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Table of Contents
ORIGINAL ARTICLE
Year : 2022  |  Volume : 11  |  Issue : 4  |  Page : 228-233

Device-associated healthcare-associated infections surveillance in an intensive care unit of a tertiary care hospital in COVID-19 patients


1 Department of Microbiology, Government Institute of Medical Sciences, Greater Noida, Uttar Pradesh, India
2 Department of Anaesthesia, Government Institute of Medical Sciences, Greater Noida, Uttar Pradesh, India
3 Department of Medicine, Government Institute of Medical Sciences, Greater Noida, Uttar Pradesh, India

Date of Submission05-Apr-2022
Date of Decision07-Jun-2022
Date of Acceptance08-Jun-2022
Date of Web Publication27-Oct-2022

Correspondence Address:
Savita Gupta
Assistant Professor, Department of Anaesthesia, Government Institute of Medical Sciences, Greater Noida 201 310, Uttar Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jcsr.jcsr_56_22

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  Abstract 


Background: Surveillance for healthcare-associated infections has a major role in hospital infection prevention and control programmes. In the present study, we estimated the impact of the COVID-19 pandemic on device-associated healthcare-associated infections (DA-HAI) ventilator-associated events (VAE), central line-associated bloodstream infection (CLABSI) and catheter-associated urinary tract infections (CAUTI).
Methods: This was a prospective surveillance study from January 2021 to June 2021 conducted in a 30-bed intensive care unit (ICU) of tertiary care, and academic healthcare organisations. Targeted surveillance was carried out by the National Healthcare Safety Network surveillance requirements of the Centers for Disease Control and Prevention.
Results: A total of 249 patients admitted to the ICU with 2920 patient days of surveillance data were included during the study. A DA-HAIs attack rate of 17.67/100 admissions was seen during the study. The device utilisation ratios of central line, ventilator and urinary catheters were 0.49, 0.60 and 0.83, respectively. VAE, CLABSI and CAUTI rates were 12.44, 6.91 and 9.01/1000 device days, respectively. Among 54 DA-HAIs reported, pathogens could be identified for 41 DA-HAI cases. The most common organisms causing VAE, CAUTI and CLABSI were Acinetobacter baumannii (42.1%), Escherichia coli (30%) and Pseudomonas aeruginosa (41.7%), respectively. Of the Gram-negative organisms 61.7% were carbapenem resistant and 50% of Staphylococcus aureus were methicillin resistant.
Conclusions: The present study shows high rates of ICU-acquired DA-HAIs and moderately high resistance patterns of the organisms causing HAIs, which poses a great risk to patient safety.

Keywords: Catheter-associated urinary tract infection, central line-associated bloodstream infection, COVID-19, device-associated healthcare-associated infections, ventilator-associated event


How to cite this article:
Goel V, Gupta S, Manocha H, Srivastava S. Device-associated healthcare-associated infections surveillance in an intensive care unit of a tertiary care hospital in COVID-19 patients. J Clin Sci Res 2022;11:228-33

How to cite this URL:
Goel V, Gupta S, Manocha H, Srivastava S. Device-associated healthcare-associated infections surveillance in an intensive care unit of a tertiary care hospital in COVID-19 patients. J Clin Sci Res [serial online] 2022 [cited 2022 Dec 5];11:228-33. Available from: https://www.jcsr.co.in/text.asp?2022/11/4/228/359809




  Introduction Top


The 2019 coronavirus pandemic (COVID-19) has had an immense impact on medical management worldwide.[1] Widespread and sustained transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) throughout COVID-19 led to high hospitalisation charges and a rapid increase in general hospital capacity to control a sudden and unexpected inflow of intensive care unit (ICU) patients.[2] To manage this unexpected pressure and provide adequate care during the emergency, most ICUs were reorganised.[3] The increase in ICU beds, reallocation of resources and shortage of medical staff may have hurt routine infection control in the hospital.[4] Therefore, the prevention of hospital-acquired infections (HAI) in COVID-19 patients is more important than ever because secondary nosocomial infections can increase morbidity and mortality. As per one study from the USA, the increase in COVID-19 has a negative impact on HAI levels and hospital infection rates, underscoring the need to balance COVID-related requirements and routine hospital infection prevention.[5] However, some studies suggest that infection prevention and control protocols first introduced to control SARS-CoV-2 transmission have a positive, indirect and unintended role in preventing HAI.[6],[7] HAI had been observed to be the most common reason for increased morbidity, mortality and cost among inpatients, especially in ICUs.[7] Surveillance of device-associated healthcare-associated infections (DA-HAI) in ICU plays a vital function in hospital infection control and quality assurance.[8],[9]

