Letter to the editor regarding "Development and internal validation of a clinical prediction model for deep surgical site infection after open extremity fractures: the BIGB2OSS score".

purposeTo critically examine the development, internal validation, calibration, and clinical interpretability of the BIGB2OSS score for predicting deep surgical site infection after open extremity fractures.

methodsA focused methodological appraisal was performed using the information reported in the original article. Candidate predictor complexity, event-to-parameter ratio, bootstrap validation, calibration assessment, model specification, and missing outcome data were evaluated against accepted prediction-model principles.

resultsThe model was developed from 45 deep-infection events after examining 18 candidate variables, corresponding to approximately 20 regression parameters (approximately 2.25 events per candidate parameter). Figure 3 reported an expected-to-observed ratio of 1.000, calibration-in-the-large of 0.000, and calibration slope of 1.000; however, these were apparent development-data estimates rather than optimism-corrected calibration measures. The apparent and optimism-adjusted C-statistics were both 0.76 with identical confidence intervals, while it was unclear whether the complete model-building sequence was repeated during bootstrapping. The model intercept and exact score-specific probabilities were not reported. In addition, 138 of 708 otherwise age-eligible patients (19.5%) lacked three-month outcome data.

conclusionThe BIGB2OSS score offers a clinically relevant framework for preliminary risk stratification, but its grouped probabilities should not yet be interpreted as validated individual risks. Full-process bootstrap validation, optimism-corrected calibration, transparent model specification, and sensitivity analyses for missing outcomes are required before external application.