Factors Predicting Bacterial Coinfection in Hospitalized COVID-19 Patients

Background. Despite multiple studies indicating a low prevalence of bacterial coinfection in coronavirus disease 2019 (COVID-19) patients, the majority of hospitalized COVID-19 patients receive one or more antibiotics. Patients with coinfection usually have multiple risk factors and poor clinical outcomes. Methods. A retrospective case control study was conducted comparing clinical characteristics and antimicrobial use in hospitalized adult COVID-19 patients with bacterial co-infections vs. randomly selected patients without co-infections (matched on month of admission). The study was conducted at three hospitals within the Montefiore Medical Center, Bronx, NY between March 1, 2020 and October 31, 2020. A multivariable logistic regression model was developed to assess the relationship of each predictor variable with coinfection status. Secondary outcomes included hospital mortality, antibiotic days of therapy (DOT), and C. difficile infection. Results. A total of 150 patients with coinfection and 150 patients without coinfection were included in the analysis. Table 1 summarized baseline characteristics and risk factors. The multivariable logistic regression model indicated that presence of a central line (OR=5.4, 95% CI: 2.7-11.1), prior antibiotic exposure within 30 days (OR=5.3, 95% CI: 2.8-10.0), prior ICU admission (OR=3.6, 95% CI: 1.7-7.6), steroid use (OR=2.7, 95% CI: 1.4-4.9), and any comorbid condition (OR=2.7, 95% CI: 1.4-5.2) were significantly associated with the development of coinfection (table 2). Mortality was higher in patients with coinfection (56% vs. 11%, p < 0.0001) (table 3). Average antibiotic DOT was 10.5 in coinfected patients compared to 4 in noncoinfected patients, (p < 0.0001). Forty-one percent of coinfected patients had a multidrug resistant organism isolated. C. difficile rate was higher in coinfected patients (4% vs. 0%, p=0.03). Conclusion. As the healthcare community contends with a 3rd year of COVID-19 pandemic, understanding risk factors most predictive of bacterial coinfection can guide empiric antimicrobial therapy and targeted stewardship interventions. Ideally, co-infection risk scores are developed which may be useful for future inpatient surges.

Covid 19 re-infection versus re-activation in two renal transplant patients

Purpose: Rare cases of potential COVID 19 re-infection have been reported throughout the world. Methods: We describe two renal transplant recipients with possible SARS-COV-2 re-infection. Results: Patient #1 is a 63-year-old man with a history of renal transplant in February 2010, who initially experienced symptoms consistent with COVID-19 in April 2020 along with several family members. Due to limitations in outpatient testing, no SARS-CoV2 testing was able to be performed but he was treated as presumed COVID-19 infection due to high community prevalence and three weeks following his symptoms, SARS-CoV2 IgG was positive. The patient subsequently had four negative PCR tests from July-September 2020. In October, he was admitted for hypoxic respiratory failure and was found to be SARS-COV-2 positive by PCR and SARS-COV-IgG was negative (Figure 1). The patient was treated with Remdesivir and recovered. Patient #2 is a 64-year-old man with history of renal transplant in 2003, who was found to be SARS-COV-2 positive by RT-PCR in April 2020 after presenting with hypoxia. The patient had an uneventful hospital course and was discharged off supplemental oxygen. He had two negative SARS-COV-2 PCR tests in August and September and his SAR-COV-2 IgG was positive. In September, he was readmitted with hypoxic respiratory failure requiring intubation and ICU admission and was again found to be SARS-COV-2 positive by PCR. The patient had a complicated hospital course and expired on September 30th (Figure 1). Conclusions: Potential cases of SARS-COV-2 re-infection have been previously reported, but it is unclear whether these are true re-infections versus reactivation of a prior infection, prolonged viral shedding, or dynamic RT-PCR results. In our cases, we believe prolonged viral shedding from the initial infection or inaccurate testing is less likely given the prolonged time interval between the two events, the multiple negative tests in between, and the severity of the second episodes. While both of these patients were suspected of having re-infections, this could not be confirmed as genomic analysis was not performed. Future studies of similar cases are needed to determine factors contributing to re-infection.

