Titration of Inspired Oxygen in Preterm Infants with Hypoxemic Respiratory Failure Using Near Infrared Spectroscopy and Pulse Oximetry: A New Approach
Bibliographic record
Abstract
Background: Titration of inspired oxygen is a challenge in preterm infants with hypoxemic respiratory failure (HRF). Monitoring of brain oxygen by near infrared spectroscopy (NIRS) has been proven to minimize the burden of hyperoxia and hypoxemia, with better understanding of cerebral autoregulation (CAR). integrating NIRS and pulse oximetry (SpO2) for titrating inspired oxygen is a novel approach. Methods: We aimed to study the impact of integrated monitoring of oxygen saturation by SpO2 and cerebral regional tissue oxygen (crRTO) by NIRS during oxygen reduction test (ORT) on reducing oxygen requirement in preterm infants with HRF. The correlation between SpO2 with crRTO, and fractional oxygen extraction (FOE) was assessed, concordance levels (r>0.5) were determined during the assessment period, and was considered as a sign of impaired autoregulation. The primary outcome was the achievement of significantly lower FiO2 at 72 hours after start of the integrated monitoring. Results: Total of 38 preterm infants were included, 27 had normal cerebral autoregulation (CAR), (group 1) in whom SpO2 was poorly correlating with cerebral regional tissue oxygen (crRTO) with (r<0.5) and had significantly greater percentage of reduction below baseline in FiO2 (Mean:34%). Eleven infants had impaired CAR (group 2) with SpO2 significantly correlating with crRTO (r>0.5) and had a linear trend of FOE inverse to SpO2 and crRTO; this was considered as an arterial saturation dependent oxygen delivery (SadDO2). Conclusion: Integrated monitoring of preterm infants by SpO2 and crRTO was associated with easier weaning of oxygen with less burden of both hyperoxia and hypoxemia.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".