Dynamics of Antimicrobial Susceptibility and Risk Factors Associated with Infections Caused by Colistin-Resistant Bacteria: A Study from the Northern Region of Haryana, India

Antimicrobial resistance (AMR) has become a “hidden epidemic” due to the lack of new antimicrobial medication breakthroughs. AMR is receiving the highest priority and attention from the World Health Organization due to its growing importance as a global health concern (Ferrara et al. 2024). Colistin is frequently used as a last-resort antibiotic to treat infections caused by multidrug-resistant Gram-negative bacterial infections (MDR-GNB), mainly when the bacteria are resistant to carbapenem. The possible cause of colistin resistance in bacteria may be due to chromosomal mutations, which often cause changes in the target site of lipopolysaccharides (LPS), or it can also occur through the transfer of plasmids carrying mcr genes (Andrade et al. 2020; Bostanghadiri et al. 2024). Early and accurate identification of colistin resistance is crucial for effective antimicrobial treatment.

Colistin is a growth stimulant often used in the cattle, poultry, and aquaculture industries, leading to its widespread dissemination in the environment. This leads to the selection and proliferation of bacteria resistant to colistin, which may infect human beings as well (Gharaibeh and Shatnawi 2019). Literature indicates that the prevalence of colistin resistance was relatively low (Chauhan et al. 2022). Nevertheless, antibiotic misuse and overprescription are considered the primary cause of the development of antimicrobial resistance. Further, the ease with which antibiotics can be acquired over the counter exacerbates the problem of antibiotic abuse, resulting in the emergence of antibiotic resistance (Mithuna et al. 2024). The several risk factors that can lead to the development of colistin resistance include colistin usage, previous colistin use, age of the patient, patients undergoing surgical procedures, duration of stay in ICUs, use of monobactams, and use of antifungal agents (Yau et al. 2009; Sharma et al. 2022). Further, the prevalence of colistin resistance among Gram-negative bacteria varies widely depending on the geographic area, duration, antimicrobial susceptibility dynamics, and method of antimicrobial testing. In this study, we hypothesized that the prevalence of colistin resistance in MDR-GNB would be significantly higher in our study population than in the domestic and global average. In addition, demographic factors like age, gender, residence, and educational level would significantly impact the prevalence of colistin resistance in MDR-GNB. Additionally, the presence of underlying comorbidities like diabetes, chronic kidney disease, or chronic obstructive pulmonary diseases would be linked to a higher risk of colistin-resistant MDR-GNB infections. To our knowledge, this is the first study investigating the risk factors and antimicrobial susceptibility dynamics from the Northern region of Haryana, India. In light of the above factors, we undertook a study to examine the dynamics of antimicrobial susceptibility and identify various risk factors associated with infections caused by colistin-resistant bacteria within our study settings.

The demographic characteristics and risk factors associated with colistin-resistant Gram-negative bacteria are depicted in Fig. 3 and Table II. Patients aged between 41 and 60 were infected with colistin-resistant bacteria compared to those in other age groups when comparing the patients’ age group. Moreover, while comparing the differences between genders, male patients had a more significant percentage of GNB resistant to colistin than females. Additionally, an association between the isolation rate of MDR GNB and colistin resistance was noted among females (p = 0.2439). Patients living in urban settings showed a higher proportion of colistin resistance when compared to patients living in rural areas (Table II). Patients with intermediate levels of education had a more significant percentage of colistin resistance compared to patients with different educational qualifications. Within the risk variables associated with colistinresistant Gram-negative pathogens, all the colistinresistant Gram-negative bacteria were found in patients who stayed in the hospital for more than five days. In diabetic individuals, colistin-resistant bacteria were identified at a rate of 56%, followed by chronic obstructive pulmonary disease (19%) and chronic renal disease (7%), respectively.

Fig. 3.

Flowchart showing the study schedule.

