Computer adaptive testing to assess impairing behavioral health problems in emergency department patients with somatic complaints.

Objectives: To assess: (1) the prevalence of mental health and substance use in patients presenting to the emergency department (ED) through use of a computer adaptive test (CAT-MH), (2) the correlation among CAT-MH scores and self- and clinician-reported assessments, and (3) the association between CAT-MH scores and ED utilization in the year prior and 30 days after enrollment. Methods: This was a single-center observational study of adult patients presenting to the ED for somatic complaints (97%) from May 2019 to March 2020. The main outcomes were computer-adaptive-assessed domains of suicidality, depression, anxiety, post-traumatic stress disorder (PTSD), and substance use. We conducted Pearson correlations and logistic regression for objectives 2 and 3, respectively. Results: From a sample of 794 patients, the proportion of those at moderate/severe risk was: 24.1% (suicidality), 8.3% (depression), 16.5% (anxiety), 12.3% (PTSD), and 20.4% (substance use). CAT-MH domains were highly correlated with self-report assessments (r = 0.49-0.79). Individuals who had 2 or more ED visits in the prior year had 62% increased odds of being in the intermediate-high suicide risk category (odds ratio [OR], 1.62; 95% confidence interval [CI], 1.07-2.44) compared to those with zero prior ED visits. Individuals who scored in the intermediate-high-suicide risk group had 63% greater odds of an ED visit within 30 days after enrollment compared to those who scored as low risk (OR, 1.63; 95% CI, 1.09, 2.44). Conclusion: The CAT-MH documented that a considerable proportion of ED patients presenting for somatic problems had mental health conditions, even if mild. Mental health problems were also associated with ED utilization.

Fluid Resuscitation and Progression to Renal Replacement Therapy in Patients With COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is associated with respiratory symptoms and renal effects. Data regarding fluid resuscitation and kidney injury in COVID-19 are lacking, and understanding this relationship is critical. OBJECTIVES: To determine if there is an association between fluid volume administered in 24 h and development of renal failure in COVID-19 patients. METHODS: Retrospective chart review; 14 hospitals in Indiana. Included patients were adults admitted between March 11, 2020 and April 13, 2020 with a positive test for severe acute respiratory syndrome coronavirus 2 within 3 days of admission. Patients requiring renal replacement therapy prior to admission were excluded. Volumes and types of resuscitative intravenous fluids in the first 24 h were obtained with demographics, medical history, and other objective data. The primary outcome was initiation of renal replacement therapy. Logistic regression modeling was utilized in creating multivariate models for determining factors associated with the primary outcome. RESULTS: The fluid volume received in the first 24 h after hospital admission was associated with initiation of renal replacement therapy in two different multivariate logistic regression models. An odds ratio of 1.42 (95% confidence interval 1.01-1.99) was observed when adjusting for age, heart failure, obesity, creatinine, bicarbonate, and total fluid volume. An odds ratio of 1.45 (95% confidence interval 1.02-2.05) was observed when variables significant in univariate analysis were adjusted for. CONCLUSIONS: Each liter of intravenous fluid administered to patients with COVID-19 in the first 24 h of presentation was independently associated with an increased risk for initiation of renal replacement therapy, supporting judicious fluid administration in patients with this disease.

Can we predict which COVID-19 patients will need transfer to intensive care within 24 hours of floor admission?

BACKGROUND: Patients with COVID-19 can present to the emergency department (ED) at any point during the spectrum of illness, making it difficult to predict what level of care the patient will ultimately require. Admission to a ward bed, which is subsequently upgraded within hours to an intensive care unit (ICU) bed, represents an inability to appropriately predict the patient's course of illness. Predicting which patients will require ICU care within 24 hours would allow admissions to be managed more appropriately. METHODS: This was a retrospective study of adults admitted to a large health care system, including 14 hospitals across the state of Indiana. Included patients were aged ≥ 18 years, were admitted to the hospital from the ED, and had a positive polymerase chain reaction (PCR) test for COVID-19. Patients directly admitted to the ICU or in whom the PCR test was obtained > 3 days after hospital admission were excluded. Extracted data points included demographics, comorbidities, ED vital signs, laboratory values, chest imaging results, and level of care on admission. The primary outcome was a combination of either death or transfer to ICU within 24 hours of admission to the hospital. Data analysis was performed by logistic regression modeling to determine a multivariable model of variables that could predict the primary outcome. RESULTS: Of the 542 included patients, 46 (10%) required transfer to ICU within 24 hours of admission. The final composite model, adjusted for age and admission location, included history of heart failure and initial oxygen saturation of <93% plus either white blood cell count > 6.4 or glomerular filtration rate < 46. The odds ratio (OR) for decompensation within 24 hours was 5.17 (95% confidence interval [CI] = 2.17 to 12.31) when all criteria were present. For patients without the above criteria, the OR for ICU transfer was 0.20 (95% CI = 0.09 to 0.45). CONCLUSIONS: Although our model did not perform well enough to stand alone as a decision guide, it highlights certain clinical features that are associated with increased risk of decompensation.

