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Background <p>Chronic pain following calcaneal fracture surgery substantially diminishes patients' quality of life, yet effective risk prediction tools remain scarce. This study aimed to develop and validate a reliable predictive model for assessing the risk of chronic pain development after calcaneal fracture surgery.</p> Methods <p>This retrospective analysis examined 398 patients who underwent calcaneal fracture surgery between January 2022 and July 2023. Patients were randomly allocated into model development (<i>n</i> = 280) and validation (<i>n</i> = 118) cohorts. Independent risk factors were identified through multivariate logistic regression analysis to construct the prediction model. Model performance was evaluated using the area under the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis.</p> Results <p>The study identified several independent predictors of postoperative chronic pain: body mass index (BMI) (OR:1.10, 95%CI:1.02–1.19, <i>P</i> = 0.014), operative duration (OR:1.01, 95%CI:1.00–1.02, <i>P</i> = 0.019), surgical approach, and Böhler angle (OR:1.03, 95%CI:1.00–1.06, <i>P</i> = 0.025). The predictive model demonstrated good discriminative ability in both development and validation cohorts, with AUC values of 0.691 (95%CI:0.63–0.75) and 0.655 (95%CI:0.56–0.77), respectively. Calibration plots showed strong agreement between predicted probabilities and observed outcomes.</p> Conclusion <p>Our newly developed predictive model, incorporating BMI, operative duration, surgical approach, and Böhler angle, effectively predicts the risk of chronic pain following calcaneal fracture surgery. This tool provides valuable guidance for clinicians in conducting individualized risk assessments and implementing targeted preventive strategies.</p>

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Development of a predictive model for post-surgical chronic pain: a retrospective analysis of calcaneal fracture patients

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月19日

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  • Shibo Zhai,
  • Shuo Zhang,
  • Xinzhe Ma,
  • Yongchao Gong,
  • Zhiyong Hou,
  • Wei Chen,
  • Lijie Ma

摘要

Background

Chronic pain following calcaneal fracture surgery substantially diminishes patients' quality of life, yet effective risk prediction tools remain scarce. This study aimed to develop and validate a reliable predictive model for assessing the risk of chronic pain development after calcaneal fracture surgery.

Methods

This retrospective analysis examined 398 patients who underwent calcaneal fracture surgery between January 2022 and July 2023. Patients were randomly allocated into model development (n = 280) and validation (n = 118) cohorts. Independent risk factors were identified through multivariate logistic regression analysis to construct the prediction model. Model performance was evaluated using the area under the receiver operating characteristic (ROC) curve, calibration plots, and decision curve analysis.

Results

The study identified several independent predictors of postoperative chronic pain: body mass index (BMI) (OR:1.10, 95%CI:1.02–1.19, P = 0.014), operative duration (OR:1.01, 95%CI:1.00–1.02, P = 0.019), surgical approach, and Böhler angle (OR:1.03, 95%CI:1.00–1.06, P = 0.025). The predictive model demonstrated good discriminative ability in both development and validation cohorts, with AUC values of 0.691 (95%CI:0.63–0.75) and 0.655 (95%CI:0.56–0.77), respectively. Calibration plots showed strong agreement between predicted probabilities and observed outcomes.

Conclusion

Our newly developed predictive model, incorporating BMI, operative duration, surgical approach, and Böhler angle, effectively predicts the risk of chronic pain following calcaneal fracture surgery. This tool provides valuable guidance for clinicians in conducting individualized risk assessments and implementing targeted preventive strategies.