0771 A Buccal Mucosal Reflectance Oximeter Accurately Measures Arterial Oxyhemoglobin Saturation and Pulse Rate
Bibliographic record
Abstract
Abstract Introduction Pulse oximeter (SpO2) devices suitable for multi-night monitoring of arterial oxyhemoglobin saturation (SaO2) are not readily available despite a need to monitor SaO2 decreases in patients with sleep apnea and pulmonary diseases during sleep. The objective of the current study was to assess the SpO2 and pulse rate accuracy of a buccal mucosal oximeter embedded into a custom-fitted overlay of the upper teeth by comparison to a gold standard (CO-oximeter SaO2 and ECG heart rate). Methods Accuracy of the buccal mucosal oximeter was assessed in healthy participants (n=12) under non-motion conditions. Participants were made progressively hypoxic by decreasing the fraction of inspired oxygen in a stepwise manner to achieve a range of SaO2 from approximately 97-70%. SpO2 and pulse rate values from the buccal mucosal oximeter were compared with CO-oximeter values of SaO2 and ECG heart rate, respectively. Results SaO2 values were evenly distributed over the range of 97-67%. Analysis of 325 CO-oximeter SaO2/buccal mucosal oximeter SpO2 data pairs yielded the following: r = 0.95; bias = 0.72; and accuracy root-mean-square (ARMS) = 2.94%. Analysis of 346 ECG heart rate/buccal mucosal oximeter pulse rate data pairs yielded the following: r = 0.99, bias = 0.30; and ARMS = 2.08%. Conclusion The results of the study indicate that the buccal mucosal oximeter accurately measures SpO2 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 providing multi-night monitoring of SaO2. Additionally, the intraoral placement of the oximeter may be particularly convenient due to its temperature regulation, protection from ambient light, and relative lack of mucosal melanin. Support (if any) This study was funded by ProSomnus Sleep Technologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".