A descriptive analysis of antimicrobial resistance patterns of who priority pathogens isolated in children from a tertiary care hospital in india

ABSTRACT The World Health Organization (WHO) has articulated a priority pathogens list (PPL) to provide strategic direction to research and develop new antimicrobials. Antimicrobial

resistance (AMR) patterns of WHO PPL in a tertiary health care facility in Southern India were explored to understand the local priority pathogens. Culture reports of laboratory specimens

collected between 1st January 2014 and 31st October 2019 from paediatric patients were extracted. The antimicrobial susceptibility patterns for selected antimicrobials on the WHO PPL were

analysed and reported. Of 12,256 culture specimens screened, 2335 (19%) showed culture positivity, of which 1556 (66.6%) were organisms from the WHO-PPL. _E. coli_ was the most common

organism isolated (37%), followed by _Staphylococcus aureus_ (16%). Total of 72% of _E. coli_ were extended-spectrum beta-lactamases (ESBL) producers, 55% of _Enterobacteriaceae_ were

resistant to 3rd generation cephalosporins due to ESBL, and 53% of _Staph. aureus_ were Methicillin-resistant. The analysis showed AMR trends and prevalence patterns in the study setting and

the WHO-PPL document are not fully comparable. This kind of local priority difference needs to be recognised in local policies and practices. SIMILAR CONTENT BEING VIEWED BY OTHERS

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21 December 2022 INTRODUCTION Antimicrobial resistance (AMR) has been recognised as a major threat to global health1. According to the World Health Organization (WHO), mutations in

microorganisms resulting in AMR, which consequently render medicines ineffective and infections persist in the body, increasing the risk of spread to others1. There are many reasons behind

the development of AMR, ranging from microbial causes to human aspects such as overuse and over-prescription of antimicrobials, agricultural and commercial application of antimicrobials in

the animal sector, and human behavioural factors2. Our ability to treat common pathogens becomes challenging because of AMR, resulting in increased duration of illness, costs, number of

complications, and deaths. By 2050, an estimated 10 million deaths are projected to occur due to AMR3, while another study projected AMR to cost the global economy US$100 trillion, in the

same period4. In 2015, the 68th World Health Assembly endorsed the Global Action Plan on AMR to tackle this global challenge5. This action plan has five strategic actions, focusing on (1)

improving awareness and understanding of AMR; (2) strengthening AMR surveillance; (3) reducing the incidence of infections; (4) optimizing antimicrobial use; and (5) developing the economic

case for AMR control. To support the Global Action Plan, WHO has developed a priority pathogens list (PPL), through a consultative process6. The prioritization process involved

multi-criteria decision analysis (MCDA) which used information from multiple sources, including disease mortality, transmissibility, treatability, health care burden, preventability in

health care settings, and preventability in community settings, etc. Twelve families of drug-resistant bacteria, posing the greatest threat to human health, were categorized as critical,

high, and medium priority organisms, in terms of their resistance to selected antimicrobials (Fig. 1). Although this categorization was intended to prioritize and stimulate research and

develop new antimicrobials for specific drug resistance, it also makes a call for the prevention of infection and the rational use of antibiotics in both humans and animals6. Indian

population is known to be the highest consumer of antibiotics in the world7. The AMR situation in India has raised grave public health concerns8 and an action plan for its control is

considered crucial9,10. Given its importance for human health, the Government of India has developed a National Action Plan on Antimicrobial Resistance (NAP-AMR) 2017–202111. Strengthening

the knowledge and evidence base through surveillance of AMR is one of the five key strategies of this action plan. The Indian Council of Medical Research (ICMR) has established an

Antimicrobial Resistance Surveillance & Research Network (AMRSN) across selected hospitals in India, focusing on drug resistance among six pathogens12. However, not many hospitals

outside this network in India track AMR patterns among these pathogens. Generating AMR related evidence from a larger number of hospitals is critical for informed decision making on AMR

related policies and practices at local settings. This study explores the AMR susceptibility patterns for WHO priority pathogens identified in clinical isolates collected in the Paediatrics

Department of a tertiary care hospital in Southern India. The results of the culture tests are mainly availed for treatment purposes but are not systematically analysed on a routine basis.

The analysis of culture results could provide further evidence and guidance for the development of antimicrobial resistance control policy at the hospital and elsewhere. This analysis aims

to compare AMR patterns in WHO priority pathogens identified in a tertiary health care facility to understand the local priorities that can be applied to local policies and practices.