*MDR – multidrug resistance, **PCR – polymerase chain reaction

Out of the 12,652 samples processed, 79% (n = 9,591) were sterile or showed no growth in culture. Conversely, 24% (n = 3,061) showed growth of pathogenic organisms, wherein 7.0% (n = 824) and 18% (n = 2,237) were Gram-positive bacteria and Gram-negative bacteria, respectively. Of 2,237 total Gram-negative bacteria, 45% (n = 995) were MDR-GNB and 56% (n = 1,242) were non-MDR GNB. Table III shows the distribution of multidrug-resistant and colistin-resistant GNB in various samples. The majority (56%) of MDR-GNB isolates were recovered from urine samples, followed by sputum (15%), pus (14%), blood (11%), wound swab (3%), endotracheal aspirate (0.2%), and high vaginal swab (0.01%), respectively. In the current study, 995 MDR GNB isolates were analyzed for colistin resistance across various bacterial species. It was noted that E. coli was the most frequently isolated species, accounting for 48% (481/995) of the total MDR-GNB isolates. Of these, 16 isolates (3%) demonstrated resistance to colistin (chi-square test, p < 0.0001). The second most common MDR GNB was Klebsiella spp., which represented 28% (280/995) of the MDR-GNB isolates, with 13 isolates (5.0%) showing resistance to colistin (chi-square test, p < 0.0001). This is followed by 16% (163/995) of Pseudomonas spp. with 19 isolates (12%) being colistin-resistant (chi-square test, p < 0.0001), 7% (70/995) of Acinetobacter spp. with eight isolates (11%) exhibiting colistin resistance (chi-square test, p < 0.0001), and 0.10% (1/995) Citrobacter freundii,% the least frequent isolate, was completely colistin-resistant (100%), respectively.

In the current study, 29% of MDR-GNB were isolated from outpatient department (OPD) patients, while 71% were sourced from the inpatient department. Figure 4 illustrates the distribution of MDR-GNB isolated from different clinical specimens collected across various inpatient departments. Table IV shows the antibiotic-resistance pattern of MDR-GNB. It was noted that most of the Enterobacterales showed resistance to cefotaxime when the antimicrobial resistance pattern of the MDR-GNB was analyzed. Nevertheless, most of the P. aeruginosa strains were resistant to cefepime (Table IV). Conversely, most of the strains of Acinetobacter spp. were resistant to imipenem. The colistin minimum inhibitory concentration (MIC) was determined for all the MDR-GNB isolates and ranged between ≤ 0.5 μg/ml to 16 μg/ml, with the majority of the isolates showing a MIC value of ≥ 0.5 μg/ml (Table V). Of the total 57 colistin-resistant isolates obtained, the majority of the isolates (n = 39) showed a MIC value of 4 μg/ml. Eleven isolates showed a MIC value of 8 μg/ml, while seven had a MIC of ≥ 16 μg/ml. The predominant colistin-resistant bacteria were P. aeruginosa (33%), followed by E. coli (28%), K. pneumonia (23%), Acinetobacter spp. (14%), and C. freundii (2%). All colistin-resistant organisms were tested negative for mcr genes (mcr-1 to mcr-5) using multiplex PCR. Table VI demonstrates that most of the colistin-resistant Gram-negative isolates were susceptible to amikacin, followed by gentamycin when comparing the antibiotic susceptibility patterns.

Fig. 4.

Distribution of multidrug-resistant Gram-negative bacilli isolated from different clinical specimens collected across various inpatient departments.

Colistin has been considered the last resort for treating multidrug-resistant bacteria, but the emergence of colistin resistance in recent years has alarmed clinicians. Several risk factors have been investigated by researchers, including repeated antibiotic exposure (especially from beta-lactam antibiotics), invasive medical procedures, the excessive and improper application of colistin as a growth promoter in agriculture and animal husbandry, and the isolation of wastewater-borne bacteria resistant to colistin (Sharma et al. 2022; Yuan and Pian 2023). Therefore, it is essential to study the risk factors, co-morbidities, and antimicrobial susceptibility patterns of colistin-resistant bacteria to restrict the further spread of colistin resistance. The findings of our study highlight the significant influence of demographic variables on the prevalence of colistin-resistant GNB (Table II). The current study found an association between age, gender, education level, and colistin resistance. Specifically, the 41–60 age group showed notably higher colistin resistance rates among patients. This was consistent with earlier research, thereby highlighting the vulnerability of this particular age group to MDR bacterial infections (Mondal et al. 2024). The study also noted a gender gap, as males had a higher colistinresistant GNB prevalence than females. This aligns with findings from another study indicating a consistent gender-related correlation with colistin resistance across multiple studies (Panigrahi et al. 2022). Further, the study found a clear urban-rural divide in colistin resistance, with urban areas showing higher prevalence than rural areas. This would probably be due to the increased availability and over-usage of antibiotics in urban areas. Additionally, we observed a notable association between education level and colistin resistance, with patients with up to intermediate-level education exhibiting a higher proportion of colistin-resistant GNB than those with higher education levels. This finding underscores the complex interplay between the level of education and antimicrobial resistance; more specifically, patients with higher education are aware of the development of antimicrobial resistance and its serious complications. Moreover, the current study identified prolonged hospital stays (> 5 days) as a significant risk factor for colistin-resistant GNB. Diabetic patients showed the highest incidence, followed by those with chronic obstructive pulmonary disease and chronic renal disease. These findings highlight the importance of considering specific patient populations and clinical contexts in combating the spread of colistin resistance.

