Internal and emergency medicine
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On December 7, 2022, China switched from dynamic zeroing strategy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reopening. A nationwide SARS-CoV-2 epidemic emerged rapidly. The effect of smoking on SARS-CoV-2 infection remains unclear. ⋯ Our study suggests a potential association between smoking and a reduced risk of SARS-CoV-2 infection and pneumonia. This indicates that nicotine and ACE2 play important roles in preventing COVID-19 and its progression. We suggest smokers use nicotine replacement therapy during hospitalization for COVID-19.
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Recurrent pericarditis, an inflammatory syndrome with a pathogenesis not fully elucidated, often presents diagnostic challenges. This study aims to assess the correlation of D-Dimer (D-D) and procalcitonin (PCT) levels with clinical, laboratory and imaging features in recurrent idiopathic pericarditis. We analyzed 412 patients with idiopathic recurrent pericarditis from 2019 to 2023 in our referral center. ⋯ PCT elevation was infrequent and unrelated to any variables. In idiopathic recurrent pericarditis unrelated to specific conditions, we observed a close association between elevated D-D levels and non-specific inflammation markers, including fever, increased CRP, and neutrophil leukocytosis. PCT levels were typically normal or mildly elevated.
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Despite progress in therapy, heart failure (HF) inflicts a heavy burden of hospital admissions. In this study, we identified among 1360 community-dwelling HF patients (mean age 70.7 ± 11.3 years, 72.5% men) subgroups sharing similar profiles of unplanned hospital admissions, based on the admission causes and frequency of each cause. Hospital discharge summaries were reviewed for the main admission cause. ⋯ The patient subgroups identified and predictors for these subgroups may guide personalized interventions to reduce the burden of unplanned hospitalizations among HF patients. Trial registration: ClinicalTrials.gov, NCT00533013. Registered 20 September 2007. https://clinicaltrials.gov/study/NCT00533013 .
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Sepsis triggers a harmful immune response due to infection, causing high mortality. Predicting sepsis outcomes early is vital. Despite machine learning's (ML) use in medical research, local validation within the Medical Information Mart for Intensive Care IV (MIMIC-IV) database is lacking. ⋯ We crafted an interpretable model for sepsis death risk prediction. ML algorithms surpassed traditional scores for sepsis mortality forecast. Validation in a Chinese teaching hospital echoed these findings.