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Record W2963953020 · doi:10.1016/j.arthro.2019.02.019

Patient‐Reported Outcomes After Use of a Bioabsorbable Collagen Implant to Treat Partial and Full‐Thickness Rotator Cuff Tears

2019· article· en· W2963953020 on OpenAlexaboutno aff
Louis F. McIntyre, Shariff K. Bishai, Paul B. Brown, Brandon D. Bushnell, Scott W. Trenhaile

Bibliographic record

VenueArthroscopy The Journal of Arthroscopic and Related Surgery · 2019
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRotator cuffTearsConcomitantImplantDemographicsElbowSurgeryVisual analogue scaleCuffMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

PURPOSE: To collect outcomes data on patients treated with a bioinductive collagen implant designed to induce rotator cuff healing in partial- and full-thickness cuff tears and to assess the safety and efficacy of the device. METHODS: Fifteen surgeons in 15 centers in the United States enrolled patients between April 2016 and August 2017 and collected standardized outcomes data. Patients 21 years of age and older, able to read and speak English, and with partial- or full-thickness tears of the rotator cuff documented by magnetic resonance imaging were included in the study. Patients were assessed preoperatively with visual analogue scale (VAS), single-assessment numeric evaluation (SANE), Veterans RAND 12-Item (VR-12), American Shoulder and Elbow Surgeons (ASES), and Western Ontario Rotator Cuff (WORC) outcomes measures. Postoperative assessment was made at 2, 6, and 12 weeks, 6 months, and 1 year. Patients underwent a standardized operative procedure with the implant. Patient demographics, comorbidities, tear types, and concomitant operative procedures were recorded. RESULTS: Patients in both groups experienced statistically significant improvement in VAS, SANE, VR-12 PCS, ASES, and WORC scores (mean values 1.1, P < .001; 86.0, P < .001; 49.7, P < .001; 85.6, P < .001; and 84.4, P < .001 for partial tears and 1.2, P < .001; 80.7, P < .001; 45.7, P < .001; 83.8, P < .0001; and 80.1, P < .001 for full-thickness tears, respectively). For the partial tear group, average times for return to driving, work, and nonoverhead athletic activity were 14.6, 37.3, and 65.6 days, and for the full-thickness group, 24.5, 50.7, and 119.2 days, respectively. In the partial-thickness group, 84% and 83% of patients reported improvement in their VAS pain and ASES scores, respectively, that met or exceeded each measure's minimal clinically important difference. In the full-thickness group, 72% and 77% of the patients met or exceeded the minimal clinically important differences for VAS pain and ASES, respectively. CONCLUSION: Outcomes after repair of partial- and full-thickness rotator cuff tears using a bioinductive implant show safety and efficacy at 1-year follow-up. LEVEL OF EVIDENCE: Retrospective case series, level IV evidence.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.086
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.017
GPT teacher head0.271
Teacher spread0.255 · 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

Citations78
Published2019
Admission routes1
Has abstractyes

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