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Background <p>Postoperative non-infectious fever (PONF) frequently occurs after arthroscopic rotator cuff repair (ARCR), yet its early identification remains challenging.</p> Methods <p>This was a retrospective, single-center study. A total of 876 ARCR patients were retrospectively analyzed and randomly assigned to training (n = 613) and validation (n = 263) cohorts. Independent predictors of PONF were identified using logistic regression. A predictive model was established and presented as a nomogram and a simplified scoring system. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).</p> Results <p>Five variables were independently associated with PONF: age ≥ 60&#xa0;years, preoperative hemoglobin &lt; 110&#xa0;g/L, albumin &lt; 35&#xa0;g/L, operative time ≥ 90&#xa0;min, and intraoperative blood loss ≥ 50&#xa0;ml. The nomogram demonstrated good discrimination, with area under the curve (AUC) values of 0.84 in the training set and 0.80 in the validation set. Calibration curves showed good agreement between predicted and actual outcomes. DCA indicated favorable clinical net benefit.</p> Conclusion <p>A predictive model for PONF after ARCR was successfully developed and validated. This model may assist clinicians in identifying high-risk patients and implementing targeted perioperative strategies. External validation in multicenter cohorts is required prior to clinical implementation.</p>

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Development and validation of a predictive model for postoperative non-infectious fever following arthroscopic rotator cuff repair

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月22日

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  • Longqiang Zou,
  • Daqing Zhu,
  • Liangcai Huang,
  • Zhengnan Li,
  • Hui Zeng,
  • Shaojian Chen

摘要

Background

Postoperative non-infectious fever (PONF) frequently occurs after arthroscopic rotator cuff repair (ARCR), yet its early identification remains challenging.

Methods

This was a retrospective, single-center study. A total of 876 ARCR patients were retrospectively analyzed and randomly assigned to training (n = 613) and validation (n = 263) cohorts. Independent predictors of PONF were identified using logistic regression. A predictive model was established and presented as a nomogram and a simplified scoring system. Model performance was evaluated using receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).

Results

Five variables were independently associated with PONF: age ≥ 60 years, preoperative hemoglobin < 110 g/L, albumin < 35 g/L, operative time ≥ 90 min, and intraoperative blood loss ≥ 50 ml. The nomogram demonstrated good discrimination, with area under the curve (AUC) values of 0.84 in the training set and 0.80 in the validation set. Calibration curves showed good agreement between predicted and actual outcomes. DCA indicated favorable clinical net benefit.

Conclusion

A predictive model for PONF after ARCR was successfully developed and validated. This model may assist clinicians in identifying high-risk patients and implementing targeted perioperative strategies. External validation in multicenter cohorts is required prior to clinical implementation.