Out of 12,652 clinical samples examined, 3,061 (24%) showed growth of pathogenic bacteria. Of these pathogens, 27% (n = 824) were found to be Gram-positive bacteria, while 73% (n = 2,237) were found to be Gram-negative bacteria, respectively. This finding followed earlier research wherein the investigators found that Gram-negative bacteria accounted for a significant portion of the infections and were often resistant to multiple antibiotics (Chakraborty et al. 2023). In the current investigation, 2,237 Gram-negative bacteria were identified from all specimens processed. Among these, 44% were MDR-GNB, and 56% were non-MDR-GNB. This finding validates a previous report from Egyptian patients, indicating a consistent geographical distribution globally (El-Kholy et al. 2021). However, a study conducted among cancer patients in the Eastern part of India reported the distribution of MDR (48%), extensive drug resistance (30%), and non-MDR-GNB (20%), respectively (Shelke et al. 2024), aligning with our findings and highlighting a consistent pattern of antimicrobial resistance across Indian geographies.

The results of the current study demonstrate that E. coli is the most often isolated MDR-GNB from clinical samples, followed by K. pneumoniae (Table IV). The isolation of MDR-GNB is a significant issue in clinical settings since these bacteria are often resistant to multiple antibiotics and can cause severe life-threatening conditions. Therefore, appropriate and timely investigations are needed to determine the best action to prevent MDR-GNB from spreading throughout hospitals. This study possesses a few limitations: a) single-center study design – the current study was conducted at a single hospital in Haryana, India, limiting the availability of information on colistin resistance across various geographies; b) selection bias of patients since the current study included 71% MDR-GNB from hospitalized patients (usually possess co-morbid conditions or severe MDR bacterial infections) rather than patients treated at outpatient clinics – this could skew the results of the current study toward higher rates of MDR bacterial infections and colistin resistance; c) sampling bias – the current study analyzed samples collected from various departments within a single hospital, this may lead to sampling bias because patients in the critical care units might have been suffering from severe preexisting infections compared to patients in other units/wards; d) the crosssectional study design of the current study minimizes the insights about the causal relationship between the risk factors and the development of colistin resistance. This is because the cross-sectional study designs analyze the association between risk factors and resistance for a particular period. However, a longitudinal study design that tracks the patients over a while would help in understating the dynamics of resistance acquisition.

Of the total MDR-GNB (n = 995) isolated in the current study, 71% were isolated from the inpatient department. MICU had the most isolations, followed by emergency, urology, and respiratory departments, ICCU, and SICU. On the other hand, a study conducted in a tertiary care teaching hospital in central India revealed most of the GNBs isolated from different medical and surgical wards (57%), followed by ICU (26%) and OPDs (17%), respectively (Soni et al. 2023). This difference in the prevalence of distribution of MDR GNB may be attributed to the difference in the geographical locations. However, we could not compare studies conducted in North Indian settings because of the scarcity of literature. Various studies have consistently reported the isolation of colistin-resistant bacteria from different hospital settings. These studies have also highlighted variations observed across different departments and sample types (Sinha et al. 2019; Panigrahi et al. 2022; Soni et al. 2023). In the current study, the most colistin-resistant bacteria were isolated from pus samples (21%), followed by blood, sputum, urine, and a wound swab, respectively (Table III). Consistent with our findings, another research group also observed a high prevalence of MDR-GNB in a study conducted in central India (Soni et al. 2023). Nonetheless, other studies conducted in two distinct locations in India have demonstrated a higher isolation rate of colistinresistant bacteria from blood, exudates, and urine, as well as from sputum and pus samples, respectively (Sinha et al. 2019; Panigrahi et al. 2022).

Antibiotic resistance patterns differ from one bacterial species to another, from genus to genus, and also among different families. It is evident from Table IV that most Enterobacterales were resistant to cefotaxime whereas most of the Pseudomonas spp. showed resistance to cotrimoxazole followed by cefotaxime. In contrast, the majority of the Acinetobacter strains were resistant to imipenem. Further, it was noted that most of the strains in the current study were susceptible to amikacin. These findings were inconsistent with the earlier studies conducted in India wherein the highest resistance among Gram-negative isolates was found to be against cefotaxime.

