SepsisNCT07167173
Predictive Model for Multidrug Resistance in Patients Admitted to the Emergency Department With Sepsis
An observational study of Sepsis and Septic Shock, run by Hospital Italiano de Buenos Aires.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Sepsis, Septic Shock
- How many people
- 10,000 participants
- Where
- No sites listed yet
- Study dates
- 15 Oct 2025to 31 Oct 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Individuals aged 18 years or older with sepsis.
Who may be able to join
- Adults aged 18 years or older.
- Attended at the Adult Emergency Department of Hospital Italiano de Buenos Aires during the periods:
- January 1, 2017 - March 20, 2020, or
- May 1, 2022 - August 10, 2025.
- Sepsis or septic shock at presentation and at least 48 hours of observation or hospital admission.
- Bacterial cultures obtained during the initial evaluation.
Who cannot join
- No indication for antibiotic therapy within the first 48 hours of hospital admission.
- No bacterial cultures performed within the first 48 hours of hospital admission.
- SARS-CoV-2 infection diagnosed within the first 72 hours of hospital admission.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
Emilio Felipe Huaier Arriazu, MD contact
About this study
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.
Read the detailed description
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
- Conditions
- Sepsis, Septic Shock
- Keywords
- Antimicrobial resistance, sepsis, predictive models
- Medical subject headings
- Sepsis, Shock, Septic
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Individuals with sepsis | 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: Baseline (within the first 48 hours of admission)
Secondary outcomes (7)
Culture positivity
Dichotomous variable. It will be considered positive or negative.
Measured: 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.
Measured: 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.
Measured: 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).
Measured: 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
Measured: 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
Measured: 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
Measured: Baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Sep 2025
- Study start15 Oct 2025 (estimated)
- Primary completion20 Oct 2025 (estimated)
- Study completion31 Oct 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (83)Papers the sponsor has linked to this study.
- Other trials for SepsisStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Cross-sectional
- Enrolment
- 10,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Hospital Italiano de Buenos Aires
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, EMILIO FELIPE HUAIER ARRIAZU, Hospital Italiano de Buenos Aires
- Investigators
- Emilio Felipe H Huaier Arriazu, MD, Principal investigator, Hospital Italiano de Buenos Aires
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07167173
- Sponsor's protocol ID
- 7441
- Status last verified
- Sep 2025
- First submitted
- 25 Jul 2025
- Last updated
- 11 Sep 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Not possible due to confidentiality and legal restrictions.
Publications
Jung K, Kashyap S, Avati A, Harman S, Shaw H, Li R, Smith M, Shum K, Javitz J, Vetteth Y, Seto T, Bagley SC, Shah NH. A framework for making predictive models useful in practice. J Am Med Inform Assoc. 2021 Jun 12;28(6):1149-1158. doi: 10.1093/jamia/ocaa318.
PubMed 33355350Rubin LG, Levin MJ, Ljungman P, Davies EG, Avery R, Tomblyn M, Bousvaros A, Dhanireddy S, Sung L, Keyserling H, Kang I; Infectious Diseases Society of America. 2013 IDSA clinical practice guideline for vaccination of the immunocompromised host. Clin Infect Dis. 2014 Feb;58(3):309-18. doi: 10.1093/cid/cit816.
PubMed 24421306Im Y, Kang D, Ko RE, Lee YJ, Lim SY, Park S, Na SJ, Chung CR, Park MH, Oh DK, Lim CM, Suh GY; Korean Sepsis Alliance (KSA) investigators. Time-to-antibiotics and clinical outcomes in patients with sepsis and septic shock: a prospective nationwide multicenter cohort study. Crit Care. 2022 Jan 13;26(1):19. doi: 10.1186/s13054-021-03883-0.
PubMed 35027073Taylor SP, Kowalkowski MA, Skewes S, Chou SH. Real-World Implications of Updated Surviving Sepsis Campaign Antibiotic Timing Recommendations. Crit Care Med. 2024 Jul 1;52(7):1002-1006. doi: 10.1097/CCM.0000000000006240. Epub 2024 Feb 22.
PubMed 38385751Rose N, Matthaus-Kramer C, Schwarzkopf D, Scherag A, Born S, Reinhart K, Fleischmann-Struzek C. Association between sepsis incidence and regional socioeconomic deprivation and health care capacity in Germany - an ecological study. BMC Public Health. 2021 Sep 7;21(1):1636. doi: 10.1186/s12889-021-11629-4.
