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Preoperative patient-reported outcome measures predict minimal clinically important difference and patient-acceptable symptomatic state following arthroscopic Bankart repair

2024· article· en· W4402971144 on OpenAlexaboutno aff
Yi Long, Zhen-Ze Zheng, X Y Li, Dedong Cui, Xing-Hao Deng, Jiang Guo, Rui Yang

Bibliographic record

VenueThe Bone & Joint Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
FundersFundamental Research Funds for the Central Universities
KeywordsMinimal clinically important differenceMedicineVisual analogue scaleReceiver operating characteristicElbowArthroscopyPhysical therapySurgeryRandomized controlled trialInternal medicine

Abstract

fetched live from OpenAlex

Aims: The aims of this study were to validate the minimal clinically important difference (MCID) and patient-acceptable symptom state (PASS) thresholds for Western Ontario Shoulder Instability Index (WOSI), Rowe score, American Shoulder and Elbow Surgeons (ASES), and visual analogue scale (VAS) scores following arthroscopic Bankart repair, and to identify preoperative threshold values of these scores that could predict the achievement of MCID and PASS. Methods: A retrospective review was conducted on 131 consecutive patients with anterior shoulder instability who underwent arthroscopic Bankart repair between January 2020 and January 2023. Inclusion criteria required at least one episode of shoulder instability and a minimum follow-up period of 12 months. Preoperative and one-year postoperative scores were assessed. MCID and PASS were estimated using distribution-based and anchor-based methods, respectively. Receiver operating characteristic curve analysis determined preoperative patient-reported outcome measure thresholds predictive of achieving MCID and PASS. Results: MCID thresholds were determined as 169.6, 6.8, 7.2, and 1.1 for WOSI, Rowe, ASES, and VAS, respectively. PASS thresholds were calculated as ≤ 480, ≥ 80, ≥ 87, and ≤ 1 for WOSI, Rowe, ASES, and VAS, respectively. Preoperative thresholds of ≥ 760 (WOSI) and ≤ 50 (Rowe) predicted achieving MCID for WOSI score (p < 0.001). Preoperative thresholds of ≤ 60 (ASES) and ≥ 2 (VAS) predicted achieving MCID for VAS score (p < 0.001). A preoperative threshold of ≥ 40 (Rowe) predicted achieving PASS for Rowe score (p = 0.005). Preoperative thresholds of ≥ 50 (ASES; p = 0.002) and ≤ 2 (VAS; p < 0.001) predicted achieving PASS for the ASES score. Preoperative thresholds of ≥ 43 (ASES; p = 0.046) and ≤ 4 (VAS; p = 0.024) predicted achieving PASS for the VAS. Conclusion: This study defined MCID and PASS values for WOSI, Rowe, ASES, and VAS scores in patients undergoing arthroscopic Bankart repair. Higher preoperative functional scores may reduce the likelihood of achieving MCID but increase the likelihood of achieving the PASS. These findings provide valuable guidance for surgeons to counsel patients realistically regarding their expectations.

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 score0.048
Threshold uncertainty score0.808

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.045
GPT teacher head0.321
Teacher spread0.276 · 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

Citations11
Published2024
Admission routes1
Has abstractyes

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