The impact of targeted oxygen reduction test in preterm infants on reducing the oxygen exposure
Bibliographic record
Abstract
BACKGROUND: Caring for infants on respiratory support is a challenge in the middle-income countries, applying a protocol of targeted oxygen reduction test (tORT) guided by daily assessment of oxygen histograms is novel and practical approach. OBJECTIVE: To study the impact of tORT guided by daily assessment of oxygen histograms as a quality improvement project aiming to decrease days on oxygen support, and duration of hospital admission in preterm infants. STUDY DESIGN: A quality project conducted in neonatal intensive care units (NICU) of two hospitals, from 2017- 2018 (Epochs II). After a period of observation of a cohort of preterm Infants, 2016-2017 (Epoch I). The main aims were to reduce days on oxygen and hospital admission days. All infants in Epoch II underwent daily assessment of oxygen histograms and a trial of oxygen reduction if applicable as per a predefined protocol. Comparison was made between these two Epochs, and the primary outcome was the time to successful discontinuation of oxygen support. RESULTS: Fifty-nine infants were included; 30 underwent the protocolized tORT (Epoch II) with a median (IQR) of 4 (2-6) tORC per infant. Postanal age at presentation (time of initial tORT assessment was performed at the postnatal age of 8 (5, 13) days. Days on oxygen and total numbers of hospital days were significantly less in Epoch II. Oxygen histograms significantly improved after tORT. CONCLUSIONS: Applying tORT guided by oxygen histograms may have a significant impact on oxygen exposure and hospitalization days of patients admitted to the NICU.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".