Use of a molecular syndromic panel for the etiological diagnosis of bloodstream infections in critically ill patients: impact on clinical outcomes and antimicrobial use from a multicenter, prospective study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Bloodstream infections (BSI) frequently occur in critically ill patients and remain associated with high mortality rates. A prospective, observational, multicenter investigation was carried out through the MULTI-SITA platform to evaluate how the addition of a molecular syndromic panel, the BIOFIRE® Blood Culture Identification 2 (BCID2) Panel (BCID2 panel), to conventional blood culture diagnostics influenced key clinical endpoints and antimicrobial use. The primary endpoint was all-cause mortality within 30 days following the onset of BSI. Among the 126 included critically ill patients with BSI, multivariable analysis identified SOFA score (hazard ratio [HR] 1.21, 95% confidence interval [CI] 1.09–1.34, p < 0.001), other concomitant infections requiring antibiotic therapy (HR 2.61, 95% CI 1.18–5.79, p = 0.018), and BSI caused by Acinetobacter spp. (HR 4.35, 95% CI 1.10–17.18, p = 0.036), Staphylococcus aureus (HR 3.38, 95% CI 1.26–9.08, p = 0.016), or Stenotrophomonas maltophilia (HR 15.97, 95% CI 2.43–104.54, p = 0.004) as associated with increased mortality, while no association was observed between use of the BCID2 panel and mortality (HR 0.97, 95% CI 0.42–2.25, p = 0.941). In secondary analyses, the use of the BCID2 panel resulted in more events of either early antimicrobial de-escalation or initiation of appropriate therapy at day one from BSI onset compared with a standard blood culture workflow (55.6% vs. 31.7%, p = 0.015). In critically ill patients with BSI, implementation of a molecular syndromic panel influenced antimicrobial management decisions without affecting mortality. Additional investigations are warranted to clarify the long-term antimicrobial stewardship implications of treatment strategies guided by molecular syndromic panels-based diagnostic workflows.
Source: Figshare
Authors: Daniele Roberto Giacobbe, Claudia Bartalucci, Greta Cattardico, Vincenzo Di Pilato, Marco Muccio, Maurizio Fedriga, Alessandro Limongelli, Alessio Signori, Alessandra Bandera, Bruno Cacopardo, Edoardo Campanella, Alessandro Caroli, Annamaria Cattelan, Marco Piscaglia, Andrea Cortegiani, Laura Curci, Gennaro De Pascale, Giuseppe Vittorio De Socio, Filippo Del Puente, Chiara Fanelli, Teresa Fasciana, Nicholas Geremia, Maddalena Giannella, Giacomo Grasselli, Chiara Maci, Ivana Maida, Davide Mangioni, Andrea Marino, Maria Mazzitelli, Maria Chiara Meloni, Marco Merli, Elena Momesso, Chiara Oltolini, Carlo Pallotto, Sandro Panese, Matteo Passerini, Emanuele Pontali, Daniele Riccucci, Matteo Rinaldi, Marco Ripa, Vincenzo Scaglione, Francesco Saverio Serino, Vincenzo Spagnuolo, Giulia Spurio, Stefania Tigano, Carlo Torti, Giovanna Travi, Laura Magnasco, Federica Portunato, Federica Briano, Malgorzata Mikulska, Lorenzo Ball, Chiara Robba, Nicolò Patroniti, Denise Battaglini, Mauro Giacomini, Gian Maria Rossolini, Maurizio Sanguinetti, Paola Morici, Anna Marchese, Antonio Vena, Matteo Bassetti
Language: English
Subfield: Microbiology (medical)
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7225095148