Development of a standard of care for patients with valosin-containing protein associated multisystem proteinopathy
Bibliographic record
Abstract
Valosin-containing protein (VCP) associated multisystem proteinopathy (MSP) is a rare inherited disorder that may result in multisystem involvement of varying phenotypes including inclusion body myopathy, Paget's disease of bone (PDB), frontotemporal dementia (FTD), parkinsonism, and amyotrophic lateral sclerosis (ALS), among others. An international multidisciplinary consortium of 40+ experts in neuromuscular disease, dementia, movement disorders, psychology, cardiology, pulmonology, physical therapy, occupational therapy, speech and language pathology, nutrition, genetics, integrative medicine, and endocrinology were convened by the patient advocacy organization, Cure VCP Disease, in December 2020 to develop a standard of care for this heterogeneous and under-diagnosed disease. To achieve this goal, working groups collaborated to generate expert consensus recommendations in 10 key areas: genetic diagnosis, myopathy, FTD, PDB, ALS, Charcot Marie Tooth disease (CMT), parkinsonism, cardiomyopathy, pulmonology, supportive therapies, nutrition and supplements, and mental health. In April 2021, facilitated discussion of each working group's conclusions with consensus building techniques enabled final agreement on the proposed standard of care for VCP patients. Timely referral to a specialty neuromuscular center is recommended to aid in efficient diagnosis of VCP MSP via single-gene testing in the case of a known familial VCP variant, or multi-gene panel sequencing in undifferentiated cases. Additionally, regular and ongoing multidisciplinary team follow up is essential for proactive screening and management of secondary complications. The goal of our consortium is to raise awareness of VCP MSP, expedite the time to accurate diagnosis, define gaps and inequities in patient care, initiate appropriate pharmacotherapies and supportive therapies for optimal management, and elevate the recommended best practices guidelines for multidisciplinary care internationally.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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".