ABSTRACT
TOPIC: Chest Infections TYPE: Original Investigations PURPOSE: Several countries have seen a two-wave pattern of the COVID-19 pandemic. However, clinical characteristics and outcomes between waves vary across regions. A study in England suggested a substantial improvement in survival amongst people admitted to critical care with COVID-19, with markedly higher survival rates in people admitted in the first wave compared with those admitted in the second wave, while a study in Africa, the second wave appeared to be much more aggressive. Therefore, regional-specific analyses are needed. METHODS: We retrospectively reviewed a de-identified dataset of patients with COVID-19 admitted to our community hospital ICU, from March 1, 2020, to February 28, 2021. Only molecularly confirmed COVID-19 cases defined by a positive result on an RT-PCR assay or NAAT of a specimen collected on a nasopharyngeal swab were included. We then identified patients from the first wave as those admitted during the initial peak of admissions observed at our hospital between March 1, 2020, and September 3, 2020. The second wave was defined as those admitted during the second peak of admissions observed between October 1, 2020, and February 28, 2021. Descriptive statistics were performed to summarize data. RESULTS: Between March 1, 2020, and February 28, 2021, a total of 190 patients were admitted to our community-hospital ICU. Of those, 132 (69.5%) were identified as patients from the first wave, and 58 (30.5%) were identified as patients from the second wave. The median age was not significantly different among patients from the first and second wave (69 years [IQR 59 – 78 years] vs. 69 years [IQR 61 – 77.25 years;p=.841]. Sex distribution was also not significantly different between the two waves (85/132 males [64.4%] vs. 40/58 males [69%];p=.541). A significantly higher rate of patients was admitted from long-term care facilities during the first wave compared to the second wave (77/132 [58.3%] vs. 7/58 [12.1%];p<.001). The distribution of comorbidities was similar between groups, except for neurocognitive disorders, which were mostly observed in the first wave (46/132 [34.8% vs. 7/58 [12.1%];p=.001). While the rates of invasive mechanical ventilation were similar between groups (75/132 [56.8%] vs. 36-58 [62.1%];p=.499, significant higher rates of patients received humidified high-flow nasal cannula (19/132 [14.4%] vs. 29/58 [50%];p<.001) and noninvasive ventilation (9/132 [6.8%] vs. 23/58 [39.7%];p<.001) during the second wave. Following the release of some pivotal clinical trials, more patients during the second wave received corticosteroids (87/132 [65.9%] vs. 56/58 [96.6%];p<.001) and remdesivir (19/132 [14.4%] vs. 48/58 [82.8%];p<.001). However, the in-hospital case-fatality rate was not significantly different between groups (68/132 [51.5%] vs. 32/58 [55.2%];p=.642). CONCLUSIONS: While epidemiological characteristics of patients with COVID-19 admitted to our ICU between the two waves were grossly similar, a significantly higher rate of patients was admitted from long-term care facilities during the first wave, and non-invasive ventilation and targeted therapies were used more during the second wave. The in-hospital case-fatality rate was not significantly different. CLINICAL IMPLICATIONS: In our community hospital in the Chicago North Shore area, the ICU case-fatality rate was not significantly different between two different waves of the COVID-19 pandemic. DISCLOSURES: No relevant relationships by Chul Won Chung, source=Web Response No relevant relationships by Goar Egoryan, source=Web Response No relevant relationships by Harvey Friedman, source=Web Response No relevant relationships by Emre Ozcekirdek, source=Web Response No relevant relationships by Ece Ozen, source=Web Response No relevant relationships by Bidhya Poudel, source=Web Response No relevant relationships by Guillermo Rodriguez-Nava, source=Web Response No relevant relationships by Daniela Trelles Garcia, source=Web Response No relevant relationships by Valer a Trelles Garcia, source=Web Response No relevant relationships by Maria Yanez-Bello, source=Web Response No relevant relationships by Qishuo Zhang, source=Web Response
ABSTRACT
SESSION TITLE: Late-breaking Abstract Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: October 18-21, 2020 PURPOSE: Coronavirus disease 2019 (COVID-19) is a new entity that has rapidly spread globally, claiming thousands of lives. Hydroxychloroquine, an agent used to prevent malaria and to treat autoimmune disorders, was being administered to COVID-19 cases to slow or prevent the disease. However, its use was rushed without sufficient evidence on efficacy and safety. METHODS: We retrospectively reviewed a de-identified dataset of 98 patients with COVID-19 admitted to a community hospital Intensive Care Unit (ICU) in Cook County, Illinois, from March 2020 to May 2020. Only confirmed COVID-19 cases, defined by a positive result on a reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay of a specimen collected on a nasopharyngeal swab were included. Co-infections were identified as the presence of positive blood cultures, sputum cultures, Legionella or pneumococcus urine antigen test, or respiratory viral panel. We performed a multivariable logistic regression analysis forcing variables that could be associated with increased risk of infection into the model, including central line placement, intubation, tocilizumab, intravenous steroids, colchicine, and hydroxychloroquine. RESULTS: Of 98 patients, the median age was 67 years (interquartile range, 57.75 – 74.25 years), 66 (67.3%) were males, 32 (32.7%) were Caucasian, and 56 (57.1%) were admitted from a Long-Term Care Facility (LTCF). 83.7% of the individuals had two or more comorbidities;the most frequent were hypertension (68.4%) and diabetes (51%). The most common targeted interventions included intravenous steroids (64.6%), azithromycin (42.9%), and hydroxychloroquine (34.7%). Among the group treated with hydroxychloroquine, 16 (47.1%) patients were found to have co-infections compared to 13 (20.3%) patients not treated with hydroxychloroquine (p=.006). The multivariable logistic regression showed increased odds of co-infection associated with the administration of hydroxychloroquine (odds ratio [OR] 4.04;95% CI 1.37 – 11.98, p=.012;Hosmer and Lemeshow goodness-of-fit test p=.724) and central line placement (OR 7.27;95% CI 1.93 – 27.31;p=.003). CONCLUSIONS: In this retrospective analysis of 98 adults with COVID-19 hospitalized in a community ICU, the patients who received hydroxychloroquine were found to have increased risk of co-infections. CLINICAL IMPLICATIONS: Hydroxychloroquine may increase the risk of co-infections in critical COVID-19 patients DISCLOSURES: No relevant relationships by Daniel Bustamante-Soliz, source=Web Response No relevant relationships by Chul Won Chung, source=Web Response No relevant relationships by Harvey Friedman, source=Web Response No relevant relationships by Elizabeth Patino, source=Web Response No relevant relationships by Guillermo Rodriguez-Nava, source=Web Response No relevant relationships by Daniela Trelles Garcia, source=Web Response No relevant relationships by Valeria Trelles Garcia, source=Web Response No relevant relationships by Maria Yanez-Bello, source=Web Response