Antimicrobial resistance (AMR) has become a major challenge to contemporary clinical practice because the progressive loss of activity of commonly used antimicrobial agents narrows therapeutic options and increases the risk of treatment failure, prolonged hospitalization, complications, and healthcare expenditure. The problem is driven by several interacting factors, including inappropriate antimicrobial exposure, transmission of resistant organisms within healthcare settings, inadequate infection prevention, and the rapid dissemination of mobile resistance determinants. The global nature of AMR has made systematic surveillance, antimicrobial stewardship, and infection-control interventions essential components of patient safety [1]. India carries a substantial and heterogeneous burden of antimicrobial resistance. Hospital-based studies have documented considerable resistance among both Gram-negative and Gram-positive pathogens, with marked geographic and institutional variation [2]. The Indian Council of Medical Research Antimicrobial Resistance Surveillance and Research Network has strengthened national understanding of resistance patterns and has highlighted increasing resistance among clinically important Gram-negative organisms, including resistance to third-generation cephalosporins, fluoroquinolones, and carbapenems [3]. National surveillance data also show that resistance mechanisms are not uniformly distributed; therefore, antimicrobial policies based solely on regional or national summaries can be insufficient for individual hospitals [4]. Routine clinical microbiology laboratories have a central role in generating local evidence. The distribution of pathogens varies with specimen type, patient population, referral pattern, hospital services, and antimicrobial exposure. Escherichia coli and Klebsiella pneumoniae are important causes of urinary tract, bloodstream, and intra-abdominal infections, whereas Pseudomonas aeruginosa and Acinetobacter species are prominent opportunistic pathogens in hospitalized and critically ill patients. Among Gram-positive organisms, Staphylococcus aureus and Enterococcus species remain clinically important because methicillin resistance and glycopeptide resistance can substantially restrict treatment choices. In Enterobacterales, extended-spectrum beta-lactamase production is particularly relevant because it is frequently associated with resistance to multiple non-beta-lactam agents. A current institutional antibiogram provides clinicians with a practical summary of the organisms encountered locally and the proportion that remain susceptible to individual antimicrobial agents. Such information supports empirical treatment decisions before culture results become available, assists antimicrobial stewardship teams in reviewing prescribing policies, and helps microbiology and infection-control units recognize unusual changes in resistance. Periodic evaluation is especially important because resistance profiles can change over relatively short intervals in tertiary care hospitals. The present study was undertaken to characterize the bacterial pathogens recovered from clinical specimens in a tertiary care hospital in Andhra Pradesh. The objectives were to determine the culture positivity and distribution of bacterial isolates across major specimen types, describe antimicrobial susceptibility patterns of the principal Gram-negative and Gram-positive organisms, estimate the frequency of selected resistance phenotypes including ESBL production, MRSA and vancomycin resistance, and determine the overall burden of multidrug-resistant isolates during the study period

Study design and setting: This prospective observational, laboratory-based study was conducted in the Department of Microbiology, Government Medical College, Ongole, Andhra Pradesh, India. The study was carried out over three months, from March 2023 to May 2023. Clinical specimens submitted to the microbiology laboratory from different hospital departments for routine aerobic bacterial culture and antimicrobial susceptibility testing constituted the study material. Study population and specimen selection: Consecutive eligible clinical specimens received during the predefined study period were considered for inclusion. The final analytical sample consisted of 500 specimens. Urine, pus/wound swabs, blood, respiratory specimens, body fluids, and other clinically relevant samples were included when