Part Ⅰ The Usage Of Antibiotics By COVID-19 Patients With Comorbidities: The Risk Of Increased Antimicrobial Resistance

Abstract

Antimicrobial resistance (AMR) is a global health issue that plays a significant role in morbidity and mortality, especially in immunocompromised patients. It also becomes a serious threat to the successful treatment of many bacterial infections. The widespread and irrelevant use of antibiotics in hospitals and local clinics is the leading cause of AMR. Under this scenario, the study was conducted in a tertiary care hospital in Lahore, Pakistan, from 2 August 2021 to 31 October 2021 to discover the prevalence of bacterial infections and AMR rates in COVID-19 patients admitted in surgical intensive care units (ICUs). Clinical samples were collected from the patients and we proceeded to identify bacterial isolates, followed by antibiotic susceptibility testing (AST) using the Kirby Bauer disk diffusion method and minimum inhibitory concentration (MIC). The data on other comorbidities were also collected from the patient’s medical record. The current study showed that the most common pathogens were E. coli (32%) and Klebsiella pneumoniae (17%). Most E. coli were resistant to ciprofloxacin (16.8%) and ampicillin (19.8%). Klebsiella pneumoniae were more resistant to ampicillin (13.3%) and amoxicillin (12.0%). The most common comorbidity was chronic kidney disease (CKD) and urinary tract infections (UTIs). Around 17 different types of antibiotics, carbapenem, fluoroquinolones, aminoglycoside, and quinolones, were highly prevalent in ICU patients. The current study provides valuable data on the clinical implication of antibiotics consumed by COVID-19 patients in SICUs and the AMR rates, especially with different comorbidities.

Keywords

antibiotic susceptibility; antimicrobial resistance pattern; antimicrobial stewardship; comorbidity; COVID-19; Cistanche's effects.

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Introduction

The pandemic of coronavirus disease 2019 (COVID-19) and antimicrobial resistance (AMR) are two simultaneous and interacting health concerns that provide significant learning opportunities. They may interact because, given the lack of particular therapies, there is a desire to employ current antimicrobials to treat critically ill COVID-19 patients [1]. The COVID-19 pandemic helps to illustrate the possible long-term effects of AMR, which is less severe but not less critical since their measurements and outcomes are comparable. Understanding how COVID-19 influences AMR trends and what to assume if they remain the same or increase in AMR will help us plan the next steps in addressing AMR [2].

COVID-19 infections have far exceeded bacterial co-infection and mortality rates compared to other common respiratory viral infections [2]. The co-infection of SARS-CoV-2 with other microbes, mainly bacteria, and fungus, is a determining factor in COVID-19 development, making diagnosis, treatment, and prognosis more complicated. In individuals with COVID-19, bacterial co-infection has been linked to disease progression and prognosis. This scenario increases the need for critical care units, antibiotic therapy, and mortality [3]. Unfortunately, due to their widespread use, we may face the emergence of multi-drug resistant (MDR) pathogens leading to reduced efficacy of most potent antimicrobials [3,4]. AMR is a global problem that poses a severe threat to the success of treating a wide range of bacterial infections and affects many hospitalized patients, and most probably becomes a serious threat to the patients who are admitted to the SICUs [5,6].

Overall, the selection and development of highly drug-resistant bacteria due to the increased use of antibiotics and disinfectants may impact the clinical prognosis of severe COVID-19 patients receiving emergency hospital care, resulting in poor patient outcomes [7,8]. In this context, highly and extensively drug-resistant organisms have been documented to cause significant co-infections in COVID-19 patients, and mortality has recently been recorded in situations when bacterial co-infections were reported in COVID-19 patients [9,10].

The bacterial co-infections that arise during SARS-CoV-2 infection must be identified and characterized in a timely fashion [11,12]. Several studies have looked into the prevalence of bacterial co-infections in COVID-19 patients, finding highly heterogeneous distributions (with differences of >50%) that can be attributed to clinical and epidemiological characteristics of each geographical location, as well as diagnostic methods and criteria, used [13–15]. As a result, a study of hospitalized patients might increase our understanding of how viruses and bacteria interact during severe disease and give detailed information on COVID-19 in our environment. Similarly, identifying the main sociodemographic and clinical factors linked to bacterial co-infection in COVID-19 patients is critical to prioritizing potential risk groups and institutional clinical and epidemiological surveillance programs to guide future etiological studies. Keeping in view the threat of high AMR rates in the COVID-19 pandemic, the current study was conducted to discover the prevalence of bacterial infections and AMR rates and other comorbidities with mortality rates in COVID-19 patients who were admitted to SICUs.

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Materials and methods

1. Ethical consideration

Before starting the research, ethical approval was obtained from the Human Research Ethics Committee, University of Central Punjab, Lahore, Pakistan. Before proceeding with the sample collection, written informed consent was obtained from the patient (or from the dependent if the patient was unstable). Studied patients have been followed up for the consumption of antibiotics from the day of admission to the day of discharge (recovery or death). The demographic data (age, gender), comorbidities, recommended antibacterial drugs, the total number of given antibacterial drugs, and the brand names were recorded in a pre-defined data collection sheet.

2. Sample Collection

The current study was conducted by the Department of Microbiology, Faculty of Life Sciences, University of Central Punjab, Lahore, collaborating with a tertiary care hospital in Lahore, Pakistan, from 2 August 2021 to 31 October 2021. A total of 856 COVID-19-positive patients (admitted to SICUs) were recruited for the current study. To include more patients, only one type of sample was collected from each patient. The respiratory samples including sputum (n = 165), tracheal aspirate (n = 156), bronchoalveolar lavage (n = 117), and pleural fluid (n = 3) were collected with other samples including urine (n = 238), wound swab (n = 102), blood (n = 60), Foley’s catheter tip (n = 6), pus swab (n = 6), and abscess (n = 3) to proceed further for bacterial cultures. The samples were collected under sterile conditions and strict standard operating procedures (SOPs). After sample collection, these were immediately transported to the Microbiology laboratory at the University of Central Punjab, Lahore, for further processing.