Continuous efforts are required to reduce morbidity and mortality associated with HAIs. The incidence of HAI in India is 6–40/1000 patient days, and the most common pathogen associated with HAI is multidrug-resistant Gram-negative bacteria.[10],[11] DA-HAI depends on the duration and frequency of equipment used in the ICU, infection control protocols and the immune constitution of patients. According to reports of patients hospitalised for COVID19, 10%–33% develop bacterial pneumonia and 2%–6% develop bloodstream infection (BSI).[5],[12] Although COVID-19-related deaths occurred mainly in the aged with severe underlying diseases, nosocomial pneumonia remains an important risk factor for patients in the ICU, and patients' health status, especially if intubated, may deteriorate in the presence of lower respiratory tract infections.

In COVID-19 hospitalised patients, the risk of ventilator-associated events (VAE) has the potential to worsen clinical status and increase mortality in these patients, as well as prolong and increase the cost of hospitalisation.[13] Moreover, despite the frequent use of multiple invasive devices in COVID-19 patients, most studies have focused on evaluating the microorganisms that cause HAI,[14],[15] and less on HAI types. There is no major study from the Indian subcontinent. This study aims to determine the rates of VAE, central line-associated BSI (CLBSI) and catheter-associated urinary tract infections (CAUTI) occurring in the ICU and the antibiotic resistance patterns of the causative agents of HAI, which may pose a major risk to patient safety in COVID-19 patients.


  Material and Methods Top


This prospective study was done on patients admitted to the 30-bed multidisciplinary dedicated COVID-19 ICU of a 500-bed tertiary care hospital in North India, over 6 months from January 2021 to June 2021. Permission to conduct the study was obtained from the Institutional Ethics Committee and the study was also registered with the Clinical Trial Registry-India (CTRI/2021/03/032361).

Our microbiology department performs culture identification and sensitivity with conventional as well as automated equipment such as the BACTEC™ Blood Culture System (BD, Franklin Lakes, United States) and VITEK® 2 compact identification and sensitivity system (bioMérieux, Inc, Marcy-l'Étoile, France) based on the Clinical and Laboratory Standards Institute guidelines.[16] We have a hospital infection control committee comprising infection control nurses (ICNs), an infection control officer and quality champion nurses for each ward and specialised area. ICNs and quality champions were trained monthly in regular batches on HAI surveillance including hand hygiene, and bundle care with ICU rounds. In our hospital, the process surveillance component of DA-HAI includes the following modules: hand hygiene compliance monitoring in ICUs, central vascular catheter care compliance monitoring, urinary catheter care compliance monitoring and monitoring of compliance with measures to prevent VAP. Components of the VAP prevention bundle included 30°–45° elevation of the head of patients, daily 'sedation interruption' and daily assessment of readiness to extubate, stress ulcer prophylaxis, deep vein thrombosis prophylaxis, cuffed endotracheal tube, subglottic suctioning, endotracheal cuff pressure of at least 20 cm and condensate in ventilatory circuits. Components of the CAUTI prevention bundle included maximal barriers precautions when the catheter was inserted, single-use lubricant, closed sterile drainage system, urinary catheter above the leg, urinary collecting bag below the level of the bladder, urinary catheter never disconnected and urinary collecting bag with <75% of capacity full. Components of CLABSI prevention bundle included hand hygiene compliance before catheter insertion or manipulation, maximum sterile precaution barrier during insertion, skin cleaning with alcohol-based chlorhexidine, daily review of central line necessity, presence of sterile dressing, single-use flushing, type of bag container for intravenous infusion, daily bath with a 2% chlorhexidine-impregnated washcloth. In the COVID-19 reverse transcriptase-polymerase chain reaction (RT-PCR) laboratory approved by the Indian Council of Medical Research, samples from suspected COVID-19 cases were received for COVID-19 testing.

