Recovery Patterns: Longitudinal Cluster Analysis of Physical Function Following Abdominal Surgery

Ann Surg. 2025 Feb 18. doi: 10.1097/SLA.0000000000006671. Online ahead of print.

ABSTRACT

BACKGROUND: A rise in the proportion of day surgery has seen a concomitant increase in the proportion of patients recovering at home. Blended eHealth is well situated to provide this group with medical support and supervision. However, a data-driven description of the heterogeneity is missing.

OBJECTIVE: To identify clinically meaningful patterns of functional recovery following abdominal surgery and describe how the emergent patient characteristics differ between them.

METHODS: This was a secondary data analysis of two datasets collected through two previously conducted RCTs. We used k-medoids clustering and Growth Mixture Modelling on the longitudinal patient reported outcome measurement information system (PROMIS) physical function (PF) t-scores of 649 patients. Differences in patient characteristics between the resultant clusters were identified through statistical tests.

RESULTS: Three clusters - fast, intermediate and uneven recovery - were identified regardless of the dataset or statistical technique. A fourth cluster - relapse - was identified by both statistical techniques but only in the presence of heavy surgery. The fifth and sixth clusters - low gain and high gain - were identified for both light and heavy surgery, but only through k-medoids clustering.

CONCLUSIONS: Trajectories of physical function following abdominal surgery are heterogenous but distinct clinically meaningful patterns can be extracted. This classification may facilitate shared-decision making during pre-operative care and future research may utilize them as targets for prediction.

PMID:39963795 | DOI:10.1097/SLA.0000000000006671