Early detection of changes in lung mechanics with oscillometry following bariatric surgery in severe obesity
Bibliographic record
Abstract
Obesity is associated with respiratory symptoms that are reported to improve with weight loss, but this is poorly reflected in spirometry, and few studies have measured respiratory mechanics with oscillometry. We investigated whether early changes in lung mechanics following weight loss are detectable with oscillometry. Furthermore, we investigated whether the changes in lung mechanics measured in the supine position following weight loss are associated with changes in sleep quality. Nineteen severely obese female subjects (mean body mass index, 47.2 ± 6.6 kg/m(2)) were evaluated using spirometry, oscillometry, plethysmography, and the Pittsburgh Sleep Quality Index before and 5 weeks after bariatric surgery. These tests were conducted in both the upright and the supine position, and pre- and postbronchodilation with 200 μg of salbutamol. Five weeks after surgery, weight loss of 11.5 ± 2.5 kg was not associated with changes in spirometry and plethysmography, with the exception of functional residual capacity. There were also no changes in upright respiratory system resistance (Rrs) or reactance following weight loss. Importantly, however, in the supine position, weight loss caused a substantial reduction in Rrs. In addition, sleep quality improved significantly and was highly correlated with the reduction in supine Rrs. Prior to weight loss, subjects did not respond to the bronchodilator when assessed in the upright position with either spirometry or oscillometry; however, with modest weight loss, bronchodilator responsiveness returned to the normal range. Improvements in lung mechanics occur very early after weight loss, mostly in the supine position, resulting in improved sleep quality. These improvements are detectable with oscillometry but not with spirometry.
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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 | 0.000 | 0.001 |
| 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 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".