Five‐degree, 10‐degree, and 20‐degree reverse Trendelenburg position during functional endoscopic sinus surgery: a double‐blind randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Using the reverse Trendelenburg position (RTP) during functional endoscopic sinus surgery (FESS) is a safe, simple, and cost-free method that has been found to reduce intraoperative blood loss. However, the critical angle of RTP that produces the least amount of bleeding without compromising surgical technique and safety remains unanswered. The objective of this study was to assess the effects of 5-degree, 10-degree, and 20-degree RTP (5-RTP, 10-RTP, and 20-RTP, respectively) on intraoperative bleeding during FESS. METHODS: This double-blind randomized controlled trial involved 75 patients with chronic rhinosinusitis (CRS) with and without nasal polyposis undergoing FESS. Twenty-five patients were enrolled into each group: 5-RTP, 10-RTP, and 20-RTP. Boezaart endoscopic field-of-view score (BS), total blood loss (TBL), mean arterial blood pressure (MABP), operating time, and blood loss per minute were recorded. An intention-to-treat analysis was used, with a Bonferroni adjustment for multiple comparisons. RESULTS: Intervention groups were comparable in age, sex, nasal polyposis, and disease severity. Mean values of BS and TBL were as follows: 5-RTP (2.0, 231 mL), 10-RTP (1.8, 230 mL), and 20-RTP (1.4, 135 mL). The differences in means were significant for BS (p < 0.01) and TBL (p = 0.03). There was no significant difference in MABP (p = 0.85), operating time (p = 0.10), or blood loss per minute (p = 0.11) between the 3 groups. Pairwise comparison between 5-RTP vs 20-RTP found significant difference in BS (p < 0.01) but not TBL (p = 0.04). Significance was not found in similar comparisons of 10-RTP vs 20-RTP and 5-RTP vs 10-RTP (p > 0.03). CONCLUSION: FESS in 20-RTP produced the best BS and lowest blood loss without compromising surgical technique.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".