Antibiotic usage and stewardship in patients with COVID-19: too much antibiotic in uncharted waters?

Evans, Terry; Davidson, Harriet; Low, Jen Mae; Basarab, Marina; Arnold, Amber

doi:10.1177/1757177420976813

Cited by 19 publications

(13 citation statements)

References 25 publications

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“…Evans et al reported that overall mortality in ICU patients with COVID-19 under mechanical ventilation at the St George’s Hospital, London, was 35%. Most of ICU patients did not have bronchoalveolar lavages undertaken, and therefore bacterial coinfections in this study were not evaluated [ 27 ]. Based on Yang et al study, the mortality rate was 32 cases in 37 critically ill patients with COVID-19 documented mechanical ventilation.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Bacterial Coinfection and Antibiotic Resistance in Patients with COVID-19 Under Mechanical Ventilation

Jamnani

Montazeri

Mirzakhani

et al. 2022

SN Compr. Clin. Med.

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Patients with confirmed SARS-CoV-2 are principally at risk of emerging superinfections, particularly those caused by Gram-negative bacteria. Therefore, in this retrospective cohort study, we investigated the presence of bacteria in endotracheal aspirate samples in severe COVID-19 patients under mechanical ventilation between 20 February 2020 and 21 September 2020 in Mazandaran Heart Center Hospital, Iran. Outcomes were compared between ICU patients with confirmed SARS-CoV-2 (corona group) and those who suffer from other disease (non-corona group). Out of 38 subjects who met the diagnostic criteria for ventilator-associated pneumonia (VAP) in ICU, 22 and 16 patients in corona and non-corona groups, respectively, were enrolled in the study. Hospital length of stay in 27% of case in corona group was > 10 days. Also, SOFA score was > 10 in 64% and 25% of corona and non-corona groups, respectively ( P < 0.05). Moreover, the number of death was significantly higher among corona patients (45%) than non-corona group (6%) in ICU ( P < 0.05). Acinetobacter spp. were the most common bacteria in nine corona patients (41%) that were 100% resistant to amikacin, gentamycin, cefixime, and imipenem antibiotics. The prevalence of antibiotic resistance among pathogens isolated from patients with COVID-19 under mechanical ventilation in ICU highlighted the importance of preventing coinfections caused by this pathogen, suggesting an essential standardized approach to antibiotic stewardship in patients with COVID-19 for successful treatment.

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Section: Discussionmentioning

confidence: 99%

Evaluation of Bacterial Coinfection and Antibiotic Resistance in Patients with COVID-19 Under Mechanical Ventilation

Jamnani

Montazeri

Mirzakhani

et al. 2022

SN Compr. Clin. Med.

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“…Other hospital ASPs have shown that they could discontinue or narrow antibiotics for CAP in patients with COVID-19 within 72 hours of admission. 33,34 This finding contrasts with a report by Cong et al, 32 who reviewed 118 publications and stratified patients with COVID-19 into mild-to-moderate or severe-to-critical illness categories. Antibiotic prescribing during the first 6 months of the COVID-19 pandemic was high (>75%) in both groups.…”

Section: Discussionmentioning

confidence: 75%

Bacterial infections and antibiotic utilization varies by coronavirus disease 19 (COVID-19) severity in hospitalized cancer patients: Analysis from the first phase of the pandemic

Maki

Steiger²,

Su³

et al. 2022

Infect. Control Hosp. Epidemiol.

