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Record W2947630577 · doi:10.1503/cjs.006918

Surgical outcomes of chronic isolated scapholunate interosseous ligament injuries: a systematic review of 805 wrists

2019· review· en· W2947630577 on OpenAlexaffvenue
Spencer J. Montgomery, Natalie J. Rollick, Jeremy F. Kubik, Alexander Meldrum, Neil J. White

Bibliographic record

VenueCanadian Journal of Surgery · 2019
Typereview
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineSubgroup analysisLigamentWristGrip strengthEvidence-based medicinePhysical therapySurgeryConfidence intervalInternal medicine

Abstract

fetched live from OpenAlex

Background: Management of chronic isolated scapholunate interosseous ligament (SLIL) injuries has generated a substantial volume of low-quality literature with descriptions of multiple new surgical techniques, and the impact of instability pattern and the optimal surgical technique remain unclear. The primary goal of this review was to compare clinical, radiographic and patient-rated outcomes between current surgical techniques. Methods: We performed a systematic literature search using multiple databases. We analyzed clinical, radiographic and patient-reported outcomes. We used a fixed-effects model weighted by sample size with combined outcomes estimated via least squares means with 95% confidence intervals. We also performed a subgroup analysis of static versus dynamic instability. Results: We assessed 805 procedures from 37 study groups, with 429 procedures used in subgroup analysis. There were no statistically significant differences in outcomes between surgical techniques or in subgroup analysis. Overall, postoperative wrist flexion and pain scores decreased, and grip strength and patient-rated outcomes improved. Conclusion: Compared to overall preoperative values, modest improvements in pain score, grip strength and functional outcome scores were obtained from a range of reconstructive procedures performed for chronic isolated SLIL injuries. No significant differences could be ascertained between surgical techniques, potentially owing to the low quality of evidence and procedure heterogeneity. This study provides accurate preoperative reference values for future studies, highlights the controversial clinical impact of instability classification, and the need for higher-quality multicentre or collaborative trials to improve our understanding and management of this common injury.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.123
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0100.004
Bibliometrics0.0020.001
Science and technology studies0.0000.000
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 head0.330
Teacher spread0.285 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations26
Published2019
Admission routes2
Has abstractyes

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