient to use in clinical practice due to their nontransparency and requirement of a large number of input variables.ObjectiveWe aimed to develop a precise, explainable, and flexible ML model to predict the risk of in-hospital mortality in patients with ST-segment elevation myocardial infarction (STEMI).MethodsThis study recruited 18,744 patients enrolled in the 2013 China Acute Myocardial Infarction (CAMI) registry and 12,018 patients from the China Patient-Centered Evaluative Assessment of Cardiac Events (PEACE)-Retrospective Acute Myocardial Infarction Study. The Extreme Gradient Boosting (XGBoost) model was derived from 9616 patients in the CAMI registry (2014, 89 variables) with 5-fold cross-validation and validated on both the 9125 patients in the CAMI registry (89 variables) and the independent China PEACE cohort (10 variables). The Shapley Additive Explanations (SHAP) approach was employed to interpret the complex relationships embedded in the proposed model.ResultsIn the XGBoost model for predicting all-cause in-hospital mortality, the variables with the top 8 most important scores were age, left ventricular ejection fraction, Killip class, heart rate, creatinine, blood glucose, white blood cell count, and use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs). The area under the curve (AUC) on the CAMI validation set was 0.896 (95% CI 0.884-0.909), significantly higher than the previous models. The AUC for the Global Registry of Acute Coronary Events (GRACE) model was 0.809 (95% CI 0.790-0.828), and for the TIMI model, it was 0.782 (95% CI 0.763-0.800). Despite the China PEACE validation set only having 10 available variables, the AUC reached 0.840 (0.829-0.852), showing a substantial improvement to the GRACE (0.762, 95% CI 0.748-0.776) and TIMI (0.789, 95% CI 0.776-0.803) scores. Several novel and nonlinear relationships were discovered between patients' characteristics and in-hospital mortality, including a U-shape pattern of high-density lipoprotein cholesterol (HDL-C).ConclusionsThe proposed ML risk prediction model was highly accurate in predicting in-hospital mortality. Its flexible and explainable characteristics make the model convenient to use in clinical practice and could help guide patient management.Trial registrationClinicalTrials.gov NCT01874691; https://clinicaltrials.gov/study/NCT01874691.

Project description:ImportanceChallenges to improving ST-segment elevation myocardial infarction (STEMI) care are formidable in low- to middle-income countries because of several system-level factors.ObjectiveTo examine access to reperfusion and percutaneous coronary intervention (PCI) during STEMI using a hub-and-spoke model.Design, setting, and participantsThis multicenter, prospective, observational study of a quality improvement program studied 2420 patients 20 years or older with symptoms or signs consistent with STEMI at primary care clinics, small hospitals, and PCI hospitals in the southern state of Tamil Nadu in India. Data were collected from the 4 clusters before implementation of the program (preimplementation data). We required a minimum of 12 weeks for the preimplementation data with the period extending from August 7, 2012, through January 5, 2013. The program was then implemented in a sequential manner across the 4 clusters, and data were collected in the same manner (postimplementation data) from June 12, 2013, through June 24, 2014, for a mean 32-week period.ExposuresCreation of an integrated, regional quality improvement program that linked the 35 spoke health care centers to the 4 large PCI hub hospitals and leveraged recent developments in public health insurance schemes, emergency medical services, and health information technology.Main outcomes and measuresPrimary outcomes focused on the proportion of patients undergoing reperfusion, timely reperfusion, and postfibrinolysis angiography and PCI. Secondary outcomes were in-hospital and 1-year mortality.ResultsA total of 2420 patients with STEMI (2034 men [84.0%] and 386 women [16.0%]; mean [SD] age, 54.7 [12.2] years) (898 in the preimplementation phase and 1522 in the postimplementation phase) were enrolled, with 1053 patients (43.5%) from the spoke health care centers. Missing data were common for systolic blood pressure (213 [8.8%]), heart rate (223 [9.2%]), and anterior MI location (279 [11.5%]). Overall reperfusion use and times to reperfusion were similar (795 [88.5%] vs 1372 [90.1%]; P = .21). Coronary angiography (314 [35.0%] vs 925 [60.8%]; P < .001) and PCI (265 [29.5%] vs 707 [46.5%]; P < .001) were more commonly performed during the postimplementation phase. In-hospital mortality was not different (52 [5.8%] vs 85 [5.6%]; P = .83), but 1-year mortality was lower in the postimplementation phase (134 [17.6%] vs 179 [14.2%]; P = .04), and this difference remained consistent after multivariable adjustment (adjusted odds ratio, 0.76; 95% CI, 0.58-0.98; P = .04).Conclusions and relevanceA hub-and-spoke model in South India improved STEMI care through greater use of PCI and may improve 1-year mortality. This model may serve as an example for developing STEMI systems of care in other low- to middle-income countries.

