Predictive performance of automated surveillance algorithms for intravascular catheter bloodstream infections: a systematic review and meta-analysis.
Accuracy
Algorithm
Automated monitoring
CLABSI
CRBSI
Healthcare associated infections
Surveillance
Journal
Antimicrobial resistance and infection control
ISSN: 2047-2994
Titre abrégé: Antimicrob Resist Infect Control
Pays: England
ID NLM: 101585411
Informations de publication
Date de publication:
31 08 2023
31 08 2023
Historique:
received:
17
04
2023
accepted:
09
08
2023
medline:
4
9
2023
pubmed:
1
9
2023
entrez:
31
8
2023
Statut:
epublish
Résumé
Intravascular catheter infections are associated with adverse clinical outcomes. However, a significant proportion of these infections are preventable. Evaluations of the performance of automated surveillance systems for adequate monitoring of central-line associated bloodstream infection (CLABSI) or catheter-related bloodstream infection (CRBSI) are limited. We evaluated the predictive performance of automated algorithms for CLABSI/CRBSI detection, and investigated which parameters included in automated algorithms provide the greatest accuracy for CLABSI/CRBSI detection. We performed a meta-analysis based on a systematic search of published studies in PubMed and EMBASE from 1 January 2000 to 31 December 2021. We included studies that evaluated predictive performance of automated surveillance algorithms for CLABSI/CRBSI detection and used manually collected surveillance data as reference. We estimated the pooled sensitivity and specificity of algorithms for accuracy and performed a univariable meta-regression of the different parameters used across algorithms. The search identified five full text studies and 32 different algorithms or study populations were included in the meta-analysis. All studies analysed central venous catheters and identified CLABSI or CRBSI as an outcome. Pooled sensitivity and specificity of automated surveillance algorithm were 0.88 [95%CI 0.84-0.91] and 0.86 [95%CI 0.79-0.92] with significant heterogeneity (I Performance of automated algorithms for detection of intravascular catheter infections in comparison to manual surveillance seems encouraging. The development of automated algorithms should consider the inclusion of results of microbiological cultures from specific specimens to exclude non-CRBSI, while the inclusion of clinical data may not have an added-value. Trail Registration Prospectively registered with International prospective register of systematic reviews (PROSPERO ID CRD42022299641; January 21, 2022). https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022299641.
Sections du résumé
BACKGROUND
Intravascular catheter infections are associated with adverse clinical outcomes. However, a significant proportion of these infections are preventable. Evaluations of the performance of automated surveillance systems for adequate monitoring of central-line associated bloodstream infection (CLABSI) or catheter-related bloodstream infection (CRBSI) are limited.
OBJECTIVES
We evaluated the predictive performance of automated algorithms for CLABSI/CRBSI detection, and investigated which parameters included in automated algorithms provide the greatest accuracy for CLABSI/CRBSI detection.
METHODS
We performed a meta-analysis based on a systematic search of published studies in PubMed and EMBASE from 1 January 2000 to 31 December 2021. We included studies that evaluated predictive performance of automated surveillance algorithms for CLABSI/CRBSI detection and used manually collected surveillance data as reference. We estimated the pooled sensitivity and specificity of algorithms for accuracy and performed a univariable meta-regression of the different parameters used across algorithms.
RESULTS
The search identified five full text studies and 32 different algorithms or study populations were included in the meta-analysis. All studies analysed central venous catheters and identified CLABSI or CRBSI as an outcome. Pooled sensitivity and specificity of automated surveillance algorithm were 0.88 [95%CI 0.84-0.91] and 0.86 [95%CI 0.79-0.92] with significant heterogeneity (I
CONCLUSIONS
Performance of automated algorithms for detection of intravascular catheter infections in comparison to manual surveillance seems encouraging. The development of automated algorithms should consider the inclusion of results of microbiological cultures from specific specimens to exclude non-CRBSI, while the inclusion of clinical data may not have an added-value. Trail Registration Prospectively registered with International prospective register of systematic reviews (PROSPERO ID CRD42022299641; January 21, 2022). https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022299641.
Identifiants
pubmed: 37653559
doi: 10.1186/s13756-023-01286-0
pii: 10.1186/s13756-023-01286-0
pmc: PMC10468855
doi:
Types de publication
Meta-Analysis
Systematic Review
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
87Investigateurs
Carlo Balmelli
(C)
Delphine Berthod
(D)
Jonas Marschall
(J)
Hugo Sax
(H)
Matthias Schlegel
(M)
Alexander Schweiger
(A)
Laurence Senn
(L)
Rami Sommerstein
(R)
Nicolas Troillet
(N)
Danielle Vuichard Gysin
(DV)
Andreas F Widmer
(AF)
Aline Wolfensberger
(A)
Walter Zingg
(W)
Informations de copyright
© 2023. BioMed Central Ltd., part of Springer Nature.
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