Intensive care outcomes in bone marrow transplant recipients: a population-based cohort analysis
Bibliographic record
Abstract
INTRODUCTION: Intensive care unit (ICU) admission for bone marrow transplant recipients immediately following transplantation is an ominous event, yet the survival of these patients with subsequent ICU admissions is unknown. Our objective was to determine the long-term outcome of bone marrow transplant recipients admitted to an ICU during subsequent hospitalizations. METHODS: We conducted a population-based cohort analysis of all adult bone marrow transplant recipients who received subsequent ICU care in Ontario, Canada from 1 January 1992 to 31 March 2002. The primary endpoint was mortality at 1 year. RESULTS: A total of 2,653 patients received bone marrow transplantation; 504 of which received ICU care during a subsequent hospitalization. Patients receiving any major procedure during their ICU stay had higher 1-year mortality than those patients who received no ICU procedure (87% versus 44%, P < 0.0001). Death rates at 1 year were highest for those receiving mechanical ventilation (87%), pulmonary artery catheterization (91%), or hemodialysis (94%). In combination, the strongest independent predictors of death at 1 year were mechanical ventilation (odds ratio, 7.4; 95% confidence interval, 4.8 to 11.4) and hemodialysis (odds ratio, 8.7; 95% confidence interval, 2.1 to 36.7), yet no combination of procedures uniformly predicted 100% mortality. CONCLUSION: The prognosis of bone marrow transplant recipients receiving ICU care during subsequent hospitalizations is very poor but should not be considered futile.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".