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Record W2592566075 · doi:10.1177/0363546517691950

Risk Factors for Revision Surgery After Superior Labral Anterior-Posterior Repair: A National Perspective

2017· article· en· W2592566075 on OpenAlexaff
Samuel A. Taylor, Ryan M. Degen, Alexander E. White, Moira M. McCarthy, Lawrence V. Gulotta, Stephen J. O’Brien, Brian C. Werner

Bibliographic record

VenueThe American Journal of Sports Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineCurrent Procedural TerminologySurgeryConcomitantBicepsLogistic regressionOdds ratioInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Data regarding risk factors for revision surgery after superior labral anterior-posterior (SLAP) repair are limited to institutional series. PURPOSE: To define risk factors for revision surgery after SLAP repair among patients in a large national database. STUDY DESIGN: Case-control study; Level of evidence, 3. METHODS: A national insurance database was queried for patients undergoing arthroscopic SLAP repair (Current Procedural Terminology [CPT] code 29807) for the diagnosis of a SLAP tear. Patients without a CPT modifier for laterality were excluded. Revision surgery was defined as (1) subsequent ipsilateral SLAP repair (CPT 29807), (2) ipsilateral arthroscopic debridement for the diagnosis of a SLAP tear (CPT 29822 or 29823, with diagnosis code 840.7), (3) subsequent ipsilateral arthroscopic biceps tenodesis (CPT 29828), (4) subsequent ipsilateral open biceps tenodesis (CPT 23430), and (5) subsequent biceps tenotomy (CPT 23405). Multivariable binomial logistic regression analysis was performed to identify risk factors for revision surgery after SLAP repair, including patient demographics/comorbidities, concomitant diagnoses, and concomitant procedures performed. Odds ratios (ORs), 95% CIs, and P values were calculated. The estimated financial impact of revision surgery was also calculated. RESULTS: There were 4751 patients who met inclusion and exclusion criteria. Overall, 121 patients (2.5%) required revision surgery after SLAP repair. Regression analysis identified numerous risk factors for revision surgery, including age >40 years (OR, 1.5; 95% CI, 1.2-1.8; P = .045), female sex (OR, 1.5; 95% CI, 1.3-1.8; P = .010), obesity (OR, 1.8; 95% CI, 1.5-2.2; P = .001), smoking (OR, 2.0; 95% CI, 1.6-2.4; P < .0001), and diagnosis of biceps tendinitis (OR, 3.5; 95% CI, 3.0-4.2; P < .0001) or long head of the biceps tearing (OR, 5.1; 95% CI, 4.1-6.3; P < .0001) at or before the time of surgery. Concomitant rotator cuff repair and distal clavicle excision were not significant risk factors for revision surgery. The cost of revision surgery averaged almost $9000. CONCLUSION: Risk factors for revision surgery after SLAP repair include age >40 years, female sex, obesity, smoking, and diagnosis of biceps tendinitis or long head of the biceps tearing. The diagnosis of biceps tendinitis (OR, 3.5) or long head of the biceps tearing (OR, 5.1) at or before the time of surgery was an especially significant risk factor for revision surgery. The high cost of revision surgery highlights the importance of appropriate indications to avoid the need for subsequent procedures.

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)0.003
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.342
Teacher spread0.316 · 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

Citations32
Published2017
Admission routes1
Has abstractyes

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