A Descriptive Report of Combination Therapy (Custom Face Mask for CPAP Integrated With a Mandibular Advancement Splint) for Long-Term Treatment of OSA With Literature Review
Bibliographic record
Abstract
JDSMStudy Objectives: This is a descriptive retrospective study about the efficacy of combination therapy using the TAP-PAP custom face mask (CFM) interface, with a literature review of combination therapy.The purpose of this study is to determine which group of failed obstructive sleep apnea (OSA) therapies would benefit from combination therapy with the CFM.The three failed therapies are mandibular advancement splint (MAS) monotherapy, continuous positive airway pressure (CPAP) monotherapy, and TAP-PAP CS (nasal pillows) combination therapy.Clinically, this will assist the clinician to understand the benefit of the CFM when the patient's current therapy fails.Methods: There was a retrospective chart review of patients on combination therapy from 2006-2012.The 75 patients who underwent combination therapy with the CFM were categorized into the three failed groups.OSA severity was compared between groups.CPAP and compliance were compared before and after CFM use.A 6-year follow-up was conducted.Results: A total of 220 charts of patients undergoing combination therapy were reviewed; 75 patients were in combination therapy with a CFM.The populations of the three groups were as follows: MAS monotherapy failed in 11 (11%), TAP-PAP CS failed in 21 (27%), and CPAP failed in 43 (57%) before the CFM was used.These patients had severe OSA with mean CPAP 14 cm H 2O. At 6-year followup, a 78% compliance rate and average CPAP of 13 cm H2O were reported.Conclusions: This study suggests that patients in whom CPAP monotherapy failed would benefit the most from the CFM.The application of the CFM is for patients with more severe OSA and is well tolerated with improved compliance.The CFM should be considered when other therapeutic methods of treating OSA have failed or when CPAP or the CPAP mask are intolerable to the patient.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".