Pulmonary Hemorrhage in Pediatric Hematopoietic Stem Cell Transplant Recipients: A Single-Center Retrospective Study
Bibliographic record
Abstract
OBJECTIVES: Pulmonary hemorrhage (PH) is a serious complication posthematopoietic stem cell transplant (HSCT). In view of limited available pediatric data, we performed a retrospective study to describe epidemiology, management, and outcomes of PH post-HSCT in children in our national center. DESIGN: Retrospective study. SETTING: Academic children's hospital (2000-2015). SUBJECTS: Children (< 18 yr) with PH and requiring PICU care post-HSCT. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The historical prevalence of PH in our center was 2.7% (31/1,148). Twenty patients had a concomitant infection, 15 had bacterial infection, 8 had viral infection, and 3 patients had a fungal infection. With a median follow-up time of 60 months, 7 of 31 patients were alive. Early PH (< 40 d post-HSCT) was associated with improved survival (6/15 vs 1/16, p = 0.035). Patients who received high-dose pulsed corticosteroid had improved survival when compared with those who did not (7/22 vs 0/9, p = 0.0012); this also applied to the subgroup of patients with a concomitant infection (5/15 vs 0, p = 0.001). None of the patients who survived had measurable respiratory sequelae. CONCLUSIONS: PH is a rare but serious complication after HSCT. Corticosteroids were associated with improved survival even in patients with a concomitant infection.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".