MétaCan
Menu
Back to cohort
Record W3015867383 · doi:10.1186/s12891-020-03238-w

A narrative review and content analysis of functional and quality of life measures used to evaluate the outcome after TSA: an ICF linking application

2020· review· en· W3015867383 on OpenAlexafffund
LU Ze, Joy C. MacDermid, Peter Rosenbaum

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2020
Typereview
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsWestern UniversityMcMaster UniversitySt Joseph's Health CareHand and Upper Limb Clinic
FundersCanadian Institutes of Health ResearchMcMaster University
KeywordsSports medicineMedicineOutcome (game theory)NarrativeQuality of life (healthcare)Quality (philosophy)RheumatologyPhysical therapyInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Total shoulder arthroplasty (TSA) is considered as the standard reconstructive surgery for patients suffering from severe shoulder pain and dysfunction caused by arthrosis. Multiple patient-reported outcome measures (PROMs) have been developed and validated that can be used to evaluate TSA outcomes. When selecting an outcome measure both content and psychometric properties must be considered. Most research to date has focused on psychometric properties. Therefore, the current study aims to summarize what PROMs are being used to assess TSA outcomes, to classify the type of measure (International society for quality of life (ISOQOL) using definitions of functioning, disability, and health (FDH), quality of life (QoL) and health-related quality of life (HRQoL)) and to compare the content of these measures by linking them to the International Classification of Functioning, Disability and Health (ICF) framework. METHODS: A literature review was performed in three databases including MEDLINE, EMBASE, and CINAHL to identify PROMs that were used in TSA studies. Meaningful concepts of the identified measures were extracted and linked to the relevant second-level ICF codes using standard linking rules. Outcome measures were classified as being FDH, HRQoL or QoL measures based on the content analysis. RESULT: Thirty-five measures were identified across 400 retrieved studies. The most frequently used PROM was the American Shoulder and Elbow Society score accounting for 21% (246) of the total citations, followed by the single item pain-related scale like visual analog scale (17%) and Simple Shoulder Test (12%). Twelve PROMs with 190 individual items fit inclusion criteria for conceptual analysis. Most codes (65%) fell under activity and participation categories. The top 3 most predominant codes were: sensation of pain (b280; 13%), hand and arm use (d445; 13%), recreational activity (d920; 8%). Ten PROMs included in this study were categorized as FDH measures, one as HRQoL measure, and one as unknown. CONCLUSIONS: Our study demonstrated that there is an inconsistency and lack of clarity in conceptual frameworks of identified PROMs. Despite this, common core constructs are evaluated. Decision-making about individual studies or core sets for outcome measurement for TSA would be advanced by considering our results, patient priorities and measurement properties.

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)0.020
metaresearch head score (Gemma)0.088
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.088
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.005
Bibliometrics0.0510.043
Science and technology studies0.0020.002
Scholarly communication0.0040.005
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.218
GPT teacher head0.441
Teacher spread0.223 · 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.

Study designSystematic review
DomainMethods
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

Citations10
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueBMC Musculoskeletal DisordersSame topicShoulder Injury and TreatmentFrench-language works237,207