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Patterns and phenotypes of enhanced recovery after surgery implementation in gynaecological oncology: A latent class analysis.

Created on 13 Aug 2026

Authors

Vasilios Pergialiotis, Dimitrios Haidopoulos, Alexandros Daponte, Dimitrios Tsolakidis, Stamatios Petousis, Ioannis Kalogiannidis, Maria Fanaki, Emmanouil Stamatakis, Theodoros Lappas, Nikolaos Thomakos

Published in

Journal of perioperative practice. Pages 17504589261473161. Aug 13, 2026. Epub Aug 13, 2026.

Abstract

Enhanced recovery after surgery protocols are widely recommended, yet their real-world implementation remains inconsistent due to multiple barriers. This study aimed to characterise implementation patterns during early enhanced recovery after surgery adoption.
We analysed 300 consecutive patients undergoing elective surgery for gynaecological malignancies across five tertiary centres. Enhanced recovery after surgery components were defined per international guidelines and coded as binary adherence indicators. Latent class analysis was used to identify implementation phenotypes based on patterns of enhanced recovery after surgery delivery. Institutional variation and known adherence barriers were also evaluated to assess their clinical impact.
Four enhanced recovery after surgery implementation phenotypes emerged: global implementation, anaesthesia-limited, postoperative-restricted, and drain-permissive. Phenotype classification demonstrated high certainty (median posterior probability 0.99) and varied significantly across institutions (p < 0.001; Cramer's V = 0.60). Poor baseline performance status and increased surgical complexity were associated with reduced adherence to anaesthesia-related and postoperative components. In contrast, the drain-permissive phenotype appeared independent of these factors, suggesting a physician-driven pattern.
Enhanced recovery after surgery implementation in gynaecological oncology clusters into distinct, clinically meaningful phenotypes rather than random variation. Recognising these structured patterns may support the development of targeted, institution-specific quality improvement strategies.

PMID:
42592796
Bibliographic data and abstract were imported from PubMed on 13 Aug 2026.

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