Inclusion criteria were COVID-19 patients confirmed with RT-PCR admitted to ICU and hospitalised for more than 48 H. All patients admitted for <48 h, who tested positive for bacterial infection within 48 h, or who had signs of existing bacterial infection on admission were excluded. Verbal oral and written informed consent was taken from the study participants or their legal representatives. ICU rounds were conducted daily by a multidisciplinary team of the infection control practitioners and targeted surveillance was conducted for 3 DA-HAI: CAUTI, CLABSI and VAE. Surveillance definitions for these DA-HAIs were aligned with the Centers for Disease Control and Prevention 2017 National Healthcare Safety Network surveillance criteria.[17] The date of insertion and the date of removal of each device were recorded, to calculate the number of device days. The monitoring form recorded patient demographics, acute and chronic health status assessment, the reason for admission, key examination findings and patient outcomes. Data collected included the following: (i) Patient days: Total number of days all patients were in the ICU during the selected period; (ii) Device days: Total number of days all patients were exposed to each device during the selected period; (iii) DA-HAI rate: Number of specific device-associated infections per 1000 device days; and (iv) Device utilisation ratio: The number of device days divided by the number of patient days. To determine device-associated infections, the following protocols were used. Blood samples were collected if a BSI was suspected. In CLABSIs suspected patients, the central venous catheter was removed aseptically and the distal 4 cm of the catheter was disconnected and cultured. For CAUTIs, under aseptic conditions, urine samples were collected from the urine sample port. For VAE, aerobic bacteria quantitative cultures were performed on samples of lower respiratory tract secretions of tracheal aspirate. Under the VAE surveillance tool are three nested tiers. A ventilator-associated condition (VAC) comprises the first tier and includes all patients with clinically significant pulmonary complications, irrespective of whether inflammation or infection may be the contributing factors. The second tier, infection-related ventilated-associated complications, is reached when VAC criteria are met in addition to signs of leucocytosis, abnormal temperature and commencement of antimicrobials. Progression to the third tier occurs when evidence exists of a pulmonary source of infection and is called probable or possible ventilator-associated pneumonia.

Statistical analysis

Continuous variables are presented as median (interquartile range). Continuous variables were compared using the Mann–Whitney U test. Categorical variables were compared using the Fisher's exact test. Statistical analysis was performed using SPSS version 21 (SPSS for Windows; SPSS Inc., Chicago, IL, USA).


  Results Top


During the study, a total of 249 COVID-19 patients were admitted to the ICU. The surveillance data were reported over 2920 patient days. [Table 1] shows the total number of unit days, the number of patients with DA-HAIs and the incidence of DA-HAIs per 1000 patient days.
Table 1: Device-associated infections per 1000 device-days: Ventilator-associated pneumonia, central line-associated bloodstream infection and catheter-associated urinary tract infections

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Fifty-four DA-HAI episodes were identified from 44 separate admissions, resulting in an incidence of 15.06/1000 patient days. A DA-HAIs attack rate of 17.67/100 admissions was seen during the study. The device utilisation ratios of central line, ventilator and urinary catheters were 0.49, 0.60 and 0.83, respectively. VAE, CLABSI and CAUTI rates were 12.44, 6.91 and 9/1000 device days, respectively.

Of the 54 DA-HAIs episodes in the present study, bacterial isolates were identified in 41 DA-HAI cases. [Table 2] shows the distribution of pathogens and the resistance pattern identified. Acinetobacter baumannii was the most common organism isolated in 31.7% of DA-HAI, followed by Pseudomonas aeruginosa in 24.39% of cases. The most common organisms causing VAE, CAUTI and CLABSI were A. baumannii (42.10%), Escherichia coli (30%) and P. aeruginosa (41.7%), respectively. About 61.7% of the Gram-negative organisms were carbapenem resistant and 50% of Staphylococcus aureus were methicillin resistant. In A. baumannii and Ps. aeruginosa, 100% resistance to amikacin was found, while resistance to carbapenem was lower in E. coli and Klebsiella but higher in A. baumannii (76.9%).
Table 2: Distribution of pathogens and antibiotic resistance associated with DA-HAI cases in the intensive care unit