Variation of mortality from sars-cov-2 infection in kidney transplant recipients over the course of the pandemic

Purpose: We aimed to investigate the mortality from SARS-CoV-2 in kidney transplant recipients in the Bronx, New York, one of the epicenters of the pandemic over the period of the pandemic. Methods: Between March 16 and November 30, 2020, 158 patients were tested positive by SARS-CoV-2 RT-PCR. Results: 94 (59.5%) were male, at a median age of 62 years old (IQR: 51-71), predominantly Hispanic (54.4%) and African American (29.7%). 127 patients were admitted to the hospital and 29 were observed at home. 75.3% received a deceased-donor renal transplant, 57% received anti-thymocyte globulin induction. Most patients were on triple immunosuppression (94.3% on calcineurin inhibitors, 86.7% on anti-metabolite, 96.7% on prednisone). Hypertension was present in 96.2%, diabetes mellitus in 62.7%, heart disease in 19.6% and lung disease in 8.9% of the patients. The figure shows the number of RT-PCR positivity and mortality over the course of the pandemic starting on March 16, 2020. A total of 50 (31.6%) died as of November 30, 2020. The mortality rate was 40% (17/43) in patients diagnosed between March 16 and 31,2020, 39% (23/59) in patients diagnosed between April 1 and 15,2020 and 29% (7/24) in patients diagnosed between April 16 and 30, 2020. Since May 1st 2020, the mortality rate has significantly decreased to 9% (3/32). Conclusions: In summary, mortality from SARS-CoV-2 infection in kidney transplant recipients was higher during the first 6 weeks of the pandemic and has significantly decreased over time. This could be explained by initial exposure of the patients with higher viral load due to lack of personal protection and social distancing due to the fact that there is no current proven treatment for SARS-CoV-2 infection and clinical approach to patients has not been changed since the beginning of the pandemic.

Prevalence and dynamics of SARS-CoV-2 IGG in kidney transplant recipients

Purpose: We aimed to investigate the prevalence and dynamics of SARS-CoV-2 IgG in kidney transplant recipients in the Bronx, New York, one of the epicenters of the pandemic Methods: Between March 16 and November 30, 2020, 158 patients tested positive by SARS-CoV-2 RT-PCR. From May 3 to November 30, 2020, 1042 patients were screened for SARS-CoV-2 IgG antibodies and 164 (15.7%) were tested positive (Figure). Results: Sixty of the 164 patients were previously diagnosed COVID-19 by RTPCR, while the remaining 104 did not have significant symptoms and had not been previously tested by RT-PCR. Overall prevalence of COVID-19 diagnosis by RT-PCR and/or SARS-CoV-2 IgG in 1130 patients were 23.2%. Seventy RT-PCR positive patients were screened for SARS-CoV-2 IgG antibody at a median of 43 days postdiagnosis (IQR: 29-57) and 60 (85.7%) were positive. A total of 39 patients out 164 who previously tested positive for SARS-CoV-2 IgG (25 diagnosed with IgG and 14 with RT-PCR) were retested at a median time of 105 days (IQR: 83-116). Twenty patients (51.3%) became seronegative at a median time of 107 days (IQR: 87-134) from their first positive SARS-CoV-2 IgG. Six patients out of 14 (43%) who were diagnosed by positive RT-PCR became seronegative at a median time of 105 days (IQR: 83-166) from their first positive SARS-CoV-2 IgG while 14 patients out of 25 (56%) who were initially diagnosed by a positive SARS-CoV-2 IgG, became seronegative at a median time of 112 days (IQR: 91-138) from date of diagnosis Conclusions: . In summary, 40% of kidney transplant recipients were asymptomatic or mildly symptomatic and developed SARS-CoV-2 IgG without requiring testing by SARS-CoV-2 RT-PCR. However, half of the patients who initially developed antibodies lost them over time raising the questions of lasting immunity against SARS-CoV-2 and how effective are those antibodies.

Treatment with monoclonal antibodies minimize severity of covid-19 illness among kidney transplant recipients

Background: The mortality rate of kidney transplant recipients with COVID-19 is significantly higher than the general population, indicating a need for effective treatment to minimize potential severe symptoms in this population. We sought to evaluate the efficacy of monoclonal antibody therapy in decreasing the severity of COVID-19 symptoms among our kidney transplant recipients. Methods: We reviewed 17 kidney transplant recipients who were infected with SARS-CoV2 and received treatment with monoclonal antibody therapy. All patients were on standard immunosuppression with Tacrolimus and Prednisone, and 88% were on Mycophenolate prior to COVID diagnosis, which was subsequently reduced or held for at least 2 weeks. Results: Of the 17 patients reviewed, median age was 61 years (range 42 to 77 years), 47% were male, 59% were Hispanic, and 29% were African American. Additionally 94% had history of hypertension, 47% diabetes mellitus, 18% coronary artery disease, and median BMI was 28.8 (range 23.4 to 41.9). Eighteen percent were transplanted <1 year, 29% between 1-5 years, 24% 6-10 years, and the remaining >10 years. All patients had mild symptoms without evidence of hypoxia, and 94% received monoclonal antibody therapy within 7 days of diagnosis. Bamlanivimab 700mg was the most commonly administered agent at 59%, while 18% received Bamlanivimab 700mg and Etesevimab 1400mg. Casirivimab 1200 mg and imdevimab 1200 mg was used in 24%. Only 2 out of the 17 patients (11.8%) required hospitalization, and both were non-COVID-19 related reasons. Five out of 17 patients (29.4%) were evaluated in the Emergency Department but not admitted. All 17 patients (100%) recovered from their COVID-19 illness. There were no episodes of graft failure. Conclusions: Our experience suggests that monoclonal antibody therapies may be beneficial in preventing severe COVID-19 in renal transplant recipients and possibly reduce the need for COVID-19 related hospitalization in this high risk population. However, larger studies are needed to confirm these findings.

