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Background: Single-photon emission computed tomography (SPECT) myocardial perfusion is frequently used to predict risk of major adverse cardiovascular events (MACE). We performed an external validation of the CRAX2MACE score, developed to estimate 2-year risk of MACE in patients with suspected coronary artery disease (CAD).
Methods: Patients who underwent clinically indicated SPECT with available follow-up for MACE were included (N = 2,985). The prediction performance for MACE (revascularization, myocardial infarction, or death) within 2 years for CRAX2MACE was compared with stress and ischemic total perfusion deficit (TPD) using area under the receiver operating characteristic curve (AUC). Calibration was assessed with calibration plots, Brier score, and the Hosmer-Lemeshow test.
Results: MACE occurred within 2 years in 243 (8.1%) patients. The AUC for CRAX2MACE (0.710, 95% CI 0.677-0.743) was significantly higher compared to stress TPD (AUC 0.669, 95% CI 0.632-0.706, P = .010) and ischemic TPD (AUC 0.664, 95% CI 0.627-0.700, P < .001). The model had acceptable goodness-of-fit (P = .103) and was well-calibrated with Brier score of 0.071.
Conclusion: CRAX2MACE had higher predictive performance for 2-year MACE than quantitative perfusion in an external population. The current model is simple to use and could be implemented to assist physicians when estimating patient risk.
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http://dx.doi.org/10.1007/s12350-022-02964-z | DOI Listing |
J Comp Neurol
March 2025
Department of Neuroscience, Carleton University, Ottawa, Ontario, Canada.
The zona incerta (ZI) supports diverse behaviors including binge feeding, sleep-wake cycles, nociception, and hunting. Diverse ZI functions can be attributed to its heterogeneous neurochemical characterization, cytoarchitecture, and efferent connections. The ZI is predominantly GABAergic, but we recently identified a subset of medial ZI GABA cells that are marked by the enzyme tyrosine hydroxylase (TH) and produce dopamine (DA).
View Article and Find Full Text PDFAnn Ital Chir
March 2025
Graduate Faculty, Suzhou Medical College Affiliated Stomatological Hospital, Soochow University, 215123 Suzhou, Jiangsu, China; Department of Implantology, Suzhou Stomatological Hospital, 215004 Suzhou, Jiangsu, China.
Aim: This study aims to explore the factors impacting implant plaque re-formation after implant polishing surgery for peri-implantitis and to establish a predictive model using crucial factors, thereby providing an evidence-based reference for managing this condition.
Methods: This retrospective study analyzed clinical data from 203 patients who underwent implant polishing and shaping procedures in Suzhou Stomatological Hospital between November 2018 and October 2023. Study subjects were divided into a training set (n = 142) and a validation set (n = 61) in a 7:3 ratio.
J Immunother Cancer
March 2025
Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
Background: Accurate prediction of pathologic complete response (pCR) following neoadjuvant immunotherapy combined with chemotherapy (nICT) is crucial for tailoring patient care in esophageal squamous cell carcinoma (ESCC). This study aimed to develop and validate a deep learning model using a novel voxel-level radiomics approach to predict pCR based on preoperative CT images.
Methods: In this multicenter, retrospective study, 741 patients with ESCC who underwent nICT followed by radical esophagectomy were enrolled from three institutions.
Contemp Clin Trials
March 2025
Department of Anesthesia and Critical Care, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Background: Pulmonary fibrosis is a major complication of the Acute Respiratory Distress Syndrome (ARDS). Pirfenidone is an approved treatment for idiopathic pulmonary fibrosis. It may attenuate ARDS-related fibrosis and decrease the need for prolonged ventilation.
View Article and Find Full Text PDFJ Biomed Inform
March 2025
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy; Department of Cardiology, Cardiology Research Laboratory, Istituto Auxologico Italiano IRCCS, Milan, Italy.
Objective: Persona validation is a challenging task, often relying on costly external validation methods. The aim of this study was the development of a novel method for Personas validation based on data already available during their creation.
Methods: A novel approach based on self-supervised machine learning (SSML) was proposed.
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