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Record W4389030010 · doi:10.1093/ofid/ofad500.2083

2465. O-serotype Distribution of <i>Escherichia coli</i> Causing Invasive Disease in Tertiary Care Hospital Patients

2023· article· en· W4389030010 on OpenAlexaff
Jeroen Geurtsen, Joachim Doua, Luis Martı́nez-Martı́nez, Patricia Palacios, Jeff Powis, Matthew Sims, Peter W. M. Hermans, Oliver Barraud, Philippe Lanotte, Joshua T. Thaden, Oscar Go, Bart Spiessens, Darren Abbanat, Florian Wagenlehner, Tetsuya Matsumoto, Marc J. M. Bonten, Michal Sarnecki, Jan Poolman

Bibliographic record

VenueOpen Forum Infectious Diseases · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsUniversity of Toronto
FundersUniversitair Medisch Centrum UtrechtUniversity of Connecticut Health CenterUniversity of ConnecticutYale UniversityOPEC Fund for International Development
KeywordsMedicineSerotypeGenotypingSeptic shockSepsisBacteremiaEscherichia coliInternal medicineGenotypeMicrobiologyVirologyAntibioticsBiology

Abstract

fetched live from OpenAlex

Abstract Background Escherichia coli is a common Gram-negative bacterium that can infect normally sterile body sites and cause invasive E. coli disease (IED) including bacteremia, sepsis and septic shock. E. coli surface O-antigens are important virulence factors that contribute to pathogenicity, making them promising targets for the development of multivalent conjugate vaccines to protect against IED. Here, we describe the prevalence of O-serotypes and O-genotypes of clinical E. coli isolates across a multinational cohort of patients with IED. Methods This was a retrospective, multicenter, noninterventional study across 17 tertiary care hospitals in Europe, North America and Asia. Patients with an IED diagnosis in the 12 months prior to data collection were included. IED was defined as E. coli presence in cultures from any normally sterile body site or urine in patients exhibiting clinical criteria of invasive disease (i.e., systemic inflammatory response syndrome [SIRS], sepsis, or septic shock) and no other identifiable site of infection. O-serotyping (agglutination) and O-genotyping (whole genome sequencing [WGS]) were conducted. Subgroup analyses were performed in isolates from patients with bacteremic vs nonbacteremic IED and in patients ≥60 years old. Results 902 patients with IED were identified (median age at initial IED diagnosis, 71.0 years; 51.6% male). The most common O-serotypes (prevalence ≥5%) based on O-genotyping were O25 (17.3% [95% CI, 14.82–20.06%]), O2 (11.7% [95% CI, 9.61–14.08%]), O6 (9.3% [95% CI, 7.44–11.49%]), O1 (6.3% [95% CI, 4.78–8.20%]), O15 (5.3% [95% CI, 3.85– 6.99%]) and O75 (5.0% [95% CI, 3.64–6.72%]) (Table 1). Collectively, these 6 most prevalent serotypes accounted for 55.0% of total isolates. A similar pattern of O-serotypes was observed in the subgroup of patients ≥60 years old (Table 2), with serotypes O25, O2 and O6 most common in both bacteremic and nonbacteremic IED isolates. Conclusion The most predominant O-serotype among IED isolates from hospitalized patients with IED was O25, followed by O2, O6, O1, O15 and O75. Such epidemiological data could inform the development of an effective prophylactic vaccine against IED. Disclosures Jeroen Geurtsen, PhD, Janssen: Employee|Janssen: Stocks/Bonds Joachim Doua, MD, MPH, Janssen: Employee|Janssen: Stocks/Bonds Patricia Ibarra de Palacios, MD, Janssen: Employee at the time of analysis Matthew Sims, MD, PhD, Astra-Zeneca: Investigator for company-sponsored studies|ContraFect: Investigator for company-sponsored studies|Crestone: Investigator for company-sponsored studies|Finch: Investigator for company-sponsored studies|Janssen: Investigator for company-sponsored studies|Leonard-Meron: Investigator for company-sponsored studies|Merck and Co: Investigator for company-sponsored studies|OpGen Inc: Advisor/Consultant|OpGen Inc: Investigator for company-sponsored studies|Pfizer: Investigator for company-sponsored studies|Prenosis: Advisor/Consultant|Prenosis: Investigator for company-sponsored studies|QIAGEN Sciences LLC: Investigator for company-sponsored studies|Roche: Investigator for company-sponsored studies|Seres Therapeutics: Investigator for company-sponsored studies Peter Hermans, PhD, Janssen: Employee at the time of analysis Joshua T. Thaden, MD, PhD, Resonantia Diagnostics, Inc: Advisor/Consultant Oscar Go, PhD, Janssen: Employee|Janssen: Stocks/Bonds Bart Spiessens, PhD, Janssen: Employee|Janssen: Stocks/Bonds Darren Abbanat, PhD, Janssen: Employee at the time of analysis Florian Wagenlehner, MD, Achaogen: Advisory Board member, study participation|Astellas: Honoraria|AstraZeneca: Honoraria|AstraZeneca: Advisory Board member|Biomedical Advanced Research and Development Authority (BARDA): Grant/Research Support|Bionorica: Honoraria|Bionorica: Meeting/travel support, study participation|Deutsches Zentrum für Infektionsforschung (DZIF): Study participation|Enteris BioPharma: Study participation|Everest Medicines: Grant/Research Support|German S3 guideline Urinary tract infections: Board Member|Glaxo Smith Kline: Advisor/Consultant|Glaxo Smith Kline: Honoraria|Glaxo Smith Kline: Consulting fees, meeting/travel support, advisory board member, principal investigator in a GSK-sponsored study|Global Antibiotic Research and Development Partnership (GARDP Foundation): Grant/Research Support|Guidelines European Association of Urology: Infections in Urology: Board Member|Helperby Therapeutics: Study participation|Janssen: Honoraria|Janssen: Advisory Board member|Klosterfrau: Honoraria|LeoPharma: Advisory Board member|MerLion: Advisory Board member|MIP Pharma: Honoraria|MSD: Advisory Board member|OM Pharma/Vifor Pharma: Advisory Board member, study participation|OM-Pharma: Honoraria|Pfizer: Honoraria|Pfizer: Advisory Board member|RosenPharma: Advisory Board member|Shionogi: Advisory Board member, study participation|Speaker research group German research foundation (DFG) Bacterial Renal Infections and Defense (FOR 5427): Study participation|Spero Therapeutics: Advisor/Consultant|Spero Therapeutics: Consulting fees|University Hospital Giessen and Marburg GmbH, and Justus Liebig University, Germany: Employee|Venatorx Pharmaceuticals, Inc.: Advisor/Consultant|Venatorx Pharmaceuticals, Inc.: Grant/Research Support|Venatorx Pharmaceuticals, Inc.: Consulting fees, Advisory Board member Tetsuya Matsumoto, MD; PhD, member of the international study steering committee for the E.mbrace study and reports payment: Board Member Marc Bonten, MD, PhD, chair of the international study steering committee for the E.mbrace study (Janssen Vaccines), with payments made to UMC Utrecht: Board Member Michal Sarnecki, MD, Janssen: Employee|Janssen: Stocks/Bonds Jan Poolman, PhD, Janssen: Employee|Janssen: Stocks/Bonds

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.262
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2023
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