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Record W2339108496 · doi:10.1371/journal.pone.0153739

Functional Ability Improved in Essential Tremor by IncobotulinumtoxinA Injections Using Kinematically Determined Biomechanical Patterns – A New Future

2016· article· en· W2339108496 on OpenAlexafffund
Olivia Samotus, Fariborz Rahimi, Mandar Jog

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsLondon Health Sciences CentreLawson Health Research InstituteWestern University
FundersParkinsonfondenMerz PharmaceuticalsLondon Health Sciences CentreNational Parkinson Foundation
KeywordsPhysical medicine and rehabilitationWristMedicineElbowKinematicsPhysical therapyUpper limbFunctional movementRehabilitationWeaknessRating scaleBiomechanicsEssential tremorElectromyographyPsychologySurgeryAnatomy

Abstract

fetched live from OpenAlex

OBJECTIVE: Effective treatment for functional disability caused by essential tremor is a significant unmet need faced by many clinicians today. Current literature regarding focal therapy by botulinum toxin type A (BoNT-A) injections uses fixed dosing regimens, which cannot be individualized, provides only limited functional benefit and unacceptable muscle weakness commonly occurs. This 38-week open label study, the longest to-date, demonstrates how kinematic technology addressed all these issues by guiding muscle selection. METHOD: Participants (n = 24) were assessed at weeks 0, 6, 16, 22, 32, and 38 and injected with incobotulinumtoxinA at weeks 0, 16, and 32. Clinical assessments including UPDRS tremor items, Fahn-Tolosa-Marin (FTM) tremor rating scale assessing tremor severity, writing and functional ability, quality of life questionnaire (QUEST) and objective kinematic assessments were completed at every visit. Participants performed two postural and two weight-bearing scripted tasks with motion sensors placed over the wrist, elbow and shoulder joints. These sensors captured angular tremor amplitude (RMS units) and acceleration joint motion that was segmented into directional components: flexion-extension (F/E), pronation-supination and radial-ulnar at the wrist, F/E at the elbow, and F/E and adduction-abduction at the shoulder. Injection parameters were determined using kinematics, followed by the clinician's determination of which muscles would contribute to the specific upper limb tremor biomechanics and dosing per participant. RESULTS: Multi-joint biomechanical recordings allowed individualized muscle selection and showed significant improvement in whole-arm function, FTM parts A-C scores, at week 6 which continued throughout the study. By week 38, the total FTM score statistically significantly reduced from 16.2±4.6 at week 0 to 9.5±6.3 (p<0.0005). UPDRS item 21 score rating action tremor was significantly reduced from 2.6±0.5 at week 0 to 1.6±1.1 (p = 0.01) at week 32. Quality of life (QUEST) significantly improved from 40.3±15.8 at week 0 to 31.1±15.3 (p = 0.035) at week 32 and to 27.8±15.3 (p = 0.028) at week 38. Kinematics provided an objective, secondary outcome measure, which showed a significant decrease in tremor amplitude in the wrist and shoulder joints (p<0.05). Eight participants (40%) self-reported mild weakness in injected muscles but had no interference in arm function. CONCLUSION: Kinematic tremor assessments provide the injector unique insight to objectively individualize and personalize injection parameters demonstrating BoNT-A effectively alleviates functional disability caused by essential tremor. Kinematic technology is a promising method for standardizing assessments and for focal upper limb tremor treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT02427646.

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.259
Teacher spread0.219 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations44
Published2016
Admission routes2
Has abstractyes

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