Laparoscopic Surgical Manipulations Affect the Mechanical Properties and the Microstructure of Polymeric Sutures
Bibliographic record
Abstract
In the last years a new clinical method to carry out surgical operations has been introduced. It consists in minimally invasive vascular surgery (also called laparoscopy). In one hand, during laparoscopy procedures, sutures cannot be handled with fingers, and the use of stainless-steel needle holders is required. In the other hand, companies that fabricate sutures clearly mention that metal-made devices should be avoided when manipulating the monofilaments. Therefore, the manipulation of the suture monofilaments (made of polymers) by laparoscopic needle holders (made of metals) is controversial. Literature in this field is limited and incomplete. Therefore, the aim of this study was to investigate the mechanical and microstructural effects of the manipulations with laparoscopic needle holder on polymeric suture monofilament. Surgipro© (polypropylene), Teflene© (polyvinylidene fluoride) and Gore-Tex© (polytetrafluoroethylene) monofilament suture were pinched with a standard clinical protocol by a surgeon. Scanning electron microscopy, micro-mechanical testing, differential scanning calorimetry, x-ray diffraction, small angle x-ray scattering and Fourier transform infrared spectroscopy were then performed. Results showed that the ultimate tensile strength of Teflene and Gore-Tex sutures does not change after pinching whereas it decreases significantly for Surgipro sutures. This is attributed to stress concentration and to the compressive strength applied on the monofilament, which are closely related to the permanent deformation of the suture after pinching. Teflene and Gore-Tex monofilament sutures showed to be not affected even after severe pinching with laparoscopic needle holders. Therefore, our results clearly showed that the use of Surgipro II sutures in laparoscopic interventions should be avoided.
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 | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".