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Related Concept Videos

Appendicitis-II: Diagnostic Studies and Management01:29

Appendicitis-II: Diagnostic Studies and Management

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Diagnosing and managing appendicitis requires a structured and comprehensive approach that spans from initial assessment to postoperative care. Here is an overview of the process:
Diagnosing Appendicitis
It requires a multifaceted approach, starting with a detailed physical examination to pinpoint the location and nature of the pain and identify any associated symptoms. Laboratory tests play a crucial role. A complete Blood Count (CBC) typically reveals leukocytosis (an increased number of...
57

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Related Experiment Video

Updated: May 27, 2025

Biomechanical Changes Related to Low Back Pain: An Innovative Tool for Movement Pattern Assessment and Treatment Evaluation in Rehabilitation
06:28

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

Daan J Toben1,2, Astrid de Wind2,3, Eva van der Meij2,4

  • 1Amsterdam UMC Vrije Universiteit Amsterdam, Public and Occupational Health, De Boelelaan 1117, Amsterdam, The Netherlands.

Annals of Surgery
|February 18, 2025
PubMed
Summary

Patients show varied physical function recovery after abdominal surgery. Identifying these distinct recovery patterns can improve personalized pre-operative care and guide future research for better patient outcomes.

Keywords:
K-medoids clusteringRecoverygrowth mixture modelinglongitudinal cluster analysisperioperative care

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Area of Science:

  • Surgical recovery research
  • Health informatics
  • Patient-reported outcomes

Background:

  • Increasing day surgery rates necessitate enhanced home recovery support.
  • Blended eHealth offers potential for remote patient supervision.
  • Lack of data-driven characterization of recovery heterogeneity hinders optimal care.

Purpose of the Study:

  • To identify distinct patterns of physical function recovery after abdominal surgery.
  • To analyze patient characteristics associated with different recovery trajectories.

Main Methods:

  • Secondary analysis of two randomized controlled trial datasets.
  • Utilized k-medoids clustering and Growth Mixture Modelling.
  • Analyzed longitudinal Patient Reported Outcome Measurement Information System (PROMIS) physical function (PF) t-scores from 649 patients.

Main Results:

  • Identified three consistent recovery patterns: fast, intermediate, and uneven.
  • A 'relapse' cluster emerged with heavy surgery.
  • Additional 'low gain' and 'high gain' clusters were observed with k-medoids clustering.

Conclusions:

  • Physical function recovery post-abdominal surgery is heterogeneous.
  • Distinct, clinically meaningful recovery patterns can be identified.
  • These patterns can inform shared decision-making and serve as targets for predictive research.