Fetal oxygenation measurement using wireless near infrared spectroscopy
Bibliographic record
Abstract
Background: Fetal well-being is determined in large part by how well the placenta is able to supply oxygen and nutrients, but current technology is unable to directly measure how well a placenta functions. Near-infrared spectroscopy (NIRS) utilizes optical methods to measure tissue oxygenation. This pilot project evaluated the feasibility of NIRS for fetal monitoring through the maternal abdominal wall using a sheep model. Methods: A miniature wireless 2-wavelength NIRS device was placed on the abdominal skin over the placenta of a pregnant ewe whose fetus had been chronically catheterized to allow arterial sampling for measurement of arterial oxygen saturation. The NIRS device has 3-paired light emitting diodes and a single photodiode detector; allowing measurement of an index of tissue oxygen saturation (TSI%). Fetal limb TSI% values were compared before and during fetal breathing movements. Correlation was made during these events between arterial values and placental TSI% monitored continuously in real time. Results: Serial measurements were obtained in a single experiment. The correlation between transcutaneous NIRS derived TSI% and direct arterial oxygen saturation was very high (R2=0.86). Measures of fetal limb TSI% were declined after episodes of fetal breathing (P<0.005). Conclusions: This correlation suggests that NIRS is sensitive enough to detect changes in fetal tissue oxygenation noninvasively through the maternal abdominal wall in real-time in a sheep model. NIRS data confirmed that fetal breathing movements decrease arterial oxygen saturation in fetal lambs. If validated by further study this optical methodology could be applied as means of monitoring fetal wellbeing in humans.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".