ObjectivesTo establish a clinical prognostic nomogram for predicting in-hospital mortality after primary percutaneous coronary intervention (PCI) among patients with ST-elevation myocardial infarction (STEMI).DesignRetrospective, multicentre, observational study.SettingThirty-nine hospitals in Hebei province.ParticipantsPatients with STEMI who underwent PCI from January 2018 to December 2019.InterventionsA multivariable logistic regression model was used to identify the factors associated with in-hospital mortality, and a nomogram was established using these factors. The performance of the nomogram was evaluated by the discrimination, calibration and clinical usefulness.Primary and secondary outcome measuresThe outcome was the factors associated with in-hospital mortality.ResultsThis study included 855 patients, among whom 223 died in hospital. Age, body mass index, systolic pressure on admission, haemoglobin, random blood glucose on admission, ejection fraction after PCI, use aspirin before admission, long lesions, thrombolysis in myocardial infarction flow grade and neutrophils/lymphocytes ratio were independently associated with in-hospital mortality (all p<0.05). In the training set, the nomogram showed a C-index of 0.947, goodness-of-fit of 0.683 and area under the receiver operating characteristic curve (AUC) of 0.947 (95% CI 0.927 to 0.967). In the testing set, the C-index was 0.891, goodness-of-fit was 0.462 and AUC was 0.891 (95% CI 0.844 to 0.939). The results indicate that the nomogram had good discrimination and good prediction accuracy and could achieve a good net benefit.ConclusionsA nomogram to predict in-hospital mortality in patients with STEMI after PCI was developed and validated in Hebei, China and showed a satisfactory performance. Prospective studies will be necessary to confirm the performance and clinical applicability and practicality of the nomogram.
Purpose: Coronary no-reflow phenomenon (NRP), a common adverse complication in patients with ST-segment elevation myocardial infarction (STEMI) treated by percutaneous coronary intervention (PCI), is associated with poor patient prognosis. In this study, the correlation between the systemic immune-inflammation index (SII) and NRP in older patients with STEMI was studied, to provide a basis for early identification of high-risk patients and improve their prognosis. Materials and methods: Between January 2017 and June 2020, 578 older patients with acute STEMI admitted to the Department of Cardiology of Hebei General Hospital for direct PCI treatment were selected for this retrospective study. Patients were divided into an NRP group and normal-flow group according to whether NRP occurred during the operation. Clinical data and the examination indexes of the two groups were collected. Logistic regression was used to analyze the independent predictors of NRP, and the receiver operating characteristic curve was used to further analyze the ability of SII to predict NRP in older patients with STEMI. Results: Multivariate logistic analysis indicated that hypertension (OR=2.048, 95% CI:1.252–3.352, P=0.004), lymphocyte count (OR=0.571, 95% CI:0.368–0.885, P=0.012), platelet count (OR=1.009, 95% CI:1.005–1.013, P<0.001), hemoglobin (OR=1.015, 95% CI:1.003–1.028, P=0.018), multivessel disease (OR=2.237, 95% CI:1.407–3.558, P=0.001), and SII≥1814 (OR=3.799, 95% CI:2.190–6.593, P<0.001) were independent predictors of NRP after primary PCI in older patients with STEMI. Receiver operating characteristic curve analysis demonstrated that SII had a high predictive value for NRP (AUC=0.738; 95% CI:0.686–0.790), with the best cut-off value of 1814, a sensitivity of 52.85% and a specificity of 85.71%. Conclusion: For older patients with STEMI undergoing primary PCI, SII is a valid predictor of NRP.
SUMMARY Combined crown and post-and-core treatment often requires multiple intermittent appointments and takes a long time. This article describes a novel method for simultaneously fabricating a custom glass fiber post-and-core and the corresponding crown. The critical step, defined as a post-and-core virtual try-in, is to construct a virtual crown abutment that mimics the profile of a real one gained after post-cementation and tooth preparation. The fully digital workflow optimizes the treatment and saves time by accomplishing restorations on the first visit.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.