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Record W6940304398 · doi:10.6084/m9.figshare.c.4072847

SENSory re-learning of the UPPer limb after stroke (SENSUPP): study protocol for a pilot randomized controlled trial

2018· other· en· W6940304398 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2018
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicMycorrhizal Fungi and Plant Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsSensory systemRandomized controlled trialStroke (engine)Activities of daily livingUpper limbRehabilitationQuality of life (healthcare)Sensory loss

Abstract

fetched live from OpenAlex

Abstract Background Many stroke survivors suffer from sensory impairments of their affected upper limb (UL). Although such impairments can affect the ability to use the UL in everyday activities, very little attention is paid to sensory impairments in stroke rehabilitation. The purpose of this trial is to investigate if sensory re-learning in combination with task-specific training may prove to be more effective than task-specific training alone to improve sensory function of the hand, dexterity, the ability to use the hand in daily activities, perceived participation, and life satisfaction. Methods/design This study is a single-blinded pilot randomized controlled trial (RCT) with two treatment arms. The participants will be randomly assigned either to sensory re-learning in combination with task-specific training (sensory group) or to task-specific training only (control group). The training will consist of 2.5 h of group training per session, 2 times per week for 5 weeks. The primary outcome measures to assess sensory function are as follows: Semmes-Weinstein monofilament, Shape/Texture Identification (STI™) test, Fugl-Meyer Assessment—upper extremity (FMA-UE; sensory section), and tactile object identification test. The secondary outcome measures to assess motor function are as follows: Box and Block Test (BBT), mini Sollerman Hand Function Test (mSHFT), Modified Motor Assessment Scale (M-MAS), and Grippit. To assess the ability to use the hand in daily activities, perceived participation, and life satisfaction, the Motor Activity Log (MAL), Canadian Occupational Performance Measure (COPM), Stroke Impact Scale (SIS) participation domain, and Life Satisfaction checklist will be used. Assessments will be performed pre- and post-training and at 3-month follow-up by independent assessors, who are blinded to the participants’ group allocation. At the 3-month follow-up, the participants in the sensory group will also be interviewed about their general experience of the training and how effective they perceived the training. Discussion The results from this study can add new knowledge about the effectiveness of sensory re-learning in combination with task-specific training on UL functioning after stroke. If the new training approach proves efficient, the results can provide information on how to design a larger RCT in the future in persons with sensory impairments of the UL after stroke. Trial registration ClinicalTrials.gov, NCT03336749 . Registered on 8 November 2017.

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)0.024
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.068
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.021
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0140.005
Bibliometrics0.0020.003
Science and technology studies0.0030.004
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0680.010

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 head0.037
GPT teacher head0.283
Teacher spread0.246 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations0
Published2018
Admission routes1
Has abstractyes

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