Related Experiment Video
Updated: Aug 6, 2026
A Postoperative Evaluation Guideline for Computer-Assisted Reconstruction of the Mandible
Published on: January 28, 2020
The FACT-Score: Development and Temporal Validation of a Clinical Risk Stratification Tool for 30-Day Complications
Armin Catic1, Georgios Karamitros2, William C Lineaweaver2
1Centre for Big Data Research in Health, University of New South Wales, Sydney, NSW, Australia.
Background:
No validated, procedure-specific tool exists for predicting 30-day complications after operative facial fracture repair. This study aimed to develop and temporally validate a clinical risk stratification tool for 30-day complications after operative facial fracture repair.
Methods:
Adults undergoing operative facial fracture repair were identified in the American College of Surgeons National Surgical Quality Improvement Program from 2007 to 2022 (n=4805). The primary outcome was a 30-day ACS-NSQIP composite surgical morbidity endpoint comprising surgical site infection, wound dehiscence, and unplanned return to the operating room. Seven algorithms were benchmarked on a random 70/30 train-test split, including logistic regression, LASSO, random forest, XGBoost, support vector machine, naive Bayes, and neural network. The best-performing model was used to develop a 3-tier risk stratification system, resulting in the Facial Fracture Adverse-event Clinical Triage (FACT)-Score. Temporal validation was performed by training on patients who underwent surgery between 2007 and 2018 (n=3299) and testing on those undergoing surgery from 2019 to 2022 (n=1506). A parsimonious 5-variable clinical nomogram and web-based calculator were constructed for clinical deployment.
Results:
The overall 30-day complication rate was 6.7% (n=320). Logistic regression achieved the highest discrimination (AUC 0.764, 95% CI 0.713-0.814) and best calibration (Brier score 0.056), significantly outperforming 5 of 6 alternative algorithms (DeLong P<0.05). On temporal validation, the FACT-Score achieved an AUC of 0.797 (95% CI 0.755-0.839) with strong calibration (intercept -0.02, slope 0.98). The 3 risk tiers showed clear separation in observed complication rates: low risk 1.8% (95% CI 0.9%-3.0%), moderate risk 7.1% (4.9%-9.3%), and high risk 22.8% (17.8%-27.8%), with an odds ratio for high versus low risk of 15.88 (95% CI 8.78-31.25).
Conclusions:
In this national cohort, machine learning did not improve prediction beyond logistic regression for facial fracture complications. The 5-variable FACT-Score provides a simple, temporally validated tool for postoperative risk stratification in facial fracture surgery. A web-based calculator is freely available for clinical use at https://factscore.github.io/FACT-SCORE/.