Antimicrobial resistance (AMR) is one of the top global public health and development threats ^[1]. The emergence and spread of multidrug-resistant organisms (MDROs) is a concern as options for treating patients with these infections are often extremely limited, and MDRO infections are associated with increased lengths of stay, costs, and mortality. AMR burden forecasts study by the Lancet estimated that in 2050, there will be 1·91 million annual deaths attributable to AMR globally and 8·22 million annual deaths associated with AMR. Cumulatively from 2025 to 2050, the study forecasts 39·1 million deaths attributable to AMR and 169 million deaths associated with AMR ^[2]. The definition most frequently used for Multidrug resistant bacteria is ‘resistant to three or more antimicrobial classes' ^[3,4].Bacteria develop antimicrobial resistance by several mechanisms such as decreased permeability across the cell wall, efflux pumps, by enzymatic inactivation (Ex: Extended spectrum beta lactamases-ESBL, Metallo beta lactamases-MBL) and by modifying the target sites (Ex: Methicillin resistant staphylococcus aureus-MRSA) ^[5].Reports from hospitals in India suggest that the prevalence of ESBL producing Gram negative bacteria range between 19% and 60%, and that of carbapenem-resistant Gram negative bacteria between 5.3% and 59%^[6,7]. ESBLs are β-lactamases conferring resistance to penicillins, cephalosporins, and aztreonam (but not to cephamycins or carbapenems) by hydrolyzing these antibiotics and are inhibited by β-lactamase inhibitors such as clavulanic acid. AmpC β-lactamases are cephalosporinases that have the ability to hydrolyze and inactivate cephalosporins, cephamycins, aminopenicillins, and monobactams but are not inhibited effectively by clavulanic acid. Carbapenems are used in treatment of ESBL and AmpC producing infections. MBLs can hydrolyze almost all β-lactams, including extended spectrum cephalosporins and carbapenems ^[5]. Detection of ESBL and MBL producers, along with documentation of their prevalence in patients and the hospital environment, is essential to understand their spread. This, in turn, enables the implementation of appropriate infection control measures, which can reduce patient morbidity and overall hospital expenditure. Keeping this in mind the present study was conducted in a tertiary care hospital in Hyderabad to study the prevalence of MDR organisms from clinical samples received from patients and correlated epidemiology.

Aim of study:

• To isolate and identify the Multidrug resistant bacteria from clinical samples received in the laboratory for bacteriological culture and sensitivity, and to upload the findings to WHONET surveillance system.
• To correlate the MDROs isolated with organisms isolated from hospital environmental samples including surface, air and water samples.

Material and methods:

Total 1784 blood culture samples, 4536 urine culture samples, 1147 sputum culture samples and 4395 exudate (pus, sterile body fluids) samples were received in the bacteriology section of department of microbiology, Osmania General Hospital during January 2025 to June 2025.

For environmental surveillance a total of 224 surface swabs were collected from different selected locations including operation theatres, surgical ICU’s, medical ICU’s, post OP wards and, orthopedic, burns wards, medical wards. In operation theatres swabs were collected from surfaces of air conditioners, diathiermy, suction apparatus, boyle’s apparatus, mayo's trolley, operation theatre table, light and wall. From wards and ICU’s surface swabs include patient bed railings, bed side table, monitor, BP apparatus, thermometer and ventilator. Air sampling was carried out by a microbial air sampler machine with a sheep blood agar plate in high- dependency areas like the operation theatre, ICU, and post-operative ward, to assess environmental sterility following fogging. Bacteriological analysis of water was carried out in selected places like overhead tanks, sumps, metro water supply, RO water plant, dialysis unit and kitchen.

The exudate samples include pus, wound swabs, sterile body fluids like pleural fluid, ascitic fluid, cerebrospinal fluid and knee aspirates. Exudates, urine and sputum samples received from patients were first subjected to Gram staining and then were inoculated on blood agar and MacConkey agar plates. The plates were incubated aerobically at 37⁰ C for 18- 24 hrs, sterile body fluids were plated on Chocolate agar along with blood agar and MacConkey agar and incubated for up to 48hrs. Blood culture processing was done by conventional method as per standard guidelines ^[5,8,9]. Swabs from Environment were processed by inoculating on Blood agar and MacConkey agar plates for aerobic culture and Robertson cooked meat broth for anaerobic growth. Aerobic cultures were reported at 18-24hrs and 48 hrs of incubation. Bacterial growth from clinical and Environmental samples was identified by its cultural characteristics, colony morphology and biochemical reactions. Antimicrobial susceptibility testing was done on Mueller Hinton Agar (MHA) by Kirby Bauer disk diffusion method as per CLSI guidelines ^[10].