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Objective: To characterize bacterial infections and antibiotic utilization in hospitalized cancer patients with coronavirus disease 2019 (COVID-19) Design: Retrospective cohort study Setting: Tertiary cancer center in New York City Patients: Hospitalized cancer patients >18 years with COVID-19 between March 1, 2020 and May 31, 2020 Methods: Patients were classified with mild (room air), moderate (nasal cannula oxygen), or severe (high-flow oxygen or mechanical ventilation) COVID-19. The primary outcome was bacterial infection rate within 30 days of COVID-19. Secondary outcomes included the proportion of patients receiving antibiotics and antibiotic length of therapy (LOT). Results: Of 358 study patients, 133, 97, and 128 had mild, moderate, and severe COVID-19, respectively. Most patients had a solid tumor (234/358, 65%). Two hundred (56%) patients had 245 bacterial infections of which 67 (27%) were microbiologically confirmed. The proportion of patients with bacterial infection increased with COVID-19 severity (mild: 47 (35%) vs moderate: 49 (51%) vs severe: 104 (81%), P<0.0001). Most (274/358, 77%) received antibiotics for a median of 4 days. The median antibiotic LOT was 7 days with 1 infection and 20 days for multiple infections (P<0.0001). Antibiotic duration was 1, 4, and 8 days (P<0.0001) in patients with mild, moderate, and severe COVID-19, respectively. Conclusions: Hospitalized cancer patients with COVID-19 had a high rate of bacterial infections. As COVID-19 severity increased, the proportion of patients diagnosed with bacterial infection and given antibiotics rose. In mild COVID-19 cases, antibiotic LOT was short, suggesting that empiric antibiotics can be safely avoided or discontinued in this group.

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“…To assess this possibility, we refit the model on a subcohort that excluded recommendations for ID consults (results unshown), and receipt of an ID consult remained strongly protective against intervention (aOR, 0.58 [95% CI, .53–.64]). Third, our cohort preceded the COVID-19 pandemic, which precipitated important changes in inpatient antimicrobial prescribing [ 23–26 ]. It is unclear how our models would generalize to periods of high COVID-19 inpatient volumes, and whether optimal models would require COVID-19-specific predictors.…”

Section: Discussionmentioning

confidence: 99%

Real-world Antimicrobial Stewardship Experience in a Large Academic Medical Center: Using Statistical and Machine Learning Approaches to Identify Intervention “Hotspots” in an Antibiotic Audit and Feedback Program

Goodman

Heil

Claeys

et al. 2022

Open Forum Infectious Diseases

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Background Prospective audit with feedback (PAF) is an impactful strategy for antimicrobial stewardship program (ASP) activities. However, because PAF requires reviewing large numbers of antimicrobial orders on a case-by-case basis, PAF programs are highly resource-intensive. The current study aimed to identify predictors of ASP intervention (i.e., feedback), and to build models to identify orders that can be safely bypassed from review, to make PAF programs more efficient. Methods We performed a retrospective cross-sectional study of inpatient antimicrobial orders reviewed by the University of Maryland Medical Center’s PAF program between 2017–2019. We evaluated the relationship between antimicrobial and patient characteristics with ASP intervention using multivariable logistic regression models. Separately, we built prediction models for ASP intervention using statistical and machine learning approaches and evaluated performance on held-out data. Results Across 17,503 PAF reviews, 4,219 (24%) resulted in intervention. In adjusted analyses, a clinical pharmacist on the ordering unit or receipt of an ID consult were associated with 17% and 56% lower intervention odds, respectively (aORs 0.83 and 0.44, P values ≤ 0.001). Fluoroquinolones had the highest adjusted intervention odds (aOR 3.22, 95% CI: 2.63–3.96). A machine learning classifier (C-statistic 0.76) reduced reviews by 49% while achieving 78% sensitivity. A “workflow simplified” regression model that restricted to antimicrobial class and clinical indication variables, two strong machine-learning-identified predictors, reduced reviews by one-third while achieving 81% sensitivity. Conclusions Prediction models substantially reduced PAF review caseloads while maintaining high sensitivities. Our results and approach may offer a blueprint for other ASPs.

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Antibiotic usage and stewardship in patients with COVID-19: too much antibiotic in uncharted waters?

Cited by 19 publications

References 25 publications

Evaluation of Bacterial Coinfection and Antibiotic Resistance in Patients with COVID-19 Under Mechanical Ventilation

Evaluation of Bacterial Coinfection and Antibiotic Resistance in Patients with COVID-19 Under Mechanical Ventilation

Bacterial infections and antibiotic utilization varies by coronavirus disease 19 (COVID-19) severity in hospitalized cancer patients: Analysis from the first phase of the pandemic

Real-world Antimicrobial Stewardship Experience in a Large Academic Medical Center: Using Statistical and Machine Learning Approaches to Identify Intervention “Hotspots” in an Antibiotic Audit and Feedback Program

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