Antibiogram Analysis of Pathogen Prevalence and Antimicrobial Susceptibility Patterns in A Tertiary Care Hospital

V. Keerthi Bhavana, Sandra Eleena Grace, Rida Muskaan, Tejaswi Vummarao, Dr. Sanjeev Kumar Rao,

doi:10.5281/zenodo.15336638

Research Paper | Open Access
Volume 03 | Issue 05 | Article Id IJPS/250304502

Antibiogram Analysis of Pathogen Prevalence and Antimicrobial Susceptibility Patterns in A Tertiary Care Hospital
V. Keerthi Bhavana* Sandra Eleena Grace Rida Muskaan Tejaswi Vummarao Dr. Sanjeev Kumar Rao
Malla Reddy College of Pharmacy, Maisammaguda, Hyderabad, Telangana, India- 500100.

Abstract

Background Information-Antibiograms are reports that summarize bacterial antibiotic susceptibility rates across different departments within a healthcare facility. By outlining bacterial susceptibility patterns to various antibiotics, they provide valuable insights for clinicians in selecting appropriate empiric antibiotic therapy. Culture sensitivity testing, which involves culturing bacteria and assessing their response to different antibiotics, is a crucial component of antibiogram development. Antibiograms help in guiding monitoring resistance trends and promote rational antibiotic use. They can help to reduce the overuse of broad-spectrum antibiotics, which can contribute to the development of resistant organisms. Early appropriate therapy is crucial to minimize morbidity and complications. Materials And Methods- A descriptive research approach with an observational study design was used for this study with culture sensitivity test information obtained from 281 patients. The results were analysed to determine pathogen presence and antibiotic susceptibility using various statistical analysis tools. This involved the careful examination of factors such as the types of pathogens identified, their frequency of occurrence, and their resistance patterns to different classes of antibiotics. Results-The results revealed high resistance to Ampicillin followed by Cefuroxime in the general medicine department, while Meropenem followed by Imipenem demonstrated the highest number of specimens obtained from the general medicine department. E.coli was the predominant pathogen, followed by Klebsiella and Pseudomonas. A survey among patients revealed inadequate knowledge of antibiotic use, with many patients self-medicating and not completing the prescribed course. These findings highlight the urgent need for improved antimicrobial stewardship and patient education to address the growing threat of antibiotic resistance. Conclusion-In conclusion, this study successfully assesses pathogen prevalence and antibiotic susceptibility in a tertiary care hospital. The Findings revealed high resistance to common antibiotics, particularly ampicillin and cefuroxime, indicating the need for effective antimicrobial stewardship. E. coli was a dominant pathogen, highlighting the importance of infection control practices. The study also underscored the need for patient education regarding antibiotic use to prevent the spread of resistant microorganisms.

Keywords

Antibiogram; Antibiotic Susceptibility; Pathogen Prevalence; Culture Sensitivity Testing

Introduction

In hospitals of broad-spectrum antibiotics are widely used, the growing problem of antimicrobial resistance poses a major challenge to the healthcare system worldwide [1]. Antibiotics are frequently prescribed in health care settings for the illness caused by a diverse range of bacteria[2]. However, the emergence of resistant strains may decrease the effectiveness of the treatment. To identify the appropriate medication and develop effective strategies for infection control, it is important to understand which bacteria are common along with their response to various antibiotics in use[3]. Detailed profiles known as antibiograms are used to demonstrate the effectiveness of antibiotics against the isolated bacteria. In a hospital setting, these profiles are vital for monitoring the resistance trends [3] . By providing current information on local resistance patterns, they assist physicians in making well-informed decisions, thereby improving patient outcomes while minimizing therapeutic failures[4]. Antibiograms can play an important role in slowing down the rapid spread of resistance in pathogens and encouraging rational use of drugs, decreasing the use of broad-spectrum antibiotics as empirical therapy, minimizing polypharmacy, and facilitating the formulation of future antibiotic policies [2] . Considering the important consequences of antimicrobial resistance and antimicrobial stewardship this study has the potential to provide insightful information about ongoing efforts to fight infections in tertiary care hospitals[3]. The patterns of microbial pathogens and their antibiotic sensitivity may change over time and geographic location[5]. This prospective study intends to outline the frequency of different pathogens and their respective patterns in antimicrobial resistance and susceptibility through an extensive antibiogram analysis at a tertiary care hospital. Additionally, it aims to address the critical need for localized data on pathogen profiles and resistance patterns, which is essential for implementing effective infection control measures and enhancing patient care outcomes in spite of the constantly evolving microbial challenges [6].

