Mortality and Pulmonary Embolism in Acute Respiratory Distress Syndrome From COVID-19 vs. Non-COVID-19
Bibliographic record
Abstract
Purpose There may be a difference in respiratory mechanics, inflammatory markers, and pulmonary emboli in COVID-19 associated ARDS vs. ARDS from other etiologies. Our purpose was to determine differences in respiratory mechanics, inflammatory markers, and incidence of pulmonary embolism in patients with and without COVID-19 associated ARDS admitted in the same period and treated with a similar ventilation strategy. Methods A cohort study of COVID-19 associated ARDS and non COVID-19 patients in a Saudi Arabian center between June 1 and 15, 2020. We measured respiratory mechanics (ventilatory ratio (VR), recruitability index (RI), markers of inflammation, and computed tomography pulmonary angiograms. Results Forty-two patients with COVID-19 and 43 non-COVID patients with ARDS comprised the cohort. The incidence of “recruitable” patients using the recruitment/inflation ratio was slightly lower in COVID-19 patients (62 vs. 86%; p = 0.01). Fifteen COVID-19 ARDS patients (35.7%) developed a pulmonary embolism as compared to 4 (9.3%) in other ARDS patients (p = 0.003). In COVID-19 patients, a D-Dimer ≥ 5.0 mcg/ml had a 73% (95% CI 45–92%) sensitivity and 89% (95% CI 71–98%) specificity for predicting pulmonary embolism. Crude 60-day mortality was higher in COVID-19 patients (35 vs. 15%; p = 0.039) but three multivariate analysis showed that independent predictors of 60-day mortality included the ventilatory ratio (OR 3.67, 95% CI 1.61–8.35), PaO2/FIO2 ratio (OR 0.93; 95% CI 0.87–0.99), IL-6 (OR 1.02, 95% CI 1.00–1.03), and D-dimer (OR 7.26, 95% CI 1.11–47.30) but not COVID-19 infection. Conclusion COVID-19 patients were slightly less recruitable and had a higher incidence of pulmonary embolism than those with ARDS from other etiologies. A high D-dimer was predictive of pulmonary embolism in COVID-19 patients. COVID-19 infection was not an independent predictor of 60-day mortality in the presence of ARDS.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".