Elasticity and breaking strength of synthetic suture materials incubated in various equine physiological and pathological solutions
Bibliographic record
Abstract
REASONS FOR PERFORMING STUDY: Selection of suture material in equine surgery is often based on costs or subjective factors, such as the surgeon's personal experience, rather than objective facts. The amount of objective data available on durability of suture materials with regard to specific equine physiological conditions is limited. OBJECTIVES: To evaluate the effect of various equine physiological and pathological fluids on the rate of degradation of a number of commonly used suture materials. STUDY DESIGN: In vitro material testing. METHODS: Suture materials were exposed in vitro to physiological fluid, followed by biomechanical analysis. Three absorbable suture materials, glycolide/lactide copolymer, polyglactin 910 and polydioxanone were incubated at 37°C for 7, 14 or 28 days in phosphate-buffered saline, equine serum, equine urine and equine peritoneal fluid from an animal with peritonitis. Five strands of each suture material type were tested to failure in a materials testing machine for each time point and each incubation medium. Yield strength, strain and Young's modulus were calculated, analysed and reported. RESULTS: For all suture types, the incubation time had a significant effect on yield strength, percentage elongation and Young's modulus in all culture media (P<0.0001). Suture type was also shown significantly to influence changes in each of yield strength, percentage elongation and Young's modulus in all culture media (P<0.0001). While the glycolide/lactide copolymer demonstrated the highest Day 0 yield strength, it showed the most rapid degradation in all culture media. For each of the 3 material characteristics tested, polydioxanone showed the least variation across the incubation period in each culture medium. CONCLUSIONS: The duration of incubation and the type of fluid have significant effects on the biomechanical properties of various suture materials. These findings are important for evidence-based selection of suture material in clinical cases.
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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 | 0.000 | 0.001 |
| 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 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".