Preoperative chest radiographs in hip fracture patients: is there any additional value?
Bibliographic record
Abstract
PURPOSE: Preoperative screening in hip fracture patients is vital to minimize perioperative complications. Preoperative chest radiographs (POCR) are performed in many hip fracture patients. Earlier research showed that few POCR abnormalities influence perioperative policy. However, no studies in nonelective patient with a specific surgical conditions have been performed. With many hip fractures per year worldwide, a significant cost reduction could be made by performing selective POCR without compromising the quality of care. This study assessed the need for POCR in hip fracture patients. METHOD: Retrospective analysis of low-energy trauma patients was performed aged 18 years and older in the VU University Medical Center for a hip fracture in a 5-year period. All preoperative diagnostics were analyzed. All adjourned operations were evaluated. RESULTS: A total of 642 patients were included, 70% female, matching current epidemiologic figures. The POCR showed abnormalities in 22.6%. In 0.6% the POCR lead to an adjournment of the operation (2.8% of abnormal POCR's). These patients suffered from pneumonia. The POCR in these cases acted as a confirmation of the clinical diagnosis. CONCLUSION: Many factors involving the treatment of hip fracture patients are of importance in minimizing the risk of complications and mortality during and after admission. In 0.6% of all performed POCR's an abnormality leads to the adjournment of the operation. In all four cases the POCR matched the clinical findings. Because the additional value of the POCR in hip fracture patients was limited, we think that its selective use in clinical abnormalities is safe and will reduce unnecessary 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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".