The utility of routine autologous bone-flap swab cultures in predicting post-cranioplasty infection
Bibliographic record
Abstract
Abstract Objective: To evaluate the utility of autologous bone-flap swab cultures performed at the time of cranioplasty in predicting postcranioplasty surgical site infection (SSI). Design: Retrospective cohort study. Participants: Patients undergoing craniectomy (with bone-flap storage in tissue bank), followed by delayed autologous bone-flap replacement cranioplasty between January 1, 2010, and November 30, 2020. Setting: Tertiary-care academic hospital. Methods: We framed the bone-flap swab culture taken at the time of cranioplasty as a diagnostic test for predicting postcranioplasty SSI. We calculated, sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios. Results: Among 282 unique eligible cases, 16 (5.6%) developed SSI after cranioplasty. A high percentage of bone-flap swab cultures were positive at the time of craniectomy (66.7%) and cranioplasty (59.5%). Most organisms from bone-flap swab cultures were Cutibacterium acnes or coagulase-negative staphylococci (76%–85%), and most SSI pathogens were methicillin-susceptible Staphylococcus aureus (38%). Bone-flap swab culture had poor sensitivity (0.07; 95% CI, 0.01–0.31), specificity (0.4; 95% CI, 0.34–0.45), and positive likelihood ratio (0.12) for predicting postcranioplasty SSI. Conclusion: Overall, autologous bone-flap swab cultures performed at the time of cranioplasty have poor utility in predicting postcranioplasty SSI. Eliminating this low-value practice would result in significant workload reductions and associated healthcare costs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".