Monitoring for paediatric pulmonary graft <i>versus</i> host disease with multiple breath washout
Bibliographic record
Abstract
Background Current diagnostic tests for pulmonary chronic graft versus host disease (p-cGvHD) are either invasive or challenging for children to perform. Multiple breath washout (MBW) has been proposed as a feasible and sensitive tool for the diagnosis of p-cGvHD. In this study, we aimed to determine the feasibility and sensitivity of MBW to monitor for p-cGvHD in children after haematopoietic stem cell transplantation (HSCT). Methods This was a prospective, single-centre cohort study, recruiting children >3 years of age undergoing HSCT between February 2019 and January 2024. MBW and spirometry were performed at regular follow-up visits out to 2 years post-HSCT. Results 46 children were included in the longitudinal analysis, five (10.9%) of whom developed p-cGvHD. MBW success rate was 93.9% (229 out of 244 visits), compared to 78.3% for spirometry (191 out of 244 visits). In children who developed p-cGvHD, compared to those who did not, peak lung clearance index (LCI) was higher (12.6 versus 6.8, p=0.0003), nadir forced expiratory volume in 1 s z-score (zFEV 1 ) was lower (−3.5 versus −0.7, p=0.005) and nadir zFEV 1 :forced vital capacity (FVC) was lower (−2.4 versus −0.3, p=0.01). The sensitivity and specificity for p-cGvHD were 100%/97.6% for peak LCI, 100%/71.1% for nadir FEV 1 and 75.0%/94.7% for nadir FEV 1 :FVC. In those who do not develop p-cGvHD, longitudinal LCI remained normal or mildly abnormal (LCI <8.0) in 98.1% of visits, compared to FEV 1 (z > −1.9) in 90.2% and zFEV 1 :FVC in 95.5% of visits. Conclusions MBW is longitudinally feasible in a post-HSCT population as young as 3 years of age. LCI is highly sensitive and specific for p-cGvHD and may help to distinguish different phenotypes of post-HSCT lung disease.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".