{"title":"Regression analysis for cardiothoracic surgeons: part 5-predicting risks and outcomes in surgery.","authors":"H Shafeeq Ahmed","doi":"10.1007/s12055-025-01901-2","DOIUrl":null,"url":null,"abstract":"<p><p>Regression analysis is a powerful tool for cardiothoracic surgeons, enabling the prediction of patient outcomes and identification of key risk factors. This article explores the fundamentals of regression, including simple, multiple, and logistic regression models, and their applications in predicting surgical success, recovery times, and complication risks. Ensuring model assumptions are valid, selecting appropriate variables, and interpreting coefficients allows clinicians to make evidence-based decisions. Advanced techniques, such as handling non-linear relationships through polynomial regression and log transformations, are essential when dealing with more complex data. These techniques are critical in clinical research for addressing key research questions.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s12055-025-01901-2.</p>","PeriodicalId":13285,"journal":{"name":"Indian Journal of Thoracic and Cardiovascular Surgery","volume":"41 4","pages":"503-514"},"PeriodicalIF":0.6000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11933567/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indian Journal of Thoracic and Cardiovascular Surgery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s12055-025-01901-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/2/5 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Regression analysis is a powerful tool for cardiothoracic surgeons, enabling the prediction of patient outcomes and identification of key risk factors. This article explores the fundamentals of regression, including simple, multiple, and logistic regression models, and their applications in predicting surgical success, recovery times, and complication risks. Ensuring model assumptions are valid, selecting appropriate variables, and interpreting coefficients allows clinicians to make evidence-based decisions. Advanced techniques, such as handling non-linear relationships through polynomial regression and log transformations, are essential when dealing with more complex data. These techniques are critical in clinical research for addressing key research questions.
Supplementary information: The online version contains supplementary material available at 10.1007/s12055-025-01901-2.
期刊介绍：
The primary aim of the Indian Journal of Thoracic and Cardiovascular Surgery is education. The journal aims to dissipate current clinical practices and developments in the area of cardiovascular and thoracic surgery. This includes information on cardiovascular epidemiology, aetiopathogenesis, clinical manifestation etc. The journal accepts manuscripts from cardiovascular anaesthesia, cardiothoracic and vascular nursing and technology development and new/innovative products.The journal is the official publication of the Indian Association of Cardiovascular and Thoracic Surgeons which has a membership of over 1000 at present.DescriptionThe journal is the official organ of the Indian Association of Cardiovascular-Thoracic Surgeons. It was started in 1982 by Dr. Solomon Victor and ws being published twice a year up to 1996. From 2000 the editorial office moved to Delhi. From 2001 the journal was extended to quarterly and subsequently four issues annually have been printed out at time and regularly without fail. The journal receives manuscripts from members and non-members and cardiovascular surgeons. The manuscripts are peer reviewed by at least two or sometimes three or four reviewers who are on the panel. The manuscript process is now completely online. Funding the journal comes partially from the organization and from revenue generated by subscription and advertisement.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