In contrast, the lowest resistance was found against imipenem (particularly isolates obtained from blood samples) (Shah et al. 2022). In contrast, substantial levels of resistance to ciprofloxacin and cefotaxime were noted against E. coli and K. pneumoniae, particularly isolates obtained from UTIs (Verma et al. 2023). This result was coherent with the current investigation, which found that more of the bacterial isolates had ciprofloxacin resistance (Table IV). This probably could be due to the intake of ciprofloxacin as a prophylactic agent in the treatment of recurrent UTIs in communities, which would have spread the resistance genes of ciprofloxacin in the communities to emerge as ciprofloxacin-resistant strains. This finding underlines the significance of improved monitoring of antimicrobial resistance patterns in the hospital. Further, better antimicrobial monitoring and antimicrobial stewardship programs in hospitals can contribute to improved antibiotic usage in the community in several ways, including: a) primarily education of healthcare workers about antimicrobial resistance and proper use of antibiotics, b) reduction of the emergence and spread of antibiotic-resistant bacteria, and c) optimization of antibiotic prescriptions by healthcare workers. Indeed, healthcare professionals’ greater understanding of antimicrobial resistance and its use can extend beyond hospital walls, reaching primary care providers and the community. The increased awareness about antibiotic resistance and the importance of responsible antibiotic use can lead to more informed decision-making by patients and healthcare providers in community settings.

Knowledge of the MIC values for colistin against MDR-GNB is essential for optimizing treatment strategies against these bacterial pathogens. In the current study, 6% (n = 57) of colistin-resistant MDR GNB were isolated from the total MDR-GNB (n = 995). However, none of the isolates harbored the mcr gene. This suggests that alternate mechanisms like chromosomal mutations or efflux pump proteins may exist in the bacteria to contribute to antimicrobial resistance (Table V). In the current study, the MICs of these bacteria varied between ≥ 0.5 μg/ml and ≤ 16 μg/ml, with most isolates demonstrating MICs ≥ 0.5 μg/ml. These results are consistent with previous studies conducted in India’s Southern, Central, and Eastern regions, suggesting a similar pattern in the Northern part of Haryana, India (Aarthi et al. 2020; Panigrahi et al. 2022).

The sensitivity pattern of colistin-resistant Gramnegative bacteria to various antibiotics is critical in combating bacterial infections. The current study presents a comprehensive overview of antibiotic sensitivity across different bacterial strains, highlighting both promising and challenging aspects of treatment. When analyzing the susceptibility pattern of colistin-resistant E. coli, K. pneumoniae, P. aeruginosa, Acinetobacter spp. and C. freundii, amikacin and gentamicin consistently demonstrated high sensitivity across most bacterial strains, while cephalosporins such as cefotaxime, ceftriaxone, and cefepime showed lower efficacy (Table VI). This variation in sensitivity underscores the necessity of modified treatment approaches based on bacterial species. For instance, while amikacin and gentamicin were effective against E. coli and Acinetobacter spp., their efficacy against K. pneumoniae and P. aeruginosa was more variable. Despite the promising efficacy of antibiotics like amikacin and gentamicin, there remains a need for more extensive research to validate these findings and optimize treatment strategies. Factors such as variations in bacterial strain and local antibiotic sensitivity patterns can significantly impact treatment outcomes. Future studies should focus on evaluating the efficacy of different antibiotics across diverse bacterial strains to identify the most effective antibiotic regimens for colistin-resistant Gram-negative bacterial infections. This research will enhance our understanding of antibiotic resistance mechanisms, help clinical practice, and improve patient outcomes. In summary, this study underlines a significant presence of multidrug-resistant and colistin-resistant Gram-negative pathogens in inpatient settings, with patterns paralleled across regional hospitals, highlighting the urgent need for robust infection control practices, targeted antibiotic stewardship programs, and comprehensive regional surveillance systems. High resistance rates to key antibiotics like cefotaxime, cefepime, and imipenem reveal the importance of these measures, especially in high-risk hospital areas, to improve treatment protocols and support effective policy decisions. Colistin resistance, particularly in P. aeruginosa, is concerning for patients with prolonged hospital stays, although amikacin and gentamicin provide alternative treatment options. Notably, none of the colistin-resistant strains in this study harbored mcr genes, indicating possible alternative resistance mechanisms. Therefore, judicious antibiotic use and public education are imperative to control further resistance spread and optimize therapeutic outcomes.