Bacterial isolates that were found to be resistant to at least three or more antibiotic classes were considered MDROs ^[3,4]. Gram-negative isolates exhibiting resistance to third-generation cephalosporins by disc diffusion were subjected to ESBL screening and confirmatory testing. Phenotypic confirmation of ESBL production was done by using combined disc method employing two disks: Ceftazidime and a combination of Ceftazidime and Clavulanic acid disc if the difference was ≥ 5 mm between the two disks, the isolate was considered as an ESBL producing as shown in fig.1.

Fig. 1: ESBL detection                                Fig. 2: MBL detection                          Fig. 3: Amp C screening

Gram-negative isolates demonstrating resistance to imipenem on initial disc diffusion susceptibility testing were subjected to screening and confirmatory tests for MBL (carbapenemase) production. Phenotypic confirmation of MBL production by combined disc method, Imipenem and a combination of Imipenem and Ethylene diamine tetra acetic acid (EDTA) were employed. If there was a zone of inhibition in the combined disc with Imipenem+ EDTA in comparison to Imipenem alone with a difference of at least ≥7mm between them, the test strain was considered as a MBL producer, fig. 2.

Isolates resistant to cefoxitin (30µg) were screened as AmpC β-lactamase producers, fig. 3.

The patient isolates that which were found to be MDRO were also subjected to colistin testing by agar dilution method.

Fig. 4: MRSA screening

Methicillin Resistant Staphylococcus aureus (MRSA) detection method Cefoxitin disks (5µg) were used as a surrogate for mecA-mediated oxacillin resistance in Staphylococcus spp. An inhibition zone diameter of ≤21 mm was reported as methicillin resistant(fig. 4) and ≥22 mm was considered as methicillin susceptible for Staphylococcus aureus. A zone of ≤ 24mm was reported as methicillin resistant and a zone of ≥ 25mm was reported as methicillin susceptible Coagulase Negative Staphylococcus species (CONS) ^[10].

Air sampling results were interpreted as per the following criteria:

For the Operation Theatre (OT), environmental sterility was considered satisfactory when bacterial counts were <35 CFU/cubic mm and no fungal colony. For the Intensive Care Unit (ICU) and Post-operative Ward, counts of <50 CFU/cubic mm for bacteria and <5 CFU/cubic mm for fungi were deemed satisfactory.

Bacteriological analysis of water was interpreted as satisfactory when total coliform count was < 3 CFU/100ml and fecal coliform count were nil.

Results:

Of 4395 exudate samples received 1231(30%) showed monomicrobial growth 223(5%) samples showed polymicrobial growth and 198(4.5%) showed contamination. Predominant isolates were Gram negative bacteria, of which 22.6%(279) were E.coli 22.1%(273) were Klebsiella species followed by 13.7%(169) Pseudomonas species, 9.2%(114) Acinetobacter species and 4.8%(60) Citrobacter species. Among Gram positive isolates S.aureus was 17.8%(220) and Coagulase Negative Staphylococcus species were 4.6%(57) which were reported only when isolated from implant wound site exudate samples. All the results summarized and depicted below in fig no. 5 & fig.no. 6. 

Of 1784 blood culture samples received 221(12.6%) showed growth, 35(2%) showed contamination. Coagulase Negative Staphylococcus species 64(29%) were predominantly isolated in paired blood culture samples among Gram positive bacteria. Among Gram negative bacteria Acinetobacter species were isolated predominantly 19.5% (43) followed by Klebsiella species 15.3%(34), Pseudomonas species 12.2%(27), E.coli 11.3%(25). Other bacteria included Enterococcus species 3.6%(8), S.aureus 3.6%(8)

Of 4536 Urine samples received 16.1%(729) showed monomicrobial growth, 8.1%(368) samples showed polymicrobial growth and contaminants. E.coli was predominant isolate 44.8%(327) among Gram negative bacteria followed by Klebsiella species 22.3%(163), Pseudomonas species 5.3%(39) Citrobacter species 3.4%(25) , and Proteus species 1.4%(10). Among Gram positive bacteria Enterococcus species was predominant 19.2%(140) followed by S.aureus 2.4%(18) and CoNS 0.2%(2).

