{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T10:20:33Z","timestamp":1790504433089,"version":"4.1.0"},"reference-count":48,"publisher":"American Medical Association (AMA)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Surg"],"published-print":{"date-parts":[[2024,7,1]]},"abstract":"\n Importance<\/jats:title>\n Prior studies demonstrated consistent associations of low skeletal muscle mass assessed on surgical planning scans with postoperative morbidity and mortality. The increasing availability of imaging artificial intelligence enables development of more comprehensive imaging biomarkers to objectively phenotype frailty in surgical patients.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To evaluate the associations of body composition scores derived from multiple skeletal muscle and adipose tissue measurements from automated segmentation of computed tomography (CT) with the Hospital Frailty Risk Score (HFRS) and adverse outcomes after abdominal surgery.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n This retrospective cohort study used CT imaging and electronic health record data from a random sample of adults who underwent abdominal surgery at 20 medical centers within Kaiser Permanente Northern California from January 1, 2010, to December 31, 2020. Data were analyzed from April 1, 2022, to December 1, 2023.<\/jats:p>\n <\/jats:sec>\n \n Exposure<\/jats:title>\n Body composition derived from automated analysis of multislice abdominal CT scans.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n The primary outcome of the study was all-cause 30-day postdischarge readmission or postoperative mortality. The secondary outcome was 30-day postoperative morbidity among patients undergoing abdominal surgery who were sampled for reporting to the National Surgical Quality Improvement Program.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n The study included 48\u202f444 adults; mean [SD] age at surgery was 61 (17) years, and 51% were female. Using principal component analysis, 3 body composition scores were derived: body size, muscle quantity and quality, and distribution of adiposity. Higher muscle quantity and quality scores were inversely correlated (\n r<\/jats:italic>\n \u2009=\u2009\u22120.42; 95% CI, \u22120.43 to \u22120.41) with the HFRS and associated with a reduced risk of 30-day readmission or mortality (quartile 4 vs quartile 1: relative risk, 0.61; 95% CI, 0.56-0.67) and 30-day postoperative morbidity (quartile 4 vs quartile 1: relative risk, 0.59; 95% CI, 0.52-0.67), independent of sex, age, comorbidities, body mass index, procedure characteristics, and the HFRS. In contrast to the muscle score, scores for body size and greater subcutaneous and intermuscular vs visceral adiposity had inconsistent associations with postsurgical outcomes and were attenuated and only associated with 30-day postoperative morbidity after adjustment for the HFRS.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this study, higher muscle quantity and quality scores were correlated with frailty and associated with 30-day readmission and postoperative mortality and morbidity, whereas body size and adipose tissue distribution scores were not correlated with patient frailty and had inconsistent associations with surgical outcomes. The findings suggest that assessment of muscle quantity and quality on CT can provide an objective measure of patient frailty that would not otherwise be clinically apparent and that may complement existing risk stratification tools to identify patients at high risk of mortality, morbidity, and readmission.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamasurg.2024.0628","type":"journal-article","created":{"date-parts":[[2024,4,10]],"date-time":"2024-04-10T11:01:25Z","timestamp":1712746885000},"page":"766","source":"Crossref","is-referenced-by-count":42,"title":["Automated CT Analysis of Body Composition as a Frailty Biomarker in Abdominal Surgery"],"prefix":"10.1001","volume":"159","author":[{"given":"Ijeamaka Anyene","family":"Fumagalli","sequence":"first","affiliation":[{"name":"Division of Research, Kaiser Permanente Northern California, Oakland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sidney 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