Prevalence of sleep disordered breathing in lung transplant recipients.
Bibliographic record
Abstract
STUDY OBJECTIVES: Weight gain and obesity are common after lung transplantation. Despite associations between these conditions and sleep disordered breathing (SDB) in the general population, the prevalence and clinical impact of SDB in lung transplant recipients is unknown. The study objective was to determine the prevalence and clinical correlates of SDB in a cohort of lung transplant recipients. METHODS: Single-center cross-sectional study. Overnight polysomnography, sleep questionnaires, and anthropomorphic measurements were conducted on 24 lung recipients transplanted at least one year previously. The primary outcome was the prevalence of SDB, defined as an apnea-hypopnea index (AHI) > or = 10 per hour. RESULTS: The prevalence of SDB was 63%. Obstructive sleep apnea (OSA) was observed in 38% and central sleep apnea (CSA) in 25%. Among all subjects, the mean AHI was 19.7 +/- 24.4 events/hour and the average weight gained after transplant was 10.5 +/- 12.3 kg. Subjects with SDB had a higher systolic blood pressure (135 +/- 12 vs. 124 +/- 13 mm Hg, p = 0.045), body mass index (BMI) (28.2 +/- 3.7 vs. 24.0 +/- 4.0 kg/m2, p = 0.008) and arousal index (28.0 +/- 26.9 vs. 10.4 +/- 6.4 per hour, p = 0.025) compared to the non-SDB group. Cyclosporine use was associated with CSA (p = 0.006). Recipients with OSA had a greater change (pre to post transplant) in BMI (5.8 +/- 4.6 vs. 2.0 +/- 2.9 kg/m2, p = 0.05) compared with non-SDB subjects. CONCLUSIONS: Sleep disordered breathing is highly prevalent after lung transplantation. Polysomnography should be considered in lung transplant recipients, especially if they have gained weight.
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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".