The impact of COVID-19 on multidrug-resistant organisms causing healthcare-associated infections: a narrative review

Witt, Lucy S; Howard‐Anderson, Jessica; Jacob, Jesse T; Jacob, Jesse T

doi:10.1093/jacamr/dlac130

Cited by 30 publications

(26 citation statements)

References 109 publications

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“…The use of Personal Protective Equipment (PPE), which was meant to protect healthcare staff and reduce infection, led to suboptimal utilization and disease transmission. 6,38 Third, host factors, including older ages, and comorbidities, facilitate the risk of MDR, as reported previously. 39 In this study, the optimal COV of NLR was demonstrated to differentiate between COVID-19 with and without SPBI.…”

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confidence: 60%

“…[3][4][5] Previous studies reported increased morbidity and mortality due to secondary bacterial infection. 6 The occurrence of secondary pulmonary bacterial infection (SPBI) was underpinned by three mechanisms, namely dysregulation of the immune response, dysbiosis of the respiratory tract microbiota, and damage to respiratory tract epithelial cells. 7,8 The management of COVID-19 has been impacted by issues related to SPBI, such as the high rate of hospitalization and prolonged hospital stays, which increase the risk of hospital-acquired infection.…”

Section: Introductionmentioning

confidence: 99%

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The Diagnostic Value of Kinetics of NLR to Identify Secondary Pulmonary Bacterial Infection Among COVID-19 Patients at Single Tertiary Hospital in Indonesia

Sumardi¹,

Valentino²,

Prasetya³

et al. 2023

IJGM

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Coronavirus disease 2019 (COVID-19) is a new respiratory tract infection caused by severe acute respiratory syndrome coronavirus-2. The presence of secondary pulmonary bacterial infection (SPBI) made COVID-19 difficult to treat. Neutrophillymphocyte count ratio (NLR) is a systemic inflammatory marker used in the diagnosis and prognosis of viral or bacterial infection. At the first 3-5 days after hyperinflammation, it occurs in relation to clinical outcome. Therefore, this study aimed to evaluate the diagnostic value of NLR based on leukocyte kinetics upon admission and after 72 hours among COVID-19 patients with or without SPBI. Patients and Methods: This retrospective cross-sectional study analyzed medical records data of admitted patients with COVID-19 according to the International Classification of Disease 10th Revision (ICD-10) between January and December 2021. The list of patients was extracted and followed by a hand search to identify the inclusion or exclusion criteria and stratified into proven and nonproven SPBI based on clinical data. The study distinguished between SPBI by means of a cut-off value (COV) on the first (D1) and third day (D3), assessed using receiver operating characteristics (ROC), as well as determined the magnitude of sensitivity, specificity, and prevalence ratio. Results: A screening process was conducted on 2902 COVID-19 patients, of which 236 were included, accounting for 8.1%. Among these patients, 87 (36.9%) were found to have proven SPBI. A considerable difference in NLR value between proven and non-proven SPBI was observed on both D1 (11.1 vs 4.2) and D3 (15.3 vs 5.2), with optimal COV of NLR on D1, D3 was found to be 5.29, 9.47, respectively (p < 0.001). Conclusion: NLR on the D1 and D3 distinguished the occurrence of SPBI among COVID-19 patients. The application of NLR assisted in the early determination of bacterial infection and helped in controlling the empirical use of antibiotics.

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confidence: 60%

Section: Introductionmentioning

confidence: 99%

The Diagnostic Value of Kinetics of NLR to Identify Secondary Pulmonary Bacterial Infection Among COVID-19 Patients at Single Tertiary Hospital in Indonesia

Sumardi¹,

Valentino²,

Prasetya³

et al. 2023

IJGM

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“…These conflicting reports suggest that impacts of COVID-19 on antibiotic resistance likely depend on the particular population, setting, and bacteria in question and may be highly context specific. Several international studies have now reported on rates of healthcare-associated infection during the pandemic [ 12 , 13 ], but few have reported data on bacterial colonization or transmission, on rates of antibiotic resistance among colonized patients, nor on the putative mechanisms driving potential pandemic-related shits in antibiotic resistance epidemiology [ 14 ]. Mathematical modelling is a useful tool to help disentangle the mechanisms linking the transmission dynamics of co-occurring pathogens, especially when data are limited.…”

Section: Introductionmentioning

confidence: 99%

Collateral impacts of pandemic COVID-19 drive the nosocomial spread of antibiotic resistance: A modelling study

