biostudies-literatureUnknown2022Wang Y<h4>Background</h4>Mortality after percutaneous coronary intervention (PCI) in ST-elevation myocardial infarction (STEMI) patients with cardiogenic shock (CS) remains high. However, the real-world risk factors for mortality in these patients are poorly defined.<h4>Objective</h4>The aim of this study is to establish a clinical prognostic nomogram for predicting in-hospital mortality after primary PCI in STEMI patients with CS.<h4>Methods</h4>This retrospective, multicenter, observational study included STEMI patients with CS who underwent PCI at 39 hospitals in Hebei Province from January 2018 to December 2019. A multivariate logistic regression model was used to identify the factors associated with in-hospital mortality. These factors were then incorporated into a nomogram and its performance was evaluated by discrimination, calibration, and clinical utility.<h4>Results</h4>This study included 274 patients, among whom 179 died in hospital. Sex, random blood glucose on admission, ejection fraction after PCI, no-reflow, and intra-aortic balloon pump (IABP) were independently associated with in-hospital mortality (all <i>P</i> < 0.05). In the training set, the nomogram showed a C-index of 0.819, goodness-of-fit of 0.08, and area under the receiver operating characteristic curve (AUC) of 0.819 (95%CI = 0.759-0.879). In the testing set, the C-index was 0.842, goodness-of-fit was 0.585, and AUC was 0.842 (95%CI = 0.715-0.970). The results indicate that the nomogram had good discrimination and good prediction accuracy and could achieve a good net benefit.<h4>Conclusion</h4>We established and validated a nomogram that provided individual prediction of in-hospital mortality for STEMI patients with CS after PCI in a Chinese population.Journal of interventional cardiology8994106https://www.ebi.ac.uk/biostudies/studies/S-EPMC8934239biostudies-literatureNomogram for Predicting In-Hospital Mortality in Patients with Acute ST-Elevation Myocardial Infarction Complicated by Cardiogenic Shock after Primary Percutaneous Coronary Intervention.PMC8934239Li XLi YLiu LQi XWang YDang YWang JfalseNomogram for Predicting In-Hospital Mortality in Patients with Acute ST-Elevation Myocardial Infarction Complicated by Cardiogenic Shock after Primary Percutaneous Coronary Intervention.<h4>Background</h4>Mortality after percutaneous coronary intervention (PCI) in ST-elevation myocardial infarction (STEMI) patients with cardiogenic shock (CS) remains high. However, the real-world risk factors for mortality in these patients are poorly defined.<h4>Objective</h4>The aim of this study is to establish a clinical prognostic nomogram for predicting in-hospital mortality after primary PCI in STEMI patients with CS.<h4>Methods</h4>This retrospective, multicenter, observational study included STEMI patients with CS who underwent PCI at 39 hospitals in Hebei Province from January 2018 to December 2019. A multivariate logistic regression model was used to identify the factors associated with in-hospital mortality. These factors were then incorporated into a nomogram and its performance was evaluated by discrimination, calibration, and clinical utility.<h4>Results</h4>This study included 274 patients, among whom 179 died in hospital. Sex, random blood glucose on admission, ejection fraction after PCI, no-reflow, and intra-aortic balloon pump (IABP) were independently associated with in-hospital mortality (all <i>P</i> < 0.05). In the training set, the nomogram showed a C-index of 0.819, goodness-of-fit of 0.08, and area under the receiver operating characteristic curve (AUC) of 0.819 (95%CI = 0.759-0.879). In the testing set, the C-index was 0.842, goodness-of-fit was 0.585, and AUC was 0.842 (95%CI = 0.715-0.970). The results indicate that the nomogram had good discrimination and good prediction accuracy and could achieve a good net benefit.<h4>Conclusion</h4>We established and validated a nomogram that provided individual prediction of in-hospital mortality for STEMI patients with CS after PCI in a Chinese population.2022-01-01T00:00:00Z20222025-05-31T22:23:42.365Z2025-05-31T22:23:42.365ZS-EPMC89342393535641910.1155/2022/8994106