Prognostic clinical prediction models for acute post‐surgical pain in adults: a systematic review
Authors' conclusion
Effective prediction models could support the prevention and treatment of acute post-surgical pain; however, existing models are at high risk of bias which may affect their reliability to inform practice.
Study context
- Population
- Studies of prognostic risk prediction models for moderate to severe acute post-surgical pain in adults14 studies · 17 models
- Outcome
- Methodological conduct and performance of prediction models
Methodological detailsPROBAST risk of bias assessment, TRIPOD adherence assessment
- PROBAST risk of bias assessment
- TRIPOD adherence assessment
Pooled result
As reported in the abstract
Discrimination (AUC or c-statistic), range
0.61 to 0.83
Models reporting calibration
7
Overall adherence to TRIPOD items, median (IQR [range]) %
62 (53-66 [47-72])%
Original publication
Prognostic clinical prediction models for acute post‐surgical pain in adults: a systematic review. Anaesthesia. Published 16 September 2024. doi:10.
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