Comparison of heart rate and oxygen saturation measurements from Masimo and Nellcor pulse oximeters in newly born term infants
Bibliographic record
Abstract
AIM: To compare heart rate (HR) measurements from Masimo and Nellcor pulse oximeters (POs) against HR measured via a three lead electrocardiograph (ECG) (HRECG ). We also compared peripheral oxygen saturation (SpO2 ) measurements between Nellcor and Masimo oximeters. METHOD: Term infants born via elective caesarean section were studied. ECG leads were placed on the infant's chest and abdomen. Masimo and Nellcor PO sensors were randomly allocated to either foot. The monitors were placed on a trolley, and data from each monitor screen captured by a video camera. HR, SpO2 measurements and signal quality were extracted. Bland-Altman analysis was used to determine agreement between HR from the ECG and each oximeter, and between SpO2 from the oximeters. RESULTS: We studied 44 infants of whom 4 were resuscitated. More than 8000 pairs of observations were used for each comparison of HR and SpO2. The mean difference (±2SD) between HRECG and HRN ellcor was -0.8 (±11) beats per minute (bpm); between HRECG and HRM asimo was 0.2 (±9) bpm. The mean (±2SD) difference between SpO2Masimo and SpO2Nellcor was -3 (±15)%. The Nellcor PO measured 20% higher than the Masimo PO at SpO2 <70%. CONCLUSION: Both oximeters accurately measure HR. There was good agreement between SpO2 measurements when SpO2 ≥70%. At lower SpO2 , agreement was poorer.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".