Meital Elbaz

Progressive multifocal leukoencephalopathy (PML) is a devastating and often fatal central nervous system infection caused by John Cunningham polyomavirus virus (JCPyV). PML results from JCPyV reactivation in the setting of impaired cellular immunity in patients with HIV, organ transplantation, severe inflammatory disease, and an increasing number of modern treatments for cancer and autoimmune diseases. The presence of clinical and imaging manifestations consistent with the diagnosis coupled with the demonstration of JCPyV by PCR in cerebrospinal fluid (CSF) are considered diagnostic. Since there are no effective antiviral treatments available, restoring immune function is a key component in PML treatment. Novel immunotherapeutic approaches can ameliorate PML. Immunotherapeutic interventions, such as use of checkpoint inhibitors and viral specific T-cell, have shown promising results, but additional data are needed. In this review, we summarize the available data on risk factors for JCPyV neurological syndrome, clinical, laboratory, and radiological features, and propose an algorithm for management.

The reported estimates of bacterial co-infection in COVID-19 patients are highly variable. We aimed to determine the rates and risk factors of bacterial co-infection and develop a clinical prediction model to support early decision-making on antibiotic use. This is a retrospective cohort study conducted in a tertiary-level academic hospital in Israel between March 2020 and May 2022. All adult patients with severe COVID-19 who had a blood or lower respiratory specimen sent for microbiological analyses within 48 h of admission were included. The primary study endpoint was the prevalence of bacterial co-infection at the time of hospital admission. We created a prediction model using the R XGBoost package. The study cohort included 1,050 patients admitted with severe or critical COVID-19. Sixty-two patients (5.9%) had a microbiologically proven bacterial infection on admission. The variables with the greatest impact on the prediction model were age, comorbidities, functional capacity, and laboratory parameters. The model achieved perfect prediction on the training set (area under the curve = 1.0). When applied to the test dataset, the model achieved 56% and 78% specificity with the area under the receiver operating curve of 0.784. The negative and positive predictive values were 0.975 and 0.105, respectively. Applying the prediction model would have resulted in a 2.5-fold increase in appropriate antibiotic use and an 18% reduction in inappropriate use in patients with severe and critical COVID-19. The use of a clinical prediction model can support decisions to withhold empiric antimicrobial treatment at the time of hospital admission without adversely affecting patient outcomes. IMPORTANCE: Estimates of bacterial coinfection in COVID-19 patients are highly variable and depend on many factors. Patients with severe or critical COVID-19 requiring intensive care unit admission have the highest risk of infection-related complications and death. Thus, the study of the incidence and risk factors for bacterial coinfection in this population is of special interest and may help guide empiric antibiotic therapy and avoid unnecessary antimicrobial treatment. The prediction model based on clinical criteria and simple laboratory tests may be a useful tool to predict bacterial co-infection in patients hospitalized with severe COVID-19.

Early reports described an increased risk of herpes zoster following receipt of mRNA-based COVID-19 vaccines. The objective was to assess whether COVID-19 vaccine is associated with varicella-zoster virus–induced neurologic disease (VZV-ND). This multicenter retrospective case-control study with a test-negative design was conducted at 12 hospitals in Israel. We included all patients admitted with VZV-ND between January 2020 and December 2021 and matched controls with a negative polymerase chain reaction result for VZV in cerebrospinal fluid. We identified 188 patients meeting the case definition of VZV-ND who were admitted during the study period. Cases were matched with 376 controls. There was no significant variation in the incidence of VZV-ND between 1 year preceding and 1 year following the deployment of BNT162b2 in Israel. Analysis of persons who had received at least 1 dose of COVID-19 vaccine (n = 259) showed similar proportions of VZV-ND and non–VZV-ND in 4 intervals (30, 42, 50, 60 days) following the last vaccine dose. The median time from the last vaccine dose to hospitalization with a neurologic syndrome was 53 days (IQR, 25–128) and 82 days (IQR, 36–132) for VZV-ND and non–VZV-ND, respectively, not reaching statistical significance (P = .056). The rate of VZV-ND in vaccinated patients was no different from the rate in the unvaccinated group (30.9% vs 35.4%, P = .2). We did not find an association between COVID-19 vaccine and VZV-ND. Since COVID-19 vaccine is now recommended yearly, every fall and winter, establishing the safety of the vaccine is of great importance.

Antimicrobial resistance (AMR) has consistently been linked to antibiotic use. However, the roles of commonly prescribed non-antimicrobial drugs as drivers of AMR may be under-appreciated. Here, we studied a cohort of patients with community-acquired pyelonephritis and assessed the association of exposure to non-antimicrobial drugs at the time of hospital admission with infection with drug-resistant organisms (DRO). Associations identified on bivariate analyses were tested using a treatment effects estimator that models both outcome and treatment probability. Exposure to proton-pump inhibitors, beta-blockers, and antimetabolites was significantly associated with multiple resistance phenotypes. Clopidogrel, selective serotonin reuptake inhibitors, and anti-Xa agents were associated with single-drug resistance phenotypes. Antibiotic exposure and indwelling urinary catheters were covariates associated with AMR. Exposure to non-antimicrobial drugs significantly increased the probability of AMR in patients with no other risk factors for resistance. Non-antimicrobial drugs may affect the risk of infection with DRO through multiple mechanisms. If corroborated using additional datasets, these findings offer novel directions for predicting and mitigating AMR.

(2020). Time course of anosmia and dysgeusia in patients with mild SARS-CoV-2 infection. Infectious Diseases: Vol. 52, No. 8, pp. 600-602.

In this cohort of 42 patients with mild COVID19 we found a unique clinical feature of acute anosmia and dysgeusia in more than third of patients. Median onset of these features was 3.3 days after onset of illness (range 0-7) with rapid recovery in most patients. Article Summary Line: Anosmia and dysgeusia appeared early in third of our patients with mild SARS-CoV-2 infection and were short-lived in most patients.