Characterisation of the Oxygenation Response to Inspired Oxygen Adjustments in Preterm Infants
Bibliographic record
Abstract
BACKGROUND: Oxygen saturation (SpO2) targeting in the preterm infant may be improved with a better understanding of the SpO2 responses to changes in inspired oxygen (FiO2). OBJECTIVE: We investigated the first-order FiO2-SpO2 relationship, aiming to quantify the parameters governing that relationship, the influences on these parameters and their variability. METHODS: In recordings of FiO2 and SpO2 from preterm infants on continuous positive airway pressure and supplemental oxygen, we identified unique FiO2 adjustments and mapped the subsequent SpO2 responses. For responses identified as first-order, the delay, time constant and gain parameters were determined. Clinical and physiological predictors of these parameters were sought in regression analysis, and intra- and inter-subject variability was evaluated. RESULTS: In 3,788 h of available data from 47 infants at 31 (28-33) post-menstrual weeks [median (interquartile range)], we identified 993 unique FiO2 adjustments followed by a first-order SpO2 response. All response parameters differed between FiO2 increments and decrements, with increments having a shorter delay, longer time constant and higher gain [2.9 (1.7-4.8) vs. 1.3 (0.58-2.6), p < 0.05]. Gain was also higher in less mature infants and in the setting of recent SpO2 instability, and was diminished with increasing severity of lung dysfunction. Intra-subject variability in all parameters was prominent. CONCLUSIONS: First-order SpO2 responses show variable gain, influenced by the direction of FiO2 adjustment and the severity of lung disease, as well as substantial intra-subject parameter variability. These findings should be taken into account in adjustment of FiO2 for SpO2 targeting in preterm infants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".