Electrospray Tandem Mass Spectrometry for Analysis of Acylcarnitines in Dried Postmortem Blood Specimens Collected at Autopsy from Infants with Unexplained Cause of Death
Bibliographic record
Abstract
BACKGROUND: Deaths from inherited metabolic disorders may remain undiagnosed after postmortem examination and may be classified as sudden infant death syndrome. Tandem mass spectrometry (MS/MS) may reveal disorders of fatty acid oxidation in deaths of previously unknown cause. METHODS: We obtained filter-paper blood from 7058 infants from United States and Canadian Medical Examiners. Acylcarnitine and amino acid profiles were obtained by MS/MS. Specialized interpretation was used to evaluate profiles for disorders of fatty acid, organic acid, and amino acid metabolism. The analyses of postmortem blood specimens were compared with the analyses of bile specimens, newborn blood specimens, and specimens obtained from older infants at risk for metabolic disorders. RESULTS: Results on 66 specimens suggested diagnoses of metabolic disorders. The most frequently detected disorders were medium-chain and very-long-chain acyl-CoA dehydrogenase deficiencies (23 and 9 cases, respectively), glutaric acidemia type I and II deficiencies (3 and 8 cases, respectively), carnitine palmitoyl transferase type II/translocase deficiencies (6 cases), severe carnitine deficiency (4 cases), isovaleric acidemia/2-methylbutyryl-CoA dehydrogenase deficiencies (4 cases), and long-chain hydroxyacyl-CoA dehydrogenase/trifunctional protein deficiencies (4 cases). CONCLUSIONS: Postmortem metabolic screening can explain deaths in infants and children and provide estimates of the number of infant deaths attributable to inborn errors of metabolism. MS/MS is cost-effective for analysis of postmortem specimens and should be considered for routine use by Medical Examiners and pathologists in unexpected/unknown infant and child death.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".