Acute respiratory distress syndrome in patients with cancer: the YELENNA prospective multinational observational cohort study
Bibliographic record
Abstract
PURPOSE: Acute respiratory failure is the leading reason for intensive care unit (ICU) admission among critically ill patients with cancer. We aimed to describe the clinical characteristics, risk factors, and outcomes of patients with cancer and acute respiratory distress syndrome (ARDS) and to evaluate associations of venovenous extracorporeal membrane oxygenation (ECMO) with outcomes in the subgroup with severe ARDS. METHODS: We conducted a multinational, prospective, observational cohort study of patients with cancer and ARDS in 13 countries in Europe and North America. The primary endpoint was 90-day mortality. RESULTS: Among 715 included patients, 73.4% had hematologic malignancies and 26.6% solid tumors; 31.2% had undergone hematopoietic stem-cell transplantation (168 allogeneic). ICU, hospital, and 90-day mortality rates were 55.3%, 70.9%, and 73.2%, respectively. By multivariate analysis, independent predictors of higher 90-day mortality were older age, peripheral vascular disease, severe ARDS at inclusion, acute kidney injury, and ICU admission as a time-limited trial (vs. full code). Conversely, lymphoma was associated with lower 90-day mortality. Among the 322 patients (45.7%) with severe ARDS at inclusion, 90-day mortality was 82.2%; with no difference between patients who received ECMO (n = 58, 18%) and those who did not (82.6% vs. 80.7%, P = 0.89). This finding remained unchanged in a double-adjusted overlap- and propensity-weighted Cox mixed-effects model (adjusted hazard ratio, 1.12; 95% confidence interval 0.65-1.94; P = 0.69). CONCLUSION: Patients with cancer and ARDS, particularly severe forms, experience high 90-day mortality, irrespective of ECMO use. These findings suggest a need for nuanced ICU goals-of-care discussions and raise concerns about the generalizability of ECMO guidelines to this population.
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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 | 0.000 |
| 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) | 0.000 | 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".