Establishing a Core Outcome Set for Creatine Transporter Deficiency and Guanidinoacetate Methyltransferase Deficiency
Bibliographic record
Abstract
Creatine transporter (CTD) and guanidinoacetate methyltransferase (GAMT) deficiencies are rare inborn errors of creatine metabolism, resulting in cerebral creatine deficiency. Patients commonly exhibit intellectual and developmental disabilities, often accompanied by behavior problems, delayed speech, seizures, and motor impairments. There is currently no efficacious treatment for CTD, while the current management for GAMT requires lifelong treatment with a protein restricted diet and intake of high amounts of oral supplements. Efforts to develop effective, sustainable treatments for these disorders are limited by the lack of clinical and patient-derived meaningful outcomes. A core outcome set (COS) can facilitate consensus about outcomes for inclusion in studies. Unfortunately, patient and caregiver perspectives have historically been overlooked in the COS development process, thus limiting their input into the outcome selection. We partnered with caregivers and health professionals to establish the first COS for CTD and GAMT. The COS developed includes seven outcomes ("Adaptive Functioning", "Cognitive Functioning", "Emotional Dysregulation", "MRS Brain Creatine", "Seizure/Convulsions", "Expressive Communication", and "Fine Motor Functions") for both CTD and GAMT, and an additional outcome for GAMT ("Serum/Plasma Guanidinoacetate") that are important to stakeholders and consequently should be considered for measurement in every clinical trial. Caregivers were valued partners throughout the COS development process, which increased community engagement and facilitated caregiver empowerment. We expect this COS will ensure a patient-centered approach for accelerating drug development for CTD and GAMT, make clinical trial results comparable, minimize bias in clinical trial outcome selection, and promote efficient use of resources.
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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 | 0.117 | 0.155 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".