The interaction between arterial oxygenation and carbon dioxide and hospital mortality following out of hospital cardiac arrest: a cohort study
Bibliographic record
Abstract
Abstract Background Outcomes following out of hospital cardiac arrest (OHCA) are poor. The optimal arterial oxygen and carbon dioxide (PaCO2) levels for managing patients following OHCA are unknown. We hypothesized that abnormalities in arterial oxygenation (PaO2/FiO2 ratio or PaO2) and PaCO2 would be associated with hospital mortality following OHCA. We hypothesized that PaCO2 would significantly modify the oxygenation–mortality relationship. Methods This was an observational cohort study using data from OHCA survivors admitted to adult critical care units in England, Wales and Northern Ireland from 2011 to 2018. Logistic regression analyses were performed to assess the relationship between hospital mortality and oxygenation and PaCO2. Results The analysis included 23,625 patients. In comparison with patients with a PaO2/FiO2 > 300 mmHg, those with a PaO2/FiO2 ≤ 100 mmHg had higher mortality (adjusted OR, 1.79; 95% CI, 1.48 to 2.15; P < 0.001). In comparison to hyperoxemia (PaO2 > 100 mmHg), patients with hypoxemia (PaO2 < 60 mmHg) had higher mortality (adjusted OR, 1.34; 95% CI, 1.10 to 1.65; P = 0.004). In comparison with normocapnia, hypercapnia was associated with lower mortality. Hypocapnia (PaCO2 ≤ 35 mmHg) was associated with higher mortality (adjusted OR, 1.91; 95% CI, 1.63 to 2.24; P < 0.001). PaCO2 modified the PaO2/FiO2–mortality and PaO2–mortality relationships, though these relationships were complex. Patients who were both hyperoxic and hypercapnic had the lowest mortality. Conclusions Low PaO2/FiO2 ratio, hypoxemia and hypocapnia are associated with higher mortality following OHCA. PaCO2 modifies the relationship between oxygenation and mortality following OHCA; future studies examining this interaction are required.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".