Antibiograms

An antibiogram is a laboratory summary report that shows the susceptibility of bacterial isolates to different antimicrobial agents. It is a critical tool in clinical microbiology and public health, helping guide effective antibiotic therapy, monitor resistance trends, and develop antimicrobial stewardship strategies. Antibiograms are compiled from cumulative microbiological testing data within a specific healthcare setting, such as a hospital, region, or community, and are updated periodically — typically on an annual basis.

Background and Purpose

The concept of the antibiogram arose alongside the development of antimicrobial susceptibility testing (AST), which determines how sensitive or resistant bacteria are to specific antibiotics. With the global rise of antimicrobial resistance (AMR), the systematic organisation of susceptibility data has become essential for guiding clinicians in the rational use of antibiotics.
An antibiogram serves several key purposes:

• To assist clinicians in selecting empiric antibiotic therapy before laboratory confirmation of pathogens.
• To track local, regional, and national resistance patterns.
• To evaluate infection control and antibiotic stewardship interventions.
• To inform hospital formularies and policy decisions regarding antimicrobial use.

By summarising the effectiveness of various antibiotics against common pathogens, antibiograms play a vital role in optimising treatment and slowing the spread of resistant bacteria.

Preparation and Methodology

Antibiograms are produced by clinical microbiology laboratories following standardised procedures established by organisations such as the Clinical and Laboratory Standards Institute (CLSI) and the European Committee on Antimicrobial Susceptibility Testing (EUCAST).
The preparation process involves several key steps:

1. Data Collection: All bacterial isolates obtained from patient samples (e.g., blood, urine, sputum, wound swabs) over a defined period are included.
2. Susceptibility Testing: Each isolate undergoes antimicrobial susceptibility testing using methods such as:
   • Disk diffusion (Kirby–Bauer method)
   • Broth microdilution
   • E-test (gradient diffusion method)
   • Automated systems (e.g., VITEK, MicroScan)
3. Data Compilation: Results are expressed as susceptible (S), intermediate (I), or resistant (R) for each antibiotic tested.
4. Statistical Aggregation: The data are aggregated by bacterial species and antibiotic type. Only the first isolate per patient per infection episode is typically included to avoid bias from duplicate samples.
5. Formatting and Reporting: Results are presented in tabular form, showing the percentage of isolates susceptible to each antibiotic.

For example:

This summary allows clinicians to visualise resistance trends rapidly and make informed empirical therapy decisions.

Types of Antibiograms

Antibiograms can vary based on their purpose and data source. The main types include:

• Cumulative (Institutional) Antibiogram: A hospital-wide summary that aggregates data from all clinical isolates over a defined period, typically one year.
• Unit-Specific Antibiogram: Focused on a particular ward or unit (e.g., intensive care, paediatrics) to capture unique microbial and resistance profiles.
• Pathogen-Specific Antibiogram: Concentrates on one bacterial species, providing detailed resistance trends across various antibiotics.
• Syndromic or Site-Specific Antibiogram: Based on infections from specific body sites (e.g., urinary tract, bloodstream).
• Regional or National Antibiogram: Compiles data from multiple institutions to monitor broader epidemiological trends in antimicrobial resistance.

Clinical Applications

Antibiograms play an essential role in clinical decision-making, particularly in empiric antibiotic therapy — the initial treatment given before culture results are available. For example:

• If the local antibiogram shows E. coli resistance to ampicillin exceeding 40%, clinicians might select an alternative agent such as ceftriaxone or nitrofurantoin for urinary tract infections.
• In intensive care settings, antibiograms help determine empiric regimens for severe infections caused by multidrug-resistant organisms (MDROs).
• They also aid in identifying emerging resistance mechanisms, such as extended-spectrum β-lactamases (ESBLs) or carbapenemases.

Moreover, antibiograms support infection control measures, guiding isolation policies and antimicrobial stewardship interventions to prevent resistance spread.

Antimicrobial Stewardship and Public Health Use

In the broader healthcare context, antibiograms are central to antimicrobial stewardship programmes (ASPs), which aim to promote the judicious use of antibiotics. By providing data-driven insights, antibiograms help:

• Identify inappropriate antibiotic prescribing patterns.
• Monitor resistance trends over time.
• Evaluate the impact of stewardship interventions.
• Assist in revising empirical therapy guidelines and hospital formularies.

Public health agencies, including the World Health Organization (WHO) and the Centers for Disease Control and Prevention (CDC), utilise aggregated antibiogram data to inform regional and national AMR surveillance systems, such as the Global Antimicrobial Resistance and Use Surveillance System (GLASS).

Interpretation and Limitations

While antibiograms are invaluable, their interpretation requires caution and understanding of their limitations:

• Population-Level Data: Antibiograms represent aggregate trends and may not predict individual patient outcomes.
• Sample Bias: They depend on the types of samples submitted and may over-represent hospital-acquired infections.
• Temporal Variability: Resistance patterns can shift rapidly; annual updates are essential for accuracy.
• Incomplete Coverage: Some antibiotics may not be tested uniformly across all isolates or laboratories.
• Limited Utility for Polymicrobial Infections: They focus on single-organism susceptibility, which may not apply to complex, mixed infections.

Clinicians must therefore integrate antibiogram data with clinical judgement, patient history, and local epidemiology when choosing empiric therapy.

Advanced and Personalised Antibiograms

With advances in computational biology and data analytics, newer forms of antibiograms are emerging:

• Electronic and Interactive Antibiograms: Digital platforms that allow dynamic data visualisation and filtering by unit, organism, or specimen type.
• Genotypic Antibiograms: Incorporate molecular testing for specific resistance genes or mutations.
• Predictive Modelling: Machine learning algorithms are increasingly being used to forecast resistance trends based on historical data and antibiotic usage patterns.
• Patient-Centric Approaches: Integration with electronic health records (EHRs) enables personalised antimicrobial recommendations tailored to the patient’s clinical context and infection history.

These innovations are enhancing the precision and clinical relevance of antibiogram-based decision support.

Global Significance

Antibiograms contribute significantly to the global effort to combat antimicrobial resistance — one of the most pressing public health threats of the 21st century. By providing reliable, localised resistance data, they enable early detection of emerging resistant strains, such as methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), and carbapenem-resistant Enterobacterales (CRE).
Their integration into surveillance networks and stewardship programmes is crucial for developing national and international policies on antibiotic use, infection control, and research priorities.