2465. O-serotype Distribution of <i>Escherichia coli</i> Causing Invasive Disease in Tertiary Care Hospital Patients
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".