METHODS AND MATERIALS

The study was conducted for a period of 6 months at the Department of Microbiology, in Malla Reddy Hospital located in Hyderabad, Telangana. This is a tertiary care setting offering health care services in all the departments and serves a diverse patient population making it ideal for executing this study. The aim was to investigate the antibiogram of different infections and understand the resistance trends in tertiary care facilities. The study period ensured the analysis encompassed a large range of microbial susceptibility and resistance trends. The sample size for this study consisted of 281 patients facilitating an analysis across multiple demographic groups and is structured as a prospective observational study. The inclusion criteria comprised susceptibility reports of the inpatients and outpatients of all genders, covering all types of specimen samples such as blood, urine, pus, sputum, and stools. The reports of the first evaluated specimen from each patient regardless of the body site. The exclusion criteria included reports of isolates with intermediate susceptibility and duplicate bacterial isolates from the same patient. The study procedure was performed by collecting data from the culture sensitivity reports provided by the microbiology department. The reports contained the results of culture sensitivity of blood, urine, sputum, pus, swab, and stool samples. The culture sensitivity testing aimed to test the pathogen presence and their sensitivity towards various antibiotics including penicillin, cephalosporins, tetracyclines, aminoglycosides, and fluoroquinolones. A survey was conducted to understand the patient’s understanding of antibiotic usage. The collected data were organized and represented in an antibiogram.

Preparation of antibiogram: The hospital antibiogram was prepared by plotting the pathogens identified in the hospital and their prevalence in percentage along with the susceptibility towards the antibiotics that are commonly used in the hospital [2,5].

RESULTS

Out of 281 samples collected, 128 showed pathogen presence, with 49 isolates from male subjects and 79 isolates from female subjects. The remaining 153 samples tested negative for pathogen presence, with 59 from males and 94 from females.

Figure .1 Distribution of Pathogens Isolated

The predominant pathogen identified is Escherichia coli with 40 isolates out of 128, followed by Klebsiella and Pseudomonas. Conversely, Candida and Staphylococcus aureus were the least frequently isolated pathogens. E. coli was the most prevalent pathogen across all age groups, with a total of 40 isolates, followed by Klebsiella 21 isolates and Pseudomonas 15 isolates. In contrast, Candida with 4 isolates, Staphylococcus aureus with 1 isolate, and Streptococcus with 4 isolates were significantly less. Coagulase Negative Staphylococcus (CONS), enterococcus, streptococcus, staphylococcus aureus, Methicillin Resistant Staphylococcus Aureus (MRSA), and Methicillin Sensitive Staphylococcus Aureus (MSSA) are other kinds of pathogens found in the health care setting. Ampicillin demonstrated a sensitivity rate of 4.3% and a resistance rate of 21.7%, indicating a relatively high level of resistance among the isolates tested. Meropenem emerged as most sensitive antibiotic, with a sensitivity rate of 25.6%.

Figure.2 Antibiotic Susceptibility Profile

Table.1 Distribution of Specimens Across Departments

Name of the department

No. of specimens obtained	Percentage total
DVL	5	1.8%
EMERGENCY	10	3.6%
ENT	9	3.2%
GENERAL MEDICINE	62	22.1%
GENERAL SURGERY	45	16.1%
GYNAECOLOGY	54	19.2%
ICU	48	17.1%
ORTHOPAEDICS	14	5.0%
PAEDIATRICS	16	5.7%
RESPIRATORY	18	6.4%

In our healthcare facility, the distribution of specimens obtained across different departments is as follows. The Department of General Medicine was the highest contributor of specimens, with 62 samples, constituted 22.1% of the total samples collected. Following behind is the Gynaecology department reported 54 specimens, representing 19.2% of the total. The Intensive Care Unit (ICU) contributed 48 samples, representing 17.1% of the overall samples

Table.2 Distribution of specimen types collected in the laboratory

Specimen Type	Count	Percentage total
PUS	23	8.2%
SPUTUM	60	21.4%
STOOL	4	1.4%
SWAB	54	19.2%
URINE	140	49.8%

The distribution of specimen types and urine samples constitute the majority of collected specimens at 49.8%, indicating a high prevalence of urinary infections among the population. Sputum samples are the second most frequent at 21.4% of the total specimens collected suggesting to focus on potential respiratory tract infections. Swabs represented 19.2% of the total specimens collected and pus samples represented 8.2% of the total specimens. Lastly, stool samples, at 1.4% of the total, suggest a lower incidence of gastrointestinal infections within the population. The highest number of pus specimens were collected from the surgery department, while sputum samples were predominantly collected from the general medicine department followed by the respiratory department. Stool samples were the least commonly collected, with two samples each from the general medicine and ICU departments. The surgery department collected the most swab samples, while urine specimens were predominantly collected for culture sensitivity tests, with the highest number of collections from the gynecology department.

