Comparative Study of Early Health Care Use after Forearm Corrective Osteotomy
Bibliographic record
Abstract
Background Bone reconstruction is frequently required for corrective osteotomy of the forearm long bones. Studies have evaluated long term outcomes but not the impact of these procedures on early postoperative complications and health care utilization. Questions/Purposes This study evaluated the early postoperative health care utilization following corrective osteotomy of the radius and/or ulna. Patients and Methods The American College of Surgeons' National Surgical Quality Improvement Program (NSQIP) was the primary data source to perform a comparative statistical analysis of the bone autograft and nonautograft (allograft, graft substitute, or no graft) procedures. We performed a review of the NSQIP database (2005–2013) to evaluate patients who underwent a corrective osteotomy of the radius and/or ulna. Results There were 362 cases; autograft (n = 117) and nonautograft (n = 245). There were no significant differences with demographics or comorbidities. The majority of cases were outpatient surgeries and there were no significant differences in anesthesia time, operative time, or hospital length of stay. Overall, the average length of stay was 0.6 days, readmission rate was 2%, and the total complication rate was 1% and there was no statistically significant difference between reconstruction groups. Harvesting of autograft was not associated with the overall 30-day complications and specific markers of health care utilization. Conclusions Our results are derived from the heterogeneous hospital setting of NSQIP contributing centers. The health care utilization and 30-day complications are low following corrective osteotomy of forearm long bones and autograft harvest did not influence the health care utilization. Level of Evidence Therapeutic Level II.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".