A graphical method for comparing nocturnal oxygen saturation profiles in individuals and populations: Application to healthy infants and preterm neonates
Bibliographic record
Abstract
Abstract Study Objectives Pulse‐oximetry (SpO2) allows the identification of important clinical physiology. However, summary statistics such as mean values and desaturation incidence do not capture the complexity of the information contained within continuous recordings. The aim of this study was to develop an objective method to quantify important SpO2 characteristics; and assess its utility in healthy infant and preterm neonate cohorts. Methods An algorithm was developed to calculate the desaturation incidence, depth, and duration. These variables are presented using three plots: SpO2 cumulative‐frequency relationship; desaturation‐depth versus incidence; desaturation‐duration versus incidence. This method was applied to two populations who underwent nocturnal pulse‐oximetry: (1) thirty‐four healthy term infants studied at 2‐weeks, 3, 6, 12, and 24‐months of age and (2) thirty‐seven neonates born <26 weeks and studied at discharge from NICU (37‐44 weeks post‐conceptual age). Results The maturation in healthy infants was characterized by reduced desaturation index (27.2/h vs 3.3/h at 2‐weeks and 24‐months, P < 0.01), and increased percentage of desaturation events ≥6‐s in duration (27.8% vs 43.2% at 2‐weeks and 3‐months, P < 0.01). Compared with term‐infants, preterm infants had a greater desaturation incidence (54.8/h vs 27.2/h, P < 0.01), and these desaturations were deeper (52.9% vs 37.6% were ≥6% below baseline, P < 0.01). The incidence of longer desaturations (≥14‐s) in preterm infants was correlated with healthcare utilization over the first 24‐months (r = 0.63, P < 0.01). Conclusions This tool allows the objective comparison of extended oximetry recordings between groups and for individuals; and serves as a basis for the development of reference ranges for populations.
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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 | 0.012 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".