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Record W2755671402 · doi:10.1177/2325967117726044

Use of PROMIS for Patients Undergoing Primary Total Shoulder Arthroplasty

2017· article· en· W2755671402 on OpenAlexaboutno aff
S. Blake Dowdle, Natalie Glass, Chris A. Anthony, Carolyn M. Hettrich

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePatient-Reported Outcomes Measurement Information SystemComputerized adaptive testingElbowCorrelationOsteoarthritisPhysical therapyArthroplastyCohortSurgeryInternal medicinePsychometricsPathology

Abstract

fetched live from OpenAlex

Background: The Patient-Reported Outcomes Measurement Information System (PROMIS) consists of question banks for health domains through computer adaptive testing (CAT). Hypothesis: For patients with glenohumeral arthritis, (1) there would be high correlation between traditional patient-reported outcome (PRO) measures and the PROMIS upper extremity item bank (PROMIS UE) and PROMIS physical function CAT (PROMIS PF CAT), and (2) PROMIS PF CAT would not demonstrate ceiling effects. Study Design: Cohort study (diagnosis); Level of evidence, 3. Methods: Sixty-one patients with glenohumeral osteoarthritis were included. Each patient completed the American Shoulder and Elbow Surgeons (ASES) assessment form, Marx Shoulder Activity Scale, Short Form–36 physical function scale (SF-36 PF), EuroQol 5 Dimensions (EQ-5D) questionnaire, Western Ontario Osteoarthritis Shoulder (WOOS) index, PROMIS PF CAT, and the PROMIS UE. Correlation was defined as high (>0.7), moderate (0.4-0.6), or weak (0.2-0.3). Significant floor and ceiling effects were present if more than 15% of individuals scored the lowest or highest possible total score on any PRO. Results: The PROMIS PF demonstrated excellent correlation with the SF-36 PF ( r = 0.81, P < .0001) and good correlation with the ASES ( r = 0.62, P < .0001), EQ-5D ( r = 0.64, P < .001), and WOOS index ( r = 0.51, P < .01). The PROMIS PF demonstrated low correlation with the Marx scale ( r = 0.29, P = .02). The PROMIS UE demonstrated good correlation with the ASES ( r = 0.55, P < .0001), SF-36 ( r = 0.53, P < .01), EQ-5D ( r = 0.48, P < .01), and WOOS ( r = 0.34, P <.01), and poor correlation with the Marx scale ( r = 0.06, P = .62). There were no ceiling or floor effects observed. The mean number of items administered by the PROMIS PRO was 4. Conclusion: These data suggest that for a patient population with operative shoulder osteoarthritis, PROMIS UE and PROMIS PF CAT may be valid alternative PROs. Additionally, PROMIS PF CAT offers a decreased question burden with no ceiling effects.

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)0.001
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 score0.140
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.036
GPT teacher head0.304
Teacher spread0.268 · 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

Citations91
Published2017
Admission routes1
Has abstractyes

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