An observational study in Sepsis and Septic Shock, sponsored by Hospital Italiano de Buenos Aires. Not yet recruiting. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-09-11.
Sponsored by Hospital Italiano de Buenos Aires · Observational
Introduction: Timely and accurate antibiotic administration in emergency department (ED) patients with sepsis or septic shock is vital, given mortality rates of 20% and over 40%, respectively. In high antimicrobial resistance (AMR) settings, selecting effective empirical antibiotics is challenging, requiring a balance between efficacy and minimizing multidrug-resistant organism (MDRO) emergence. A predictive model estimating AMR probability could optimize antibiotic use, improve outcomes, and reduce resistance. Although risk factors are known, no single validated model exists for predicting multidrug resistance in sepsis. Accurate prediction must integrate patient history, pathogen profiles, infection source, and antibiotic characteristics.
Objectives: To estimate AMR prevalence in adult ED patients with sepsis or septic shock and develop a validated predictive model estimating AMR probability and likely pathogens. The model will follow a three-phase approach: (1) predict culture positivity, (2) estimate pathogen likelihood, and (3) predict AMR. Additionally, we aim to describe individual-level statistics for both predictable and unpredictable cases based on model performance.
Methods: A cross-sectional study will be conducted at Hospital Italiano's adult ED over 70 months (Jan 1, 2017-Mar 20, 2020 and May 1, 2022-Aug 10, 2025), excluding the COVID-19 period. Primary outcomes include culture positivity, bacterial species, and MDRO prevalence. Frequency analyses will use positive cultures, species, and resistance classifications (MDRO, MDR, XDR, PDR), including mechanisms (e.g., MRSA, ESBL, KPC, MBL, OXA). Denominators will include all sepsis patients and, separately, culture-positive cases. Confidence intervals (95%) will be calculated using normal approximation. Multivariate logistic regression with backward stepwise selection will identify predictors and interactions. A hierarchical model will be developed based on culture results, pathogen identification, and resistance profiles.
Introduction:
Timely and accurate antibiotic administration in emergency department (ED) patients with sepsis or septic shock is vital, given mortality rates of 20% and over 40%, respectively. In high antimicrobial resistance (AMR) settings, selecting effective empirical antibiotics is challenging, requiring a balance between efficacy and minimizing multidrug-resistant organism (MDRO) emergence. A predictive model estimating AMR probability could optimize antibiotic use, improve outcomes, and reduce resistance. Although risk factors are known, no single validated model exists for predicting multidrug resistance in sepsis. Accurate prediction must integrate patient history, pathogen profiles, infection source, and antibiotic characteristics.
Objectives
In adult patients who present to an emergency department in a tertiary care center with sepsis or septic shock:
1-Prevalence and Associated Factors
1a- Estimate the prevalence of AMR/resistance patterns with clinical significance.
1b- Describe the predictive factors associated with AMR in this population.
1c- Generally, and in clinically relevant subgroups: by probable focus, clinically relevant pathogens, severity.
2- Generation and Validation of Predictive Models 2a- Generate and validate clinically useful predictive models to predict the probability of AMR.
2b- Generate and validate clinically useful predictive models to predict the probability of common/relevant pathogens.
2c- Evaluate the performance of stepwise predictive models in three stages: 1. Prediction of positive culture, 2. Intermediate prediction of pathogen, and 3. Prediction of AMR.
2d- Describe and evaluate point statistics on deterministic and unpredictable individuals based on the best predictive models.
Methods:
A cross-sectional study will be conducted at Hospital Italiano's adult ED over 70 months (Jan 1, 2017-Mar 20, 2020 and May 1, 2022-Aug 10, 2025), excluding the COVID-19 period. Primary outcomes include culture positivity, bacterial species, and MDRO prevalence. Frequency analyses will use positive cultures, species, and resistance classifications (MDRO, MDR, XDR, PDR), including mechanisms (e.g., MRSA, ESBL, KPC, MBL, OXA). Explanatory variables - Potential predictors of resistance include: Patient characteristics, Invasive devices, Immunosuppression, Comorbidities, Therapeutic adequacy, Medical history, Antibiotic use, Clinical status and Diagnostic studiesDenominators will include all sepsis patients and, separately, culture-positive cases. Confidence intervals (95%) will be calculated using normal approximation. Multivariate logistic regression with backward stepwise selection will identify predictors and interactions.
A hierarchical model will be developed based on culture results, pathogen identification, and resistance profiles. The sample will be randomly divided into a generation sample (2/3 of the sample) and a validation sample (1/3 of the sample). For the generation and validation of predictive models, the positive culture, each selected relevant bacteria, MDRO, MDR, XDR, PDR will be used as outcome variables.