Shirreff

Temime

et al. 2023

PLoS Med

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Background Circulation of multidrug-resistant bacteria (MRB) in healthcare facilities is a major public health problem. These settings have been greatly impacted by the Coronavirus Disease 2019 (COVID-19) pandemic, notably due to surges in COVID-19 caseloads and the implementation of infection control measures. We sought to evaluate how such collateral impacts of COVID-19 impacted the nosocomial spread of MRB in an early pandemic context. Methods and findings We developed a mathematical model in which Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and MRB cocirculate among patients and staff in a theoretical hospital population. Responses to COVID-19 were captured mechanistically via a range of parameters that reflect impacts of SARS-CoV-2 outbreaks on factors relevant for pathogen transmission. COVID-19 responses include both “policy responses” willingly enacted to limit SARS-CoV-2 transmission (e.g., universal masking, patient lockdown, and reinforced hand hygiene) and “caseload responses” unwillingly resulting from surges in COVID-19 caseloads (e.g., abandonment of antibiotic stewardship, disorganization of infection control programmes, and extended length of stay for COVID-19 patients). We conducted 2 main sets of model simulations, in which we quantified impacts of SARS-CoV-2 outbreaks on MRB colonization incidence and antibiotic resistance rates (the share of colonization due to antibiotic-resistant versus antibiotic-sensitive strains). The first set of simulations represents diverse MRB and nosocomial environments, accounting for high levels of heterogeneity across bacterial parameters (e.g., rates of transmission, antibiotic sensitivity, and colonization prevalence among newly admitted patients) and hospital parameters (e.g., rates of interindividual contact, antibiotic exposure, and patient admission/discharge). On average, COVID-19 control policies coincided with MRB prevention, including 28.2% [95% uncertainty interval: 2.5%, 60.2%] fewer incident cases of patient MRB colonization. Conversely, surges in COVID-19 caseloads favoured MRB transmission, resulting in a 13.8% [−3.5%, 77.0%] increase in colonization incidence and a 10.4% [0.2%, 46.9%] increase in antibiotic resistance rates in the absence of concomitant COVID-19 control policies. When COVID-19 policy responses and caseload responses were combined, MRB colonization incidence decreased by 24.2% [−7.8%, 59.3%], while resistance rates increased by 2.9% [−5.4%, 23.2%]. Impacts of COVID-19 responses varied across patients and staff and their respective routes of pathogen acquisition. The second set of simulations was tailored to specific hospital wards and nosocomial bacteria (methicillin-resistant Staphylococcus aureus, extended-spectrum beta-lactamase producing Escherichia coli). Consequences of nosocomial SARS-CoV-2 outbreaks were found to be highly context specific, with impacts depending on the specific ward and bacteria evaluated. In particular, SARS-CoV-2 outbreaks significantly impacted patient MRB colonization only in settings with high underlying risk of bacterial transmission. Yet across settings and species, antibiotic resistance burden was reduced in facilities with timelier implementation of effective COVID-19 control policies. Conclusions Our model suggests that surges in nosocomial SARS-CoV-2 transmission generate selection for the spread of antibiotic-resistant bacteria. Timely implementation of efficient COVID-19 control measures thus has 2-fold benefits, preventing the transmission of both SARS-CoV-2 and MRB, and highlighting antibiotic resistance control as a collateral benefit of pandemic preparedness.

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“…14,24 The COVID-19 pandemic has led to a significant increase in hospital-acquired MDRO rates in many regions. 25 According to the CDC, there has been a 78% increase in hospital-onset CRAB cases. 26 This increase is likely due to a variety of factors, including human factors such as staffing shortages, inadequate use of personal protective equipment, and poor hand hygiene compliance.…”

Section: Discussionmentioning

confidence: 99%

Contribution of active surveillance cultures to the control of hospital-acquired carbapenem-resistant Acinetobacter baumannii in an endemic hospital setting

Ben-David,

Cohen,

Levi

et al. 2023

Infect. Control Hosp. Epidemiol.

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Background: Despite the increasing rates of carbapenem-resistant Acinetobacter baumannii (CRAB) carriage among hospitalized patients in endemic settings, the role of active surveillance cultures and cohorting is still debated. We sought to determine the long-term effect of a multifaceted infection-control intervention on the incidence of CRAB in an endemic setting. Methods: A prospective, quasi-experimental study was performed at a 670-bed, acute-care hospital. The study consisted of 4 phases. In phase I, basic infection control measures were used. In phase II, CRAB carriers were cohorted in a single ward with dedicated nursing and enhanced environmental cleaning. In phase III large-scale screening in high-risk units was implemented. Phase IV comprised a 15-month follow-up period. Results: During the baseline period, the mean incidence rate (IDR) of CRAB was 44 per 100,000 patient days (95% CI, 37.7–54.1). No significant decrease was observed during phase II (IDR, 40.8 per 100,000 patient days; 95% CI, 30.0–56.7; P = .97). During phase III, despite high compliance with control measures, ongoing transmission in several wards was observed and the mean IDR was 53.9 per 100,000 patient days (95% CI, 40.5–72.2; P = .55). In phase IV, following the implementation of large-scale screening, a significant decrease in the mean IDR was observed (25.8 per 100,000 patient days; 95% CI, 19.9–33.5; P = .03). An overall reduction of CRAB rate was observed between phase I and phase IV (rate ratio, 0.6; 95% CI, 0.4–0.9; P < .001). Conclusions: The comprehensive intervention that included intensiﬁed control measures with routine active screening cultures was effective in reducing the incidence of CRAB in an endemic hospital setting.

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The impact of COVID-19 on multidrug-resistant organisms causing healthcare-associated infections: a narrative review

Cited by 30 publications

References 109 publications

The Diagnostic Value of Kinetics of NLR to Identify Secondary Pulmonary Bacterial Infection Among COVID-19 Patients at Single Tertiary Hospital in Indonesia

The Diagnostic Value of Kinetics of NLR to Identify Secondary Pulmonary Bacterial Infection Among COVID-19 Patients at Single Tertiary Hospital in Indonesia

Collateral impacts of pandemic COVID-19 drive the nosocomial spread of antibiotic resistance: A modelling study

Contribution of active surveillance cultures to the control of hospital-acquired carbapenem-resistant Acinetobacter baumannii in an endemic hospital setting

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