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Record W4309342471 · doi:10.1016/j.jhsg.2022.10.005

Clinical Utility of Patient-Reported Outcome Measures Used for Tendon and Nerve Transfers for Tetraplegia in New Zealand

2022· article· en· W4309342471 on OpenAlexaboutno aff
K. Anne Sinnott Jerram, Jennifer A. Dunn, Richard Peter Smaill, James Middleton

Bibliographic record

VenueJournal of Hand Surgery Global Online · 2022
Typearticle
Languageen
FieldMedicine
TopicNerve Injury and Rehabilitation
Canadian institutionsnot available
FundersUniversity of Sydney
KeywordsTetraplegiaMedicinePhysical medicine and rehabilitationOutcome (game theory)TendonTendon transferPhysical therapySurgerySpinal cordSpinal cord injuryEconomics

Abstract

fetched live from OpenAlex

PurposeThis study determines the clinical utility of patient-reported outcome measures used to measure outcomes of upper extremity (UE) reconstructive procedures in individuals with tetraplegia. The patient-reported outcome measures are the Canadian Occupational Performance Measure, the Capabilities of Upper Extremity Questionnaire (CUE-Q), and the Personal Wellbeing Index.MethodsRetrospective data of 43 individuals with spinal cord injury (SCI) levels C4-C7 tetraplegia, and American Spinal Injury Association Impairment Scale grades A-D who had upper limb reconstructive surgery were reviewed. Participants were grouped according to their SCI level and resultant surgical procedures into higher SCI severity and lower SCI severity groups.ResultsThe mean age of participants was 26.3 years (SD 13.4; range 13–64 years). The higher-severity SCI group required elbow and hand reconstruction surgery, whereas the lower-severity group only required hand reconstruction surgery. Important differences in Canadian Occupational Performance Measure priorities were identified between the higher and lower SCI severity groups. Question redundancy was evident with the CUE-Q. The self-report Personal Wellbeing Index captures the possible impacts of improved UE function on an individual’s perceived sense of personal wellbeing.ConclusionsIn this patient-reported outcome measure analysis, we found that the level of impairment influences patient priorities. Functional measures ought to consider UE impairment and personal wellbeing as a construct in this population, given the demands of surgery.Type of Study/Level of EvidencePrognostic II This study determines the clinical utility of patient-reported outcome measures used to measure outcomes of upper extremity (UE) reconstructive procedures in individuals with tetraplegia. The patient-reported outcome measures are the Canadian Occupational Performance Measure, the Capabilities of Upper Extremity Questionnaire (CUE-Q), and the Personal Wellbeing Index. Retrospective data of 43 individuals with spinal cord injury (SCI) levels C4-C7 tetraplegia, and American Spinal Injury Association Impairment Scale grades A-D who had upper limb reconstructive surgery were reviewed. Participants were grouped according to their SCI level and resultant surgical procedures into higher SCI severity and lower SCI severity groups. The mean age of participants was 26.3 years (SD 13.4; range 13–64 years). The higher-severity SCI group required elbow and hand reconstruction surgery, whereas the lower-severity group only required hand reconstruction surgery. Important differences in Canadian Occupational Performance Measure priorities were identified between the higher and lower SCI severity groups. Question redundancy was evident with the CUE-Q. The self-report Personal Wellbeing Index captures the possible impacts of improved UE function on an individual’s perceived sense of personal wellbeing. In this patient-reported outcome measure analysis, we found that the level of impairment influences patient priorities. Functional measures ought to consider UE impairment and personal wellbeing as a construct in this population, given the demands of surgery.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.084
GPT teacher head0.378
Teacher spread0.294 · 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 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".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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