Acute Respiratory Failure Outcomes in Patients with Hematologic Malignancies and Hematopoietic Cell Transplant: A Secondary Analysis of the EFRAIM Study
Bibliographic record
Abstract
Patients with allogeneic hematopoietic cell transplantation (HCT) who develop acute respiratory failure (ARF) are perceived to have worse outcomes than autologous HCT recipients and non-transplant patients with hematologic malignancy (HM). Within a large international prospective cohort, we evaluated clinical outcomes in these 3 populations. We conducted a secondary analysis of the EFRAIM study, a multicenter observational study of immunocompromised adults with ARF admitted to 62 intensive care units (ICUs) in 16 countries. We described characteristics and compared outcomes of patients with HM who did not undergo transplantation and patients who underwent autologous or allogeneic HCT using multivariable logistic regression and propensity score-matched analyses. A total of 801 patients were included: 570 who did not undergo transplantation, 86 autologous HCT recipients and 145 allogeneic HCT recipients. Acute myelogenous leukemia (171 of 570; 30%) was the most common HM and most common indication for allogeneic HCT (76 of 145; 52%). Compared with the patients who did not undergo HCT and autologous HCT recipients, allogeneic HCT recipients were younger, had fewer comorbid conditions, and were more likely to undergo diagnostic bronchoscopy in the ICU. Unadjusted ICU and hospital mortality were 35% and 45%, respectively, across the entire cohort. In multivariable regression analysis, autologous HCT (odds ratio [OR], 1.07; 95% confidence interval [CI], .57 to 2.03; P = .82) and allogeneic HCT (OR, .99; 95% CI, .60 to 1.66; P = .98) were not associated with higher hospital mortality compared with the no-HCT cohort, adjusting for demographic, functional, clinical, malignancy, and ARF characteristics. The results were similar when analyzed using propensity score-matching techniques. Our findings indicate that autologous and allogeneic HCT recipients who develop ARF and require ICU admission have similar hospital mortality as patients with HM not treated with HCT.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".