RESULTS A total of 12,256 culture specimens collected at paediatrics outpatient department and paediatrics inpatient wards were screened for bacteriological results, of which 2335 (19%)

showed culture positivity. Of these, 1556 were from the set of WHO PPL organisms. The largest number of bacterial isolation was seen in urine specimens (755/1556) followed by blood

(241/1556) (Table 1). _E. coli_ was the most common organism isolated (576), followed by _Staphylococcus aureus_ (252). Among the main WHO PPL organisms identified, 72% of _E. coli_ and 63%

of _Klebsiella_ spp. were resistant to 3rd generation cephalosporins due to extended-spectrum beta-lactamase (ESBL), and 53% of the _Staph. aureus_ were Methicillin-resistant (Table 2).

Overall, nearly half of _Enterobacteriaceae_ were resistant to carbapenem (46%) or 3rd generation cephalosporins due to ESBL (55%). The carbapenem resistance in _Pseudomonas aeruginosa_ was

found low (5%). Time trend analysis of selected WHO ‘Critical priority’ pathogens over the past 4 years showed a high proportion of resistance for carbapenem in _E coli_, _Klebsiella

pneumoniae,_ and _Enterobacter cloacae_ (Fig. 2). Similarly, _E. coli_ and _Klebsiella pneumoniae_ continued to show a high proportion of ESBL (Fig. 3). Among the WHO ‘High priority’

pathogens, _Staph. aureus_ continued to show a high proportion of methicillin-resistance (Fig. 4). Three of the WHO ‘High priority’ pathogens namely, _Helicobacter pylori_ (clarithromycin-

resistant), _Campylobacter_ spp. (fluoroquinolone-resistant), and _Neisseria gonorrhoeae_ (3rd generation cephalosporin-resistant and fluoroquinolone-resistant), were not detected in our

study specimens and antimicrobial sensitivity information was not available. Similarly, one of the WHO ‘Medium priority’ pathogen, _Haemophilus influenzae_ (ampicillin-resistant), was not

observed in this study, and antimicrobial sensitivity information was not available. DISCUSSION The 2017 guidance document of WHO indicated the highest carbapenem resistance worldwide in

_Acinetobacter baumannii_ (91%) and _Pseudomonas aeruginosa_ (82%), which is one of the reasons for classifying them as Critical Priority6 pathogens. The same study reported > 50%

carbapenem resistance in _Acinetobacter baumannii_, and 31% to 50% carbapenem resistance in _Pseudomonas aeruginosa_ in the Indian sub-continent in the general population. Early results from

the surveillance data from up to 22 ICMR-AMRSN sites in India showed around 80% carbapenem resistance in _Acinetobacter baumannii_ and around 30% in _Pseudomonas aeruginosa_12. However,

another study in children from Mumbai, India, identified only 15% of _Pseudomonas aeruginosa_ are resistant to carbapenem13 which is comparable to current study. The carbapenem-resistance in

_Acinetobacter baumannii_ and _Pseudomonas aeruginosa_ are 12% and 5% respectively in the current study in paediatric population. The WHO report6 identified high carbapenem resistance in

_E. coli_ (55%), _Klebsiella_ (70%), and _Enterobacter_ spp. (59%) in the general population, which is not far apart to the findings in this study in paediatric population. The ICMR-AMRSN

data also showed similar carbapenem resistance prevalence in _Klebsiella pneumoniae_ (40–50%) but a significantly lower level in _E. coli_ (15–25%) in the general population12. The ESBL

trends in _E. coli_ and _Klebsiella_ spp. (70–80%) as well as methicillin-resistance in _Staph. aureus_ (53%) were high in this study and comparable to the WHO report. However, due to the

low sample size of _Salmonella_ spp., _Shigella_ spp. and _Streptococcus pneumoniae_, it may not be appropriate to compare the results from this study to others. Several studies on AMR have

been published in India in recent years13,14,15. A retrospective 5 year follow-up study in a tertiary care hospital in North India showed increasing trends of AMR in urinary tract

infection-causing isolates14. Increasing trends of AMR was observed among gram negative isolates from samples collected across seven hospitals in India over 4 years, but the reported

