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Excess resource use and cost of drug-resistant infections for six key pathogens in Europe: a systematic review and Bayesian meta-analysis.
Kingston, Rhys; Vella, Venanzio; Pouwels, Koen B; Schmidt, Johannes E; Abdelatif El-Abasiri, Radwa A; Reyna-Villasmil, Eduardo; Hassoun-Kheir, Nasreen; Harbarth, Stephan; Rodríguez-Baño, Jesús; Tacconelli, Evelina; Arieti, Fabiana; Gladstone, Beryl Primrose; de Kraker, Marlieke E A; Naylor, Nichola R; Robotham, Julie V.
Afiliación
  • Kingston R; Field Service Data Science Team, UK Health Security Agency, London, UK.
  • Vella V; GSK, Siena, Italy.
  • Pouwels KB; Nuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK.
  • Schmidt JE; GSK, Siena, Italy.
  • Abdelatif El-Abasiri RA; Nuffield Department of Population Health, Health Economics Research Centre, University of Oxford, Oxford, UK.
  • Reyna-Villasmil E; Infectious Diseases and Microbiology Division, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen Macarena, Department of Medicine, University of Sevilla/CSIC, Sevilla, Spain.
  • Hassoun-Kheir N; Infection Control Program, Geneva University Hospitals and Faculty of Medicine, WHO Collaborating Center, Geneva, Switzerland.
  • Harbarth S; Infection Control Program, Geneva University Hospitals and Faculty of Medicine, WHO Collaborating Center, Geneva, Switzerland.
  • Rodríguez-Baño J; Infectious Diseases and Microbiology Division, Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen Macarena, Department of Medicine, University of Sevilla/CSIC, Sevilla, Spain.
  • Tacconelli E; Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, Verona, Italy.
  • Arieti F; Infectious Diseases, Department of Diagnostics and Public Health, University of Verona, Verona, Italy.
  • Gladstone BP; Department of Internal Medicine, DZIF-Clinical Research Unit, Infectious Diseases, University Hospital Tübingen, Tübingen, Germany.
  • de Kraker MEA; Infection Control Program, Geneva University Hospitals and Faculty of Medicine, WHO Collaborating Center, Geneva, Switzerland.
  • Naylor NR; HCAI, Fungal, AMR, AMU, & Sepsis Division, UK Health Security Agency, London, UK.
  • Robotham JV; HCAI, Fungal, AMR, AMU, & Sepsis Division, UK Health Security Agency, London, UK. Electronic address: julie.robotham@ukhsa.gov.uk.
Clin Microbiol Infect ; 30 Suppl 1: S26-S36, 2024 Mar.
Article en En | MEDLINE | ID: mdl-38128781
ABSTRACT

BACKGROUND:

Quantifying the resource use and cost of antimicrobial resistance establishes the magnitude of the problem and drives action.

OBJECTIVES:

Assessment of resource use and cost associated with infections with six key drug-resistant pathogens in Europe.

METHODS:

A systematic review and Bayesian meta-analysis. DATA SOURCES MEDLINE (Ovid), Embase (Ovid), Econlit databases, and grey literature for the period 1 January 1990, to 21 June 2022. STUDY ELIGIBILITY CRITERIA Resource use and cost outcomes (including excess length of stay, overall costs, and other excess in or outpatient costs) were compared between patients with defined antibiotic-resistant infections caused by carbapenem-resistant (CR) Pseudomonas aeruginosa and Acinetobacter baumannii, CR or third-generation cephalosporin Escherichia coli (3GCREC) and Klebsiella pneumoniae, methicillin-resistant Staphylococcus aureus, and vancomycin-resistant Enterococcus faecium, and patients with drug-susceptible or no infection.

PARTICIPANTS:

All patients diagnosed with drug-resistant bloodstream infections (BSIs).

INTERVENTIONS:

NA. ASSESSMENT OF RISK OF BIAS An adapted version of the Joanna Briggs Institute assessment tool, incorporating case-control, cohort, and economic assessment frameworks. METHODS OF DATA

SYNTHESIS:

Hierarchical Bayesian meta-analyses were used to assess pathogen-specific resource use estimates.

RESULTS:

Of 5969 screened publications, 37 were included in the review. Data were sparse and heterogeneous. Most studies estimated the attributable burden by, comparing resistant and susceptible pathogens (32/37). Four studies analysed the excess cost of hospitalization attributable to 3GCREC BSIs, ranging from -€ 2465.50 to € 6402.81. Eight studies presented adjusted excess length of hospital stay estimates for methicillin-resistant S. aureus and 3GCREC BSIs (4 each) allowing for Bayesian hierarchical analysis, estimating means of 1.26 (95% credible interval [CrI], -0.72 to 4.17) and 1.78 (95% CrI, -0.02 to 3.38) days, respectively.

CONCLUSIONS:

Evidence on most cost and resource use outcomes and across most pathogen-resistance combinations was severely lacking. Given the importance of this evidence for rational policymaking, further research is urgently needed.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Systematic_reviews Idioma: En Revista: Clin Microbiol Infect Asunto de la revista: DOENCAS TRANSMISSIVEIS / MICROBIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Systematic_reviews Idioma: En Revista: Clin Microbiol Infect Asunto de la revista: DOENCAS TRANSMISSIVEIS / MICROBIOLOGIA Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido