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Development and Validation of a Novel Risk Score for In-Hospital Major Bleeding in Acute Myocardial Infarction:-The SWEDEHEART Score.

ABSTRACT: Background Bleeding risk stratification in acute coronary syndrome is of highest clinical interest but current risk scores have limitations. We sought to develop and validate a new in-hospital bleeding risk score for patients with acute myocardial infarction. Methods and Results From the nationwide SWEDEHEART (Swedish Web-System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies) register, 97,597 patients with acute myocardial infarction enrolled from 2009 until 2014 were selected. A full model with 23 predictor variables and 8 interaction terms was fitted using logistic regression. The full model was approximated by a model with 5 predictors and 1 interaction term. Calibration, discrimination, and clinical utility was evaluated and compared with the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) and CRUSADE (Can Rapid Risk Stratification of Unstable Angina Patients Suppress Ad verse Outcomes With Early Implementation of the ACC /AHA Guidelines) scores. Internal and temporal validity was assessed. In-hospital major bleeding, defined as fatal, intracranial, or requiring surgery or blood transfusion, occurred in 1356 patients (1.4%). The 5 predictors in the approximate model that constituted the SWEDEHEART score were hemoglobin, age, sex, creatinine, and C-reactive protein. The ACTION and CRUSADE scores were poorly calibrated in the derivation cohort and therefore were recalibrated. The SWEDEHEART score showed higher discriminative ability than both recalibrated scores, overall ( C-index 0.80 versus 0.73/0.72) and in all predefined subgroups. Decision curve analysis demonstrated consistently positive and higher net benefit for the SWEDEHEART score compared with both recalibrated scores across all clinically relevant decision thresholds. The original ACTION and CRUSADE scores showed negative net benefit. Conclusions The 5-item SWEDEHEART score discriminates in-hospital major bleeding in patients with acute myocardial infarction and has superior model performance compared with the recalibrated ACTION and CRUSADE scores.

SUBMITTER: Simonsson M

PROVIDER: S-EPMC6474938 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BACKGROUND:Bleeding complications in patients with acute ST-segment elevation myocardial infarction (STEMI) have been associated with increased risk of subsequent adverse consequences. OBJECTIVE:The objective of our study was to develop and externally validate a diagnostic model of in-hospital bleeding. METHODS:We performed multivariate logistic regression of a cohort for hospitalized patients with acute STEMI in the emergency department of a university hospital. Participants: The model development data set was obtained from 4262 hospitalized patients with acute STEMI from January 2002 to December 2013. A set of 6015 hospitalized patients with acute STEMI from January 2014 to August 2019 were used for external validation. We used logistic regression analysis to analyze the risk factors of in-hospital bleeding in the development data set. We developed a diagnostic model of in-hospital bleeding and constructed a nomogram. We assessed the predictive performance of the diagnostic model in the validation data sets by examining measures of discrimination, calibration, and decision curve analysis (DCA). RESULTS:In-hospital bleeding occurred in 112 of 4262 participants (2.6%) in the development data set. The strongest predictors of in-hospital bleeding were advanced age and high Killip classification. Logistic regression analysis showed differences between the groups with and without in-hospital bleeding in age (odds ratio [OR] 1.047, 95% CI 1.029-1.066; P<.001), Killip III (OR 3.265, 95% CI 2.008-5.31; P<.001), and Killip IV (OR 5.133, 95% CI 3.196-8.242; P<.001). We developed a diagnostic model of in-hospital bleeding. The area under the receiver operating characteristic curve (AUC) was 0.777 (SD 0.021, 95% CI 0.73576-0.81823). We constructed a nomogram based on age and Killip classification. In-hospital bleeding occurred in 117 of 6015 participants (1.9%) in the validation data set. The AUC was 0.7234 (SD 0.0252, 95% CI 0.67392-0.77289). CONCLUSIONS:We developed and externally validated a diagnostic model of in-hospital bleeding in patients with acute STEMI. The discrimination, calibration, and DCA of the model were found to be satisfactory. TRIAL REGISTRATION:ChiCTR.org ChiCTR1900027578; http://www.chictr.org.cn/showprojen.aspx?proj=45926.