they were appropriately collected, labelled, transported, and accompanied by adequate clinical information. Specimens with inadequate quantity, improper labelling, leakage, obvious contamination, or unsuitability for routine bacterial culture were excluded. When repeated isolates represented the same organism from the same patient and clinical episode, only the first clinically significant isolate was considered for resistance profiling to minimize duplication. Microbiological processing and identification: Specimens were processed using standard bacteriological procedures appropriate to the specimen type. Samples were inoculated onto suitable routine culture media and incubated under appropriate aerobic conditions. Significant growth was assessed according to the clinical specimen and routine laboratory criteria. Bacterial isolates were identified by colony morphology, Gram staining, and conventional biochemical reactions. The identification workflow was supported by routine quality-control procedures used in the laboratory. Antimicrobial susceptibility testing: Antimicrobial susceptibility testing was performed using the Kirby-Bauer disk diffusion method [5]. Antimicrobial agents were selected according to organism group, specimen type, and the routine laboratory panel, and inhibition-zone diameters were interpreted using Clinical and Laboratory Standards Institute breakpoints applicable during the study period. For the principal Gram-negative isolates, the analytical panel included amikacin, ceftazidime, cefepime, ciprofloxacin, piperacillin-tazobactam, and meropenem. For major Gram-positive isolates, relevant agents included cefoxitin where applicable, gentamicin/high-level gentamicin, ciprofloxacin, clindamycin, linezolid, vancomycin, and ampicillin. Resistance phenotypes and definitions: ESBL production in E. coli and Klebsiella isolates was assessed phenotypically using routine screening and confirmatory principles based on cephalosporin-clavulanate synergy, consistent with approaches used in Indian multicentre surveillance [6]. Methicillin resistance in S. aureus was determined using cefoxitin susceptibility. Enterococcal vancomycin resistance was recorded from routine susceptibility results. Multidrug resistance was defined as acquired non-susceptibility to at least one antimicrobial agent in three or more antimicrobial categories, following the international consensus definition [7]. Statistical analysis and ethics: Data were summarized using frequencies and percentages. Culture positivity across specimen categories was compared using the chi-square test, with P<0.05 considered statistically significant. Patient identifiers were excluded from the analytical dataset. Necessary Permissions were obtained before starting the study.

A total of 500 clinical specimens obtained from patients attending different clinical departments of the tertiary care hospital were included. Of these, 318 (63.6%) yielded significant bacterial growth, while 182 (36.4%) showed no significant growth. Urine was the most frequently received specimen (36.0%), followed by pus/wound swabs (24.0%), blood (18.0%), respiratory specimens (14.0%), and other specimens/body fluids (8.0%). Culture positivity was highest among pus/wound specimens (74.2%), followed by urine (67.8%) and respiratory specimens (65.7%). The distribution of culture positivity differed significantly across specimen categories (chi-square=23.13, P<0.001), as shown in Table 1. Table 1. Distribution and culture positivity of clinical specimens (n=500) Specimen type Total specimens, n (%) Culture positive, n (%) Culture negative, n (%) Urine 180 (36.0) 122 (67.8) 58 (32.2) Pus/wound swab 120 (24.0) 89 (74.2) 31 (25.8) Blood 90 (18.0) 41 (45.6) 49 (54.4) Respiratory specimens 70 (14.0) 46 (65.7) 24 (34.3) Other specimens/body fluids 40 (8.0) 20 (50.0) 20 (50.0) Total 500 (100) 318 (63.6) 182 (36.4) Among the 318 bacterial isolates, Gram-negative organisms predominated, accounting for 228 (71.7%), while Gram-positive organisms constituted 90 (28.3%). E. coli was the most frequently isolated organism, with 92 (28.9%) isolates, followed by Klebsiella spp. with 61 (19.2%), S. aureus with 48 (15.1%), and P. aeruginosa with 39 (12.3%). Enterococcus spp. accounted for 24 (7.5%) and Acinetobacter spp. for 20 (6.3%) isolates. The specimen-wise distribution of all bacterial isolates is presented in Table 2. Table 2. Distribution of bacterial isolates