Evidence map›Paper›PMID 42141875›Full record

ArticleEuro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin2026

First results of a national deployment of a fully automated central-line-associated bloodstream infection (CLABSI) surveillance system, Switzerland, 2022 to 2023.

Gaud Catho, Jason Toko, Loïc Fortchantre, Elia Lo Priore, Carlo Balmelli, Lauro Damonti, Philipp Jent, Estelle Moulin, Bruno Grandbastien, Peter W Schreiber and 9 more

Abstract readMulticenter Study
In one paragraph

Article in Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

19 authors.

Gaud CathoInfectious Diseases Division, Central Institute, Valais Hospital, Sion, Switzerland.
Jason TokoInfection Control Programme and World Health Organization Collaborating Centre, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.
Loïc FortchantreInfection Control Programme and World Health Organization Collaborating Centre, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.
Elia Lo PrioreDivision of Infectious Diseases, Department of Medicine, Ente Ospedaliero Cantonale, Lugano, Switzerland.
Carlo BalmelliDivision of Infectious Diseases, Department of Medicine, Ente Ospedaliero Cantonale, Lugano, Switzerland.
Lauro DamontiDepartment of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Philipp JentDepartment of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Estelle MoulinInfection Prevention and Control Unit, Infectious Diseases Service, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Bruno GrandbastienInfection Prevention and Control Unit, Infectious Diseases Service, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
Peter W SchreiberDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
Sarah Tschudin-SutterDivision of Infectious Diseases and Infection Control, Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland.
Jan Adam RothDivision of Infectious Diseases and Infection Control, Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland.
Lorenzo CiulliniInfection Control Programme and World Health Organization Collaborating Centre, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.
Claudine ReiberDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
Walter ZinggDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
Alexandra U ScherrerSwissnoso National Center for Infection Control, Bern, Switzerland.
Stephan HarbarthInfection Control Programme and World Health Organization Collaborating Centre, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.
Niccolò BuettiUniversité Paris-Cité, INSERM, IAME, UMR 1137, Paris, France.
Swissnoso working groupThe members of the Swissono group are acknowledged at the end of the article.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUNDAccurate, fully automated systems may increase efficiency of healthcare-associated infections (HAI) surveillance.AIMWe aimed to validate the performance of a fully automated surveillance system for central-line-associated bloodstream infections (CLABSI) in critically ill patients in Switzerland.METHODSWe conducted a multicentre retrospective study across six secondary and tertiary care hospital networks' intensive care units (ICU). A centrally hosted, fully automated algorithm was implemented to detect catheter-related bloodstream infections (CRBSI), CLABSI and ICU-onset bloodstream infections (ICU-BSI). Algorithm performance was validated against an anonymised manual review of random samples of positive blood cultures. Incidence data were computed for each hospital.RESULTSFrom January 2022 to December 2023, we analysed 131,166 patient days, 108,719 catheter days and 7,832 positive blood cultures from 1,931 ICU patients. Median age was 65 years (interquartile range (IQR): 53-73), 458 (23.7%) were female. For CLABSI and CRBSI, the algorithm demonstrated a specificity of 95.3% (95% confidence interval (CI): 92.7-97.0), sensitivity of 86.5% (95% CI: 79.8-91.2), positive predictive value of 87.0% (95% CI: 80.4-91.7) and negative predictive value of 95.1% (95% CI: 92.5-96.8). CRBSI/CLABSI and ICU-BSI incidence rates were 3.23/1,000 catheter days (95% CI: 2.91-3.57) and 2.42/1,000 patient days (95% CI: 2.17-2.70), respectively. Most identified microorganisms for CRBSI/CLABSI were

Indexed as

BacteremiaCatheterization, Central VenousCatheter-Related InfectionsCross InfectionPopulation SurveillanceAgedAlgorithmsAutomationCritical IllnessEnterococcus faeciumFemaleHumansIncidenceIntensive Care UnitsMaleMiddle Agedautomatedbloodstream infectioncatheter-infectionCLABSIdigitalexternal validationhealthcare associated infectionsIntensive care unitsensitivityspecificity

Identifiers

PMID42141875
PMCPMC13170418

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.