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Record W3213552210 · doi:10.1016/j.jseint.2021.09.017

Why patients fail to achieve a Patient Acceptable Symptom State (PASS) after total shoulder arthroplasty?

2021· article· en· W3213552210 on OpenAlex
Elliott W. Cole, Samuel G. Moulton, Brian C. Werner, Patrick J. Denard

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJSES International · 2021
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
FundersArthrex
KeywordsMedicineElbowFirst passRange of motionRetrospective cohort studyArthroplastyPhysical therapySurgery

Abstract

fetched live from OpenAlex

Background The purpose of this study was to compare patient-reported outcomes (PROs) and range of motion (ROM) measurements between patients achieving and failing to achieve a Patient Acceptable Symptom State (PASS) after anatomic total shoulder arthroplasty (TSA) to determine which PRO questions and ROM measurements were the primary drivers of poor outcomes. Methods A retrospective review of a multicenter database identified 301 patients who had undergone primary TSA between 2015 and 2018 with ROM and PRO data recorded preoperatively and at a minimum of two years postoperatively. The primary outcome was the difference in active ROM between patients achieving and failing to achieve the PASS threshold for the American Shoulder and Elbow Surgeons (ASES) and Single Assessment Numeric Evaluation (SANE) scores. The secondary outcome was the difference in self-reported pain levels between those achieving and failing to achieve a PASS. Results Based on the ASES PASS threshold, 87% (261/301) of patients achieved a PASS after TSA, whereas 13% did not. Based on the SANE PASS threshold, 69% (208/301) of patients achieved a PASS after TSA, whereas 31% did not. Patients who failed to achieve a PASS after TSA were younger and had lower short form-12 mental health scores than those who did. There was a significant difference in pain between those who achieved and failed to achieve a PASS after TSA (ASES PASS current shoulder pain 16.5% vs. 95%, P < .001, SANE PASS current shoulder pain 13% vs. 58.1%, P < .001). Those failing to reach a PASS had significantly higher pain levels (ASES PASS Visual Analog Scale pain scores [4.2 vs. 0.4, P < .001] and SANE PASS Visual Analog Scale pain scores [2.0 vs. 0.4, P < .001]) and worse function in nearly all domains of the ASES and Western Ontario Osteoarthritis of the Shoulder index after surgery. There was little difference in ROM between those reaching and failing to reach a PASS (no difference in active external rotation with the arm adducted, active internal rotation at the nearest spinal level, or active internal rotation with the shoulder abducted to 90 degrees for ASES and SANE PASS). Conclusion There is variability in the percentage of patients who achieve a PASS after TSA, ranging from 69% to 87% depending on the PRO used to define the threshold. Patients who did not achieve a PASS after TSA were significantly more likely to have pain, whereas there were very few differences in ROM, indicating pain as the primary driver of failing to achieve a PASS. Setting realistic postoperative expectations for pain relief may be important for improving patient-reported results after TSA.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0050.000

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 head0.010
GPT teacher head0.279
Teacher spread0.270 · 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