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Early prediction of blood stream infection in a prospectively collected cohort
Örebro universitet, Institutionen för medicinska vetenskaper. Department of Laboratory Medicine, Clinical Microbiology.ORCID-id: 0000-0002-8904-600X
Department of Infectious Diseases, Örebro University Hospital, Örebro, Sweden.
Department of Infectious Diseases, Örebro University Hospital, Örebro, Sweden.ORCID-id: 0009-0007-5318-1473
Department of Laboratory Medicine, Clinical Microbiology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.
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2021 (Engelska)Ingår i: BMC Infectious Diseases, E-ISSN 1471-2334, Vol. 21, nr 1, artikel-id 316Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

BACKGROUND: Blood stream infection (BSI) and sepsis are serious clinical conditions and identification of the disease-causing pathogen is important for patient management. The RISE (Rapid Identification of SEpsis) study was carried out to collect a cohort allowing high-quality studies on different aspects of BSI and sepsis. The aim of this study was to identify patients at high risk for BSI who might benefit most from new, faster, etiological testing using neutrophil to lymphocyte count ratio (NLCR) and Shapiro score.

METHODS: Adult patients (≥ 18 years) presenting at the emergency department (ED) with suspected BSI were prospectively included between 2014 and 2016 at Örebro University Hospital. Besides extra blood sampling, all study patients were treated according to ED routines. Electronic patient charts were retrospectively reviewed. A modified Shapiro score (MSS) and NLCR were extracted and compiled. Continuous score variables were analysed with area under receiver operator characteristics curves (AUC) to evaluate the ability of BSI prediction.

RESULTS: The final cohort consisted of 484 patients where 84 (17%) had positive blood culture judged clinically significant. At optimal cut-offs, MSS (≥3 points) and NLCR (> 12) showed equal ability to predict BSI in the whole cohort (AUC 0.71/0.74; sensitivity 69%/67%; specificity 64%/68% respectively) and in a subgroup of 155 patients fulfilling Sepsis-3 criteria (AUC 0.71/0.66; sensitivity 81%/65%; specificity 46%/57% respectively). In BSI cases only predicted by NLCR> 12 the abundance of Gram-negative to Gram-positive pathogens (n = 13 to n = 4) differed significantly from those only predicted by MSS ≥3 p (n = 7 to n = 12 respectively) (p < 0.05).

CONCLUSIONS: MSS and NLCR predicted BSI in the RISE cohort with similar cut-offs as shown in previous studies. Combining the MSS and NLCR did not increase the predictive performance. Differences in BSI prediction between MSS and NLCR regarding etiology need further evaluation.

Ort, förlag, år, upplaga, sidor
BioMed Central (BMC), 2021. Vol. 21, nr 1, artikel-id 316
Nyckelord [en]
Bacteremia, Clinical decision rules, Sepsis
Nationell ämneskategori
Infektionsmedicin
Identifikatorer
URN: urn:nbn:se:oru:diva-90961DOI: 10.1186/s12879-021-05990-3ISI: 000636178800001PubMedID: 33810788Scopus ID: 2-s2.0-85103852609OAI: oai:DiVA.org:oru-90961DiVA, id: diva2:1543790
Anmärkning

Funding Agencies:

Research Committee of Örebro County Council  

Örebro University 

Tillgänglig från: 2021-04-13 Skapad: 2021-04-13 Senast uppdaterad: 2026-04-13Bibliografiskt granskad
Ingår i avhandling
1. Molecular based approaches for detection of bloodstream infections
Öppna denna publikation i ny flik eller fönster >>Molecular based approaches for detection of bloodstream infections
2026 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Bloodstream infection (BSI) is a life-threatening condition associated with high mortality. Pathogen identification is essential for patient management, yet blood culture (BC), the diagnostic gold standard, may require 2–5 days and has reduced sensitivity after antimicrobial treatment. This thesis investigates modern molecular DNA sequencing approaches for detecting bacterial DNA as a diagnostic alternative. In Study I, a cohort of 484 patients with suspected BSI was described, and prediction tools were applied to identify patients at high risk of BSI for subsequent studies. Study II used whole blood samples from 51 patients to detect bacterial DNA with short-read sequencing and showed low concordance with routine BC results. In Study III, a shotgun metagenomic workflow using the Nanopore platform was developed, and DNA extraction efficiency was evaluated in contrived samples. Bacterial DNA recovery was slightly higher in whole blood than in plasma, but no firm conclusion regarding the optimal sample matrix could be drawn. We also observed that extraction efficiency differed between bacterial species. Based on these methodological challenges and limited sensitivity, Study IV evaluated bacterial DNA enrichment prior to sequencing through short BC incubation (4 h) followed by targeted 16S gene sequencing in 161patients selected using the criteria defined in Study I. This workflow showed increased diagnostic performance, with sensitivity of 56.8% and specificity of 46.7% compared with BC. Additional bacteria with plausible clinical relevance were detected in a few patients with negative routine BC. Overall, the sequencing protocols evaluated in this thesis provided limited additional diagnostic value for BSI compared to BC. In comparison with the literature, we highlight methodological challenges to guide future research in this area.

Ort, förlag, år, upplaga, sidor
Örebro: Örebro University, 2026. s. 98
Serie
Örebro Studies in Medicine, ISSN 1652-4063 ; 353
Nyckelord
Bloodstream infection, Bacteremia, Blood culture, Metagenomics, High-throughput nucleotide sequencing, Nanopore sequencing
Nationell ämneskategori
Allmänmedicin
Identifikatorer
urn:nbn:se:oru:diva-127338 (URN)9789175297651 (ISBN)9789175297668 (ISBN)
Disputation
2026-05-08, Örebro universitet, Campus USÖ, hörsal X1, Södra Grev Rosengatan 32, Örebro, 13:00 (Engelska)
Opponent
Handledare
Tillgänglig från: 2026-02-17 Skapad: 2026-02-17 Senast uppdaterad: 2026-04-22Bibliografiskt granskad

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Nestor, DavidKihlberg, PernillaRasmussen, GunlögKällman, JanCajander, SaraMölling, PaulaSundqvist, Martin

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Nestor, DavidKihlberg, PernillaRasmussen, GunlögKällman, JanCajander, SaraMölling, PaulaSundqvist, Martin
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