Abnormal Neurological Features Predict Poor Survival and Should Preclude Liver Transplantation in Patients with Deoxyguanosine Kinase Deficiency
Bibliographic record
Abstract
Deoxyguanosine kinase (DGUOK) deficiency is the commonest type of mitochondrial DNA depletion associated with a hepatocerebral phenotype. In this article, we evaluate predictors of survival and therapeutic options in patients with DGUOK deficiency. A systematic search of MEDLINE, LILAC, and SCIELO was carried out to identify peer-reviewed clinical trials, randomized controlled trials, meta-analyses, and other studies with clinical pertinence. DGUOK deficiency was searched with the terms dGK, DGUOK, mitochondrial DNA depletion, mtDNA, and hepatocerebral. Bibliographies of identified articles were reviewed for additional references. Thirteen identified studies met the inclusion criteria and were used in this study. The analysis revealed that DGUOK deficiency is associated with a variable clinical phenotype. Long-term survival is best predicted by the absence of profound hypotonia, significant psychomotor retardation, or nystagmus. In the presence of these features, there is increased mortality, and liver transplantation does not confer increased survival. In summary, liver transplantation appears to be futile in the presence of specific neurological signs or symptoms in patients affected with DGUOK deficiency. Conversely, in the absence of these neurological features, liver transplantation may be considered a potential treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".