Project description:The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), that causes coronavirus disease 2019 (COVID-19), has resulted in a global pandemic. Patients with cardiovascular risk factors or established cardiovascular disease are more likely to experience severe or critical COVID-19 illness and myocardial injury is a key extra-pulmonary manifestation. These patients frequently present with ST-elevation on an electrocardiogram (ECG) due to multiple etiologies including obstructive, non-obstructive, and/or angiographically normal coronary arteries. The incidence of ST-elevation myocardial infarction (STEMI) mimics in COVID-19-positive hospitalized patients, and the association with morbidity and mortality is unknown. Understanding the natural history and appropriate management of COVID-19 patients presenting with ST elevation is essential to inform patient management decisions and protect healthcare workers. Methods:The Society for Cardiovascular Angiography and Interventions (SCAI) and The Canadian Association of Interventional Cardiology (CAIC) in conjunction with the American College of Cardiology Interventional Council have collaborated to create a multi-center observational registry, NACMI. This registry will enroll confirmed COVID-19 patients and persons under investigation (PUI) with new ST-segment elevation or new onset left bundle branch block (LBBB) on the ECG with clinical suspicion of myocardial ischemia. We will compare demographics, clinical findings, outcomes and management of these patients with a historical control group of over 15,000 consecutive STEMI activation patients from the Midwest STEMI Consortium using propensity matching. The primary clinical outcome will be in- hospital major adverse cardiovascular events (MACE) defined as composite of all-cause mortality, stroke, recurrent MI, and repeat unplanned revascularization in COVID-19 confirmed or PUI. Secondary outcomes will include the following: reporting of etiologies of ST Elevation; cardiovascular mortality due to myocardial infarction, cardiac arrest and /or shock; individual components of the primary outcome; composite primary outcome at 1 year; as well as ECG and angiographic characteristics. Conclusion:The multicenter NACMI registry will collect data regarding ST elevation on ECG in COVID-19 patients to determine the etiology and associated clinical outcomes. The collaboration and speed with which this registry has been created, refined, and promoted serves as a template for future research endeavors.

Project description:BackgroundMyocardial infarction (MI) is the most prevalent cardiovascular disease globally and is considered a public health problem. In Peru, MI is the second leading cause of death at the national level, with a mortality rate that exceeds 10% in the hospital setting. The study aims to determine the clinical and epidemiological characteristics of ST-segment elevation myocardial infarction (STEMI) in tertiary care facilities belonging to the Peruvian public health system.Methods and analysisThis will be a prospective, observational, multicenter study, with baseline and two follow-up assessments: at admission to the health service, and 30 days and 12 months after admission. This multicenter study will be conducted in 27 hospitals located in the main cities of Peru. The patients included in the study will be over 18 years of age, of either sex, and will have been admitted to the health facility with a diagnosis of acute coronary syndrome with ST-segment elevation. The Kaplan-Meier method will be used to estimate the cumulative in-hospital mortality of patients at 30 days and 12 months of follow-up, and the log-rank test will be used to evaluate the differences between the survival curves between reperfused and non-reperfused patients. Subsequently, to evaluate the risk factors for successful reperfusion and cardiovascular adverse events, generalized linear models of the binomial family with log link function will be used to estimate the bivariate and multivariate relative risk (RR) with their respective 95% confidence intervals. This project was approved by the Ethics and Research Committee of the National Cardiovascular Institute (Instituto Nacional Cardiovascular "Carlos Alberto Peschiera Carrillo"-INCOR [in Spanish]; Approval report 21/2019-CEI).DiscussionAmong the strengths, the observational design will allow the inclusion of a large sample of patients, which will significantly contribute to the knowledge base on STEMI in Peru. It should be noted that this study is the first to examine the clinical-epidemiological characteristics of STEMI in high-resolution hospital centers in Peru with follow-up one year after the event, providing knowledge of these observable characteristics in daily clinical routine. Likewise, the multicenter nature of the study will increase the external validity of the findings. In terms of limitations, the observational design of the study can only describe associations and not causality. Furthermore, since data from medical records will be used, there could be imprecision in the data.

Dataset Information

Simple risk score based on the China Acute Myocardial Infarction registry for predicting in-hospital mortality among patients with non-ST-segment elevation myocardial infarction: results of a prospective observational cohort study.

Publications

Simple risk score based on the China Acute Myocardial Infarction registry for predicting in-hospital mortality among patients with non-ST-segment elevation myocardial infarction: results of a prospective observational cohort study.

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