Hospital affiliated to the University of Manitoba.
Bibliographic record
Abstract
Reprocessamento de cateteres cardíacos: uma revisão Reuse of cardiac catheters: a review Hemodynamic catheters are widely reused mainly in developing countries where the cost of new devices is very high. Scientific publications point to an absence of validated cleaning and sterilization processes and there is a consensus that reusing these devices causes physical, chemical and functional damage. So what is the evidence related to the reuse of this kind of catheter? The objective of this study is to identify scientific evidence related to the effects of reprocessing. A search for publications in English, Portuguese and Spanish was performed in Medline/Pubmed and LILACS using Medical Subject Headings (MeSH) terms and free terms without stipulating restraints on time. In total 21 papers were analyzed. It was found that there is commonly damage to the surface polymers as identified by electronic microscopy. Failure in the cleaning and sterilization processes was identified by the presence of debris and microorganisms at the end of the procedure. The results of this study are very important when choosing to reuse hemodynamic catheters. Descriptors: Balloon dilatation, instrumentation. Equipment reuse. Cross infection. Sterilization.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.225 | 0.047 |
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".