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Clinical measurement tools to assess trunk performance after stroke: a systematic review

2018· review· en· W2813901829 on OpenAlexaboutno aff
Gregorio Sorrentino, Patrizio Sale, Claudio Solaro, Alessia Rabini, Cesare Cerri, Giorgio Ferriero

Bibliographic record

VenueEuropean Journal of Physical and Rehabilitation Medicine · 2018
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsTrunkMedicinePhysical medicine and rehabilitationSittingPhysical therapyStroke (engine)RehabilitationBalance (ability)

Abstract

fetched live from OpenAlex

INTRODUCTION: Stroke may result in decreased trunk muscle strength and limited trunk coordination, frequently determining loss of autonomy due to the trunk impairment. Furthermore, sitting balance has been repeatedly identified as an important predictor of motor and functional recovery after stroke. Given the importance of the trunk, it is therefore mandatory that validated tools be available to assess its performance. A systematic review of the currently available clinical measurement tools to assess trunk performance after stroke has been carried out. EVIDENCE ACQUISITION: We searched the PubMed database from January 2006 to April 2017 to select articles which reported or included a clinical measure of trunk performance used in an adult stroke population. The data collected were integrated with the results of a previous review published in 2006. A total of 302 articles were identified, of which 19 were eligible for inclusion. EVIDENCE SYNTHESIS: Numerous clinical tools have been validated to assess trunk performance after stroke, including the Trunk Control Test, the Trunk Impairment Scale, the Postural Assessment Scale for Stroke, the Ottawa Sitting Scale, the Modified Functional Reach Test, the Function In Sitting Test, the Physical Ability Scale, the Trunk Recovery Scale, the Balance Assessment in Sitting and Standing Positions, and the and Sitting-Rising Test. CONCLUSIONS: Several scales and tests have been demonstrated to be valid for assessing trunk performance in stroke. Some of these have already been refined by Rasch analysis to increase their psychometric characteristics. Further psychometric analysis of these tools in large and different samples is, however, still needed.

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)0.010
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.292
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.112
GPT teacher head0.393
Teacher spread0.282 · 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.

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

Citations49
Published2018
Admission routes1
Has abstractyes

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