PubMed 34493250Cornistein W, Santonato D, Novau PA, Fabbro LG, Jorge MF, Malvicini MA, Vilches V, Iudica FM. Synergy between infection control and antimicrobial stewardship programs to control carbapenem-resistant Enterobacterales. Antimicrob Steward Healthc Epidemiol. 2023 Sep 26;3(1):e162. doi: 10.1017/ash.2023.439. eCollection 2023.
PubMed 37771737Kherabi Y, Thy M, Bouzid D, Antcliffe DB, Rawson TM, Peiffer-Smadja N. Machine learning to predict antimicrobial resistance: future applications in clinical practice? Infect Dis Now. 2024 Apr;54(3):104864. doi: 10.1016/j.idnow.2024.104864. Epub 2024 Feb 12.
PubMed 38355048Peiffer-Smadja N, Delliere S, Rodriguez C, Birgand G, Lescure FX, Fourati S, Ruppe E. Machine learning in the clinical microbiology laboratory: has the time come for routine practice? Clin Microbiol Infect. 2020 Oct;26(10):1300-1309. doi: 10.1016/j.cmi.2020.02.006. Epub 2020 Feb 12.
PubMed 32061795Bisarya R, Song X, Salle J, Liu M, Patel A, Simpson SQ. Antibiotic Timing and Progression to Septic Shock Among Patients in the ED With Suspected Infection. Chest. 2022 Jan;161(1):112-120. doi: 10.1016/j.chest.2021.06.029. Epub 2021 Jun 26.
PubMed 34186038Mertz D, Frei R, Periat N, Zimmerli M, Battegay M, Fluckiger U, Widmer AF. Exclusive Staphylococcus aureus throat carriage: at-risk populations. Arch Intern Med. 2009 Jan 26;169(2):172-8. doi: 10.1001/archinternmed.2008.536.
PubMed 19171814Giannella M, Trecarichi EM, De Rosa FG, Del Bono V, Bassetti M, Lewis RE, Losito AR, Corcione S, Saffioti C, Bartoletti M, Maiuro G, Cardellino CS, Tedeschi S, Cauda R, Viscoli C, Viale P, Tumbarello M. Risk factors for carbapenem-resistant Klebsiella pneumoniae bloodstream infection among rectal carriers: a prospective observational multicentre study. Clin Microbiol Infect. 2014 Dec;20(12):1357-62. doi: 10.1111/1469-0691.12747. Epub 2014 Aug 11.
PubMed 24980276Cano A, Gutierrez-Gutierrez B, Machuca I, Torre-Gimenez J, Gracia-Ahufinger I, Natera AM, Perez-Nadales E, Caston JJ, Rodriguez-Bano J, Martinez-Martinez L, Torre-Cisneros J. Association between Timing of Colonization and Risk of Developing Klebsiella pneumoniae Carbapenemase-Producing K. pneumoniae Infection in Hospitalized Patients. Microbiol Spectr. 2022 Apr 27;10(2):e0197021. doi: 10.1128/spectrum.01970-21. Epub 2022 Mar 24.
PubMed 35323035Temkin E, Solter E, Lugassy C, Chen D, Cohen A, Schwaber MJ, Carmeli Y; CPE Working Group. The Natural History of Carbapenemase-Producing Enterobacterales: Progression From Carriage of Various Carbapenemases to Bloodstream Infection. Clin Infect Dis. 2024 Jul 19;79(1):22-29. doi: 10.1093/cid/ciae110.
PubMed 38447961Blagojevic C, Brown KA, Diong C, Fridman DJ, Johnstone J, Langford BJ, Lee SM, MacFadden DR, Schwartz KL, Daneman N. Long-term Risk of Infection Among Patients Colonized With Antimicrobial-Resistant Pathogens: A Population-wide Cohort Study. Open Forum Infect Dis. 2024 Dec 2;11(12):ofae712. doi: 10.1093/ofid/ofae712. eCollection 2024 Dec.
PubMed 39703788Schlebusch S, Graham RMA, Jennison AV, Lassig-Smith MM, Harris PNA, Lipman J, O Cuiv P, Paterson DL. Standard rectal swabs as a surrogate sample for gut microbiome monitoring in intensive care. BMC Microbiol. 2022 Apr 12;22(1):99. doi: 10.1186/s12866-022-02487-0.
PubMed 35413802
Study at a glance
From the registry record, last updated by the sponsor on 11 Sep 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Predictive Model for Multidrug Resistance in Patients Admitted to the Emergency Department With Sepsis
- ClinicalTrials.gov ID
- NCT07167173
- Acronym / sponsor ID
- 7441
- Conditions
- Sepsis, Septic Shock
- Keywords
- Antimicrobial resistance, sepsis, predictive models
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 10,000 participants (estimated)
- Lead sponsor
- Hospital Italiano de Buenos AiresUniversity, hospital or other
- Study start
- 15 Oct 2025 (estimated)
- Primary completion
- 20 Oct 2025 (estimated)
- Study completion
- 31 Oct 2025 (estimated)
- First posted
- 11 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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
Study design
- Observational model
- Other
- Time perspective
- Cross-sectional
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Individuals with sepsis | – | –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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Individuals aged 18 years or older with sepsis.
