Disparities in oxygen saturation and hypoxic burden levels in obstructive sleep apnoea patient’s response to oral appliance treatment
Bibliographic record
Abstract
Abstract Background Oxygen saturation indices show a strong correlation with long‐term health outcomes. Nonetheless, evidence on the relationship between reduction in respiratory events and increase in oxygenation levels following oral appliance (OA) treatment is scarce. Objectives To verify the relationship between reduction in the apnoea‐hypopnoea index (AHI) and oxygen saturation levels following OA treatment, we have conducted an evaluation of polysomnography (PSG) and clinical parameters associated with the improvement of oxygen desaturation. Methods OSA patients ( n = 48) who received an OA and had pre‐ and post‐treatment PSG were classified into three responder groups according to the change in AHI and min O 2 post‐treatment: responder AHIonly (decrease in AHI of ≥50% but increase in min O 2 level of <4% or decrease); responder MinO2only (increase in min O 2 level of ≥4% but decrease in AHI <50% or increase) and responder Congruous (decrease in AHI of ≥50% and increase in min O 2 level of ≥4%). Various demographic and PSG variables were statistically compared among groups. Results There were 26 (54.17%) responder AHIonly , 9 (18.75%) responder MinO2only and 13 (27.08%) responder Congruous . Pre‐treatment min O 2 was significantly lower in responder MinO2only . A higher pre‐treatment min O 2 showed a significant correlation with a smaller amount of change in mean O 2 ( r = −.486) and min O 2 ( r = −.764) with treatment. Pre‐treatment min O 2 showed the strongest ability to predict those who would show a ≥4% min O 2 increase following treatment. Conclusion Certain patients do not show sufficient decrease in hypoxaemia in spite of the improvement in AHI. Pre‐treatment min O 2 should be considered in OA treatment planning regarding its close relation to improvements in oxygenation levels with treatment.
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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 | 0.002 |
| 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) | 0.002 | 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".