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  Discussion Top


There is an important need to identify an approach to make sure the continual of standard infection prevention programmes even in times of public health crises. This study used a standardised monitoring methodology to determine DA-HAI rates in COVID-19 ICU patients. A total of 249 patients were admitted during the study with 54 episodes of device-associated nosocomial infections. The DA-HAIs attack rate was 17.7/100 admissions and the incidence of DA-HAI rate of 15.06/1000 patient days. In the present study VAE, CLABSI and CAUTI rates were 12.4, 6.9 and 9.0/1000 device days, respectively in comparison to 13.5, 7.01 and 8.6/1000 device days in 2019. Thus, an increase of 7.6% and 1.4% in VAE and CLBSI rates, while a decrease of 4.52% in CAUTI rates was seen. This is in comparison to study by International Nosocomial Infection Control Consortium (INICC)[18] where 2019–2020 rate comparisons were 2.5 and 4.7 CLABSIs per 1000 central line days (P = 0.0006), 9.7 and 12.58 VAEs per 1000 mechanical ventilator days (P = 0.10) and 1.6 and 1.4 CAUTIs per 1000 urinary catheter days (P = 0.69). Secondary infections such as BSI and pneumonia may be assisted in COVID-19 probably because of greater disease severity and excessive workload. In another study[19] during the COVID-19 pandemic, average CAUTI, CLBSI and VAE rates were 2.0, 1.4 and 1.4, respectively, however from pre-COVID levels there was a reduction of 28.01% and 37.6% in CAUTI and CLBSI while an increase of 5.2% in VAE. In one study[20] before COVID in a 2100-bed hospital in India, CAUTI, VAE and CLABSI rates were 0.97, 10.5 and 0.43/1000 device days, respectively. In a study[21] during COVID from the USA, CLABSI rates during the pandemic period were 0.85/1000-line days and 16.4/1000 patient days. This shows that DA-HAI is influenced by different hospital settings.

In an ICU, there is a strong positive correlation between device utilisation and hospital infection.[21] This study showed a higher utilisation ratio of central line (0.49), ventilator (0.60) and urinary catheters (0.83) compared with the ratio reported by the INICC in India (0.39, 0.53 and 0.21, respectively) in pre-COVID era.[25] Common non-invasive methods of ventilatory support and earlier removal of invasive devices should be encouraged in an ICU.

The different organisms involved in CAUTI, CLABSI and VAP were mainly Gram-negative organisms such as Acinetobacter spp., P. aeruginosa, Klebsiella pneumonia and E. coli is similar to several surveillance studies.[12],[18],[22],[23],[24],[25],[26] A. baumannii was the most common isolate, followed by P. aeruginosa (31.7% and 24.4%, respectively) similar to a study from India.[27] In a study from Delhi,[28] K. pneumoniae (33.3%) was the predominant pathogen, followed by A. baumannii (27.1%) with overall antibiotic resistance of 84%. In a study from Italy,[29] COVID-19 patients who developed a BSI following ICU admission, Enterococcus faecalis was identified as the cause of the BSI in 18% of patients. Moreover, 10 out of 13 A. baumannii (76.9%) were carbapenem resistant. Two of four Staphylococcus aureus isolates were methicillin-resistant in VAE cases. The proportion of Gram-negative bacteria resistant to carbapenems was 74.2%,[27] while in the present study carbapenem resistance was seen in 61.7% of Gram-negative bacilli. Studies suggest that antibiotic treatment for secondary bacterial and fungal nosocomial infections in COVID-19 patients may further predispose COVID-19 patients to these secondary infections.[27],[28] This highlights the importance of antimicrobial stewardship programmes focussing on supporting the optimal selection of empiric treatment and culture-based de-escalation during appropriate antimicrobial use.

There are several limitations in the present surveillance data. First, this study is a single-centre COVID-19 ICU study, which may limit the result generalisation. Secondarily, because of increasing ICU patient commitments, staff turnover and rapid discharges/deaths/transfers, the efficiency of monitoring may vary over time. VAE classification only detects those complications severe enough to produce a sustained respiratory worsening and many ventilator-associated respiratory infections and ventilator-associated tracheobronchitis can be missed.

