Perioperative Auto-titrated Continuous Positive Airway Pressure Treatment in Surgical Patients with Obstructive Sleep Apnea
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Obstructive sleep apnea (OSA) may worsen postoperatively. The objective of this randomized open-label trial is to determine whether perioperative auto-titrated continuous positive airway pressure (APAP) treatment decreases postoperative apnea hypopnea index (AHI) and improves oxygenation in patients with moderate and severe OSA. METHODS: The consented patients with AHI of more than 15 events/h on preoperative polysomnography were randomized into the APAP or control group (receiving routine care). The APAP patients received APAP for 2 or 3 preoperative, and 5 postoperative nights. All patients were monitored with oximetry for 7 to 8 nights (N) and underwent polysomnography on postoperative N3. The primary outcome was AHI on the postoperative N3. RESULTS: One hundred seventy-seven OSA patients undergoing orthopedic and other surgeries were enrolled (APAP: 87 and control: 90). There was no difference between the two groups in baseline data. One hundred six patients (APAP: 40 and control: 66) did polysomnography on postoperative N3, and 100 patients (APAP: 39 and control: 61) completed the study. The compliance rate of APAP was 45%. The APAP usage was 2.4-4.6 h/night. In the APAP group, AHI decreased from preoperative baseline: 30.1 (22.1, 42.5) events/h (median [25th, 75th percentile]) to 3.0 (1.0, 12.5) events/h on postoperative N3 (P < 0.001), whereas, in the control group, AHI increased from 30.4 (23.2, 41.9) events/h to 31.9 (13.5, 50.2) events/h, P = 0.302. No significant change occurred in the central apnea index. CONCLUSIONS: The trial showed the feasibility of perioperative APAP for OSA patients. Perioperative APAP treatment significantly reduced postoperative AHI and improved oxygen saturation in the patients with moderate and severe OSA.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it