Pre‐transplant lung function is predictive of survival following pediatric bone marrow transplantation
Bibliographic record
Abstract
BACKGROUND: Pulmonary toxicity is well described in recipients of bone marrow transplants (BMT), and accounts for a sizeable proportion of post-transplant mortality. The majority of the data on post-transplant pulmonary function is from adults, although several small pediatric case series have been described. In adults, pre-transplant lung function has been predictive of post-transplant respiratory failure and mortality. This use of pulmonary function testing, that is, for pre-transplant risk counseling, is novel but has never been applied to pediatric patients. We hypothesized that in children, as in adults, pre-transplant pulmonary function would also be predictive of outcome post-transplantation morbidity. PROCEDURE: Retrospective database analysis of pulmonary function tests of patients undergoing first myeloablative BMT at two large children's hospitals. RESULTS: Two hundred seventy-three subjects had at least one pre-transplant PFT, and 317 subjects had at least one post-transplant PFT available for analysis. While the majority of patients had normal or mildly reduced pre-transplant flows and lung volume, 25% had moderately or severely reduced diffusion. All lung function parameters decreased post-transplant with a slow improvement over ensuing years. The Lung Function Score, a combined measurement of FEV(1) and DLCO, was highly associated with post-transplant survival. Hazard ratios for mortality (compared to the best LFS) ranged from 1.654 to 2.454. CONCLUSIONS: Lung function prior to bone marrow transplant, especially diffusing capacity, is frequently abnormal. Lung function frequently decreases shortly post-transplant and tends to improve over time, but frequently remains abnormal even years after transplant. Post-transplant survival is related to pre-transplant lung function.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".