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:ObjectivesThe risk of adverse events and prognostic factors are changing in different time phases after acute myocardial infarction (AMI). The incidence of adverse events is considerable in the early period after AMI hospitalisation. Therefore, dynamic risk prediction is needed to guide postdischarge management of AMI. This study aimed to develop a dynamic risk prediction instrument for patients following AMI.DesignA retrospective analysis of a prospective cohort.Setting108 hospitals in China.ParticipantsA total of 23 887 patients after AMI in the China Acute Myocardial Infarction Registry were included in this analysis.Primary outcome measuresAll-cause mortality.ResultsIn multivariable analyses, age, prior stroke, heart rate, Killip class, left ventricular ejection fraction (LVEF), in-hospital percutaneous coronary intervention (PCI), recurrent myocardial ischaemia, recurrent myocardial infarction, heart failure (HF) during hospitalisation, antiplatelet therapy and statins at discharge were independently associated with 30-day mortality. Variables related to mortality between 30 days and 2 years included age, prior renal dysfunction, history of HF, AMI classification, heart rate, Killip class, haemoglobin, LVEF, in-hospital PCI, HF during hospitalisation, HF worsening within 30 days after discharge, antiplatelet therapy, β blocker and statin use within 30 days after discharge. The inclusion of adverse events and medications significantly improved the predictive performance of models without these indexes (likelihood ratio test p<0.0001). These two sets of predictors were used to establish dynamic prognostic nomograms for predicting mortality in patients with AMI. The C indexes of 30-day and 2-year prognostic nomograms were 0.85 (95% CI 0.83-0.88) and 0.83 (95% CI 0.81-0.84) in derivation cohort, and 0.79 (95% CI 0.71-0.86) and 0.81 (95% CI 0.79-0.84) in validation cohort, with satisfactory calibration.ConclusionsWe established dynamic risk prediction models incorporating adverse event and medications. The nomograms may be useful instruments to help prospective risk assessment and management of AMI.Trial registration numberNCT01874691.

Project description:Background The Predicting Bleeding Complications in Patients Undergoing Stent Implantation and Subsequent Dual Antiplatelet Therapy (PRECISE-DAPT) score has been shown to predict out-of-hospital major bleeding after myocardial infarction treated with percutaneous coronary intervention and dual antiplatelet therapy (DAPT). However, large validation studies have been scarce and the discriminative ability for patients with a preexisting bleeding risk factor (elderly, underweight, women, anemia, kidney dysfunction, or cancer) in a real-world setting is unknown. Methods and Results Patients undergoing percutaneous coronary intervention for myocardial infarction between 2008 and 2017 were included from the SWEDEHEART (Swedish Web System for Enhancement of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies) registry (n=66 295). The predictive value of the PRECISE-DAPT score for rehospitalization with major bleeding during dual antiplatelet therapy was evaluated using receiver operating characteristic analyses. A high PRECISE-DAPT score (≥25; n=13 894) was associated with increased risk of major bleeding (3.9% versus 1.8%; hazard ratio [HR], 2.2; 95% CI, 2.0-2.5; P<0.001) compared with a non-high score (<25; n=52 401). The score demonstrated a c-statistic of 0.64 (95% CI, 0.63-0.66). The discriminative ability of the score to further stratify bleeding risk in patients with preexisting bleeding risk factors was poor, especially in patients who are elderly (c-statistic=0.57; 95% CI, 0.55-0.60) or underweight (c-statistic=0.56; 95% CI, 0.51-0.61), for whom a non-high PRECISE-DAPT score was associated with similar bleeding risk as a high PRECISE-DAPT score in the general myocardial infarction population. Conclusions In this nationwide population-based study, the PRECISE-DAPT score performed moderately in the general myocardial infarction population and poorly in patients with preexisting bleeding risk factors, where its usefulness seems limited.

Project description:ObjectivesThe aim of this study was to determine whether frailty is associated with increased bleeding risk in the setting of acute myocardial infarction (AMI).BackgroundFrailty is a common syndrome in older adults.MethodsFrailty was examined among AMI patients ≥65 years of age treated at 775 U.S. hospitals participating in the ACTION (Acute Coronary Treatment and Intervention Outcomes Network) Registry from January 2015 to December 2016. Frailty was classified on the basis of impairments in 3 domains: walking (unassisted, assisted, wheelchair/nonambulatory), cognition (normal, mildly impaired, moderately/severely impaired), and activities of daily living. Impairment in each domain was scored as 0, 1, or 2, and a summary variable consisting of 3 categories was then created: 0 (fit/well), 1 to 2 (vulnerable/mild frailty), and 3 to 6 (moderate-to-severe frailty). Multivariable logistic regression was used to examine the independent association between frailty and bleeding.ResultsAmong 129,330 AMI patients, 16.4% had any frailty. Frail patients were older, more often female, and were less likely to undergo cardiac catheterization. Major bleeding increased across categories of frailty (fit/well 6.5%; vulnerable/mild frailty 9.4%; moderate-to-severe frailty 9.9%; p < 0.001). Among patients who underwent catheterization, both frailty categories were independently associated with bleeding risk compared with the non-frail group (vulnerable/mild frailty adjusted odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.23 to 1.44; moderate-to-severe frailty adjusted OR: 1.40, 95% CI: 1.24 to 1.58). Among patients managed conservatively, there was no association of frailty with bleeding (vulnerable/mild frailty adjusted OR: 1.01, 95% CI: 0.86 to 1.19; moderate-to-severe frailty adjusted OR: 0.96, 95% CI: 0.81 to 1.14).ConclusionsFrail patients had lower use of cardiac catheterization and higher risk of major bleeding (when catheterization was performed) than nonfrail patients, making attention to clinical strategies to avoid bleeding imperative in this population.

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Development and Validation of a Novel Risk Score for In-Hospital Major Bleeding in Acute Myocardial Infarction:-The SWEDEHEART Score.

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