Antimicrobial Resistance (AMR) in bacterial pathogens poses a global challenge, contributing to elevated morbidity and mortality rates. The emergence of Multidrug-Resistant (MDR) patterns in both Gram-positive and negative bacteria has led to infections that are challenging to treat and, in some cases, they may even be untreatable with conventional antimicrobials. The alarming rise in emerging resistance, coupled with inadequate infection control practices, facilitates the spread of resistant bacteria among patients and the environment (Frieriet al., 2017). Hence, getting access to up-to-date epidemiological data on antimicrobial resistance in commonly encountered bacterial pathogen is valuable not only for determining treatment strategies but also for establishing effective AMSPs in hospitals (Akova, 2016).

The fundamental principle of AMSP involves establishing empiric antibiotic recommendations for commonly encountered infections, with antibiograms serving as a crucial tool for providing therapy guidance (Klinkeret al., 2020). The hospital or traditional antibiogram is a periodic summary of the antimicrobial susceptibilities of local bacterial isolates submitted to the hospital’s clinical microbiology laboratory. It is often used by clinicians to access local susceptibility rates as an aid in selecting empiric antibiotic therapy and in monitoring resistance trends over time within an institution (Truonget al., 2021). While most institutions rely on TA, recognizing the importance of integrating SA into clinical decisions enhances the effectiveness of empiric antibiotic therapy (Klinkeret al., 2021).

Despite the TA reflecting local resistance patterns, there are several limitations, including (a) the absence of syndromic-specific recommendations; (b) typically lacking information on organism distribution for a specific infection; (c) limited utility for infections caused by two or more pathogens; and (d) being constructed using historical data that may not necessarily reflect current susceptibility data (Cooket al., 2021). Appropriate empiric therapy is thought to be an important factor in improving clinical outcomes. To improve antibiotic treatment, prescribing must be based partly on infection epidemiology. The antibiogram has now evolved in complexity and utility from its traditional version into more modern forms, now capable of providing more accurate and useful information about antimicrobial susceptibility (Klinkeret al., 2022).

To guarantee patients receive the right empiric antibiotic treatment based on the suspected infection site, hospital location and patient characteristics, AMSPs need to extend their approach beyond TA. By collaborating with clinical microbiologists, AMSPs can effectively develop more advanced antibiograms to enhance the optimization of empiric antibiotic therapy (Klinkeret al., 2021). Hence, the present study aims to compare the susceptibility rate of traditional versus syndromic antibiogram to optimize empiric antibiotic therapy. The development of an infection-specific antibiogram increases the likelihood of appropriate antibiotic coverage before the organism is identified in culture. Additionally, it is useful for the surveillance of antibiotic resistance in hospital settings.

This cross-sectional study was conducted over 6 months in a tertiary care hospital in Chennai. The study protocol was approved by the Institutional Human Ethics Committee (Ethical Clearance No.: IEC/2023/016) and the research was performed in conformance with the Helsinki Declaration.

This study included patients aged 18 and above with positive bacterial culture reports for Urinary Tract Infection (UTI), Respiratory Tract Infection (RTI) and Bloodstream Infection (BSI) associated with common pathogens such as Escherichia coli (E. coli), streptococci and Salmonella typhi. This study excluded patients with negative culture reports and positive culture reports of organisms other than the above-mentioned organisms. Based on the inclusion criteria, 400 samples were included in this study.

A data collection form was designed to record patient data like age, gender, IP no., OP no., patient location, diagnosis, sample collected, results of the culture report with antibiotic sensitivity and resistance pattern. To analyze the antibiotic susceptibility of the most common pathogens associated with UTI, RTI and BSI, SAs were developed and compared with TA. The TA included the three most common pathogens from all sources, while the SA considered the three most common pathogens from a specific source and patient location.

Clinical laboratory and Standard Institute guidelines, institutional protocols and hospital formulary were taken into consideration while choosing antibiotics. Antibiotics included in the analysis were chosen based on their availability and accessibility within the healthcare setting where the study was conducted.

The collected data were analyzed using SPSS version 23 (SPSS Inc., Chicago, IL, USA). A chi-square test was used to compare the antibiotic susceptibility rate between TA and SA. A p-value <0.05 was considered statistically significant at a 5% level of significance to the confidence interval of 95%.

A total of 400 bacterial isolates were examined, which consisted of 233 urinary isolates, 58 respiratory isolates and 59 blood isolates. The three most frequently identified organisms were E. coli, Streptococci and Salmonella typhi. We compared the cumulative susceptibilities of these bacteria using both TA and SA as shown in Tables 1–3 respectively. Antibiotic susceptibility for the above three bacteria based on patient location were represented in Figures 1–3.

Figure 1:
Antibiotic Susceptibility for E. coli based on Patient Location.

Figure 2:
Antibiotics Susceptibility for Streptococci species based on Patient Location.

Figure 3:
Antibiotics Susceptibility for Salmonella typhi based on Patient Location.

Table 1 illustrates that a statistically significant difference was found in the susceptibility rate for FOSFO, AMIK and NIT between TA and SA.

Table 2 illustrates that a statistically significant difference was found in the susceptibility rate for AMP and DOX between TA and SA.

Table 3 illustrates that no statistically significant difference was found in the susceptibility rate between TA and SA.