To reduce the diseases associated with health care, DA-HAI surveillance is important as it accurately describes and takes into account the significance and characteristics of the traumatic situation created by such infections. Due to secondary infections with resistant pathogens in COVID-19 patients, it is important to have antimicrobial stewardship and infection control programmes.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Khetrapal S, Bhatia R. Impact of COVID-19 pandemic on health system & sustainable development goal 3. Indian J Med Res 2020;151:395-9.  Back to cited text no. 1
[PUBMED]  [Full text]  
2.
Jog S, Kelkar D, Bhat M, Patwardhan S, Godavarthy P, Dhundi U, et al. Preparedness of acute care facility and a hospital for COVID-19 pandemic: What we did! Indian J Crit Care Med 2020;24:385-92.  Back to cited text no. 2
    
3.
Nazir N, Gupta S. Preparing for a COVID-19 pandemic: A review of operating room outbreak response measures in a large tertiary hospital in India. Ain Shams J Anesthesiol 2021;13:30.  Back to cited text no. 3
    
4.
Iordanou S, Middleton N, Papathanassoglou E, Raftopoulos V. Surveillance of device associated infections and mortality in a major Intensive Care Unit in the Republic of Cyprus. BMC Infect Dis 2017;17:607.  Back to cited text no. 4
    
5.
Baker MA, Sands KE, Huang SS, Kleinman K, Septimus EJ, Varma N, et al. The impact of coronavirus disease 2019 (COVID-19) on healthcare-associated infections. Clin Infect Dis 2022;74:1748-54.  Back to cited text no. 5
    
6.
Wee LE, Conceicao EP, Tan JY, Magesparan KD, Amin IB, Ismail BB, et al. Unintended consequences of infection prevention and control measures during COVID-19 pandemic. Am J Infect Control 2021;49:469-77.  Back to cited text no. 6
    
7.
Johnson NB, Hayes LD, Brown K, Hoo EC, Ethier KA; Centers for Disease Control and Prevention (CDC). CDC National Health Report: Leading causes of morbidity and mortality and associated behavioral risk and protective factors-United States, 2005-2013. MMWR Suppl 2014;63:3-27.  Back to cited text no. 7
    
8.
Rosenthal VD, Jarvis WR, Jamulitrat S, Silva CP, Ramachandran B, Dueñas L, et al. Socioeconomic impact on device-associated infections in pediatric Intensive Care Units of 16 limited-resource countries: International Nosocomial Infection Control Consortium findings. Pediatr Crit Care Med 2012;13:399-406.  Back to cited text no. 8
    
9.
Goel V, Gupta S, Bisht D, Sharma R. Bundle of care approach to reduce ventilator-associated pneumonia in the Intensive Care Unit in a tertiary care teaching hospital in North India. Lung India 2019;36:177-8.  Back to cited text no. 9
[PUBMED]  [Full text]  
10.
Goel V, Hogade SA, Karadesai S. Ventilator associated pneumonia in a medical Intensive Care Unit: Microbial aetiology, susceptibility patterns of isolated microorganisms and outcome. Indian J Anaesth 2012;56:558-62.  Back to cited text no. 10
[PUBMED]  [Full text]  
11.
Cole J, Barnard E. The impact of the COVID-19 pandemic on healthcare acquired infections with multidrug resistant organisms. Am J Infect Control 2021;49:653-4.  Back to cited text no. 11
    
12.
Kumar S, Sen P, Gaind R, Verma PK, Gupta P, Suri PR, et al. Prospective surveillance of device-associated health care-associated infection in an Intensive Care Unit of a tertiary care hospital in New Delhi, India. Am J Infect Control 2018;46:202-6.  Back to cited text no. 12
    
13.
Singh S, Pandya Y, Patel R, Paliwal M, Wilson A, Trivedi S. Share surveillance of device-associated infections at a teaching hospital in rural Gujarat-India. Indian J Med Microbiol 2010;28:342-7.  Back to cited text no. 13
[PUBMED]  [Full text]  
14.
Menon G, Subramanian A, Baby P, Daniel N, Radhika R, George M, et al. Incidence of device associated-healthcare associated infections from a neurosurgical Intensive Care Unit of a tertiary care center: A retrospective analysis. Anesth Essays Res 2020;14:454-60.  Back to cited text no. 14
  [Full text]  
15.
Ripa M, Galli L, Poli A, Oltolini C, Spagnuolo V, Mastrangelo A, et al. Secondary infections in patients hospitalized with COVID-19: Incidence and predictive factors. Clin Microbiol Infect 2021;27:451-7.  Back to cited text no. 15
    
16.
Clinical and Laboratory Standards Institute, 2017: Performance Standards for Antimicrobial Susceptibility Testing CLSI Supplement M100 Clinical; 2017. Available from: http://clsi.org/blog/2017/01/08/clsi-publishes-new-antimicrobial-susceptibility-testing-standards. [Last accessed on 2022 Jan 03].  Back to cited text no. 16
    
