Pediatric Hematopoietic Stem Cell Transplant and Intensive Care
Bibliographic record
Abstract
OBJECTIVES: Mortality for pediatric patients who require intensive care posthematopoietic stem cell transplant still remains high. Previously at our institution, survival rates were 44% for patients who required mechanical ventilation posthematopoietic stem cell transplant. We conducted a review of patients to identify whether there has been any improvement in survival over the past 12 years and to identify any risk factors that contribute to mortality. DESIGN: Retrospective chart review. SETTING: PICU and hematopoietic stem cell transplant unit of a single tertiary children's hospital. PATIENTS: Children less than 18 years old undergoing hematopoietic stem cell transplant who required admission to the ICU between January 2000 and December 2011. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: There were 350 separate admissions to the ICU for 206 patients posthematopoietic stem cell transplant. Median Age was 9.3 years (range, 1-17 yr). Median time from hematopoietic stem cell transplant to admission was 35 days (interquartile range, 13-152 d), and 59% of patients were male. Survival to ICU discharge for all admissions was 75%, which equated to 57% of all patients. Of the admissions that required invasive mechanical ventilation, 48% survived to ICU discharge, with a survival to ICU discharge of 36% if there was more than one admission requiring mechanical ventilation. Survival to ICU discharge was 33% if renal replacement therapy was required. Mechanical ventilation, inotrope/vasopressor use, and number of organ dysfunction within an admission were predictors of mortality. Having an underlying malignant condition or an autologous hematopoietic stem cell transplant was associated with a more favorable outcome. CONCLUSIONS: This is the largest single-center series for pediatric patients who require intensive care posthematopoietic stem cell transplant and demonstrates that this group of patients still faces high mortality. There has been an improvement in survival for those patients who require renal replacement therapy and also for patients who require mechanical ventilation more than once; however, the need for mechanical ventilation still remains a significant predictor of mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".