Clinical relevance of diffusing lung capacity for carbon monoxide (DLCO) in patients with acid sphingomyelinase disease (ASMD): a post-hoc analysis
Bibliographic record
Abstract
Background: ASMD, a rare lysosomal storage disease, has a wide range of clinical manifestations, including interstitial lung disease (ILD), present in >80% of patients. Respiratory disease is a leading cause of death in ASMD. Percent (%) predicted DLCO is a sensitive measure of reduced pulmonary function in ILD, but its clinical relevance in ASMD patients remains unclear. Objective: This post-hoc analysis evaluated the relationship between DLCO and mortality risk in patients with ASMD type B and type A/B using pooled data from a prospective natural history study and retrospective cohort studies of ASMD patients. Methods: Medical records of 68 patients with ASMD type B or type A/B (age of diagnosis: 1–12 years) and with ≥1 DLCO measurement were pooled from the prospective (n=40) and retrospective (n=28) studies; % predicted DLCO were imputed for 10 records (9/68 patients), assuming a linear decrease of 1% annually. A Cox proportional hazards model was fitted using DLCO in two categories (DLCO<60% and ≥60%) as a time-varying predictor (symptomatic respiratory manifestations are prominent at DLCO<60%). Results: A hazard ratio [95% confidence interval] of 0.77 [0.22–2.67] was estimated indicating a lower mortality risk associated with higher % predicted DLCO category (DLCO ≥60 [less severe]) vs lower % predicted DLCO category (DLCO <60 [more severe]), but the result was not statistically significant (p=0.69) likely due to the small sample size. Conclusion: Mortality risk was higher in patients with lower % predicted DLCO, showing how DLCO affects overall survival in ASMD; prospective validation is warranted to confirm these findings.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".