Quantitative analysis of catheter roughness induced by cutting and manipulation: a potential prothrombotic risk
Bibliographic record
Abstract
Thrombosis is a major complication of central venous access devices, its incidence depending on material, diameter, tip position, and tip surface. Catheters are usually cut to the appropriate length for accurate positioning. Cutting is not recommended, however, as rough surfaces can serve as a nidus for thrombosis. The present study was performed to assess the roughness of catheter tips provided by various manufacturers versus the roughness once cut and handled. Three types of catheters (Hickman, Port-a-Cath, and Per Q Cath) were cut by scissors, iris scissors, or scalpel, and were handled with debakey forceps, a needle driver, adson with teeth or adson without teeth, to determine the damage created on the catheter. The uncut manufactured tip was compared as a control. Scanning electron microscopy was used for imaging of all samples, and roughness was quantified by atomic force microscopy for the cutting methods. Qualitative results by scanning electron microscopy showed that scalpel-cut and manufactured ends appeared smoother relative to those cut with scissors or iris scissors. This complemented the roughness analysis by atomic force microscopy. Catheters handled by debakey forceps and adsons with teeth showed most roughness, visible as deep holes or a grainy surface when observed by high-magnification scanning electron microscopy. Overall, the smoothest result was produced by scalpel, followed by the manufactured end, scissors, and iris scissors. Handling should be minimized, and use of adsons with teeth, needle drivers and debakey forceps should be avoided, as they can leave permanent damage. Adsons without teeth appeared the least damaging.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".