A Buccal Mucosal Oximeter Accurately Measures Arterial Oxyhemoglobin Saturation
Bibliographic record
Abstract
Purpose: While arterial oxyhemoglobin saturation (SaO 2 ) decreases during sleep in many patients with sleep apnea and pulmonary diseases, personalized oximeters suitable for multi-night monitoring of SpO 2 are not readily available. The present report describes a custom buccal mucosal intraoral oximeter that might provide the opportunity for such long-term monitoring given its strong accuracy in measuring SpO 2 over a range of clinically relevant hypoxemia. Patients and Methods: The intraoral buccal mucosal oximeter was constructed by encapsulating a reflectance pulse oximeter in an overlay of the maxillary dentition. Accuracy was assessed during non-motion conditions in normal participants (n = 12) made progressively hypoxic by decreasing the partial pressure of end-tidal oxygen (PETO 2 ). CO-oximeter values of SaO 2 from arterial blood constituted the “gold standard” for comparison with the buccal mucosal oximeter’s values. The oximeter’s pulse rate and an electrocardiogram (ECG) determined heart rate were also compared. Results: Analysis of 325 paired SaO 2 values from the CO-oximeter and buccal mucosal oximeter yielded the following: r = 0.95; bias = 0.72; and accuracy root-mean-square (A RMS ) = 2.94%. Results from the pulse rate/ECG analysis were: r = 0.99; bias = 0.30; and A RMS = 2.08 bpm. Conclusion: These results reveal robust accuracy of the buccal mucosal oximeter measurement of SaO 2 and pulse rate, as shown by good agreement with a “gold standard” over a wide range of arterial hypoxemia. Such clinically acceptable accuracy indicates that this novel reflectance oximeter may prove useful in management of patients with sleep-induced hypoxemia by allowing for long-term monitoring of SaO 2 . Keywords: hypoxia, oximetry, intraoral pulse oximeter, respiratory monitoring, obstructive sleep apnea, remote patient monitoring
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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 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".