Safety of day-case endoscopic sinus surgery in England: An observational study using an administrative dataset
Bibliographic record
Abstract
Background: As elective surgical services recover from the COVID-19 pandemic a movement towards day-case surgery may reduce waiting lists. However, evidence is needed to show that day-case surgery is safe for many ENT operations including endoscopic sinus surgery (ESS). We aimed to investigate the safety of ESS in England. Methods: This was an observational, secondary analysis of administrative data. Participants were all patients in England undergoing elective ESS procedure aged ≥ 17 years during for the five years from 1st April 2014 to 31st March 2019. The exposure variable was day-case or overnight stay. The primary outcome was emergency readmission within 30 days post-discharge. Results: Data were available for 49,223 patients operated on across 129 NHS hospital trusts. In trusts operating on more than 50 patients in the study period, rates of day-case surgery varied from 100% to 20.6%. Rates of day-case surgery increased from 64.0% in 2014/15 to 78.7% in 2018/19. Day-case patients had lower rates of 30-day emergency readmission (odds ratio 0.71, 95% confidence interval 0.62 to 0.81). For secondary outcomes measures, there was no evidence of poorer outcomes for day-case patients. Outcomes for patients operated on in trusts with ≥80% day-case rates compared to patients operated on in trusts with <50% rates of day-case surgery were similar. Conclusions: ESS can safely be performed as day-case surgery at current rates. There is a potential to increase rates of day-case ESS in England, especially in departments that currently have low rates of day-case ESS.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".