Risk factors for prolonged stay after ambulatory surgery: economic considerations
Bibliographic record
Abstract
The risk factors that prolong length of stay of ambulatory patients can be classified as preoperative, intraoperative, and postoperative. Preoperative factors include the type of surgery, ear, nose and throat and strabismus surgery, old age and pre-existing congestive heart failure. Intraoperative factors include increasing length of surgery, and general anesthesia, while postoperative factors include postoperative nausea and vomiting, excessive pain and adverse cardiovascular events. The factors that anesthesiologists can address to reduce length of stay are postoperative nausea and vomiting and excessive pain. Multimodal management of postoperative nausea and vomiting and pain can minimize adverse events and thereby reduce length of stay in the postanesthetic care unit, but will not necessarily lead to a reduction in staffing levels. As personnel costs contribute the majority of postanesthetic care unit costs, more than 95%, direct financial savings may not be possible from eliminating adverse events alone. Optimizing the use of the postanesthetic care unit and reducing total hours in the unit with higher operating room turnover may lead to indirect financial benefits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".