Treated incidence of psychotic disorders in the multinational EU-GEI study

Importance: Psychotic disorders contribute significantly to the global disease burden, yet the latest international incidence study of psychotic disorders was conducted in the 1980s. Objectives: To estimate the incidence of psychotic disorders using comparable methods across 17 catchment areas in 6 countries and to examine the variance between catchment areas by putative environmental risk factors. Design, Setting, and Participants: An international multisite incidence study (the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions) was conducted from May 1, 2010, to April 1, 2015, among 2774 individuals from England (2 catchment areas), France (3 catchment areas), Italy (3 catchment areas), the Netherlands (2 catchment areas), Spain (6 catchment areas), and Brazil (1 catchment area) with a first episode of nonorganic psychotic disorders (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10] codes F20-F33) confirmed by the Operational Criteria Checklist. Denominator populations were estimated using official national statistics. Exposures: Age, sex, and racial/ethnic minority status were treated as a priori confounders. Latitude, population density, percentage unemployment, owner-occupied housing, and single-person households were treated as catchment area-level exposures. Main Outcomes and Measures: Incidence of nonorganic psychotic disorders (ICD-10 codes F20-F33), nonaffective psychoses (ICD-10 codes F20-F29), and affective psychoses (ICD-10 codes F30-F33) confirmed by the Operational Criteria Checklist. Results: A total of 2774 patients (1196 women and 1578 men; median age, 30.5 years [interquartile range, 23.0-41.0 years]) with incident cases of psychotic disorders were identified during 12.9 million person-years at risk (crude incidence, 21.4 per 100\u202f000 person-years; 95% CI, 19.4-23.4 per 100\u202f000 person-years). A total of 2183 patients (78.7%) had nonaffective psychotic disorders. After direct standardization for age, sex, and racial/ethnic minority status, an 8-fold variation was seen in the incidence of all psychotic disorders, from 6.0 (95% CI, 3.5-8.6) per 100\u202f000 person-years in Santiago, Spain, to 46.1 (95% CI, 37.3-55.0) per 100\u202f000 person-years in Paris, France. Rates were elevated in racial/ethnic minority groups (incidence rate ratio, 1.6; 95% CI, 1.5-1.7), were highest for men 18 to 24 years of age, and were lower in catchment areas with more owner-occupied homes (incidence rate ratio, 0.8; 95% CI, 0.7-0.8). Similar patterns were observed for nonaffective psychoses; a lower incidence of affective psychoses was associated with higher area-level unemployment (incidence rate ratio, 0.3; 95% CI, 0.2-0.5). Conclusions and Relevance: This study confirmed marked heterogeneity in risk for psychotic disorders by person and place, including higher rates in younger men, racial/ethnic minorities, and areas characterized by a lower percentage of owner-occupied houses

Safety, Efficacy and Pharmacokinetics of Anidulafungin in Patients 1 Month to <2 Years of Age with Invasive Candidiasis, including Candidemia

Nineteen patients 1 month to &lt;2 years of age with (n = 16) or at high risk of (n = 3) invasive candidiasis received anidulafungin for 5-35 days (3 mg/kg day 1, 1.5 mg/kg daily thereafter) followed by optional fluconazole (NCT00761267). Most treatment-emergent adverse events were mild/moderate, and no treatment-related deaths occurred. End of intravenous therapy global response success rate was 68.8%. Pharmacokinetics were similar to adult patients

Using a 29-mRNA Host Response Classifier To Detect Bacterial Coinfections and Predict Outcomes in COVID-19 Patients Presenting to the Emergency Department

Clinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial coinfection, and determining illness severity since current practices require separate workflows. Here, we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and bacterial coinfections and predicting clinical severity of COVID-19. A total of 161 patients with PCR-confirmed COVID-19 (52.2% female; median age, 50.0 years; 51% hospitalized; 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene blood RNA), and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter. The IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrollment, and the remaining patients oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial coinfection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e., Clostridioides difficile colitis (n = 1), urinary tract infection (n = 1), and clinically diagnosed bacterial infections (n = 3), for a specificity of 99.4%. Two of 101 (2.8%) patients in the IMX-SEV-3 "Low" severity classification and 7/60 (11.7%) in the "Moderate" severity classification died within 30 days of enrollment. IMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19 and bacterial coinfections and predicted patients' risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management, including more accurate treatment decisions and optimized resource utilization. IMPORTANCE We assay the utility of the single-test IMX-BVN-3/IMX-SEV-3 classifiers that require just 2.5 mL of patient blood in concurrently detecting viral and bacterial infections as well as predicting the severity and 30-day outcome from the infection. A point-of-care device, in development, will circumvent the need for blood culturing and drastically reduce the time needed to detect an infection. This will negate the need for empirical use of broad-spectrum antibiotics and allow for antibiotic use stewardship. Additionally, accurate classification of the severity of infection and the prediction of 30-day severe outcomes will allow for appropriate allocation of hospital resources