Why patients fail to achieve a Patient Acceptable Symptom State (PASS) after total shoulder arthroplasty?
Bibliographic record
Abstract
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.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".