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◆ Frontiers in genetics2026-01-01

Risk factors and early warning scoring system for chronic postsurgical pain following video-assisted thoracoscopic surgery in elderly lung cancer patients: a retrospective cohort study.

Degui Wang, Weichen Pan, Qinghua Shi, Yuhong Liu

一句话结论 · In one sentence

This study identified seven independent risk factors for CPSP following VATS in elderly lung cancer patients and established a practical early warning scoring system with good predictive performance (AUC = 0.847), enabling preoperative risk stratification and facilitating targeted preventive interventions to improve long-term outcomes. External multicenter validation is warranted before clinical implementation.

原始摘要(英文原文)· Original abstract
BACKGROUND: Chronic postsurgical pain (CPSP) is a clinically significant and frequently underrecognized complication of video-assisted thoracoscopic surgery (VATS) for lung cancer, affecting a substantial proportion of elderly patients and adversely impacting quality of life and long-term recovery. In elderly populations, the risk of CPSP is compounded by age-related physiological vulnerabilities, high comorbidity burden, and psychosocial factors that predispose to central sensitization and pain chronification. Despite growing awareness of CPSP as a distinct clinical entity under the IASP ICD-11 classification, validated risk stratification tools specific to elderly patients undergoing VATS remain lacking. This study aims to identify independent clinical risk factors for CPSP following VATS in elderly lung cancer patients and to develop a practical, evidence-based early warning scoring system to support preoperative risk stratification and targeted preventive interventions. METHODS: A retrospective cohort study was conducted on 200 elderly patients (aged ≥65 years) who underwent VATS for lung cancer from 12 November 2023 to 13 August 2025 at a tertiary care center and were categorized into the CPSP group (n = 100) and non-CPSP group (n = 100) based on pain persistence beyond 3 months postoperatively. Comprehensive demographic, clinical, surgical, and perioperative data were collected. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors. A predictive scoring system was developed based on regression coefficients, and its discriminatory performance was assessed using receiver operating characteristic (ROC) curve analysis. RESULTS: The overall incidence of CPSP was 50.0% (100/200) in this elderly cohort. Multivariate logistic regression identified seven independent risk factors: advanced age (≥75 years, OR = 3.24, 95% CI: 1.78-5.89, p < 0.001), female gender (OR = 2.16, 95% CI: 1.24-3.76, p = 0.007), preoperative chronic pain (OR = 4.52, 95% CI: 2.15-9.51, p < 0.001), anxiety/depression (OR = 2.87, 95% CI: 1.52-5.42, p = 0.001), extensive lymph node dissection (OR = 3.08, 95% CI: 1.65-5.75, p < 0.001), intraoperative blood loss >50 mL (OR = 2.45, 95% CI: 1.32-4.54, p = 0.005), and inadequate acute postoperative pain control (OR = 3.76, 95% CI: 1.98-7.14, p < 0.001). A 0-17 point early warning scoring system was established: low risk (0-4 points, CPSP probability 8.3%), moderate risk (5-8 points, 47.7%), and high risk (≥9 points, 84.4%). The scoring system demonstrated good discriminatory performance with AUC of 0.847 (95% CI: 0.794-0.900), sensitivity 82.0%, and specificity 78.0% at the optimal cut-off of 7 points, pending external validation. CONCLUSION: This study identified seven independent risk factors for CPSP following VATS in elderly lung cancer patients and established a practical early warning scoring system with good predictive performance (AUC = 0.847), enabling preoperative risk stratification and facilitating targeted preventive interventions to improve long-term outcomes. External multicenter validation is warranted before clinical implementation.
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Risk factors and early warning scoring system for chronic postsurgical pain following video-assisted thoracoscopic surgery in elderly lung cancer patients: a retrospective cohort study. — 科研速览 Science Skim