according to specimen type (n=318) Organism Urine Pus/wound Blood Respiratory Other Total, n (%) E. coli 62 16 5 4 5 92 (28.9) Klebsiella spp. 24 9 8 17 3 61 (19.2) S. aureus 4 28 9 4 3 48 (15.1) P. aeruginosa 8 16 2 11 2 39 (12.3) Enterococcus spp. 15 3 4 0 2 24 (7.5) Acinetobacter spp. 2 6 3 8 1 20 (6.3) Coagulase-negative staphylococci 1 3 9 0 1 14 (4.4) Proteus spp. 5 5 0 0 0 10 (3.1) Enterobacter spp. 1 2 1 2 0 6 (1.9) Streptococcus spp. 0 1 0 0 3 4 (1.3) Total 122 89 41 46 20 318 (100) Antimicrobial susceptibility among Gram-negative isolates Among E. coli isolates, the highest susceptibility was observed to meropenem (91.3%), followed by amikacin (84.8%) and piperacillin-tazobactam (79.3%). Susceptibility to ceftazidime, cefepime, and ciprofloxacin was lower. Klebsiella spp. demonstrated susceptibility rates of 83.6% to meropenem, 75.4% to amikacin, and 72.1% to piperacillin-tazobactam. P. aeruginosa showed highest susceptibility to amikacin (76.9%), followed by piperacillin-tazobactam (74.4%) and meropenem (69.2%). Acinetobacter spp. demonstrated lower susceptibility across the tested agents, including 45.0% susceptibility to amikacin and 40.0% to meropenem. These findings are detailed in Table 3. Table 3. Antimicrobial susceptibility pattern of major Gram-negative bacterial isolates Antimicrobial agent E. coli (n=92), n (%) susceptible Klebsiella spp. (n=61), n (%) susceptible P. aeruginosa (n=39), n (%) susceptible Acinetobacter spp. (n=20), n (%) susceptible Amikacin 78 (84.8) 46 (75.4) 30 (76.9) 9 (45.0) Ceftazidime 44 (47.8) 27 (44.3) 24 (61.5) 5 (25.0) Cefepime 47 (51.1) 29 (47.5) 26 (66.7) 6 (30.0) Ciprofloxacin 35 (38.0) 24 (39.3) 25 (64.1) 6 (30.0) Piperacillin-tazobactam 73 (79.3) 44 (72.1) 29 (74.4) 7 (35.0) Meropenem 84 (91.3) 51 (83.6) 27 (69.2) 8 (40.0) ESBL production was detected in 41 of 92 (44.6%) E. coli isolates and 29 of 61 (47.5%) Klebsiella isolates. Carbapenem resistance was observed in 8 (8.7%) E. coli isolates and 10 (16.4%) Klebsiella isolates. Antimicrobial susceptibility among Gram-positive isolates Among the 48 S. aureus isolates, 32 (66.7%) were susceptible to cefoxitin, while 16 (33.3%) were classified as MRSA. Susceptibility to clindamycin and gentamicin was 72.9% and 75.0%, respectively. All S. aureus isolates were susceptible to vancomycin and linezolid. Among the 24 Enterococcus spp. isolates, 15 (62.5%) were susceptible to ampicillin, 22 (91.7%) to vancomycin, and 23 (95.8%) to linezolid. Two Enterococcus isolates (8.3%) demonstrated vancomycin resistance. Table 4 summarizes the susceptibility pattern of the major Gram-positive isolates. Table 4. Antimicrobial susceptibility pattern of major Gram-positive isolates Antimicrobial agent S. aureus (n=48), n (%) susceptible Enterococcus spp. (n=24), n (%) susceptible Ampicillin - 15 (62.5) Gentamicin/high-level gentamicin* 36 (75.0) 14 (58.3) Ciprofloxacin 27 (56.3) 10 (41.7) Clindamycin 35 (72.9) - Linezolid 48 (100) 23 (95.8) Vancomycin 48 (100) 22 (91.7) *High-level gentamicin testing applies to Enterococcus spp. as appropriate. Multidrug resistance Overall, 129 of the 318 bacterial isolates (40.6%) fulfilled the definition of multidrug resistance. MDR was more frequent among Gram-negative isolates, occurring in 101 of 228 (44.3%), compared with 28 of 90 (31.1%) Gram-positive isolates. The highest MDR proportion was observed among Acinetobacter spp. (60.0%), followed by Klebsiella spp. (50.8%), E. coli (42.4%), and P. aeruginosa (35.9%). Organism-specific MDR frequencies are shown in Table 5. Table 5. Distribution of multidrug-resistant bacterial isolates Organism Total isolates MDR isolates, n (%) E. coli 92 39 (42.4) Klebsiella spp. 61 31 (50.8) S. aureus 48 16 (33.3) P. aeruginosa 39 14 (35.9) Enterococcus spp. 24 7 (29.2) Acinetobacter spp. 20 12 (60.0) Coagulase-negative staphylococci 14 4 (28.6) Proteus spp. 10 3 (30.0) Enterobacter spp. 6 2 (33.3) Streptococcus spp. 4 1 (25.0) Total 318 129 (40.6) Taken together, the results showed a predominance of Gram-negative bacterial pathogens, particularly E. coli and Klebsiella spp., with considerable resistance to cephalosporins and fluoroquinolones and comparatively greater retained activity of amikacin, piperacillin-tazobactam, and meropenem among the major Enterobacterales. The substantial frequency of MDR isolates, especially among Acinetobacter spp., Klebsiella spp., and E. coli, indicates a significant local antimicrobial-resistance burden.

