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Record W4293046435 · doi:10.1016/j.ymgme.2022.08.005

Epidemiology, methods of diagnosis, and clinical management of patients with arginase 1 deficiency (ARG1-D): A systematic review

2022· review· en· W4293046435 on OpenAlexaboutno aff
Aseel Bin Sawad, John Jackimiec, Mark Bechter, Allison Trucillo, Kristina Lindsley, Anil Bhagat, Jennifer Uyei, George A. Díaz

Bibliographic record

VenueMolecular Genetics and Metabolism · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEpidemiologySpasticityPediatricsDiseasePopulationSystematic reviewMEDLINEIntensive care medicinePhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Arginase 1 Deficiency (ARG1-D) is a rare, progressive, metabolic disorder that is characterized by devastating manifestations driven by elevated plasma arginine levels. It typically presents in early childhood with spasticity (predominately affecting the lower limbs), mobility impairment, seizures, developmental delay, and intellectual disability. This systematic review aims to identify and describe the published evidence outlining the epidemiology, diagnosis methods, measures of disease progression, clinical management, and outcomes for ARG1-D patients. METHODS: A comprehensive literature search across multiple databases such as MEDLINE, Embase, and a review of clinical studies in ClinicalTrials.gov (with results reported) was carried out per PRISMA guidelines on 20 April 2020 with no date restriction. Pre-defined eligibility criteria were used to identify studies with data specific to patients with ARG1-D. Two independent reviewers screened records and extracted data from included studies. Quality was assessed using the modified Newcastle-Ottawa Scale for non-comparative studies. RESULTS: Overall, 55 records reporting 40 completed studies and 3 ongoing studies were included. Ten studies reported the prevalence of ARG1-D in the general population, with a median of 1 in 1,000,000. Frequently reported diagnostic methods included genetic testing, plasma arginine levels, and red blood cell arginase activity. However, routine newborn screening is not universally available, and lack of disease awareness may prevent early diagnosis or lead to misdiagnosis, as the disease has overlapping symptomology with other diseases, such as cerebral palsy. Common manifestations reported at time of diagnosis and assessed for disease progression included spasticity (predominately affecting the lower limbs), mobility impairment, developmental delay, intellectual disability, and seizures. Severe dietary protein restriction, essential amino acid supplementation, and nitrogen scavenger administration were the most commonly reported treatments among patients with ARG1-D. Only a few studies reported meaningful clinical outcomes of these interventions on intellectual disability, motor function and adaptive behavior assessment, hospitalization, or death. The overall quality of included studies was assessed as good according to the Newcastle-Ottawa Scale. CONCLUSIONS: Although ARG1-D is a rare disease, published evidence demonstrates a high burden of disease for patients. The current standard of care is ineffective at preventing disease progression. There remains a clear need for new treatment options as well as improved access to diagnostics and disease awareness to detect and initiate treatment before the onset of clinical manifestations to potentially enable more normal development, improve symptomatology, or prevent disease progression.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.042
GPT teacher head0.392
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations26
Published2022
Admission routes1
Has abstractyes

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