Can Noninvasive Hemoglobin Testing Be Used to Detect Postpartum Anemia? [A253]
Bibliographic record
Abstract
INTRODUCTION: Noninvasive hemoglobin analyzers measure hemoglobin percutaneously and offer the benefit of a one-time spot check without phlebotomy. The objective of this study was to determine the validity of noninvasive hemoglobin testing for detection of postpartum anemia (hemoglobin <10 g/dL). METHODS: A convenience sample of 584 women aged 18 and over were recruited on postpartum day 1 following a singleton delivery. Two noninvasive hemoglobin monitors, Masimo Pronto Pulse CO-Oximeter (Pronto) and Masimo Rad-67 Pulse CO-Oximeter (Rad-67), were evaluated and compared to the postpartum phlebotomy hemoglobin value. RESULTS: Of 584 participants, 31% (181) had postpartum anemia by phlebotomy hemoglobin measurement. Bland-Altman plots determined a positive bias of 2.4 (±1.2) g/dL with the Pronto and 2.2 (±1.1) g/dL with the Rad-67. Low sensitivity was observed: 15% for Pronto and 16% for Rad-67. Adjusting for the fixed positive bias, the Pronto demonstrated a sensitivity of 68% and specificity of 84%, while the Rad-67 demonstrated a sensitivity of 78% and specificity of 88%. CONCLUSION: A consistent overestimation of hemoglobin by the noninvasive monitors compared to phlebotomy hemoglobin result was observed. Even after adjusting for the fixed positive bias, the sensitivity for detecting postpartum anemia was low. Detection of postpartum anemia should not be based on these devices alone.
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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 | 0.005 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".