The effect of stem material and surface treatment on the torsional stability at the metal–cement interface of upper limb joint replacement systems
Bibliographic record
Abstract
Stem surface treatment and material are two design factors that may affect the onset of implant loosening. For upper limb applications, no known in vitro studies have addressed the role of these two factors on cemented implant stability. Therefore, the purpose of this study was to compare the torsional stability of cemented titanium and cobalt chrome stems with varying surface treatments in vitro. Thirty implant stems of circular cross-section (Ø = 8mm) were machined from cobalt chrome (n = 15) and titanium (n = 15). For each type, stems were subdivided into three groups for application of clinically relevant surface treatments: smooth, sintered beads, or plasma spray. Stems were potted in bone cement, allowed 24 h to cure, and placed in a materials testing machine. Stems were tested under cyclic torsion (1-30 Nm), using a staircase loading protocol. Failure was defined as either the first rapid increase in stem rotation without resistance, or attaining a maximum torque of 30 Nm. Implant stems with non-smooth surfaces offered greater resistance to torsion (p < 0.05), with the plasma spray treatment outlasting the beaded and smooth stems (p < 0.05). Titanium offered superior interface strength (p < 0.05) but reduced resistance to motion (p < 0.05) when compared to cobalt chrome. Therefore, these design features should be considered during upper limb implant design.
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 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 | 0.020 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".