What are the predictors of emergency department utilization and readmission following extremity bone sarcoma resection?
Bibliographic record
Abstract
INTRODUCTION: Treatment for bone sarcomas are large undertakings. Emergency department (ED) visits and unplanned hospital readmissions are a potential target for cost containment. The purpose of this study was to evaluate the risk factors for ED visits and unplanned readmissions following extremity bone sarcoma surgery. METHODS: Data from Optum Labs Data Warehouse, a national administrative claims database, was analyzed to identify patients with extremity bone sarcomas from 2006 to 2017. Multivariable logistic regression was used to identify factors associated with ED visits and readmissions. RESULTS: Of 1390 (743 males, 647 female) adult patients, 137 (12%) visited the ED and 245 (18%) were readmitted within 30 days of discharge. The most common indication for ED visits (n = 63, 45.9%) and readmission (n = 119, 48.5%) were complications of surgery. Length of stay >10 days was associated with ED utilization (OR, 1.83; P = .01) and readmission (OR, 4.47; P < .001). CONCLUSION: One in ten patients will use the ED, and one in five patients will be readmitted to the hospital within 30 days of discharge following extremity bone sarcoma surgery. Length of stay was associated with ED visits and readmission. These patients could be targeted with alternative management strategies in the outpatient setting with early clinical follow-up to minimize readmission.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".