Enhancing predictive accuracy: Assessing the laparoscopic hysterectomy readmission score in a diverse endometrial cancer population.

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Bibliographic Details
Title: Enhancing predictive accuracy: Assessing the laparoscopic hysterectomy readmission score in a diverse endometrial cancer population.
Authors: Lightfoot MDS; Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Perlmutter Cancer Center, New York University Langone Health, New York, NY, United States of America. Electronic address: michelle.lightfoot@nyulangone.org., Sinnott JA; Department of Statistics, The Ohio State University College of Arts and Sciences, Columbus, OH, United States of America., Meade CE; Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH, United States of America., Barrington DA; Gynecologic Oncology Section, Women's Services and The Ochsner Cancer Institute, Ochsner Health, New Orleans, LA, USA., Cosgrove CM; Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, College of Medicine, The Ohio State University, Columbus, OH, United States of America., Chambers LM; Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, College of Medicine, The Ohio State University, Columbus, OH, United States of America., Felix AS; Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, OH, United States of America.
Source: Gynecologic oncology [Gynecol Oncol] 2025 Sep; Vol. 200, pp. 105-111. Date of Electronic Publication: 2025 Jul 29.
Publication Type: Journal Article
Journal Info: Publisher: Academic Press Country of Publication: United States NLM ID: 0365304 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1095-6859 (Electronic) Linking ISSN: 00908258 NLM ISO Abbreviation: Gynecol Oncol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1095-6859
DOI:10.1016/j.ygyno.2025.07.021