Total shoulder arthroplasty with a second-generation tantalum trabecular metal-backed glenoid component
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: We evaluated clinical and radiographic outcomes of total shoulder arthroplasty (TSA) using the second-generation Trabecular Metal (TM) Glenoid component. The first generation component was withdrawn in 2005 after a series of failures were reported. Between 2009 and 2012, 40 consecutive patients with unilateral TSA using the second-generation component were enrolled in this clinical study. The mean age of the patients was 63.8 years (40 to 75) and the mean follow-up was 38 months (24 to 42). METHODS: Patients were evaluated using the Constant score (CS), the American Shoulder and Elbow Surgeons (ASES) score and routine radiographs. RESULTS: Significant differences were found between the pre- and post-operative CS (p = 0.003), ASES (p = 0.009) scores and CS subscores of pain (p < 0.001), strength (p < 0.001) and mobility items (p < 0.05). No glenoid or humeral components migrated. Posterior thinning of the keel and slight wear at the polyethylene-TM interface was observed in one patient but was asymptomatic. Radiolucent lines were found around three humeral (< 1.5 mm) and two glenoid components (< 1 mm) and all were asymptomatic. DISCUSSION: TSA with the second-generation TM Glenoid component results in satisfactory to excellent clinical performance, function, and subjective satisfaction at a mean follow-up of about three years. Radiographic changes were few and did not affect the outcome. TAKE HOME MESSAGE: This paper highlights that the second generation Trabecular Metal Glenoid has better outcomes than those reported with the first-generation component.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it