A narrative review and content analysis of functional and quality of life measures used to evaluate the outcome after TSA: an ICF linking application
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.088 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.051 | 0.043 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".