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Record W4252767298 · doi:10.1177/2325967113s00100

A Prospective Follow-up of Patients Treated Surgically or Non-Surgically for Full-thickness Rotator Cuff Tears

2013· article· en· W4252767298 on OpenAlexaboutno aff
Joel Gagnier, Hanna N. Oltean, Asheesh Bedi, James E. Carpenter, Bruce S. Miller

Bibliographic record

VenueOrthopaedic Journal of Sports Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRotator cuffTearsElbowVisual analogue scaleSurgeryPhysical therapyProspective cohort studyLogistic regressionPatient satisfactionRotator cuff injuryInternal medicine

Abstract

fetched live from OpenAlex

Objectives: The objectives of this project are: (1) to compare the efficacy of surgical versus non-surgical management of full-thickness rotator cuff tears, and (2) to detect variables that predict success within each treatment group. Methods: Patients who presented to our care for management of symptomatic full-thickness rotator cuff tears were enrolled in our Shoulder Registry and clinical data were collected prospectively. In addition to baseline demographic information, the following outcome measures were collected at baseline, 6 months, 1 year and annually up to 3 years: Western Ontario Rotator Cuff (WORC) Index, American Shoulder and Elbow Surgeons (ASES) score, Modified Marx Shoulder Activity Level Scale, VR-12, 100-point Single Assessment Numeric Evaluation (SANE) rating, 100-point visual analog scale (VAS) for pain, and a patient satisfaction scale. All patients were allocated treatment as recommended by the attending surgeon. We described all patient demographic characteristics, and performed linear and logistic regression for variables associated with treatment allocation and with treatment effects. We also used Student’ t-tests and Wilcoxon rank-sum tests where appropriate, to explore differences in treatment effects between the groups for all outcome measures at all time points. Results: A total of 292 patients were included with 155 allocated to surgery and 137 to non-surgical treatment. Those allocated to surgery were younger (58.6 years vs 65.2 years; P<.0001), less likely to have diabetes (12% vs 21%; P=0.05), more likely to have a known traumatic injury (71% vs 55%; P=0.002), and tended to be worse off on all outcome measures at baseline then the non-surgical group. Both the surgical group and non-surgical group improved on all outcome measures across the follow up period with several variables predicting changes at each time point. Table 1 contains the list of specific variables that predicted improved outcomes separately for both treatment groups. Also, at one year the surgical group improvement was significantly greater than the non-surgical group on all outcome measures. At both two and three years the surgical group showed a significantly greater degree of improvement than the non-surgical group on both the WORC index and the ASES score. Conclusion: We found that patients with rotator cuff tears who undergo surgical or nonsurgical treatment tend to improve, with patients allocated to surgery improving to a greater degree across three years of follow-up. In addition, there appear to be important predictors of improved outcomes that may help us to tailor our treatments to individuals with specific characteristics.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.014
GPT teacher head0.277
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2013
Admission routes1
Has abstractyes

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