Robotics & Machine Learning Daily News2024,Issue(Oct.8) :144-145.

First Affiliated Hospital of Soochow University Reports Findings in Subarachnoid Hemorrhage (Development and validation of a machine-learning model for predicti ng postoperative pneumonia in aneurysmal subarachnoid hemorrhage)

Robotics & Machine Learning Daily News2024,Issue(Oct.8) :144-145.

First Affiliated Hospital of Soochow University Reports Findings in Subarachnoid Hemorrhage (Development and validation of a machine-learning model for predicti ng postoperative pneumonia in aneurysmal subarachnoid hemorrhage)

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Abstract

New research on Central Nervous System Diseases and Conditions-Subarachnoid Hemorrhage is the subject of a report. A ccording to news reporting out of Suzhou, People's Republic of China, by NewsRx editors, research stated, "Pneumonia is a common postoperative complication in p atients with aneurysmal subarachnoid hemorrhage (aSAH), which is associated with poor prognosis and increased mortality. The aim of this study was to develop a predictive model for postoperative pneumonia (POP) in patients with aSAH." Our news journalists obtained a quote from the research from the First Affiliate d Hospital of Soochow University, "A retrospective analysis was conducted on 308 patients with aSAH who underwent surgery at the Neurosurgery Department of the First Affiliated Hospital of Soochow University. Univariate and multivariate log istic regression and lasso regression analysis were used to analyze the risk fac tors for POP. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the constructed model. F inally, the effectiveness of modeling these six variables in different machine l earning methods was investigated. In our patient cohort, 23.4% (n = 72/308) of patients experienced POP. Univariate, multivariate logistic regress ion analysis and lasso regression analysis revealed age, Hunt-Hess grade, mechan ical ventilation, leukocyte count, lymphocyte count, and platelet count as indep endent risk factors for POP. Subsequently, these six factors were used to build the final model. We found that age, Hunt-Hess grade, mechanical ventilation, leu kocyte count, lymphocyte count, and platelet count were independent risk factors for POP in patients with aSAH."

Key words

Suzhou/People's Republic of China/Asia/Brain Diseases and Conditions/Cardiovascular Diseases and Conditions/Central Nervous System Diseases and Conditions/Cerebrovascular Disorders/Cyborgs/Eme rging Technologies/Health and Medicine/Infectious Disease/Intracranial Hemorr hages/Lung Diseases and Conditions/Machine Learning/Pneumonia/Pulmonology/R espiratory Tract Diseases and Conditions/Respiratory Tract Infections/Risk and Prevention/Subarachnoid Hemorrhage

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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