Impact of Obstructive Sleep Apnea on Left Ventricular Mass and Diastolic Function
Bibliographic record
Abstract
We wished to determine if obstructive sleep apnea (OSA) is associated with increased left ventricular mass (LVM) and impaired left ventricular diastolic function (LVDF) independently of coexisting obesity, hypertension (HTN), and diabetes mellitus (DM). Patients without primary cardiac disease, referred for evaluation of OSA (n = 533), had overnight polysomnography and Doppler echocardiography while awake. Patients were divided, according to the apnea-hypopnea index (AHI), into an OSA group (AHI > or = 5/h, n = 353) and a non-OSA group (AHI < 5/h, n = 180). In men, LVM was greater in the OSA group (98.9 +/- 25.6 versus 92.3 +/- 22.5 g/m, p = 0.023) despite exclusion of those with HTN and DM. A similar trend was noted in women. Regression analysis revealed that LVM was correlated with body mass index (BMI) (beta = 0.480, p < 0.0005), age (beta = 0.16, p = 0.001), and the presence of HTN (beta = 0.137, p = 0.003) in men and with BMI (beta = 0.501, p < 0.0005) in women, but not with AHI or oxygen saturation during sleep. The ratio of peak early filling velocity to peak late filling velocity (E/A), an index of LVDF, was similar in both groups (1.28 +/- 0.32 versus 1.34 +/- 0.31, p = 0.058); it was correlated with age (beta = -0.474, p < 0.0005), but not with AHI or oxygen saturation during sleep. We conclude that OSA is not associated with increased LVM or impaired LVDF independently of obesity, HTN, or advancing age.
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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 | 0.003 |
| 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) | 0.001 | 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 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".