Table.3 Patient Population Breakdown by Age and Gender

Age	Male	Female
0 – 20	23	32
21 – 40	21	93
41 - 86	60	58

The 41 - 86 years had the highest number of isolates, followed by the 21 – 40 age group, while the 0 – 20 age group yielded the lowest number of isolates.

Table.4 Distribution of Isolated Pathogens by Department

PATHOGEN ISOLATED	DVL	EMERGENCY	ENT	GEN-MED	GYNAECOLOGY	ICU	ORTHOPAEDICS	PEDIATRIC	RESPIRATORY	SURGERY	TOTAL
Candida	0	0	0	2	0	2	0	0	0	0	4
Coagulase-Negative Staphylococcus	0	0	0	2	7	1	0	0	0	1	11
Enterococcus	0	0	1	0	1	1	0	1	0	2	6
E Coli	1	1	0	6	7	7	1	3	0	14	40
Klebsiella	1	1	1	2	2	6	2	0	3	3	21
MRSA	0	0	1	0	2	2	1	0	0	5	11
MSSA	0	0	0	4	2	0	1	0	0	2	9
Proteus Vulgaris	0	0	0	1	0	0	0	0	0	2	4
Pseudomonas	0	1	2	3	1	2	0	0	2	4	15
Staphylococcus Aureus	0	0	0	0	0	0	0	0	0	1	1
Streptococcus	0	0	0	0	0	3	0	1	0	0	4
None	3	7	4	42	32	24	9	11	13	10	155
Total	5	10	9	62	54	48	14	16	18	45	281

Pus samples exhibited the highest prevalence of Escherichia coli indicating its contribution to post-surgical infection and abscess formation, while Klebsiella was most commonly isolated from sputum indicating its contribution in respiratory infection. Swab samples showed a predominance of Pseudomonas, Stool specimens were devoid of any pathogen growth. Similarly, E. coli was again the most frequent pathogen isolated from urine.

Figure .3 Hospital Antibiogram – November – April 2024

Figure Legends:

Figure number	Description
Fig 1	Age-Based Pathogen Frequency is displayed in this bar graph. The x-axis represents various microbial pathogens, while the y-axis denotes the number of isolates. Bars are segmented by age group: blue (0-20 years), orange (21-40 years), and grey (41-86 years), with yellow representing the total number of isolates for each pathogen. E. coli and Klebsiella are the most prevalent pathogens overall. Further analysis of age-specific distributions may reveal trends in pathogen prevalence across different age groups.
Fig 2	This stacked bar graph illustrates the percentages of antibiotic sensitivity and resistance. Each bar corresponds to a specific antibiotic, with the blue sections indicating the percentage of sensitive isolates and the orange sections representing resistant ones. Notably, antibiotics like imipenem and meropenem demonstrate high sensitivity, as seen by the predominance of blue. In contrast, ampicillin and several cephalosporins show greater resistance, highlighted by the dominance of orange. This visualization facilitates a quick comparison of the effectiveness of different antibiotics.
Fig 3	This figure displays a hospital antibiogram of the tertiary care setting in which the study was conducted from November 2023 to April 2024, showing antibiotic susceptibility. Rows list antibiotics (e.g., Ampicillin, Amikacin), and columns list bacterial pathogens (e.g., Enterococcus, E. coli). "S" denotes sensitivity, "R" denotes resistance, with green indicating highest sensitivity and red highest resistance. The table reveals varying resistance patterns across pathogens and antibiotics, highlighting potential treatment challenges. "NA" likely indicates "not applicable" or "not tested

