Hemostatic effect of hot saline irrigation during functional endoscopic sinus surgery: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: The endoscopically magnified operative field in functional endoscopic sinus surgery (FESS) makes even a small amount of bleeding a potentially significant hindrance. It is thought that irrigation with hot saline during surgery may improve surgical field of view by producing a hemostatic effect. Our objective was to assess the effectiveness of hot saline irrigation (HSI) compared to room temperature saline irrigation (RTSI) in the control of intraoperative bleeding during FESS. METHODS: Sixty-two chronic rhinosinusitis (CRS) patients undergoing FESS were randomized to 2 treatment arms in an equal ratio. Subjects received either HSI (49°C) or RTSI (18°C), 20 mL every 10 minutes, for the duration of FESS. The Boezaart endoscopic field of view grading system was the primary outcome measure. Boezaart score, heart rate, and mean arterial blood pressure (MABP) were recorded at 10-minute intervals between irrigations. RESULTS: Mean endoscopic surgical field of view (Boezaart score) did not significantly differ between the HSI and RTSI groups (1.5 ± 0.6 vs 1.3 ± 0.5; p = 0.23). However, when FESS was longer than 2 hours in duration, the Boezaart scores were significantly better in the HSI group (1.6 ± 0.6 vs 1.2 ± 0.4; p = 0.04). We found that blood loss per minute was significantly reduced (p = 0.02) in all cases in which HSI was used (2.3 ± 1.0) compared to RTSI (1.7 ± 1.1). Despite this, heart rate (p = 0.32) and MABP (p = 0.14) did not significantly differ between treatment groups. CONCLUSION: HSI may be beneficial in improving surgical field of view in FESS after 2 hours of operating time. A significant reduction in rate of blood loss may be attained with HSI.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 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 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".