Of 1147 sputum samples 15%(171) showed growth , 2.6%(30) showed salivary contamination Klebsiella pneumoniae was predominant isolate 57.3%(98) followed by pseudomonas species 21.6%(37) Acinetobacter species 10%(17), S.aureus 6.4%(11) and Streptococcus pneumoniae1.7% (3); as summarized in table no1 below.

Table No.1: Summary of clinical isolates from different samples

Fig 5: Summary of Gram Positive isolates in total clinical isolates

Fig 6: Summary of Gram Negative isolates in total clinical isolates

Table 2: Summary of surface swabs

Table 3: Air sampling results

Out of the total 2352 bacterial isolates from various clinical samples, Multidrug resistance was seen in 1121(47.6%) isolates as shown in table no:4 comprising predominantly of E.coli 70.5%(n=445) followed by 57%(n=324) Klebsiella species, 47%(n=128) Pseudomonas species 57.5%(n=103) Acinetobacter species, 35.8%(n=92) S.aureus. Bacteria including Citrobacter species, Proteus species, Enterobacter species, Burkholderia species and Enterococcus species also showed multidrug resistance.

Table 4: Summary of MDRO’s

Of the 163 Klebsiella species isolated from urine samples 36% (59) were ESBL producers, 8% (13) were ESBL & AmpC producers and 8% (13) were MBL producers. Of 273 Klebsiella species isolated from the exudate samples 62.5% (171) were ESBL and 6% (16) were MBL producers. Of 34 Klebsiella species isolated from blood samples 25% (7) were ESBL producers.

Out of the 327 E.coli isolated from urine samples 60% (197) were ESBL Producers, 12% (39) Both ESBL &Amp C producers and 4.7%(15) were MBL Producers. Of 279 E.coli isolated from Exudates 66.7% (186) were ESBL producers. Of 25 E.coli isolated from Blood culture samples 33% (8) were ESBL producers.

Of 169 Pseudomonas species isolated from exudates 17.6%(30) were MBL producers. Of 27 Pseudomonas species isolated from blood 9%(2) were MBL producers.

Of 114 Acinetobacter species isolated from exudates, 43 Acinetobacter species isolates from blood and 17 Acinetobacter species isolates from sputum 12.5%(14), 16.7%(7), 28%(5) were MBL producers  respectively.

The MDRO isolates subjected to Colistin agar dilution showed MIC <2m/dl, which is intermediate according to CLSI fig 7.

Fig 7 : Colistin agar dilution

Among the environmental surface swabs isolates 189(84.3%) showed no bacterial growth as summerised in table no 2. 20(8.9%) CoNS, 9(4%) Diptheroids, 3(1.3%) S.aureus and 3(1.3%) Klebsiella species were isolated from swabs collected from wards. All swabs from operation theatres showed no bacterial growth.

Out of the 3 S.aureus, 1 isolate was MRSA. MRSA found on patient-side table. Klebsiella species showed sensitivity to all the tested antibiotics. The 3 Klebsiella species were isolated from swabs of the same ward indicating potential contamination or hospital associated pathogen.

Among the air sampling results during 6 months of study, operation theatres showed 3.2%(32) unsatisfactory results as shown in table no.3. ICU and post op ward showed 9.76% and 9.6% unsatisfactory results. The areas showing unsatisfactory results were advised to repeat the air sampling after deep cleaning the surfaces, cleaning the air conditioners and fogging the respective areas.

Cleaning and Chlorination of sump was advised where the bacteriological analysis was unsatisfactory.