3. Isolation and Identification of Bacterial Isolates

All samples except urine were proceeded for Gram staining first to see the microscopic characteristics of bacteria and then, based on the sample type, inoculated (including urine samples) on blood, MacConkey, chocolate, and cysteine electrolyte deficient (CLED) agar media. After culture inoculation, the agar plates were incubated at 37 ◦C initially for 18 to 24 h. After the first incubation, the agar plates were observed for the appearance of bacterial colonies. In case there were no bacterial colonies, the plates were re-incubated for the second and third reading, respectively, except for blood cultures which were reinoculated and rechecked until the seventh day of sample collection. The negative plates were reported as having “No bacterial growth” while the positive bacterial cultures further proceeded for bacterial identification and AST.

The final bacterial identification was undertaken using Gram staining, the appearance of bacterial colonies on the agar plates, and biochemical identification. The colonies of Gram-positive bacteria proceeded to the catalase test first, and if the catalase test was positive, the colonies proceeded further for coagulase, DNAs, and Optochin disk tests, accordingly. However, the Gram-negative bacteria were first examined in terms of their appearance as lactose fermenters or non-fermenter and then proceeded to indole, citrate, and oxidase tests and the analytical profile indexing (API) biochemical identification kit.

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4. Antibiotic Susceptibility Testing (AST)

After the isolation and identification of the organisms, the AST was performed to check their antibiotic susceptibility patterns using a Kirby Bauer disk diffusion assay and MIC (where applicable) [16]. The bacterial colonies were first mixed in a pre-prepared 0.5% MacFarland standard solution to dilute colonies to check the susceptibility patterns. After the inoculum of the test organism, these were inoculated three-dimensionally into a Muller Hinton (MH) agar (MH) agar plate with the help of a sterile cotton swab.

The antibiotics were checked according to the clinical laboratory standards institute (CLSI) guidelines (2017) for each microorganism [16]. The antibiotics were dispensed on inoculated MH agar plates and incubated for 18 to 24 h at 37 ◦C. After the incubation period, the zone of inhibition was measured using a labeled measuring scale. The CLSI guidelines followed the zone of inhibition (measured in mm) for each of the antibiotics v/s organisms. The final AST results were noted as resistant, sensitive, or intermediate.

According to the CLSI guidelines (2017), the zone of inhibition for fosfomycin was only available to be reported in E. coli and Enterococcus faecalis isolates using the disk diffusion method. The sensitivity patterns were based on minimum inhibitory concentrations (MICs) for all other recommended bacterial isolates.

5. Statistical Analysis

The final data was recorded in Microsoft Excel and transferred to the SPSS version 26.0 (IBM, New York, NY, USA). The Frequencies and percentages were calculated from the recorded data. The association between the comorbidities and treatment outcome, type of bacterial infection, and severity of COVID-19 were analyzed using the Pearson Chi-square (X2) test where a p-value of <0.05 was considered statistically significant.

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Basit Zeshan 1, Mohmed Isaqali Karobari 2,3,4, Nadia Afzal 5, Amer Siddiq 6, Sakeenabi Basha 7, Syed Nahid Basheer 8, Syed Wali Peeran 9, Mohammed Mustafa 10, Nur Hardy A. Daud 11, Naveed Ahmed 1,12, Chan Yean Yean 12 and Tahir Yusuf Noorani 2.

1. Department of Microbiology, Faculty of Life Sciences, University of Central Punjab, Lahore 540000, Pakistan; dr.basitzeshan@ucp.edu.pk (B.Z.); naveed.malik@student.usm.my (N.A.)

2. Conservative Dentistry Unit, School of Dental Sciences, Universiti Sains Malaysia, Health Campus, Kubang Kerian, Kota Bharu 16150, Kelantan, Malaysia; tahir@usm.my

3 Department of Conservative Dentistry & Endodontics, Saveetha Dental College & Hospitals, Saveetha Institute of Medical and Technical Sciences University, Chennai 600077, Tamil Nadu, India

4 Department of Restorative Dentistry & Endodontics, Faculty of Dentistry, University of Puthisastra, Phnom Penh 12211, Cambodia

5 Basic Health Unit Hospital (BHU) Mora, Tehsil and District Nankana Sahib, Nankana Sahib 39100, Pakistan; nadia.afzal511@gmail.com

6 Faculty of Medicine, Riphah International University, Islamabad 46000, Pakistan; 5400@students.riphah.edu.pk

7 Department of Community Dentistry, Faculty of Dentistry, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia; sakeena@tudent.edu.sa

8 Department of Restorative Dental Sciences, College of Dentistry, Jazan University, Jazan 45142, Saudi Arabia; syednahidbasheer@gmail.com

9 Department of Periodontics, Armed Forces Hospital Jizan, Jazan 82722, Saudi Arabia; doctorsyedwali@yahoo.in

10 Department of Conservative Dental Sciences, College of Dentistry, Prince Sattam Bin Abdulaziz University, P.O. Box 173, Al-Kharj 11942, Saudi Arabia; ma.mustafa@psau.edu.sa

11 Faculty of Sustainable Agriculture, Universiti Malaysia Sabah, Sandakan Campus, Locked Bag No.3, Sandakan 90509, Sabah, Malaysia; nur.hardy@ums.edu.my

12 Department of Medical Microbiology and Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu 16150, Kelantan, Malaysia; yychan@usm.my