This prospective laboratory-based study demonstrated a culture positivity of 63.6% among 500 clinical specimens. The yield varied significantly by specimen type, with the highest positivity in pus/wound specimens, followed by urine and respiratory samples. Differences in culture positivity across hospitals are expected because diagnostic yield is influenced by specimen selection, prior antimicrobial exposure, referral patterns, case mix, and laboratory practices. The predominance of Gram-negative organisms in the present study is consistent with the broader Indian surveillance experience, which has repeatedly emphasized the clinical importance of resistant Gram-negative pathogens in tertiary care settings [3,4]. E. coli was the leading isolate, followed by Klebsiella spp., S. aureus, and P. aeruginosa. This distribution reflects the contribution of urinary, wound, bloodstream, and respiratory infections to routine microbiology workload. ESBL production was identified in 44.6% of E. coli and 47.5% of Klebsiella isolates. Gautam et al. reported phenotypic ESBL production in approximately one-third of E. coli and 42% of K. pneumoniae isolates across Indian tertiary centres, with substantial inter-centre variation [6]. Earlier Indian studies also documented high ESBL frequencies, illustrating the persistence of beta-lactam resistance as an important hospital problem [8]. In the present dataset, meropenem retained activity against 91.3% of E. coli and 83.6% of Klebsiella isolates; however, the presence of carbapenem-resistant isolates remains clinically important because national surveillance has documented increasing carbapenem resistance [3,4]. P. aeruginosa showed relatively higher susceptibility to amikacin, piperacillin-tazobactam, and meropenem than to ceftazidime or ciprofloxacin. Comparable Indian data have shown useful activity of aminoglycosides, beta-lactam/beta-lactamase inhibitor combinations, and carbapenems against P. aeruginosa, although susceptibility varies by institution and time period [14]. Acinetobacter spp. displayed the most concerning profile in the present study, with only 40.0% susceptibility to meropenem and the highest MDR proportion at 60.0%. Multicentre Indian investigations have demonstrated widespread carbapenem-resistance determinants and successful resistant lineages among A. baumannii, supporting continued surveillance of this pathogen [13]. Among S. aureus isolates, 33.3% were MRSA, while all isolates remained susceptible to vancomycin and linezolid. The Indian surveillance network reported methicillin resistance around 41% in a large multicentre dataset [10], whereas a subsequent meta-analysis estimated a pooled MRSA prevalence of approximately 27% across included Indian studies [11]. Enterococcal vancomycin resistance was 8.3% in the present series, lower than the 24% reported by Phukan et al. in a North-East Indian tertiary centre [12], again demonstrating institutional variability. Overall, 40.6% of isolates met the MDR definition, with a higher proportion among Gram-negative than Gram-positive organisms. Earlier hospital surveillance from India has similarly documented substantial multidrug resistance across E. coli, Klebsiella, Pseudomonas, Acinetobacter, MRSA, and VRE [9]. These findings support regular preparation of institution-specific antibiograms, culture-directed therapy, antimicrobial stewardship, and coordinated infection-prevention practices. LIMITATIONS This study has several limitations. It was conducted at a single tertiary care centre over a short three-month period, limiting assessment of seasonal and long-term resistance trends. Detailed patient-level variables, prior antimicrobial exposure, clinical outcomes, and ward-specific risk factors were not analyzed. Molecular characterization of resistance determinants was not performed. Susceptibility testing also depended on organism-specific routine laboratory panels, which restricted direct comparison across all bacterial species.

