Characterization of Factors Associated With Death in Deceased Patients With Mitochondrial Disorders
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Mitochondrial disorders are multiorgan disorders resulting in significant morbidity and mortality. We aimed to characterize death-associated factors in an international cohort of deceased individuals with mitochondrial disorders. METHODS: This cross-sectional multicenter observational study used data provided by 26 mitochondrial disease centers from 8 countries from January 2022 to March 2023. Individuals with genetically confirmed mitochondrial disorders were included, along with patients with clinically or genetically diagnosed Leigh syndrome. Collected data included demographic and genetic diagnosis variables, clinical phenotype, involvement of organs and systems, conditions leading to death, and supportive care. We defined pediatric and adult groups based on age at death before or after 18 years, respectively. We used Kruskal-Wallis with post hoc Dunn test with Bonferroni correction and Fisher exact test for comparisons, Spearman rank test for correlations, and multiple linear regression for multivariable analysis. RESULTS: < 0.001). On multivariate analysis, individuals with movement disorders and nuclear gene involvement had increased odds of any respiratory support use (OR 2.42 (95% CI 1.17-5.22) and OR 2.39 (95% CI 1.16-5.07), respectively). DISCUSSION: This international collaboration highlights the importance of respiratory care and infection management and provides a reference for prognostication across different mitochondrial disorders.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".