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ObjectiveThe COVID-19 pandemic generated a massive amount of clinical data, which potentially holds yet undiscovered answers related to COVID-19 morbidity, mortality, long term effects, and therapeutic solutions. The objective of this study was to generate insights on COVID-19 mortality-associated factors and identify potential new therapeutic options for COVID-19 patients by employing artificial intelligence analytics on real-world data. MethodsA Bayesian statistics-based artificial intelligence data analytics tool (bAIcis(R)) within Interrogative Biology(R) platform was used for network learning, inference causality and hypothesis generation to analyze 16,277 PCR positive patients from a database of 279,281 inpatients and outpatients tested for SARS-CoV-2 infection by antigen, antibody, or PCR methods during the first pandemic year in Central Florida. This approach generated causal networks that enabled unbiased identification of significant predictors of mortality for specific COVID-19 patient populations. These findings were validated by logistic regression, regression by least absolute shrinkage and selection operator, and bootstrapping. ResultsWe found that in the SARS-CoV-2 PCR positive patient cohort, early use of the antiemetic agent ondansetron was associated with increased survival in mechanically ventilated patients. ConclusionsThe results demonstrate how real world COVID-19 focused data analysis using artificial intelligence can generate valid insights that could possibly support clinical decision-making and minimize the future loss of lives and resources.
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ObjectiveThe Seraph(R)100 Microbind Affinity Blood Filter(R) (Seraph 100) is an extracorporeal medical countermeasure that can remove many pathogens from blood, including the SARS-CoV-2 virus. The aim of this study was to evaluate safety and efficacy of Seraph 100 treatment for severe coronavirus disease 2019 (COVID-19). DesignMulticenter retrospective observational cohort study. SettingIntensive care units across four of thirteen participating sites who have completed data extraction. PatientsCritically ill COVID-19 patients treated with Seraph 100 under an Emergency Use Authorization (n=53) and historical control patients who met criteria for treatment (n=46). InterventionExtracorporeal treatment with the Seraph 100 filter. Measurements and Main ResultsAt baseline, the median age was 61 years, 72.7% were male, and 59.6% required mechanical ventilation. The groups were matched in terms of sex, race/ethnicity, body mass index, APACHE II score, need for mechanical ventilation, and other COVID-19 treatments. However, patients in the Seraph 100 group were younger with a median age of 61 years (IQR 42-65) compared to controls who had a median age of 64 (IQR 56-68, p=0.036). The Seraph 100 group also had a lower median Charlson comorbidity index (2, IQR 0-3) compared to control patients (3, IQR 2-4, p=0.006). Mortality was lower in the Seraph 100 treated group compared to the historical controls (37.7% vs 67.4%, respectively, p=0.003). Multivariable logistic regression analysis yielded an odds ratio of 0.27 (95% confidence interval 0.09-0.79, p=0.016). Of the 53 patients treated with Seraph 100, only 1 patient experienced a serious adverse event (transient hypotension at the start of the treatment which required a brief period of vasopressor support). ConclusionsThese data suggest that broad spectrum, pathogen agnostic, extracorporeal blood purification technologies can be safely and effectively deployed to meet new pathogen threats as an adjunct to standard treatments while awaiting the development of directed pharmacologic therapies and/or vaccines.
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BackgroundObservational studies have consistently described poor clinical outcomes and increased ICU mortality in patients with severe coronavirus disease 2019 (COVID-19) who require mechanical ventilation (MV). Our study describes the clinical characteristics and outcomes of patients with severe COVID-19 admitted to ICU in the largest health care system in the state of Florida, United States. MethodsRetrospective cohort study of patients admitted to ICU due to severe COVID-19 in AdventHealth health system in Orlando, Florida from March 11th until May 18th, 2020. Patients were characterized based on demographics, baseline comorbidities, severity of illness, medical management including experimental therapies, laboratory markers and ventilator parameters. Major clinical outcomes analyzed at the end of the study period were: hospital and ICU length of stay, MV-related mortality and overall hospital mortality of ICU patients. ResultsOut of total of 1283 patients with COVID-19, 131 (10.2%) met criteria for ICU admission (median age: 61 years [interquartile range {IQR}, 49.5-71.5]; 35.1% female). Common comorbidities were hypertension (84; 64.1%), and diabetes (54; 41.2%). Of the 131 ICU patients, 109 (83.2%) required MV and 9 (6.9%) received ECMO. Lower positive end expiratory pressure (PEEP) were observed in survivors [9.2 (7.7-10.4)] vs non-survivors [10 (9.1-12.9] p= 0.004]. Compared to non-survivors, survivors had a longer MV length of stay (LOS) [14 (IQR 8-22) vs 8.5 (IQR 5-10.8) p< 0.001], Hospital LOS [21 (IQR 13-31) vs 10 (7-1) p< 0.001] and ICU LOS [14 (IQR 7-24) vs 9.5 (IQR 6-11), p < 0.001]. The overall hospital mortality and MV-related mortality were 19.8% and 23.8% respectively. After exclusion of hospitalized patients, the hospital and MV-related mortality rates were 21.6% and 26.5% respectively. ConclusionsOur study demonstrates an important improvement in mortality of patients with severe COVID-19 who required ICU admission and MV in comparison to previous observational reports and emphasize the importance of standard of care measures in the management of COVID-19.