Epidemiology of Antimicrobial-use and Antimicrobial-resistant Infections in Four Hospitals in Thailand
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Drug Resistance, Bacterial, Bacteremia. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Thailand
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
The main goal of this retrospective observational study is to understand how stepping down antibiotic treatment (called antibiotic de-escalation) affects patients who receive it compared to those who don't after received a short-course (≤7 days) of parenteral antibiotics. The investigators will use past medical records from four public referral hospitals in Thailand from the year 2019 to 2024. The investigators will firstly evaluate which types of patients are more likely to receive antibiotic de-escalation. Then, the investigators will estimate the impact of antibiotic de-escalation, while taking those differences into account. This way, it will help us understand the impact of antibiotic de-escalation in real-world clinical practice. The investigators also aim to assess how accurate automated outbreak detection systems are at detecting outbreaks, evaluate patterns of antimicrobial use and antimicrobial-resistant infections, and develop new indicators for antimicrobial stewardship that are applicable for local and national actions in low and middle-income countries.
Detailed description
Rationale:
Despite the availability of guidance documents for implementing antimicrobial stewardship (AMS) programs at both hospital and national levels, there is a lack of robust data to monitor and evaluate the current antimicrobial use practice in low and middle-income countries (LMICs). Evidence on the impact of antibiotic de-escalation on antimicrobial-resistant (AMR) infection is limited. In addition, practical guidelines on how to utilize and analyze routine data for LMICs have not been established.
Objective:
In this study, our primary objective is (a) to evaluate impact of antibiotic de-escalation. Our secondary objectives are (b) to estimate accuracy of automated outbreak detection systems, (c) to evaluate epidemiology of antimicrobial use (AMU) and AMR infections and associations between AMU and AMR infections, and (d) to develop AMS outcome indicators that are applicable for local and national actions in low and middle-income countries (LMICs)
Methodology:
The investigators will conduct a retrospective data analysis using individual-level electronic databases of hospital admission, ward transfer, microbiology laboratory and drug dispensing from four hospitals (including Chiangrai Prachanukroh Hospital, Chiangrai; Sunpasitthiprasong Hospital, Ubon Ratchathani; Phrachomklao Hospital, Phetchaburi; and Chaoprayayommarat Hospital, Suphanburi) from January 2019 to December 2024 in Thailand.
The hospital admission data collected will include hospital number (HN) and admission number (AN), sex, age, admission wards, admission dates, discharge dates, discharge outcomes (discharge type and discharge status) and ICD-10. The ward transfer data collected will include HN, AN, ward, data transfer in and date transfer out. The microbiology laboratory data collected will include HN, AN, ward, specimen type, specimen collection date, report dates, culture results and antimicrobial susceptibility results. The drug dispensing data collected will include, HN, AN, drug name, drug code, route of drug administration, the dosage regimen, drug start dates, drug stop dates, wards and departments of prescribing physicians. The HN and AN will be used to link the three databases together. The ward data will also be used to evaluate the cluster of AMR infection. The department of prescribing physicians will be used to understand AMS and antimicrobial use (AMU) by department because multiple wards are mixed wards (i.e. having patients from multiple departments in the same wards). Infection and Prevention Control (IPC) team's records of cluster will be used to evaluate the accuracy of automated outbreak detection systems. All data will be protected at the highest security.
Inverse Probability of Treatment Weighting (IPTW) will be used to evaluate impact of antibiotic de-escalation on new AMR BSI. Descriptive analysis and regression models will also be used.
Outcomes:
In this study, our primary outcomes are (a1) the relative risk of new AMR BSI in patients who receive antibiotic de-escalation compared to those who do not after a short-course (≤7 days) of parenteral antibiotics, and (a2) the relative risk of in-hospital 30-day mortality. Our secondary outcomes include (b) the accuracy of automated outbreak detection systems, (c) factors associated with AMU and AMR infections, and (d) factors associated with new AMS outcome indicators.
Findings of this study, particularly impact of antibiotic de-escalation on new AMR BSI and new AMS outcome indicators will be used to expand AutoMated tool for Antimicrobial resistance Surveillance System (AMASS) with AMS modules (i.e. AMASS version 4.0), under collaboration with the Ministry of Public Health Thailand. The investigators anticipate that findings of this study will support the monitoring and evaluation of AMS practice at both hospital and national levels in Thailand and other LMICs in the future.
Primary outcome measures
- New antimicrobial-resistant bloodstream infection [Time frame: 6 years]
- In-hospital 30-day mortality [Time frame: 6 years]
Secondary outcome measures (8)
- Sensitivity of automated outbreak detection systems [Time frame: 5 years, from 2020 to 2024]
- Specificity of automated outbreak detection systems [Time frame: 5 years, from 2020 to 2024]
- Positive predictive value (PPV) of automated outbreak detection systems [Time frame: 5 years, from 2020 to 2024]
- Negative predictive value (NPV) of automated outbreak detection systems [Time frame: 5 years, from 2020 to 2024]
- Day of therapy (DOT) per 1,000 bed-days [Time frame: 6 years]
- Length of therapy (LOT) per 1,000 bed-days [Time frame: 6 years]
- Frequency of antimicrobial resistance bloodstream infection [Time frame: 6 years]
- Utility of new AMS indicators [Time frame: 6 years]
Eligibility criteria
For primary objectives Inclusion Criteria
- All age and gender
- Admitted to four collaborating hospitals from 1 Jan 2019 to 31 Dec 2024
- Received a parenteral antibiotic for at least four consecutive days
- Were still hospitalized on day 8 after starting a parenteral antibiotic
Exclusion criteria
- Admitted as day admissions to four collaborating hospitals from 1 Jan 2019 to 31 Dec 2024
- Had a clinical specimen collected within 2 calendar days of starting a parenteral antibiotic culture positive for an antimicrobial-resistant organism or Staphylococcus aureus
Antimicrobial-resistant (AMR) organism is defined as an organism that is resistant to Access and Low Watch antibiotics, and if the organism is the cause of infection, the recommended antimicrobial therapy involves the use of Medium Watch, High Watch or Reserve antibiotics. The common organisms include methicillin-resistant S. aureus, methicillin-resistant coagulase-negative Staphylococcus spp., ampicillin-resistant Enterococcus spp., vancomycin-resistant Enterococcus spp., 3rd-generation cephalosporin-resistant Gram-negative bacterium and carbapenem-resistant Gram-negative bacterium. The definition of organism includes organisms frequently associated with contamination including coagulase-negative staphylococci, viridans group streptococci, Corynebacterium spp., Bacillus spp., Diptheroid spp., Micrococcus spp. and Propionibacterium spp.. All types of specimens are included (e.g. sputum and tracheal suction). We excluded such patients because the study has no clinical data to differentiate whether the isolated AMR organisms are causing infections or represent colonization.
For secondary objectives
Inclusion criteria
- All age and gender
- Admitted to four collaborating hospitals from 1 Jan 2019 to 31 Dec 2024
Exclusion criteria
- Admitted as day admissions to four collaborating hospitals from 1 Jan 2019 to 31 Dec 2024
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Other
Study locations
Thailand · 4 centers
- Chiangrai Prachanukroh Hospital — Chiang Rai
- Phrachomklao Hospital — Phetchaburi
- Chaoprayayommarat Hospital — Suphan Buri
- Sunpasitthiprasong Hospital — Ubon Ratchathani
Identifiers
NCT: NCT07082465 · Micro2501