Ligamentum Teres Injuries of the Hip: A Systematic Review Examining Surgical Indications, Treatment Options, and Outcomes
Bibliographic record
Abstract
PURPOSE: Hip arthroscopy is becoming a common technique for the diagnosis and treatment of ligamentum teres pathologic conditions. This systematic review aims to determine the indications/contraindications, treatments, and surgical outcomes for management of ligamentum teres injuries. METHODS: We searched EMBASE, MEDLINE, and PubMed databases from 1946 to November 28, 2013 for all relevant English articles pertaining to surgical treatment of the ligamentum teres. A hand search of the reference sections of included articles was performed, and all relevant articles were systematically screened in duplicate, with agreement and descriptive statistics presented. RESULTS: We identified 1,016 studies, 9 of which (4 case series and 5 case reports) met our eligibility criteria. These studies had a total of 87 patients (89 hips) who had undergone either arthroscopic debridement (81 patients, 83 hips) or reconstruction with autografting, allografting, or synthetic grafting (6 patients) of a torn ligamentum teres. Major qualifications for surgery included persistent hip pain despite conservative treatment and mechanical symptoms or instability symptoms (e.g., clicking or locking). Advanced arthritis (i.e., radiographic joint space < 2 mm) was the only reported contraindication. Patients were followed postoperatively for 1.5 to 60 months and were assessed using subjective methods (i.e., modified Harris Hip Score [mHHS] and Non-Arthritic Hip Score [NAHS]). Overall, both debridement and reconstruction improved the condition of patients, with a 40% increase in reported postoperative functional scores as well as a reported 89% of patients who were able to return to regular activity/sport. CONCLUSIONS: Ligamentum teres debridement is indicated for short-term relief of hip pain caused by partial-thickness tears (type 2) failing conservative management, whereas reconstruction with autografts, allografts, or synthetic grafts may be indicated for type 1 (full-thickness) ligamentum teres tears that are deemed "reparable," cause instability, have failed previous debridement, or a combination of these conditions. LEVEL OF EVIDENCE: Level IV, systematic review of Level IV and Level V studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".