carbapenem resistance prevalence in _Klebsiella_ spp. (39%) and _E. coli_ (12%) were lower than current study15. Among _Enterobacteriaceae_ isolated from a paediatric tertiary care hospital

in Mumbai, 24% were extended spectrum beta-lactamase (ESBL) producers and 27% were carbapenem-resistant isolates showing a lower resistance level than the current study13. As our study is

based on a retrospective dataset, it has several limitations. Although the health facility maintains a good quality of clinical and laboratory services along with proper documentation, one

cannot ensure that the quality checks in retrospective data are fully compatible with the highest quality standards of a well-conducted prospective study. Although the sample collection,

microbiological analysis, and report updates use standard procedures, it has likely been conducted by different people over the 5 year period, which may have had inter-personnel variations

on the quality of laboratory procedures. It is possible that at any given point of the study period new laboratory staff may have joined, may have taken time while undergoing training to

implement standardized procedures. Also, laboratory reports are manually entered into computerized system which is subject to human error and specific terms used during data entry are

subject to human variations. There were no standard inclusion criteria for sample collection as it was generally left to the discretion of the treating physician. In conclusion, among the

WHO PPL pathogens, _E. coli, Klebsiella species_, _Enterobacteriaceae, and Staph. aureus_ (methicillin-resistant) have high AMR in the study site. On the other hand, AMR patterns for

_Acinetobacter baumanni_, _Pseudomonas aeruginosa,_ and _Staph. aureus_ (vancomycin resistant) is lower than the WHO global estimates. These findings can guide local priorities, policy, and

practices. We recommend large health facilities to monitor and review emerging AMR patterns and trends periodically to prioritise, plan, and implement health facility level policies and

guidelines for the optimal use of antimicrobials. METHODS The study was conducted at the Yenepoya Medical College Hospital in Mangalore, South India. Typically, the Paediatric Department

collected around 2000 clinical specimens every year for culture tests from both outpatient and hospitalized cases. The sources and types of specimens collected for culture included blood,

urine, stool, pus, cerebrospinal fluid (CSF), sputum, and any other bodily fluids or other clinical specimens such as catheter, umbilical, and central line tips. As this is a retrospective

study, the sample selection for specimen collection was left to the discretion of the treating physician as sampling criteria was not predefined. The specimens were referred to the

laboratory in the Department of Microbiology for antimicrobial culture tests and antibiogram. The Kirby-Bauer disk diffusion method and/or by BD phoenix automated system were used for

performing antimicrobial susceptibility patterns and reported according to standard (Clinical Laboratory Standards Institute—CLSI) guidelines16,17,18,19,20. The confirmation of ESBL was done

as per the same CLSI guidelines. Once tests were performed, results were entered into the computer backbone system at the Department of Microbiology which was a specific database for the

tertiary hospital included in the study. The antibiogram reports generally covered the following antimicrobials: Carbapenem, Chloramphenicol, Cotrimoxazole, Nitrofurantoin, Piperacillin,

Piperacillin-Tazobactam, Tetracyclin, Tigecycline, Aztreonam, Amikacin, Gentamycin, Tobramycin, Ciprofloxacin, Levofloxacin, Norfloxacin, Cefoperazone, Ceftriaxone, Cefotaxime, Ceftazidime,

Cefepime, Cefazolin, Cefuroxime, Cefoxitin, Imipenem, Meropenem, Polymyxin B, and Colistin. The sample collection, microbiological analysis, and report entry on the computer were done on a

routine basis alongside the provision of healthcare services. These test results for antimicrobial susceptibility patterns were retrospectively accessed through the computer backbone system

during this study. Administrative permission to access laboratory culture records was obtained from Yenepoya Medical College. Retrospective culture reports between 1st January 2014 to 31st

October 2019 from various clinical specimens were extracted from the computer backbone system. The culture access numbers for all specimens with positive results were used to track the

antibiogram (i.e., which antibiotics were tested, and which were susceptible or resistant) results. The antibiogram for all culture isolates was extracted. Culture access numbers were also

used to track the culture source and the date of sample collection to the antibiograms. Culture reports of all paediatric cases were included in the study, irrespective of the location of

sample collection, namely: outpatients, inpatient wards, and neonatal and paediatric intensive care units (ICUs). The laboratory reports indicating contamination were excluded at data entry.