17.
Centers for Disease Control and Prevention. Identifying Healthcare-Associated Infections (HAI) for NHSN Surveillance; 2017. Available from: http://www.cdc.gov/nhsn/pdfs/validation/2017/pcsmanual_2017.pdf. [Last accessed on 2022 Feb 06].  Back to cited text no. 17
    
18.
Rosenthal VD, Myatra SN, Divatia JV, Biswas S, Shrivastava A, Al-Ruzzieh MA, et al. The impact of COVID-19 on health care-associated infections in Intensive Care Units in low- and middle-income countries: International Nosocomial Infection Control Consortium (INICC) findings. Int J Infect Dis 2022;118:83-8.  Back to cited text no. 18
    
19.
Mitra M, Ghosh A, Pal R, Basu M. Prevention of hospital-acquired infections: A construct during COVID-19 pandemic. J Family Med Prim Care 2021;10:3348-54.  Back to cited text no. 19
  [Full text]  
20.
Ganesan V, Sundaramurthy R Sr., Thiruvanamalai R, Sivakumar VA, Udayasankar S, Arunagiri R, et al. Device-associated hospital-acquired infections: Does active surveillance with bundle care offer a pathway to minimize them? Cureus 2021;13:e19331.  Back to cited text no. 20
    
21.
Fakih MG, Bufalino A, Sturm L, Huang RH, Ottenbacher A, Saake K, et al. Coronavirus disease 2019 (COVID-19) pandemic, central-line-associated bloodstream infection (CLABSI), and catheter-associated urinary tract infection (CAUTI): The urgent need to refocus on hardwiring prevention efforts. Infect Control Hosp Epidemiol 2022;43:26-31.  Back to cited text no. 21
    
22.
Ong CC, Farhanah S, Linn KZ, Tang YW, Poon CY, Lim AY, et al. Nosocomial infections among COVID-19 patients: An analysis of Intensive Care Unit surveillance data. Antimicrob Resist Infect Control 2021;10:119.  Back to cited text no. 22
    
23.
Mathur P, Khurana S, Kumar S, Gupta D, Aggrawal R, Soni KD, et al. Device associated infections at a trauma surgical center of India: Trend over eight years. Indian J Med Microbiol 2021;39:15-8.  Back to cited text no. 23
    
24.
Kumar S, Sen P, Gaind R, Verma PK, Gupta P, Suri PR, et al. Prospective surveillance of device-associated health care-associated infection in an Intensive Care Unit of a tertiary care hospital in New Delhi, India. Am J Infect Control 2018;46:202-6.  Back to cited text no. 24
    
25.
Rosenthal VD, Duszynska W, Ider BE, Gurskis V, Al-Ruzzieh MA, Myatra SN, et al. International Nosocomial Infection Control Consortium (INICC) report, data summary of 45 countries for 2013-2018, Adult and Pediatric Units, Device-associated Module. Am J Infect Control 2021;49:1267-74.  Back to cited text no. 25
    
26.
Mehta Y, Jaggi N, Rosenthal VD, Kavathekar M, Sakle A, Munshi N, et al. Device-associated infection rates in 20 cities of India, data summary for 2004-2013: Findings of the International Nosocomial Infection Control Consortium. Infect Control Hosp Epidemiol 2016;37:172-81.  Back to cited text no. 26
    
27.
Vijay S, Bansal N, Rao BK, Veeraraghavan B, Rodrigues C, Wattal C, et al. Secondary infections in hospitalized COVID-19 patients: Indian experience. Infect Drug Resist 2021;14:1893-903.  Back to cited text no. 27
    
28.
Khurana S, Singh P, Sharad N, Kiro VV, Rastogi N, Lathwal A, et al. Profile of co-infections & secondary infections in COVID-19 patients at a dedicated COVID-19 facility of a tertiary care Indian hospital: Implication on antimicrobial resistance. Indian J Med Microbiol 2021;39:147-53.  Back to cited text no. 28
    
29.
Giacobbe DR, Battaglini D, Ball L, Brunetti I, Bruzzone B, Codda G, et al. Bloodstream infections in critically ill patients with COVID-19. Eur J Clin Invest 2020;50:e13319.  Back to cited text no. 29
    



 
 
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