Accuracy of Multiple Pulse Oximeters in Stable Critically Ill Patients
Bibliographic record
Abstract
BACKGROUND: An accurate S pO 2 value is critical in order to optimally titrate oxygen delivery to patients and to follow oxygenation guidelines. Limited prospective data exist on real-world performance of pulse oximeters in critically ill patients. The objective of this study was to assess accuracy and bias of the S pO 2 values measured by several oximeters in hospitalized subjects. METHODS: We included stable adults in the ICU with an arterial catheter in place. Main exclusion criteria were poor S pO 2 signal and S pO 2 > 96%. In each subject, we simultaneously evaluated 4 oximeters: Nonin (Plymouth, Minnesota) embedded in the FreeO 2 device (OxyNov, Québec City, Québec, Canada), Masimo (Radical-7, Masimo, Irvine, California), Philips (FAST, Philips, Amsterdam, the Netherlands), and Nellcor (N-600, Medtronic, Minneapolis, Minnesota). Arterial blood gases were drawn and simultaneously each oximeters' S pO 2 values were collected. S pO 2 values were compared to the reference (arterial oxygen saturation [S aO 2 ] value) to determine bias and accuracy. The ability for oximeters to detect hypoxemia and the impact of oximeters on oxygen titration were evaluated. RESULTS: We included 193 subjects (153 male, mean age 66 y) in whom 211 sets of measurements were performed. The skin pigmentation evaluated by Fitzpatrick scale showed 96.2% of subjects were light skin (types 1 and 2). One oximeter overestimated S aO 2 (Philips, +0.9%), whereas the 3 others underestimated S aO 2 (Nonin −3.1%, Nellcor −0.3%, Masimo −0.2%). S aO 2 was underestimated with Nonin oximeter in 91.3% of the cases, whereas it was overestimated in 55.2% of the cases with Philips oximeter. Moderate hypoxemia (S aO 2 86–90% or P aO 2 55–60 mm Hg) was detected in 92, 33, 42, and 11% of the cases with Nonin, Nellcor, Masimo, and Philips, respectively. CONCLUSIONS: We found significant bias and moderate accuracy between the tested oximeters and the arterial blood gases in the studied population. These discrepancies may have important clinical impact on the detection of hypoxemia and management of oxygen therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".