Does the French Paradox cementing technique improve or compromise femoral stem stability? An in vitro cadaver study
Bibliographic record
Abstract
BACKGROUND: The French Paradox (FP) technique, characterised by line-to-line cementing, has recently been applied to polished tapered stems with favourable results despite the thin cement mantle created. However, it contravenes the minimum 2-mm cement mantle described in the standard (STD) cementing technique. AIM: This experimental study aimed to compare the FP and STD cementing techniques by comparing the cement mantle thickness, micromotion, and alignment of a polished tapered stem under clinically relevant loads. METHODS: Stems were implanted into 4 pairs of human cadaveric hips. Femurs within each pair were randomly allocated to receive either the STD or FP technique. 5 linear variable displacement transducers (LVDTs) were used to measure the real-time motion of the stem relative to the femur. The specimens were mounted onto a joint motion simulator and cyclically loaded with axial compression (0-1,600 N) and internal torsion (0-15 Nm). RESULTS: No significant differences were found in permanent migration, initial and long-term inducible motion, or stem alignment between techniques. The FP technique resulted in a thinner cement mantle (∆1.0 ± 0.2 mm). The mean permanent migration was below 20 μm, and inducible motions were below 100 μm for both techniques. CONCLUSIONS: Both FP and STD cementing techniques resulted in well-fixed stems with low migration and inducible motion.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".