Key inclusion criteria (6 listed)
- Adults aged 18 years or older.
- Attended at the Adult Emergency Department of Hospital Italiano de Buenos Aires during the periods:
- Sepsis or septic shock at presentation and at least 48 hours of observation or hospital admission.
- Bacterial cultures obtained during the initial evaluation.
Key exclusion criteria (3 listed)
- No indication for antibiotic therapy within the first 48 hours of hospital admission.
- No bacterial cultures performed within the first 48 hours of hospital admission.
- SARS-CoV-2 infection diagnosed within the first 72 hours of hospital admission.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Proportion of episodes with multidrug-resistant organisms (MDRO)
Time frame: Baseline (within the first 48 hours of admission)
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
7 secondary outcomes
Culture positivity
Time frame: Baseline
Bacterial species (Number of Participants with each microorganism species)
Time frame: Baseline
Enzymatic resistance mechanisms (Number of Participants with each enzymatic mechanism detected)
Time frame: Baseline
Carbapenemase genotypes (Number of participants with each genotypic resistance mechanism -KPC, NDM, VIM, OXA-48, IMP- detected by multiplex PCR assay)
Time frame: Baseline
Proportion of episodes with MDR organisms
Time frame: Baseline
Proportion of episodes with XDR organisms
Time frame: Baseline
Proportion of episodes with PDR organisms
Time frame: Baseline
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 11 Sep 2025.
- Background: PubMed 33355350Jung K, Kashyap S, Avati A, Harman S, Shaw H, Li R, Smith M, Shum K, Javitz J, Vetteth Y, Seto T, Bagley SC, Shah NH. A framework for making predictive models useful in practice. J Am Med Inform Assoc. 2021 Jun 12;28(6):1149-1158. doi: 10.1093/jamia/ocaa318.
- Background: PubMed 24421306Rubin LG, Levin MJ, Ljungman P, Davies EG, Avery R, Tomblyn M, Bousvaros A, Dhanireddy S, Sung L, Keyserling H, Kang I; Infectious Diseases Society of America. 2013 IDSA clinical practice guideline for vaccination of the immunocompromised host. Clin Infect Dis. 2014 Feb;58(3):309-18. doi: 10.1093/cid/cit816.
- Background: PubMed 35027073Im Y, Kang D, Ko RE, Lee YJ, Lim SY, Park S, Na SJ, Chung CR, Park MH, Oh DK, Lim CM, Suh GY; Korean Sepsis Alliance (KSA) investigators. Time-to-antibiotics and clinical outcomes in patients with sepsis and septic shock: a prospective nationwide multicenter cohort study. Crit Care. 2022 Jan 13;26(1):19. doi: 10.1186/s13054-021-03883-0.
- Background: PubMed 38385751Taylor SP, Kowalkowski MA, Skewes S, Chou SH. Real-World Implications of Updated Surviving Sepsis Campaign Antibiotic Timing Recommendations. Crit Care Med. 2024 Jul 1;52(7):1002-1006. doi: 10.1097/CCM.0000000000006240. Epub 2024 Feb 22.
- Background: PubMed 34493250Rose N, Matthaus-Kramer C, Schwarzkopf D, Scherag A, Born S, Reinhart K, Fleischmann-Struzek C. Association between sepsis incidence and regional socioeconomic deprivation and health care capacity in Germany - an ecological study. BMC Public Health. 2021 Sep 7;21(1):1636. doi: 10.1186/s12889-021-11629-4.
- Background: PubMed 37771737Cornistein W, Santonato D, Novau PA, Fabbro LG, Jorge MF, Malvicini MA, Vilches V, Iudica FM. Synergy between infection control and antimicrobial stewardship programs to control carbapenem-resistant Enterobacterales. Antimicrob Steward Healthc Epidemiol. 2023 Sep 26;3(1):e162. doi: 10.1017/ash.2023.439. eCollection 2023.
- Background: PubMed 38355048Kherabi Y, Thy M, Bouzid D, Antcliffe DB, Rawson TM, Peiffer-Smadja N. Machine learning to predict antimicrobial resistance: future applications in clinical practice? Infect Dis Now. 2024 Apr;54(3):104864. doi: 10.1016/j.idnow.2024.104864. Epub 2024 Feb 12.
