A Multicenter Retrospective Cohort Study to Characterize Patients Hospitalized With Multisystem Inflammatory Syndrome in Adults and Coronavirus Disease 2019 in the United States, 2020-2021.

BACKGROUND: The diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-associated multisystem inflammatory syndrome in adults (MIS-A) requires distinguishing it from acute coronavirus disease 2019 (COVID-19) and may affect clinical management. METHODS: In this retrospective cohort study, we applied the US Centers for Disease Control and Prevention case definition to identify adults hospitalized with MIS-A at 6 academic medical centers from 1 March 2020 to 31 December 2021. Patients MIS-A were matched by age group, sex, site, and admission date at a 1:2 ratio to patients hospitalized with acute symptomatic COVID-19. Conditional logistic regression was used to compare demographic characteristics, presenting symptoms, laboratory and imaging results, treatments administered, and outcomes between cohorts. RESULTS: Through medical record review of 10 223 patients hospitalized with SARS-CoV-2-associated illness, we identified 53 MIS-A cases. Compared with 106 matched patients with COVID-19, those with MIS-A were more likely to be non-Hispanic black and less likely to be non-Hispanic white. They more likely had laboratory-confirmed COVID-19 ≥14 days before hospitalization, more likely had positive in-hospital SARS-CoV-2 serologic testing, and more often presented with gastrointestinal symptoms and chest pain. They were less likely to have underlying medical conditions and to present with cough and dyspnea. On admission, patients with MIS-A had higher neutrophil-to-lymphocyte ratio and higher levels of C-reactive protein, ferritin, procalcitonin, and D-dimer than patients with COVID-19. They also had longer hospitalization and more likely required intensive care admission, invasive mechanical ventilation, and vasopressors. The mortality rate was 6% in both cohorts. CONCLUSIONS: Compared with patients with acute symptomatic COVID-19, adults with MIS-A more often manifest certain symptoms and laboratory findings early during hospitalization. These features may facilitate diagnosis and management.

Using body temperature and variables commonly available in the EHR to predict acute infection: a proof-of-concept study showing improved pretest probability estimates for acute COVID-19 infection among discharged emergency department patients.

OBJECTIVES: Obtaining body temperature is a quick and easy method to screen for acute infection such as COVID-19. Currently, the predictive value of body temperature for acute infection is inhibited by failure to account for other readily available variables that affect temperature values. In this proof-of-concept study, we sought to improve COVID-19 pretest probability estimation by incorporating covariates known to be associated with body temperature, including patient age, sex, comorbidities, month, and time of day. METHODS: For patients discharged from an academic hospital emergency department after testing for COVID-19 in March and April of 2020, we abstracted clinical data. We reviewed physician documentation to retrospectively generate estimates of pretest probability for COVID-19. Using patients' COVID-19 PCR test results as a gold standard, we compared AUCs of logistic regression models predicting COVID-19 positivity that used: (1) body temperature alone; (2) body temperature and pretest probability; (3) body temperature, pretest probability, and body temperature-relevant covariates. Calibration plots and bootstrap validation were used to assess predictive performance for model #3. RESULTS: Data from 117 patients were included. The models' AUCs were: (1) 0.69 (2) 0.72, and (3) 0.76, respectively. The absolute difference in AUC was 0.029 (95% CI -0.057 to 0.114, p=0.25) between model 2 and 1 and 0.038 (95% CI -0.021 to 0.097, p=0.10) between model 3 and 2. CONCLUSIONS: By incorporating covariates known to affect body temperature, we demonstrated improved pretest probability estimates of acute COVID-19 infection. Future work should be undertaken to further develop and validate our model in a larger, multi-institutional sample.

Reduction of theta rhythm dissociates grid cell spatial periodicity from directional tuning.

Grid cells recorded in the medial entorhinal cortex of freely moving rats exhibit firing at regular spatial locations and temporal modulation with theta rhythm oscillations (4 to 11 hertz). We analyzed grid cell spatial coding during reduction of network theta rhythm oscillations caused by medial septum (MS) inactivation with muscimol. During MS inactivation, grid cells lost their spatial periodicity, whereas head-direction cells maintained their selectivity. Conjunctive grid-by-head-direction cells lost grid cell spatial periodicity but retained head-direction specificity. All cells showed reduced rhythmicity in autocorrelations and cross-correlations. This supports the hypothesis that spatial coding by grid cells requires theta oscillations, and dissociates the mechanisms underlying the generation of entorhinal grid cell periodicity and head-direction selectivity.