Characteristics of COVID-19 patients with bacterial coinfection admitted to the hospital from the emergency department in a large regional healthcare system.

INTRODUCTION: The rate of bacterial coinfection with SARS-CoV-2 is poorly defined. The decision to administer antibiotics early in the course of SARS-CoV-2 infection depends on the likelihood of bacterial coinfection. METHODS: We performed a retrospective chart review of all patients admitted through the emergency department with confirmed SARS-CoV-2 infection over a 6-week period in a large healthcare system in the United States. Blood and respiratory culture results were abstracted and adjudicated by multiple authors. The primary outcome was the rate of bacteremia. We secondarily looked to define clinical or laboratory features associated with bacteremia. RESULTS: There were 542 patients admitted with confirmed SARS-CoV-2 infection, with an average age of 62.8 years. Of these, 395 had blood cultures performed upon admission, with six true positive results (1.1% of the total population). An additional 14 patients had positive respiratory cultures treated as true pathogens in the first 72 h. Low blood pressure and elevated white blood cell count, neutrophil count, blood urea nitrogen, and lactate were statistically significantly associated with bacteremia. Clinical outcomes were not statistically significantly different between patients with and without bacteremia. CONCLUSIONS: We found a low rate of bacteremia in patients admitted with confirmed SARS-CoV-2 infection. In hemodynamically stable patients, routine antibiotics may not be warranted in this population.

Discovery of cancer biomarkers through the use of mouse models.

Although our understanding of the molecular pathogenesis of common types of cancer has improved considerably, the development of effective strategies for cancer diagnosis and treatment have lagged behind. Mouse models of cancer potentially represent an efficient means for uncovering diagnostic markers as genetic alterations associated with human tumors can be engineered in mice. In addition, defined stages of tumor development, breeding conditions, and blood sampling can all be controlled and standardized to limit heterogeneity. Alternatively human cancer cells can be injected into mice and tumor development monitored in xenotransplants. Mouse-based studies promise to elucidate a repertoire of protein changes that occur in blood and biological fluids during tumor development. This is illustrated in a study in which we have applied a three-dimensional intact protein analysis system (IPAS) to elucidate detectable protein changes in serum from immunodeficient mice with lung xenografts from orthotopically implanted human A549 lung adenocarcinoma cells. With sufficiently detailed protein sequence identifications, the observed protein changes can be attributed to either the host mouse or the human tumor cells. It is noteworthy that the majority of increases identified have corresponded to relatively abundant serum proteins, some of which have previously been reported as increased in the sera of cancer patients. Proteomic studies of mouse models of cancer allow assessment of the range of changes in plasma proteins that occur with tumor development and may lead to the identification of potential cancer markers applicable to humans.

Genetic mapping of loci controlling diethylstilbestrol-induced thymic atrophy in the Brown Norway rat.

Chronic estrogen administration can lead to thymic atrophy in rodents. In this article we report that the Brown Norway (BN) rat is sensitive to thymic atrophy induced by the estrogen diethylstilbestrol (DES). By contrast, DES does not induce significant thymic atrophy in the August x Copenhagen-Irish (ACI) strain. The sensitivity of the BN rat to DES-induced thymic atrophy appears to segregate as an incompletely dominant trait in crosses between the BN and ACI strains. In a (BN x ACI)F(2) population, we find strong evidence for three major genetic determinants of sensitivity to DES-induced thymic atrophy on rat Chromosome (RNO) 10 and RNO2. Genotypes at these loci, termed Esta1, 2, and 3, do not have a significant impact on the ability of DES to induce pituitary tumorigenesis or inhibit growth of these F(2) rats. These data indicate that the genetic factors that control DES-induced thymic atrophy are distinct from those that control the effects of DES on pituitary mass and body mass. The Esta intervals on RNO10 and RNO2 overlap with loci that control sensitivity to radiation-induced thymocyte apoptosis, as well as susceptibility to a variety of allergic and autoimmune pathologies, including allergic encephalitis, arthritis, and glomerulonephritis in rodents. These observations suggest that common genetic determinants may control sensitivity to estrogen-induced thymic atrophy, maintenance of thymocyte homeostasis, and immune function.