Pao 2/Fio 2 Ratio Derived From the Spo 2/Fio 2 Ratio to Improve Mortality Prediction Using the Pediatric Index of Mortality-3 Score in Transported Intensive Care Admissions*
Bibliographic record
Abstract
OBJECTIVES: To derive a relationship between the SpO2/FIO2 ratio and PaO2/FIO2 ratio across the entire range of SpO2 values (0-100%) and to evaluate whether mortality prediction using the Pediatric Index of Mortality-3 can be improved by the use of PaO2/FIO2 values derived from SpO2/FIO2. DESIGN: Retrospective analysis of prospectively collected data. SETTING: A regional PICU transport service. PATIENTS: Children transported to a PICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The relationship between SpO2/FIO2 and PaO2/FIO2 across the entire range of SpO2 values was first studied using several mathematical models in a derivation cohort (n = 1,235) and then validated in a separate cohort (n = 306). The best SpO2/FIO2-PaO2/FIO2 relationship was chosen according to the ability to detect respiratory failure (PaO2/FIO2 ≤ 200). The discrimination of the original Pediatric Index of Mortality-3 score and a derived Pediatric Index of Mortality-3 score (where SpO2/FIO2-derived PaO2/FIO2 values were used in place of missing PaO2/FIO2 values) were compared in a different cohort (n = 1,205). The best SpO2/FIO2-PaO2/FIO2 relationship in 1,703 SpO2/FIO2-to-PaO2/FIO2 data pairs was a linear regression equation of ln[PF] regressed on ln[SF]. This equation identified children with a PaO2/FIO2 less than or equal to 200 with a specificity of 73% and sensitivity of 61% in children with SpO2 less than 97% (92% and 33%, respectively, when SpO2 ≥ 97%) in the validation cohort. PaO2/FIO2 derived from SpO2/FIO2 (derived PaO2/FIO2) was better at predicting PICU mortality (area under receiver operating characteristic curve, 0.64; 95% CI, 0.55-0.73) compared with the original PaO2/FIO2 (area under receiver operating characteristic curve, 0.54; 95% CI, 0.49-0.59; p = 0.02). However, there was no difference in the original and derived Pediatric Index of Mortality-3 scores and their discriminatory ability for mortality. CONCLUSIONS: SpO2-based metrics perform no worse than arterial blood gas-based metrics in mortality prediction models. Future Pediatric Index of Mortality score versions may be improved by the inclusion of risk factors based on oxygen saturation values, especially in settings where PaO2 values are missing in a significant proportion of cases.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".