Infectious diseases are controlled and cured with antimicrobial agents. Antibiotics pose different actions against microorganisms such as bacteriostatic and bactericidal mechanisms. The problem of antibiotic resistance emerged shortly after the discovery of antibiotics. Comprehending the pattern of resistance is important before continuing the use of current antibiotics (Abushaheenet al., 2020). Though antibiotic resistance is a global health threat, India is one among other countries with high per-capita antibiotic consumption. Antimicrobial resistance claimed the lives of 1.27 million individuals across the globe in 2019. By 2050, it is predicted that Asia will experience 4.7 million deaths by antimicrobial resistance (Farooquiet al., 2018).

Utilizing broad spectrum antibiotics as the first line of treatment is effective in targeting the common organisms believed to be responsible for the infection until the results of the culture test are available. Once the antibiotic susceptibility data are available and the etiologic pathogen has been identified, empiric therapy should be tailored to a definitive regimen (Altafet al., 2023). This may ultimately decrease the incidence of antibiotic resistance. Many bacterial infections persist, with UTI, RTI and BSI being frequently reported. UTIs are the predominant bacterial infection that is faced universally, regardless of age, gender, or location.

Furthermore, among certain groups such as pregnant women, UTIs enhance the risk of preterm delivery and miscarriage (Oliet al., 2017). As a result, there is an increase in the frequency of prescribing intrapartum antibiotics prophylactically (Patangiaet al., 2022). Therefore, the careful selection of antibiotics improves the susceptibility rate.

Besides UTI, another significant factor contributing to the frequent use of antibiotics in adults is RTI (Huang et al., 2022). The etiologic agent for RTI varies regionally, resulting in antibiotic susceptibility variation. This phenomenon results in increased consumption of over-the-counter antibiotics which directly paves the way for antibiotic resistance. BSIs impact about 30 million people, either through the invasion of bacteria into the blood or the spread of infection from other areas of the body. The advanced stage of BSI ends up with sepsis that requires proper medical attention and appropriate antibiotic therapy to lower mortality rate (Nestoret al., 2021). Thus, monitoring the etiologic agent and their resistance pattern in BSI is very essential. Hence, the development of disease-specific antibiograms can be instrumental for hospitals seeking to develop antibiotic preservation programs like restricted antibiotic formularies (Al-Dahiret al., 2015).

This study mainly focusing on effective strategies to develop SA for three common disease specific pathogens that have been compared with the susceptibility rate of TA. Cumulative susceptibilities for E. coli, streptococci and salmonella were compared between TA and SA. E. coli showed a significant difference in susceptibilities for fosfomycin, amikacin and nitrofurantoin (p=0.007, <0.001, 0.464). A Study conducted by (Gardineret al., 2019), shows that nitrofurantoin is effective in case of cystitis even during pregnancy (not beyond 38 weeks of gestation) also, many MDR organisms have high susceptibility towards nitrofurantoin and development of resistance is very rare. They also say that, uniqueness in the structure of fosfomycin aids in minimizing the cross-resistance with other antibiotics. Hence, many MDR isolates retain their susceptibilities to fosfomycin (Gardineret al., 2019). Nowadays cases of UTI caused by ESBL-EC are increasing and studies show that amikacin is effective in treating it (Cho et al., 2015). There is a constant change in UTI antibiogram due to empiric antibiotic overuse (Oliet al., 2017).

Streptococci showed a significant difference in susceptibilities for ampicillin and doxycycline (p=0.0279 and 0.0010). Studies reveal that ampicillin provides effective treatment for RTI when the etiological agent is S. pneumoniae (Cillonizet al., 2018). The main aim of developing ampicillin was to prevail over certain drawbacks of penicillins such as broad-spectrum coverage and development of resistance (Majhiet al., 2014). The Infectious Diseases Society of America suggests doxycycline as an alternative drug for penicillin allergic patients. (Dallaset al., 2013), compared tetracycline with doxycycline and reported that, while considering MIC values doxycycline is more effective than tetracycline.

Overall, our study revealed that TA showed lower susceptibilities for E. coli and Streptococci when compared to SA. The variability in susceptibility rate may be due to the inclusion of isolates from all the samples in TA (Klinkeret al., 2020) in contrast to SA which included samples only from urine and respiratory samples.

But in case of salmonella, no significant difference was seen between TA and SA, as in our study salmonella was present only in blood samples. Thus, TA may misguide the clinician, as it does not accurately reflect the susceptibility rate of antibiotics. Hence, there is a need for developing infection specific antibiograms to ensure that the patient receives appropriate empiric antibiotic therapy based on the suspected site of infection and the etiologic agent (Klinkeret al., 2021).

According to our research findings, it is evident that TA does not accurately reflect the susceptibility rate of antibiotics when compared to SA. The research clearly demonstrates the disparities in susceptibility rates of isolated microorganisms between a syndromic and traditional antibiogram. These differences are crucial, not only for selecting most effective empirical antimicrobial therapy for a patient but also helps in monitoring the resistance pattern of antibiotics to certain organisms within a healthcare setting. Therefore, we suggest integrating syndrome-specific susceptibility data in an institution’s antibiogram to enhance guidance for clinicians in choosing appropriate empiric therapy for individual patients.

The authors express their gratitude to the Management of C.L. Baid Metha College of Pharmacy for their encouragement, support, guidance and facility for the research work.