Risk prediction models for complications after flap repair surgery: a systematic review and meta-analysis.

Abstract

Objective: To systematically evaluate the performance and applicability of risk prediction models for complications after flap repair and to provide guidance for building and refining models.

Methods: PubMed, Embase, Web of Science, the Cochrane Library, CNKI, SinoMed, VIP and Wanfang were searched for studies on risk prediction models for flap complications. The search period is from inception to December 28, 2024. The PROBAST tool was used to evaluate the quality of the prediction model research, and Stata 18 software was employed to meta-analyze the predictors of the models.

Results: A total of 16 studies were included, 28 risk prediction models were constructed, and the area under the receiver operating characteristic curve (AUC) ranged from 0.655 to 0.964, with 16 prediction models performing well (AUC > 0.7). Eleven articles underwent model calibration, 16 were validated internally, and 3 were validated externally. The results of the PROBAST review revealed that all 16 studies were at high risk of bias. The incidence rate of flap complications was 14.8% (95% CI, 10.7 - 19.0%). Body mass index (BMI), smoking history, long flap reconstruction time, diabetes mellitus, hypertension, and postoperative infection were independent risk factors for complications after flap repair (P < 0.05).

Conclusion: The risk prediction model for complications after flap repair has certain predictive value, but the overall risk of bias is high, and there is a lack of external validation; thus, it needs to be further enhanced and optimized to increase its prediction accuracy and clinical practicability.