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Record W4210737894 · doi:10.1186/s13023-022-02172-5

Development of a standard of care for patients with valosin-containing protein associated multisystem proteinopathy

2022· review· en· W4210737894 on OpenAlexaff
Manisha Kak Korb, Allison Peck, Lindsay N. Alfano, Kenneth I. Berger, M. James, Nupur Ghoshal, Elise Healzer, Claire Henchcliffe, Shaida Khan, Pradeep P.A. Mammen, Sujata Patel, Gerald Pfeffer, Stuart H. Ralston, Bhaskar Roy, William W. Seeley, Andrea Swenson, Tahseen Mozaffar, Conrad C. Weihl, Virginia Kimonis, Roberto D. Fanganiello, Grace Lee, Ryan Patrick Mahoney, Jordi Díaz‐Manera, Teresinha Evangelista, Miriam Freimer, Thomas E. Lloyd, Benison Keung, Hani Kushlaf, Margherita Milone, Merrilee Needham, Johanna Palmio, Tanya Stojkovic, Rocío‐Nur Villar‐Quiles, Leo H. Wang, Matthew Wicklund, Frederick R. Singer, Mallory Jones, Bruce L. Miller, S. Ahmad Sajjadi, André Obenaus, Michael D. Geschwind, Ammar Al‐Chalabi, James Wymer, Nita Chen, Katie Kompoliti, Stephani C. Wang, Catherine A. Boissoneault, Betsaida Cruz-Coble, Kendrea L. Garand, Anna J. Rinholen, Lauren Tabor Gray, Jeffrey Rosenfeld, Ming Guo, Nathan Peck

Bibliographic record

VenueOrphanet Journal of Rare Diseases · 2022
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversity of Calgary
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute on AgingMedical Research CouncilNational Institute for Health and Care ResearchNational Institutes of HealthMotor Neurone Disease AssociationUniversity of Texas Southwestern Medical Center
KeywordsMedicineMyopathyDiseaseDementiaIntensive care medicineBioinformaticsPathology

Abstract

fetched live from OpenAlex

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.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.043
metaresearch head score (Gemma)0.074
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.043
Threshold uncertainty score0.227

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.074
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.001
Science and technology studies0.0040.002
Scholarly communication0.0050.004
Open science0.0050.009
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.0040.002

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 head0.024
GPT teacher head0.288
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations36
Published2022
Admission routes1
Has abstractyes

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