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Reprocessamento de cateteres de angiografia cardiovascular após uso clínico e contaminados artificialmente: avaliação da eficácia da limpeza e da esterilização.

2006· dissertation· pt· W1573918447 on OpenAlexaboutno aff
Silma Maria Cunha Pinheiro Ribeiro

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldImmunology and Microbiology
TopicMedical Device Sterilization and Disinfection
Canadian institutionsnot available
Fundersnot available
KeywordsReuseBioburdenMedicineEnvironmental scienceEngineeringSurgeryWaste management

Abstract

fetched live from OpenAlex

The healthy assistance implies in risk, which can be maximized, minimized or projected based on the scientific data. The reprocessing of single used devices is a practice that each day has demanded efforts of the healthcare professionals in order to search and to produce scientific evidences to help them make decision in relation to not reuse or reuse under safety conditions. The objective of this study was to evaluate different cleaning processes and sterilization in ethylene oxide 100% of the angiographic catheters in order to determine the capacity in reducing of the bioburden and the organic residual before and after patient use, as well as in simulated use with soil test. It is an experimental research, comparative and controlled permed in the Research Centre of the Saint Boniface General Hospital affiliated to the University of Manitoba located in Winnipeg, Canada. The catheters had been used only one time for coronariographic exam and submitted to the analysis of organic residues (hemoglobin, carbohydrate, protein and endotoxin) by in situ and destructive test reading by spectrophotometer. The bioburden was evaluated by microbial culture. These experiments had been performed in four phases, being the first immediately after patient use to determine the basaline soil; the second after patient use and cleaning of the catheter by different methods; the third after patient use, soil test inoculation and cleaning by different methods. The fourth phase was performed after patient use and simulated reuse. Descriptive and analytical statistic analysis by parametric statistical tests (variance analysis) or no parametric tests (Kruskall-Wallis) were performed. Had been considered bilateral tests with a significance level < 0,05 and the confidence interval was 95%. It was considered clening failure of the cleaning process any positive results of the detention of organic and microbiological residue. The catheters were submitted to the following cleaning methods: manual washing with enzymatic detergent with tap water or reverse osmosis sterile rinsing; manual washing with hydrogen peroxide detergent rinsing in reverse osmosis sterile water, automated washing with no rinse or reverse osmose sterile water; hydrogen peroxide detergent pumping with tap water or reverse osmosis sterile rinsing . The results gotten in our study showed the maintenance of the bioburden before and after the cleaning of the catheters. In the baseline phase 8,2% of the cultures were positive cultures and the microbial load was 500CFU/device. After cleaning it was 8,3% and the average microbial load was 250 CFU/device. The baseline organic residues data were hemoglobin 146,3g/device, protein 628,5 g/device, carbohydrate 7,0g/device and endotoxin 38,0EU/device. After five simulated use, the indirect hemoglobin concentration was lower of the test limit of detention, protein = 107,7 g/device, carbohydrate = 340,1g/device and endotoxin=5,4EU/device. The organic residual analysis according the cleaning methods found different levels of reduction. The cleaning methods that had used a hydrogen peroxide detergent showed better performance relating the enzymatic detergents methods, as well as hydrogen peroxide detergent pumping with

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.025
GPT teacher head0.290
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2006
Admission routes1
Has abstractyes

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