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Record W2582320869 · doi:10.1097/pcc.0000000000001075

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*

2017· article· en· W2582320869 on OpenAlexfundno aff
Samiran Ray, Libby Rogers, Christina Pagel, Sainath Raman, Mark Peters, Padmanabhan Ramnarayan

Bibliographic record

VenuePediatric Critical Care Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsnot available
FundersHospital for Sick ChildrenNational Institute for Health and Care ResearchNHS Health Scotland
KeywordsMedicineIntensive careStandardized mortality ratioAnesthesiaIntensive care medicineMortality rateInternal medicine

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.076
GPT teacher head0.377
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations35
Published2017
Admission routes1
Has abstractyes

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