THE EFFECT OF CROSS-SECTIONAL STEM SHAPE ON THE TORSIONAL STRENGTH OF CEMENTED IMPLANTS
Bibliographic record
Abstract
The torsional strength of cemented implants is likely influenced by stem geometry. Five straight stems with different cross-sectional shapes (circular, oval, triangular, round-rectangular, sharp-rectangular) were custom-machined. The stems were cemented into tubes using bone cement, and subjected to torsion (2.5deg/min)(n=7). At initial failure (crack through the cement mantle or loss of cement-stem adhesion), the sharp-rectangular stem resisted over 33% more torque than the other four stems (p=0.13). At ultimate failure (5° stem rotation), the resistance provided by the circular stem was less than 12% of either rectangular stem (p To determine the influence of cross-sectional implant stem shape on cement failure under torsional loading. The sharp-rectangular stem provided the greatest torsional resistance against initial failure. At ultimate failure, the two rectangular stems performed better than the other stems, with the circular stem providing the least torsional resistance. A stem design that provides increased resistance to torsion will, in all likelihood, improve the longevity of cemented stemmed implants. Five straight stems with different cross-sectional shapes (circular, oval, triangular, round-rectangular, sharp-rectangular) were custom-machined. Each stem was cemented in a square aluminum tube using Simplex® cement (Stryker, Michigan, USA). A materials testing machine was used to apply torsion to the stem at 2.5 deg/minute until failure. ‘Initial failure’ was defined as the appearance of a crack through the cement mantle and/or the loss of cement-stem adhesion. ‘Ultimate failure’ was defined as 5° of stem rotation. Results (n=7) were compared using one-way ANOVAs with post-hoc Student-Newman-Keuls tests (p=0.05). The sharp-rectangular stem withstood over 33% more torque at initial failure than the other stems (p=0.13). At ultimate failure, the circular stem provided significantly less torsional resistance than the other four stems (p Funding: Natural Sciences and Engineering Research Council, University of Western Ontario
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 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".