DISCUSSION

This study offers important insights into the issue of antimicrobial resistance in healthcare environments, highlighting the urgent need for effective strategies to tackle this public health concern. Through the isolation and identification of the causative agents, assessment of their antibiotic susceptibility, and the creation of a cumulative antibiogram, we have revealed notable resistance patterns that require the attention of health professionals and policymakers. Our analysis showed concerning resistance rates, especially against common antibiotics like Ampicillin and cefuroxime. These results reflect the global trend of rising antimicrobial resistance, which significantly threatens effective treatment options. On the other hand, Meropenem was identified as the most effective antibiotic, followed by Imipenem. The consistent sensitivity to carbapenems in our findings, as well as in studies like that of Pilli Hema Prakash Kumari, highlights their importance as crucial tools in the fight against resistant infections[2]. However, it also raises concerns about their overuse, which could contribute to the development of further resistance. Our demographic analysis showed that most specimens came from the general medicine department, followed by gynecology and the intensive care unit. This specimen distribution is vital for effective infection control and antibiotic management. Additionally, a contrast with earlier studies like Inderpal Kaur's, which highlighted significant collection from pulmonary medicine, indicates the need for local context in analysing resistance patterns[4]. The high number of urine samples indicates a considerable prevalence of urinary infections, which aligns with findings from Kritu Panta et al. This pattern necessitates increased attention to urinary tract infections in clinical environments, where prompt and suitable antibiotic prescribing is essential to prevent the rise of resistance[7]. Our study also highlights Escherichia coli as a common pathogen affecting all age groups, making it the most dominant organism in our microbial profile. In contrast, other pathogens like Candida spp., Staphylococcus aureus, and Streptococcus species were isolated less frequently. This aligns with findings from Kumari and colleagues at the GITAM Institute and Mukherjee et al. from a tertiary care hospital in Western Odisha, which consistently show E. coli prevalence in various clinical environments [2,8]. The prevalence of E. coli aligns with rising antibiotic resistance trends, especially in Gram-negative bacteria, as highlighted in various studies. This situation raises concerns about treatment strategies, particularly given the growing resistance that could hinder patient outcomes. Our findings reveal a significant number of infections among the 21-86 years age group, indicating increased vulnerability in these demographics. This trend may be linked to a mix of lifestyle choices, immune responses, and common comorbidities that raise infection risk. In contrast, the lower percentage of specimens from the 0-20 years age group might reflect reduced susceptibility to certain infections, differences in clinical symptoms in younger individuals, or healthcare-seeking behaviors that lead to fewer samples being collected from this group. A detailed examination of specimen types across medical disciplines provides key insights into the infection landscape at our institution. The Surgery department's notable collection of pus and swab samples emphasizes the need for attentiveness towards surgical site infections (SSIs) and wound-related complications. In General Medicine, a high number of sputum specimens underscores the prevalence of respiratory infections, confirming issues like pneumonia and bronchitis. Gastroenterology, with its limited stool samples, still points to concerns about gastrointestinal infections. In Gynaecology, the large volume of urine specimens highlights the common occurrence of urinary tract infections, necessitating targeted diagnostic and management strategies. The ICU department reflects a diverse range of specimens of stool, sputum, and urine showcasing the complex infections treated in critical care. Our study offers important insights into the demographic and clinical traits of the population, highlighting notable gender differences that affect disease dynamics. Females made up the majority of all age groups, especially in the 21-40 range. Conversely, the highest number of males was found in the older group of 41-86 years. This gender distribution is crucial for understanding potential differences in disease prevalence and severity, a trend supported by Mukherjee et al., who noted a significant prevalence of infections in middle-aged females and elderly males [8] . The survey accompanying this study highlighted a troubling pattern in antibiotic use among patients. A significant 97.2% reported having taken antibiotics, with 76.7% obtaining them from local pharmacies before consulting healthcare professionals. The survey also indicated that 69.8% of patients do not know the name of the antibiotic they are using. When asked if their problem is resolved after visiting a physician, they confirmed that they are relived. These findings highlight the need for better patient education on antibiotic use and the importance of consulting healthcare professionals [9].

CONCLUSION

This study provides important insights into the landscape of antimicrobial resistance (AMR), highlighting a high rate of resistance to commonly used antibiotics such as ampicillin and cefuroxime. This situation emphasizes the urgent need for improved antimicrobial stewardship. E. coli was found to be a major pathogen across different age groups, raising concerns due to its strong link to antibiotic resistance. Furthermore, the results underline the necessity of effective infection control measures and targeted interventions, especially given the high incidence of urinary tract infections in the gynecology department. The research also points out the significant impact of patient knowledge and behaviour on AMR, calling for a thorough education on the proper use of antibiotics, including aspects like dosage, duration, and the importance of consulting healthcare professionals before self-medicating. Additional research is required to clarify the factors behind the high prevalence of E. coli and to evaluate how various antibiotic treatments affect patient outcomes. By focusing on these critical areas, healthcare providers can more effectively tackle AMR and improve patient care. The study's careful data collection from 281 patients is essential for identifying emerging resistance trends and is crucial for preventing the spread of resistant microorganisms in healthcare environments.

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