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1.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21260776

RESUMO

The novel coronavirus disease-19 (COVID-19) pandemic caused by SARS-CoV-2 has ravaged global healthcare with previously unseen levels of morbidity and mortality. To date, methods to predict the clinical course, which ranges from the asymptomatic carrier to the critically ill patient in devastating multi-system organ failure, have yet to be identified. In this study, we performed large-scale integrative multi-omics analyses of serum obtained from COVID-19 patients with the goal of uncovering novel pathogenic complexities of this disease and identifying molecular signatures that predict clinical outcomes. We assembled a novel network of protein-metabolite interactions in COVID-19 patients through targeted metabolomic and proteomic profiling of serum samples in 330 COVID-19 patients compared to 97 non-COVID, hospitalized controls. Our network identified distinct protein-metabolite cross talk related to immune modulation, energy and nucleotide metabolism, vascular homeostasis, and collagen catabolism. Additionally, our data linked multiple proteins and metabolites to clinical indices associated with long-term mortality and morbidity, such as acute kidney injury. Finally, we developed a novel composite outcome measure for COVID-19 disease severity and created a clinical prediction model based on the metabolomics data. The model predicts severe disease with a concordance index of around 0.69, and furthermore shows high predictive power of 0.83-0.93 in two previously published, independent datasets.

2.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20080044

RESUMO

A surge of patients with coronavirus disease 2019 (COVID-19) presenting to New York City hospitals in March 2020 led to a sharp increase in the utilization of blood cultures, which overwhelmed the capacity of automated blood culture instruments. We sought to evaluate the utilization and diagnostic yield of blood cultures during the COVID-19 pandemic to determine prevalence and common etiologies of bacteremia, and to inform a diagnostic approach to relieve blood culture overutilization. We performed a retrospective cohort analysis of 88,201 blood cultures from 28,011 patients at a multicenter network of hospitals within New York City to evaluate order volume, positivity rate, time to positivity, and etiologies of positive cultures in COVID-19. Ordering volume increased by 34.8% in the second half of March 2020 compared to the first half of the month. The rate of bacteremia was significantly lower among COVID-19 patients (3.8%) than COVID-19 negative patients (8.0%) and those not tested (7.1%), p < 0.001. COVID-19 patients had a high proportion of organisms reflective of commensal skin microbiota, reducing the bacteremia rate to 1.6% when excluded. More than 98% of all positive cultures were detected within 4 days of incubation. Bloodstream infections are very rare for COVID-19 patients, which supports the judicious use of blood cultures in the absence of compelling evidence for bacterial coinfection. Clear communication with ordering providers is necessary to prevent overutilization of blood cultures during COVID-19 surges, and laboratories should consider shortening the incubation period from 5 days to 4 days to free additional capacity.

3.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20072116

RESUMO

ObjectiveTo characterize patients with coronavirus disease 2019 (COVID-19) in a large New York City (NYC) medical center and describe their clinical course across the emergency department (ED), inpatient wards, and intensive care units (ICUs). DesignRetrospective manual medical record review. SettingNewYork-Presbyterian/Columbia University Irving Medical Center (NYP/CUIMC), a quaternary care academic medical center in NYC. ParticipantsThe first 1000 consecutive patients with laboratory-confirmed COVID-19. MethodsWe identified the first 1000 consecutive patients with a positive RT-SARS-CoV-2 PCR test who first presented to the ED or were hospitalized at NYP/CUIMC between March 1 and April 5, 2020. Patient data was manually abstracted from the electronic medical record. Main outcome measuresWe describe patient characteristics including demographics, presenting symptoms, comorbidities on presentation, hospital course, time to intubation, complications, mortality, and disposition. ResultsAmong the first 1000 patients, 150 were ED patients, 614 were admitted without requiring ICU-level care, and 236 were admitted or transferred to the ICU. The most common presenting symptoms were cough (73.2%), fever (72.8%), and dyspnea (63.1%). Hospitalized patients, and ICU patients in particular, most commonly had baseline comorbidities including of hypertension, diabetes, and obesity. ICU patients were older, predominantly male (66.9%), and long lengths of stay (median 23 days; IQR 12 to 32 days); 78.0% developed AKI and 35.2% required dialysis. Notably, for patients who required mechanical ventilation, only 4.4% were first intubated more than 14 days after symptom onset. Time to intubation from symptom onset had a bimodal distribution, with modes at 3-4 and 9 days. As of April 30, 90 patients remained hospitalized and 211 had died in the hospital. ConclusionsHospitalized patients with COVID-19 illness at this medical center faced significant morbidity and mortality, with high rates of AKI, dialysis, and a bimodal distribution in time to intubation from symptom onset.

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