List of Abbreviations (Abbreviation - Meaning) ABA - Acinetobacter baumannii AMR - Antimicrobial Resistance ESBL - Extended Spectrum Beta-Lactamase-producing Enterobacterales ESKAPE - Acronym summarizing the main clinically relevant resistant germs currently, each letter represents the initial of the scientific name of the bacterium: Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp.
CPE - carbapenemase-producing Enterobacteriaceae GNB - Gram-Negative Bacilli GPC - Gram-Positive Cocci KPC - Carbapenem-resistant Klebsiella pneumoniae MBL - Metallo-beta-lactamase MDR - Multidrug-resistant MOR - Multidrug-resistant Organisms MRSA - Methicillin-resistant Staphylococcus aureus OXA - Oxacillinase-type Carbapenemase PAE MR - Multidrug-resistant Pseudomonas aeruginosa PDR - Pan-resistant SOFA - Sepsis-related Organ Failure Assessment SSC - Surviving Sepsis Campaign VRE - Vancomycin-resistant Enterococci XDR - Extremely resistant
1,899 studies on the registry are indexed under Sepsis; 462 are open to participants now.
This study's planned enrollment of 10,000 is above the median of 160 across 931 observational studies indexed under Sepsis.
Browse Sepsis studies →Hospital Italiano de Buenos Aires is the lead sponsor of 128 studies on the registry; 23 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Individuals aged 18 years or older with sepsis.
Attended at the Adult Emergency Department of Hospital Italiano de Buenos Aires during the periods:
Exclusion Criteria
Individuals aged 18 years or older who present to the Adult Emergency Department (CEA) at the Hospital Italiano de Buenos Aires between 01/01/2017 and 10/08/2025 with sepsis or septic shock and requiring at least 48 hours of observation or admission. The COVID-19 pandemic period will be excluded.
Proportion of episodes with multidrug-resistant organisms (MDRO)
Percentage of episodes with a positive bacterial culture that meet criteria for multidrug resistance (MDR or greater, i.e., MDR/XDR/PDR), defined according to Magiorakos et al., 2012. Unit of Measure: % of culture-positive episodes
Time frame: Baseline (within the first 48 hours of admission)
Culture positivity
Dichotomous variable. It will be considered positive or negative.
Time frame: Baseline
Bacterial species (Number of Participants with each microorganism species)
Categorical variable; the following will be considered: Escherichia coli, Salmonella, Shigella, Klebsiella pneumoniae, Proteus mirabilis, other Proteus species (P. penneri or P. vulgaris), Morganella morganii, Providencia stuartii, Providencia rettgeri, Serratia marcescens, Citrobacter koseri, Citrobacter freundii, Enterobacter cloacae, Klebsiella aerogenes, Hafnia alvei, Pseudomonas aeruginosa, Acinetobacter baumannii, Stenotrophomonas maltophilia, Enterococcus faecalis, Enterococcus faecium, Staphylococcus aureus, coagulase-negative Staphylococcus, Streptococcus pneumoniae, group A beta-hemolytic Streptococcus, Streptococcus pyogenes, Haemophilus influenzae, Neisseria meningitidis, Listeria monocytogenes, others.
Time frame: Baseline
Enzymatic resistance mechanisms (Number of Participants with each enzymatic mechanism detected)
Categorical variable, the following will be considered: No enzymatic mechanism; MRSA; VRE; KPC; MBL; OXA.
Time frame: Baseline
Carbapenemase genotypes (Number of participants with each genotypic resistance mechanism -KPC, NDM, VIM, OXA-48, IMP- detected by multiplex PCR assay)
Categorical variable; the following will be considered: Types of carbapenemases if studied (for example, KPC, NDM, VIM, IMP, OXA-48 like).
Time frame: Baseline
Proportion of episodes with MDR organisms
Percentage of culture-positive episodes classified as MDR (resistant to ≥1 agent in ≥3 antimicrobial categories). Unit of Measure: % of culture-positive episodes
Time frame: Baseline
Proportion of episodes with XDR organisms
Percentage of culture-positive episodes classified as XDR (non-susceptible to ≥1 agent in all but ≤2 categories). Unit of Measure: % of culture-positive episodes
Time frame: Baseline
Proportion of episodes with PDR organisms
Percentage of culture-positive episodes classified as PDR (non-susceptible to all agents in all categories). Unit of Measure: % of culture-positive episodes
Time frame: Baseline
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Hospital Italiano de Buenos Aires