Dynamics of Leukocyte Subpopulations Reconstitution Predict Infection Propensity in a Multiethnic Real World Cohort Treated with Anti-CD19 CAR-T Cell Therapy (Axicabtagene-Ciloleucel)

Background: Adoptive immunotherapy using CD19-targeted Chimeric Antigen Receptor T-cells (CAR-T) has revolutionized the treatment of relapsed/refractory diffuse large B-cell lymphoma (DLBCL). We have demonstrated the efficacy of FDA-approved axicabtagene ciloleucel (Yescarta) in a multiethnic New York City underserved population with 80% complete response (CR) rate in the first ten patients treated at our institution (Abbasi et al., 2020). There is limited data on the propensity of infections and lymphohematopoietic reconstitution after Day 30 (D30) following CAR-T cell therapy. In this study, we evaluated the prevalence and nature of infectious complications in an expanded cohort of DLBCL patients treated with CD19 CAR-T therapy and its association with the dynamics of leukocyte subpopulation reconstitution post-CAR-T cell therapy. Methods: We conducted a retrospective study of patients who received CAR-T therapy at our institution between 2018-2020. Variables collected include patient demographics, absolute neutrophil (ANC), lymphocyte (ALC) and monocyte counts (AMC) at Day 30, hematologic reconstitution (ANC≥ 1500/µL) at Day 90 (D90), presence or absence of infections after D30 by clinical and/or microbiological parameters. Associations between presence of infection and D30 ANC, ALC, AMC, ANC/ALC ratio, AMC/ALC ratio were assessed using Kruskal-Wallis test. Association between infection and hematologic reconstitution at D90 was done using Chi-square test. Kaplan-Meier curves with log-rank test were used to evaluate overall survival (OS) and progression-free survival (PFS). Results: Nineteen patients were evaluated in our study, consisting of 42% (8) Hispanic, 32% (6) Caucasian, 21% (4) African-American, and 5% (1) Asian subjects. Based on clinical and microbiologic data, 47% (9) developed an infection after D30 (infection group) while 53% (10) of subjects remained infection-free after D30 (non-infection group). The most common infection type observed was viral (11 patients) followed by bacterial (8 patients) and fungal (3 patients) (Table 1). Of 25 total infectious events, 44% (11) were grade 1 or 2 and 48% (12) were grade 3 with 10 being viral in etiology. Two deaths occurred due to an infectious process. Three patients tested SARS-CoV-2 positive and were hospitalized with COVID-19 pneumonia. Median OS and PFS has not been reached in either group. To determine the kinetics of lymphohematopoietic reconstitution and its association with infection risk, we evaluated the relationship between cytopenias and rates of infection after D30. Notably, compared to non-infection group, infection group had a higher median ALC (1000/µL vs 600/µL p=0.04), a lower median ANC/ALC ratio (1.4 vs 4.5 p<0.01) and a lower median AMC/ALC at D30 (0.36 vs 1.33, p=0.01) (Table 2). In addition, patients in the infection group had a lower rate of hematologic reconstitution (ANC >1500/µL) at D90. We observed that only 22% (2) of patients had recovered ANC > 1500/µLin the infection group as opposed to 80% (8) in the non-infection group at D90 (p= 0.038). Rates of cytokine release syndrome (CRS) were comparable between the two groups (55.6% vs 70% p=0.52). Surprisingly, rates of immune-effector cell associated neurotoxicity syndrome (ICANS) was lower (55.6%) in the infection group compared to (90%) non-infection group (p=0.09). Fourteen of 19 patients had follow-up over one year, of which 8 (57%) remained in complete remission (CR). Conclusions: We demonstrate an infection rate of 47% (9) beyond D30 in patients undergoing CD19 CAR-T. Increased ALC, lower ANC/ALC and AMC/ALC ratios at D30 may be predictive of infectious complications. Median OS has not been reached in our cohort. Given the potential clinical impact, our observations should be corroborated using larger datasets. [Formula presented] Disclosures: Steidl: Pieris Pharmaceuticals: Consultancy;Bayer Healthcare: Research Funding;Stelexis Therapeutics: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees;Ai eron Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Janakiram: ADC Therapeutics, FATE therapeutics, TAKEDA pharmaceuticals: Research Funding. Verma: BMS: Consultancy, Research Funding;acceleron: Consultancy, Honoraria;Janssen: Research Funding;stelexis: Current equity holder in private company;Medpacto: Research Funding.