- Background: PubMed 32061795Peiffer-Smadja N, Delliere S, Rodriguez C, Birgand G, Lescure FX, Fourati S, Ruppe E. Machine learning in the clinical microbiology laboratory: has the time come for routine practice? Clin Microbiol Infect. 2020 Oct;26(10):1300-1309. doi: 10.1016/j.cmi.2020.02.006. Epub 2020 Feb 12.
- Background: PubMed 34186038Bisarya R, Song X, Salle J, Liu M, Patel A, Simpson SQ. Antibiotic Timing and Progression to Septic Shock Among Patients in the ED With Suspected Infection. Chest. 2022 Jan;161(1):112-120. doi: 10.1016/j.chest.2021.06.029. Epub 2021 Jun 26.
- Background: PubMed 19171814Mertz D, Frei R, Periat N, Zimmerli M, Battegay M, Fluckiger U, Widmer AF. Exclusive Staphylococcus aureus throat carriage: at-risk populations. Arch Intern Med. 2009 Jan 26;169(2):172-8. doi: 10.1001/archinternmed.2008.536.
- Background: PubMed 24980276Giannella M, Trecarichi EM, De Rosa FG, Del Bono V, Bassetti M, Lewis RE, Losito AR, Corcione S, Saffioti C, Bartoletti M, Maiuro G, Cardellino CS, Tedeschi S, Cauda R, Viscoli C, Viale P, Tumbarello M. Risk factors for carbapenem-resistant Klebsiella pneumoniae bloodstream infection among rectal carriers: a prospective observational multicentre study. Clin Microbiol Infect. 2014 Dec;20(12):1357-62. doi: 10.1111/1469-0691.12747. Epub 2014 Aug 11.
- Background: PubMed 35323035Cano A, Gutierrez-Gutierrez B, Machuca I, Torre-Gimenez J, Gracia-Ahufinger I, Natera AM, Perez-Nadales E, Caston JJ, Rodriguez-Bano J, Martinez-Martinez L, Torre-Cisneros J. Association between Timing of Colonization and Risk of Developing Klebsiella pneumoniae Carbapenemase-Producing K. pneumoniae Infection in Hospitalized Patients. Microbiol Spectr. 2022 Apr 27;10(2):e0197021. doi: 10.1128/spectrum.01970-21. Epub 2022 Mar 24.
- One Health. \[cited 22 Mar 2025\]. Available: https://www.who.int/europe/initiatives/one-healthLink provided by the sponsor.
- References \& Sources. In: The UK Sepsis Trust \[Internet\]. 9 Aug 2024 \[cited 9 Mar 2025\]. Available: https://sepsistrust.org/about-sepsis/references-sources/Link provided by the sponsor.
- Surviving Sepsis Campaign. In: Society of Critical Care Medicine (SCCM) \[Internet\]. \[cited 6 Apr 2025\]. Available: https://www.sccm.org/survivingsepsiscampaignLink provided by the sponsor.
- Global antimicrobial resistance and use surveillance system (GLASS) report: 2022. World Health Organization; 9 Dec 2022 \[cited 3 Oct 2023\]. Available: https://www.who.int/publications/i/item/9789240062702Link provided by the sponsor.
- Bastin MT, Rech M, Betthauser K, Heavner M, Horng M, King T, et al. 1206: Beta-lactam dosing in patients with sepsis and Aki: A multicenter observational study. Crit Care Med. 2023;51: 601-601.Link provided by the sponsor.
- Surveillance of antimicrobial resistance in Europe 2017. In: European Centre for Disease Prevention and Control \[Internet\]. 15 Nov 2018 \[cited 3 Oct 2023\]. Available: https://www.ecdc.europa.eu/en/publications-data/surveillance-antimicrobial-resistance-eLink provided by the sponsor.
- Individual participant dataSharing planned: No. Not possible due to confidentiality and legal restrictions.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Emilio Felipe Huaier Arriazu, MD contact
Emilio Felipe H Huaier Arriazu, MD principal investigator
Hospital Italiano de Buenos Aires
Questions about this trial
What is this clinical trial studying?
An observational study of Sepsis and Septic Shock, run by Hospital Italiano de Buenos Aires.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 11 Sep 2025. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Emilio Felipe Huaier Arriazu, MD (+5491149590200 ext. 8165 / 9542, emilio.huaier@hospitalitaliano.org.ar), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Proportion of episodes with multidrug-resistant organisms (MDRO) (time frame: Baseline (within the first 48 hours of admission)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07167173, which also lists 83 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 11 Sep 2025.