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Record W4415674867 · doi:10.1111/aas.70137

Optimal Cutoffs for the Ratio of Arterial Oxygen Partial Pressure to Inspired Oxygen Fraction in Categorizing Respiratory Impairment Severity in Organ Failure Scores

2025· article· en· W4415674867 on OpenAlexaff
Anssi Pölkki, Matti Reinikainen, Bram Rochwerg, Christian Jung, Cornelius Sendagire, Dipayan Chaudhuri, Greg S. Martin, Tuomas Selander, Rui P. Moreno, Mervyn Singer, John G. Laffey, Pirkka T. Pekkarinen

Bibliographic record

VenueActa Anaesthesiologica Scandinavica · 2025
Typearticle
Languageen
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversityImpact
Fundersnot available
KeywordsFraction of inspired oxygenPartial pressureIntensive careRespiratory failureOxygenOxygen deliveryOxygen pressureRespiratory system

Abstract

fetched live from OpenAlex

BACKGROUND: , hereafter P/F ratio) is a key component of the Sequential Organ Failure Assessment (SOFA) score. It reflects the severity of hypoxaemic respiratory failure. The ongoing revision of the SOFA score requires data-driven cutoffs for P/F ratio as well as rational criteria for respiratory support. In this study, we aimed to determine the optimal P/F ratio cutoffs for determining respiratory failure categories in the revised SOFA score and examined whether advanced respiratory support should be a prerequisite for the most severe categories. METHODS: We used the database of the intensive care unit of Kuopio University Hospital, Finland, for cutoff derivation and the eICU database, a multicenter U.S. intensive care registry, for external validation. We identified cutoffs most discriminative for hospital mortality using the log-rank statistic test with the Contal and O'Quigley method. In external validation, these cutoffs were compared with those in the current respiratory SOFA score. RESULTS: Optimal cutoffs were identified as follows: P/F ratio > 40 kPa (normal), 30-40 kPa (mild impairment), 20-30 kPa (moderate impairment), 10-20 kPa (severe impairment), and ≤ 10 kPa (critical impairment). These cutoffs resulted in clear separation of the severity categories (chi-square for log-rank statistic 356.9). They outperformed the current respiratory SOFA score cutoffs in the validation cohort (AUROC 0.615, 95% CI 0.607-0.622 vs. AUROC 0.610, 95% CI 0.603-0.618, p < 0.001). Advanced respiratory support was associated with higher mortality, but its inclusion as a prerequisite improved discrimination only in the moderately impaired respiratory function category, not in the severely or critically impaired categories. CONCLUSION: P/F ratio cutoffs using 10 kPa (75 mmHg) intervals were identified to be optimal for distinguishing stages of respiratory failure severity. The impact of respiratory support on P/F ratio-mortality associations suggests the need to calibrate any P/F ratio-based score by support level, but optimal calibration methods require further study. EDITORIAL COMMENT: In this study, the cut-off values for the partial pressure of arterial oxygen to the fraction of inspired oxygen (P/F ratio) were investigated in a large Finnish intensive care database and validated externally with the US intensive care registry. The aim was to support a revision of the cut-off values for the P/F ratio in the Sequential Organ Failure Assessment (SOFA) score. The results showed that incremental changes in the P/F ratio of 10 kPa are better than 13 kPa and emphasize the need for critical assessment of the current SOFA score.

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)0.015
metaresearch head score (Gemma)0.036
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 score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.042
GPT teacher head0.321
Teacher spread0.279 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

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