Low incidence of subsequent bacteraemia or fungaemia after removal of a colonized intravascular catheter tip

Buetti, Niccolò; Priore, Elia Lo; Atkinson, Andrew; Kronenberg, Andreas; Marschall, Jonas; Burnens, André P.; Cherkaoui, Abdessalam; Gaia, Valéria; Dubuis, Olivier; Viollier, A.G.; Egli, Adrian; Luyet, S.; Nordmann, Patrice; Perreten, Vincent; Piffaretti, Jean-Claude; Prod’hom, Guy; Schrenzel, Jacques; Leib, Stephen L.; Widmer, Andreas F.; Zanetti, Giorgio; Zbinden, Reinhard

doi:10.1016/j.cmi.2017.09.009

Cited by 9 publications

(6 citation statements)

References 9 publications

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“…They still have potential value for future discussion. The prevailing view supports that the six features, analyzed in the current study are good predictors of ICU-AF ( 7 , 37–42 ). Controlling these six operations is an effective way to reduce ICU-AF.…”

Section: Discussionsupporting

confidence: 74%

Identifying the risk factors of ICU-acquired fungal infections: clinical evidence from using machine learning

Zhao,

Lai,

Tang

et al. 2024

Front. Med.

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BackgroundFungal infections are associated with high morbidity and mortality in the intensive care unit (ICU), but their diagnosis is difficult. In this study, machine learning was applied to design and define the predictive model of ICU-acquired fungi (ICU-AF) in the early stage of fungal infections using Random Forest.ObjectivesThis study aimed to provide evidence for the early warning and management of fungal infections.MethodsWe analyzed the data of patients with culture-positive fungi during their admission to seven ICUs of the First Affiliated Hospital of Chongqing Medical University from January 1, 2015, to December 31, 2019. Patients whose first culture was positive for fungi longer than 48 h after ICU admission were included in the ICU-AF cohort. A predictive model of ICU-AF was obtained using the Least Absolute Shrinkage and Selection Operator and machine learning, and the relationship between the features within the model and the disease severity and mortality of patients was analyzed. Finally, the relationships between the ICU-AF model, antifungal therapy and empirical antifungal therapy were analyzed.ResultsA total of 1,434 cases were included finally. We used lasso dimensionality reduction for all features and selected six features with importance ≥0.05 in the optimal model, namely, times of arterial catheter, enteral nutrition, corticosteroids, broadspectrum antibiotics, urinary catheter, and invasive mechanical ventilation. The area under the curve of the model for predicting ICU-AF was 0.981 in the test set, with a sensitivity of 0.960 and specificity of 0.990. The times of arterial catheter (p = 0.011, OR = 1.057, 95% CI = 1.053–1.104) and invasive mechanical ventilation (p = 0.007, OR = 1.056, 95%CI = 1.015–1.098) were independent risk factors for antifungal therapy in ICU-AF. The times of arterial catheter (p = 0.004, OR = 1.098, 95%CI = 0.855–0.970) were an independent risk factor for empirical antifungal therapy.ConclusionThe most important risk factors for ICU-AF are the six time-related features of clinical parameters (arterial catheter, enteral nutrition, corticosteroids, broadspectrum antibiotics, urinary catheter, and invasive mechanical ventilation), which provide early warning for the occurrence of fungal infection. Furthermore, this model can help ICU physicians to assess whether empiric antifungal therapy should be administered to ICU patients who are susceptible to fungal infections.

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Section: Discussionsupporting

confidence: 74%

Identifying the risk factors of ICU-acquired fungal infections: clinical evidence from using machine learning

Zhao,

Lai,

Tang

et al. 2024

Front. Med.

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“…Information about the microbiological method (quantitative sonication vs semiquantitative roll plate culture) was not routinely made available by the participating laboratories. However, in a previous analysis using a similar dataset, 83% of the participating laboratories used the semiquantitive roll plate culture method 13. Additional culture tip reports of another catheter tip with the same microorganism in the same patient within 7 days were excluded.…”

Section: Methodsmentioning

confidence: 99%

Catheter-related infections: does the spectrum of microbial causes change over time? A nationwide surveillance study

et al. 2018

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ObjectivesTo estimate the incidence and epidemiology of catheter-related bloodstream infections (CRBSIs) on a national scale by using prospective epidemiological data from the Swiss Antibiotic Resistance Surveillance System (ANRESIS).DesignObservational study.SettingNational surveillance from 2008 to 2015 of acute hospitals in Switzerland.ParticipantsWe included acute Swiss hospitals that sent blood cultures and catheter tip culture results on a regular basis during the entire study period to the ANRESIS database.Outcome measureA catheter-related bloodstream infection (termed ‘modified CRBSI’, mCRBSI) was defined as isolating the same microorganism with identical antibiogram from ≥1 blood cultures (performed ±7 days around the catheter removal) as the one recovered from the catheter tip. Incidence rates of mCRBSI were calculated per 1000 admissions.ResultsFrom 2008 to 2015, the mCRBSI incidence rate decreased from 0.83 to 0.58 episodes/1000 admissions (−6% per year, p<0.001). Coagulase-negative staphylococci, Staphylococcus aureus and fungi all exhibited decreasing trends, while rates of enterococci and Gram-negative bacteria remained stable.ConclusionsThe overall incidence of mCRBSI in Switzerland is decreasing; however, the incidence of mCRBSI due to Enterococci and Gram-negative micro-organisms did not change over time. These pathogens may grow in importance in catheter-related infections, which would have clinical implications for the choice of empirical treatment.

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“…An additional episode of catheter tip culture 24 hours after the previous episode was considered a separate episode. Moreover, based on previous studies, a period other than ±3 days of catheter removal was selected for catheter-related blood culture, and predictive performance was recalculated in the same way: (i) blood cultures obtained 7 days before to 2 days after catheter removal [ 7 ] and (ii) blood cultures obtained 2 days before to 1 day after catheter removal [ 8 ]. PPV is a particularly useful diagnostic test measure obtained from gram staining of catheter tips.…”

Section: Methodsmentioning

confidence: 99%

Predictive Performance of Gram Staining of Catheter Tips for Candida Catheter-Related Bloodstream Infections

Yamada

Iwamoto

Ishikane

et al. 2022

Open Forum Infectious Diseases

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Low incidence of subsequent bacteraemia or fungaemia after removal of a colonized intravascular catheter tip

Abstract: A very low incidence of subsequent bloodstream infection was observed if a microorganism was identified on a removed IVC tip without concurrent bacteraemia. The risk of subsequent bloodstream infection increased if C. albicans, S. aureus, or S. marcescens were identified in this context.

Cited by 9 publications

References 9 publications

Identifying the risk factors of ICU-acquired fungal infections: clinical evidence from using machine learning

Identifying the risk factors of ICU-acquired fungal infections: clinical evidence from using machine learning

Catheter-related infections: does the spectrum of microbial causes change over time? A nationwide surveillance study

Predictive Performance of Gram Staining of Catheter Tips for Candida Catheter-Related Bloodstream Infections

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