Discussion:

In the present study among 2352 bacterial isolates 1121(47.6%) isolates were MDRO’s. In studies from different parts of the country, prevalence of MDROs ranges from 30% to 60%^[7]. Study done by Vishnu Kaniyarakkal et.al showed MDROs at 58%  where Predominant MDRO were E.coli 66%  similar to the present study where MDR E.coli are 70.5%^[11]. The present study shows 26.8% of E.coli from all the clinical samples with 44.8% E.coli in Urinary isolates which is in accordance to study conducted and by Kanika Bhargava et al in 2022 (55%)^{[12 ]}. In Exudate samples predominant isolates were Gram negative bacteria E.coli 22.6% and Klebsiella 22.1% whereas the studies done by Ramya Rengaraj et al in 2021 showed S.aureus with 28.4% as the most prevalent pathogen in pus samples^[13]. Predominant isolate in paired Blood culture samples was CoNS (29%) similar to the study done by Pradheep Kumar Kokku et al in 2020 with 26.7 % CoNS isolates, Followed by Acinetobacter species 19.4%(14). The most common pathogen isolated in sputum sample in the present study was Klebsiella species 57.3%  followed by Pseudomonas species 21.6%  and Acinetobacter species 9.9%  similar to study done by Mahale R P et al in 2024 in which Klebsiella spp  (47.18%) was the most common pathogen followed by Pseudomonas (21.31%) and Acinetobacter spp. (17.55%)^[15].

In the present study the highest ESBL producing organism was E.coli (60.6% ) isolated from urine samples similar to the study done by Nagaraj, P. et al with 50.4%. ESBL E.coli ^[16].

MBL production was seen in 14.5% of Acinetobacter species and 11.8% Pseudomonas species isolates similar to the study done by Aradita C, et al with 12.3% MBL production ^[17] .

In Environmental surface samples 84.3% of swabs were sterile indicating good overall cleanliness. Coagulase Negative staphylococci represented 8.9% of isolates. Despite their commensal nature, CoNS have emerged as significant opportunistic pathogens, particularly in nosocomial settings ^[18]. As this study is conducted at a tertiary care Government hospital where critical and terminally ill patients are referred from other hospitals as a last resort, CoNS in the environment can act as a source of infection in immunocompromised patients. Klebsiella species and S.aureus were isolated in 1.3% (3) of swabs which are clinically significant. Compared to the study done by G.V. Padmaja et al in 2016 which showed 26% of ESBL’s and 10% of MBL’s producing Gram negative bacteria in environmental samples ^[19].The reason in the decline may be attributed to the active infection control committee and regular infection control rounds and surveillance at the hospital. Areas showing unsatisfactory results in Air sampling were given visit by Infection control committee team and advised required corrections.

Conclusion:

There is an increasing emergence of nosocomial infections caused by Multidrug-resistant pathogens, including ESBL and MBL-producing bacteria, which significantly contribute to antimicrobial resistance. This information which is uploaded to WHONET is useful for guiding clinicians in selecting appropriate empirical antibiotic therapy by generating ward specific antibiograms. Conducting regular surveillance studies in all hospitals is crucial for gathering data on the susceptibility patterns of both clinical and environmental isolates. The present study has taken a complete approach by conducting air, water and surface surveillance and correlating these findings with clinical isolates. Studies incorporating both environmental and clinical isolates provide insights into the transmission dynamics of hospital acquired infections and emphasize the necessity of stringent cleaning protocols and preventive measures.

STATISTICAL METHODS:

Descriptive statistics like mean and percentage were used to infer data. Microsoft office 2019 was used to make tables.

Acknowledgment: None

Conflict of interest: the authors declare that there is no conflict of interest.

Author’s contribution:

Dr. G.V.Padmaja conceptualized and supervised the study.

Dr. Uzma and Dr. Nazia performed tests, data validation and data curation.

All authors contributed equally writing and approving the final manuscript for publication.

Funding: None

Data availability:

Included in manuscript

Ethics statement: Institutional Ethical clearance taken for the study.

References:

1. World Health Organization. (2023).Antimicrobial resistance. https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance
2. GBD 2021 Antimicrobial Resistance Collaborators. (2024). Global burden of bacterial antimicrobial resistance 1990–2021: A systematic analysis with forecasts to 2050.The Lancet, 404(10459), 1199–1226. https://doi.org/10.1016/S0140-6736(24)01867-1
3. Magiorakos, A. P., Srinivasan, A., Carey, R. B., et al. (2012). Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: An international expert proposal for interim standard definitions for acquired resistance.Clinical Microbiology and Infection, 18(3), 268–281. https://doi.org/10.1111/j.1469-0691.2011.03570.x
4. Centers for Disease Control and Prevention. (n.d.).Multidrug-Resistant Organism (MDRO) and Clostridioides difficile infection (CDI) module: National Healthcare Safety Network. Centers for Disease Control and Prevention. https://www.cdc.gov
5. Winn, W. C., & Koneman, E. W. (2016).Koneman’s color atlas and textbook of diagnostic microbiology (7th ed.). Lippincott Williams & Wilkins.
6. Bhattacharya, S. (2011). Is screening patients for antibiotic-resistant bacteria justified in the Indian context?Indian Journal of Medical Microbiology, 29(3), 213–217. https://doi.org/10.4103/0255-0857.83902
7. Patel, R., Joshi, P., Patel, N., & Modi, C. (2024). Incidence density rate of multidrug-resistant organisms (MDRO) at a tertiary care teaching hospital: A retrospective cross-sectional study.Indian Journal of Microbiology Research, 11(2), 107–112.
8. Collee, J. G., Marmion, B. P., Fraser, A. G., & Simmons, A. (1996).Mackie & McCartney practical medical microbiology (14th ed.). Churchill Livingstone.
9. Cheesbrough, M. (2006).District laboratory practice in tropical countries: Part 2 (2nd ed.). Cambridge University Press.
10. Clinical and Laboratory Standards Institute. (2024).Performance standards for antimicrobial susceptibility testing(32nd ed., CLSI document M100-A34). Clinical and Laboratory Standards Institute.
11. Kaniyarakkal, V., Variamkandi, S. B., George, K., et al. (2021). Microbiological profile of significant multidrug-resistant organisms isolated in a tertiary care centre, Kerala, India.International Journal of Research and Review, 8(5), 404–411.
12. Bhargava, K., Nath, G., Bhargava, A., Kumari, R., Aseri, G. K., & Jain, N. (2022). Bacterial profile and antibiotic susceptibility pattern of uropathogens causing urinary tract infection in the eastern part of Northern India.Frontiers in Microbiology, 13, 965053.
13. Velu, P., Rengaraj, R., Gurumurthy, H., & Ali, S. M. (2021). Evaluation of antimicrobial susceptibility pattern of pathogenic bacteria causing urinary tract infection in a teaching hospital.International Journal of Current Microbiology and Applied Sciences, 10(9), 456–463.
14. Kokku, P. K., Priyadarshini, T., & Sravanthi, C. H. (2020). Bacteriological profile and antimicrobial sensitivity pattern of blood culture isolates.Journal of Evidence Based Medicine and Healthcare, 7(38), 2092–2095.
15. Mahale, R. P., Darpan Sheth, P., & Murthy, N. S. (2024). Evaluating the sputum bacteriological profile of lower respiratory tract infections with Bartlett score analysis in a tertiary care hospital in Southern Karnataka.Cureus, 16(6), e61924.
16. Sivarajan, V., Mudaliar, Y., Nagaraj, P., Natarajan Balakrishnan, M. R., Manikandan, N., Sree, K., Raj, M., Jothiraj, M., & Perumal, K. (2024). The prevalence of multidrug-resistantEscherichia coli in Chennai and whole genome sequence analysis of carbapenem-resistant Escherichia coli  Indian Journal of Microbiology, 64(2), 467–474.
17. Aradita, K., Rao, K., & Lakshminarayana, S. A. (2024). Detection of metallo-beta-lactamase (MBL) producingPseudomonas aeruginosa and Acinetobacter  from a tertiary care hospital. Journal of Research in Applied and Basic Medical Sciences, 10(1), 72–79.
18. Shah, P. K., Bhandari, N., & Joshi, R. D. (2024). Molecular characterization and antibiotic susceptibility pattern of coagulase-negative staphylococci (CoNS) isolated from clinical samples in a tertiary care hospital, Kathmandu, Nepal.The Bioscan, 19(Suppl. 1), 165–171. https://doi.org/10.63001/tbs.2024.v19.i02.S1.pp165-171
19. Padmaja, G. V., & Rao, R. K. (2016). Prevalence of extended-spectrum beta-lactamases and metallo-beta-lactamases producing bacteriological isolates with correlational epidemiological study of ESBLs and MBLs in MGM Hospital.International Journal of Contemporary Medical Research, 3(6), 1769–1771.