The reports containing duplicate or repeat samples, from the same source and subject, were also excluded so that the results for the same pathogens are not duplicated or repeated in the

analysis. Pathogens other than those in the WHO PPL were excluded from the analysis. The antimicrobial sensitivity tests other than the ones listed in WHO PPL were also excluded from the

analysis. Some of the WHO PPL pathogens were not included in this study as culture specimens were collected from children which do not generally include genitourinary swabs or gastric biopsy

specimens suitable for the culture of _Neisseria gonorrhoeae_ or _Helicobacter pylori_. Similarly, _Campylobacter_ spp. was also not identified in the specimens either because of low

incidence or because samples collected may not be best suited for its isolation. The data entry and analysis were performed on Microsoft Excel. The data from the computer backbone was

entered directly on a master Excel sheet followed by the removal of duplicates. De-identified data were organised by specimen types (such as blood, urine, etc.) in chronological order of

specimen collection date. A list of WHO PPL bacterial pathogens isolated were prepared by their species (such as _E coli_), specimen type, and resistance patterns. The list classified

pathogens into three main groups (Critical Priority, High Priority, and Medium Priority) for selected antimicrobials, based on WHO PPL (Fig. 1). The PPL defines the priority of pathogens

based on resistance to specific antimicrobials such as carbapenems, 3rd generation cephalosporins, vancomycin, methicillin, penicillins, or fluoroquinolones. A table presenting the number of

organisms isolated in the study site by specimen type was prepared. Another table was prepared to present selected AMR patterns in specific pathogens as defined by WHO PPL. Time trend

graphs were prepared for some key pathogens. ETHICAL ISSUES This study did not involve human subjects directly. An approval from the scientific and ethics committees of Yenepoya Medical

College (Name: _Yenepoya Ethics Committee-1_) was obtained for this study. The _Yenepoya Ethics Committee-1_ waived the need for participants to provide informed consent. To maintain

confidentiality, no identifiable information such as names, addresses, or phone numbers of subjects were collected. The data set, once finalised, was delinked from culture access numbers

before analysis, to retain confidentiality. ETHICS APPROVAL AND CONSENT TO PARTICIPATE The _Yenepoya Ethics Committee-1_ waived the need for participants to provide informed consent as

described under the manuscript. This study did not involve human subjects directly, no consent process was involved. All methods were carried out in accordance with relevant guidelines and

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Download references ACKNOWLEDGEMENTS We thank Mr. Satyajit Sarkar for editing and Ms. Athira Ramesh for research support. FUNDING This research was funded by the International Vaccine

Institute by the Swedish International Development Cooperation Agency [5410054] and the Bill & Melinda Gates Foundation. The International Vaccine Institute acknowledges its donors

including the Republic of Korea and the Republic of India. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Department of Paediatrics, Yenepoya Medical College, Mangalore, India Vijayalaxmi V.

Mogasale & Prakash Saldanha * Department of Microbiology, Yenepoya Medical College, Mangalore, India Vidya Pai * Yenepoya Research Centre, Yenepoya (Deemed to be) University, Mangalore,

India P. D. Rekha * Policy and Economic Research Department, International Vaccine Institute, Seoul, South Korea Vittal Mogasale Authors * Vijayalaxmi V. Mogasale View author publications

You can also search for this author inPubMed Google Scholar * Prakash Saldanha View author publications You can also search for this author inPubMed Google Scholar * Vidya Pai View author

publications You can also search for this author inPubMed Google Scholar * P. D. Rekha View author publications You can also search for this author inPubMed Google Scholar * Vittal Mogasale

View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS V.V.M. served as Principal Investigator for this study and took overall responsibility for

protocol development, study design, ethics approval, data collection, analysis, and drafted the manuscript. V.M. conceptualized the study design, guided data extraction, analysis, and edited

the manuscript. P.S., V.S., and R.P.D. provided institutional support in data collection, expert advice, and contributed to the manuscript. All authors have approved the final version of

the manuscript. CORRESPONDING AUTHOR Correspondence to Vittal Mogasale. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION

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al._ A descriptive analysis of antimicrobial resistance patterns of WHO priority pathogens isolated in children from a tertiary care hospital in India. _Sci Rep_ 11, 5116 (2021).

https://doi.org/10.1038/s41598-021-84293-8 Download citation * Received: 19 July 2020 * Accepted: 09 February 2021 * Published: 04 March 2021 * DOI:

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