Understanding temporal dynamics of COVID-19 symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVID_pos; n = 2,317) versus COVID-19-negative (COVID_neg; n = 74,850) patients for the week preceding the PCR testing date, we identify anosmia/dysgeusia (27.1-fold), fever/chills (2.6-fold), respiratory difficulty (2.2-fold), cough (2.2-fold), myalgia/arthralgia (2-fold), and diarrhea (1.4-fold) as significantly amplified in COVID_pos over COVID_neg patients. The combination of cough and fever/chills has 4.2-fold amplification in COVID_pos patients during the week prior to PCR testing, in addition to anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.

A panel of experts convened by the International Society for Infectious Diseases (ISID) has reviewed and consolidated current recommendations for preventing vascular catheter infections, particularly central line-associated bloodstream infections (CLABSIs). This review provides healthcare professionals with insights into key issues such as the rates of CLABSI in high-income countries and low- and middle-income countries, the attributable extra length of stay, cost and mortality, and risk factors. This position paper highlights evidence-based strategies for preventing infections, applicable to both high-income and low- and middle-income countries.

To report the Mayo Clinic experience with COVID-19 related to patient outcomes. We conducted a retrospective chart review of patients diagnosed with COVID-19 between March 1, 2020 and July 31, 2020 at any of the Mayo Clinic sites. We abstracted pertinent comorbidities such as age, gender, body mass index, Charlson Comorbidity Index (CCI) variables, and treatments received. Factors associated with hospitalization and mortality were assessed in univariate and multivariate models. A total of 7,891 patients with confirmed COVID-19 with research authorization on file received care across the Mayo Clinic during the study period. Of these, 7217 patients were adults ≥ 18 years old which were analyzed further. 897 (11.3%) patients required hospitalization, and 354 (4.5%) patients received care in the Intensive Care Unit (ICU). All hospitalized patients were reviewed by a COVID-19 Treatment Review Panel, and 77.5% of inpatients received a COVID-19 directed therapy. Overall mortality was 1.1%, with 7.1% mortality in hospitalized patients and 11.9% in patients requiring ICU care. Mayo Clinic outcomes of COVID-19 patients in the ICU, hospital and community compare favorably to those reported nationally. This likely reflects the impact of interprofessional multidisciplinary team evaluation, effective leveraging of clinical trials and available treatments, deployment of remote monitoring tools, and maintenance of adequate operating capacity to not require surge adjustments. These best practices can help guide other health care systems with the continuing response to the COVID-19 pandemic.

Understanding temporal dynamics of COVID-19 patient symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVID _pos ; n=2,317) versus COVID-19-negative (COVID _neg ; n=74,850) patients for the week preceding the PCR testing date, we identify anosmia/dysgeusia (27.1-fold), fever/chills (2.6-fold), respiratory difficulty (2.2-fold), cough (2.2-fold), myalgia/arthralgia (2-fold), and diarrhea (1.4-fold) as significantly amplified in COVID _pos over COVID _neg patients. The combination of cough and fever/chills has 4.2-fold amplification in COVID _pos patients during the week prior to PCR testing, and along with anosmia/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.