Gram-negative bacteria constituted the majority of clinically significant isolates, with E. coli and Klebsiella spp. predominating. A substantial proportion of Enterobacterales expressed ESBL production, while resistance to carbapenems was already detectable. MRSA accounted for one-third of S. aureus isolates, and vancomycin resistance was identified among Enterococcus spp. The overall MDR prevalence of 40.6%, particularly the high burden observed in Acinetobacter and Klebsiella, demonstrates the need for continuous local resistance surveillance. Regular institutional antibiograms, prompt microbiological diagnosis, antimicrobial stewardship, and rigorous infection-prevention practices are essential to preserve antimicrobial effectiveness and support evidence-based empirical therapy in tertiary care hospitals. Periodic review of prescribing policies should be linked directly to evolving laboratory resistance data.

1. Laxminarayan R, Duse A, Wattal C, Zaidi AKM, Wertheim HFL, Sumpradit N, et al. Antibiotic resistance-the need for global solutions. Lancet Infect Dis. 2013;13(12):1057-1098. doi:10.1016/S1473-3099(13)70318-9. 2. Kumar SG, Adithan C, Harish BN, Sujatha S, Roy G, Malini A. Antimicrobial resistance in India: a review. J Nat Sci Biol Med. 2013;4(2):286-291. doi:10.4103/0976-9668.116970. 3. Walia K, Madhumathi J, Veeraraghavan B, Chakrabarti A, Kapil A, Ray P, et al. Establishing Antimicrobial Resistance Surveillance & Research Network in India: journey so far. Indian J Med Res. 2019;149(2):164-179. doi:10.4103/ijmr.IJMR_226_18. 4. Veeraraghavan B, Walia K. Antimicrobial susceptibility profile & resistance mechanisms of Global Antimicrobial Resistance Surveillance System (GLASS) priority pathogens from India. Indian J Med Res. 2019;149(2):87-96. doi:10.4103/ijmr.IJMR_214_18. 5. Bauer AW, Kirby WMM, Sherris JC, Turck M. Antibiotic susceptibility testing by a standardized single disk method. Am J Clin Pathol. 1966;45(4):493-496. 6. Gautam V, Thakur A, Sharma M, Singh A, Bansal S, Sharma A, et al. Molecular characterization of extended-spectrum beta-lactamases among clinical isolates of Escherichia coli & Klebsiella pneumoniae: a multi-centric study from tertiary care hospitals in India. Indian J Med Res. 2019;149(2):208-215. doi:10.4103/ijmr.IJMR_172_18. 7. Magiorakos AP, Srinivasan A, Carey RB, Carmeli Y, Falagas ME, Giske CG, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18(3):268-281. doi:10.1111/j.1469-0691.2011.03570.x. 8. Mathur P, Kapil A, Das B, Dhawan B. Prevalence of extended spectrum beta lactamase producing gram negative bacteria in a tertiary care hospital. Indian J Med Res. 2002;115:153-157. 9. Wattal C, Goel N, Oberoi JK, Raveendran R, Datta S, Prasad KJ. Surveillance of multidrug resistant organisms in tertiary care hospital in Delhi, India. J Assoc Physicians India. 2010;58 Suppl:32-36. 10. Indian Network for Surveillance of Antimicrobial Resistance (INSAR) group, India. Methicillin resistant Staphylococcus aureus (MRSA) in India: prevalence & susceptibility pattern. Indian J Med Res. 2013;137(2):363-369. 11. Ghia CJ, Waghela S, Rambhad G. A systemic literature review and meta-analysis reporting the prevalence and impact of methicillin-resistant Staphylococcus aureus infection in India. Infect Dis (Auckl). 2020;13:1178633720970569. doi:10.1177/1178633720970569. 12. Phukan C, Lahkar M, Ranotkar S, Saikia KK. Emergence of vanA gene among vancomycin-resistant enterococci in a tertiary care hospital of North-East India. Indian J Med Res. 2016;143(3):357-361. doi:10.4103/0971-5916.182627. 13. Vijayakumar S, Mathur P, Kapil A, Das BK, Ray P, Gautam V, et al. Molecular characterization & epidemiology of carbapenem-resistant Acinetobacter baumannii collected across India. Indian J Med Res. 2019;149(2):240-246. doi:10.4103/ijmr.IJMR_2085_17. 14. Javiya VA, Ghatak SB, Patel KR, Patel JA. Antibiotic susceptibility patterns of Pseudomonas aeruginosa at a tertiary care hospital in Gujarat, India. Indian J Pharmacol. 2008;40(5):230-234. doi:10.4103/0253-7613.44156