Rapid progression and mortality of lysosomal acid lipase deficiency presenting in infants
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to enhance understanding of lysosomal acid lipase deficiency (LALD) in infancy. METHODS: Investigators reviewed medical records of infants with LALD and summarized data for the overall population and for patients with and without early growth failure (GF). Kaplan-Meier survival analyses were conducted for the overall population and for treated and untreated patients. RESULTS: Records for 35 patients, 26 with early GF, were analyzed. Prominent symptom manifestations included vomiting, diarrhea, and steatorrhea. Median age at death was 3.7 months; estimated probability of survival past age 12 months was 0.114 (95% confidence interval (CI): 0.009-0.220). Among patients with early GF, median age at death was 3.5 months; estimated probability of survival past age 12 months was 0.038 (95% CI: 0.000-0.112). Treated patients (hematopoietic stem cell transplant (HSCT), n = 9; HSCT and liver transplant, n = 1) in the overall population and the early GF subset survived longer than untreated patients, but survival was still poor (median age at death, 8.6 months). CONCLUSIONS: These data confirm and expand earlier insights on the progression and course of LALD presenting in infancy. Despite variations in the nature, onset, and severity of clinical manifestations, and treatment attempts, clinical outcome was poor.Genet Med 18 5, 452-458.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".