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Identifying At-Risk Subgroups for Acute Postsurgical Pain: A Classification Tree Analysis.

Yang Wang1, Zejun Liu1, Shuanghong Chen1

  • 1Key Laboratory of Cognition and Personality, Southwest University, Chongqing, China.

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This summary is machine-generated.

Classification tree analysis (CTA) identified pain self-efficacy, disease onset, pain catastrophizing, and BMI as key predictors of acute postoperative pain. CTA helps identify patients at higher risk for severe pain.

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Area of Science:

  • Pain Medicine
  • Medical Statistics
  • Psychosomatic Medicine

Background:

  • Acute postsurgical pain is a prevalent issue with potential long-term adverse effects.
  • Predicting and managing acute postsurgical pain remains a clinical challenge.

Purpose of the Study:

  • To evaluate the predictive value of presurgery sociodemographics, pain experiences, psychological factors, and surgery-related variables on acute postsurgical pain.
  • To compare logistic regression with classification tree analysis (CTA) for identifying predictors of postoperative pain.

Main Methods:

  • Prospective study design involving 259 patients (175 women, 84 men).
  • Patients completed self-report measures 24 hours before surgery and pain intensity ratings 48-72 hours after surgery.
  • Logistic regression and classification tree analysis (CTA) were employed to analyze predictors.

Main Results:

  • Logistic regression initially identified pain self-efficacy as the sole significant predictor.
  • CTA revealed that pain self-efficacy, its interaction with disease onset, pain catastrophizing, and body mass index predicted pain intensity.
  • CTA findings were validated using a revised logistic regression model.

Conclusions:

  • Classification tree analysis (CTA) is a valuable tool for identifying patient subgroups at varying risks for severe acute postoperative pain.
  • Interacting patient characteristics, beyond individual factors, are crucial for predicting postoperative pain intensity.
  • This approach enhances the ability to stratify patients based on their risk for severe acute pain.