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Record W3197221403 · doi:10.1097/phm.0000000000001869

Systematic Review of Motor Function Scales and Patient-Reported Outcomes in Spinal Muscular Atrophy

2021· review· en· W3197221403 on OpenAlexaff
Jennifer W. Wu, Laura Pepler, Bridget Maturi, Alexandria C. F. Afonso, Janice Sarmiento, Renee Haldenby

Bibliographic record

VenueAmerican Journal of Physical Medicine & Rehabilitation · 2021
Typereview
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsRoche (Canada)
Fundersnot available
KeywordsMedicineSpinal muscular atrophyPhysical medicine and rehabilitationMotor functionDiseasePhysical therapyPopulationMEDLINEPathology

Abstract

fetched live from OpenAlex

ABSTRACT: Spinal muscular atrophy is a heterogeneous disease that results in loss of motor function. In an evolving treatment landscape, establishing the suitability and limitations of existing motor function scales and patient-reported outcomes used to monitor patients with this disease is important. A systematic review was conducted to examine utility of motor function scales and patient-reported outcomes in evaluating patients with spinal muscular atrophy. Published literature was reviewed up to June 2021 with no start date restriction. Of the reports screened, 122 were deemed appropriate for inclusion and are discussed in this review (including 24 validation studies for motor function scales or patient-reported outcomes). Fifteen motor function scales and patient-reported outcomes were identified to be commonly used (≥5 studies), of which 11 had available validation assessments. Each instrument has its strengths and limitations. It is imperative that the patient population (e.g., age, mobility), goals of treatment, and outcomes or endpoints of interest be considered when selecting the appropriate motor function scales and patient-reported outcomes for clinical studies.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.548
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.360
Teacher spread0.345 · 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.

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

Citations29
Published2021
Admission routes1
Has abstractyes

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