Predicting critical illness on initial diagnosis of COVID-19 based on easily obtained clinical variables: development and validation of the PRIORITY model.

OBJECTIVES: We aimed to develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of coronavirus disease 2019 (COVID-19), to identify patients at risk of critical outcomes. METHODS: We used data from the SEMI-COVID-19 Registry, a cohort of consecutive patients hospitalized for COVID-19 from 132 centres in Spain (23rd March to 21st May 2020). For the development cohort, tertiary referral hospitals were selected, while the validation cohort included smaller hospitals. The primary outcome was a composite of in-hospital death, mechanical ventilation, or admission to intensive care unit. Clinical signs and symptoms, demographics, and medical history ascertained at presentation were screened using least absolute shrinkage and selection operator, and logistic regression was used to construct the predictive model. RESULTS: There were 10 433 patients, 7850 in the development cohort (primary outcome 25.1%, 1967/7850) and 2583 in the validation cohort (outcome 27.0%, 698/2583). The PRIORITY model included: age, dependency, cardiovascular disease, chronic kidney disease, dyspnoea, tachypnoea, confusion, systolic blood pressure, and SpO2 ≤93% or oxygen requirement. The model showed high discrimination for critical illness in both the development (C-statistic 0.823; 95% confidence interval (CI) 0.813, 0.834) and validation (C-statistic 0.794; 95%CI 0.775, 0.813) cohorts. A freely available web-based calculator was developed based on this model (https://www.evidencio.com/models/show/2344). CONCLUSIONS: The PRIORITY model, based on easily obtained clinical information, had good discrimination and generalizability for identifying COVID-19 patients at risk of critical outcomes.

Seroprevalence of vaccine-preventable and non-vaccine-preventable infections in migrants in Spain.

BACKGROUND: Updated seroprevalence studies of infections in migrants may aid the design of tailored vaccination and prevention programmes. The objective of this study was to describe the seroprevalence rates for potentially transmissible viral infections in migrants attended at a referral centre in a major European city. METHODS: Descriptive analysis of seroprevalence of vaccine-preventable and non-vaccine-preventable infections in migrants attended at a centre in Madrid, Spain (2018-19). Recorded variables included age, gender, country of birth/continent of origin, time from arrival to Spain until first clinic visit, rubella, measles, mumps, varicella (VZV), hepatitis B virus (HBV), hepatitis A virus (HAV), hepatitis C virus (HCV) and HIV serology. RESULTS: In total, 468 patients were included, 135 females (28.8%) and 333 males (71.2%), mean age 30.4 years. The majority of patients were from Africa (52.5%, of which 88.2% from sub-Saharan Africa), followed by Latin America (38.5%) and other areas (9%). Seroprevalence for tested migrants for rubella, measles and mumps was < 95% in the group overall (91% rubella, 88% measles, 83% mumps) and lower rates were observed in migrants >20 years (compared with those ≤ 20 years). Over 10% of females were potentially susceptible (negative/indeterminate serology) to rubella (11.4%), measles (12.7%) or mumps (10.3%). Lowest rates of rubella seropositivity were in Latin American migrants (over 12% potentially susceptible); measles and mumps seropositivity was lowest in migrants from areas other than Africa/Latin America (74% and 68%, respectively). Seroprevalence rates were 91% for VZV, 90% overall for HAV, ~6% for HBV chronic infection (~50% of migrants tested susceptible), 2% for HCV and 6% for HIV. CONCLUSIONS: Differences in seroprevalence for vaccine-preventable and transmissible infections according to gender, age range and area of origin were observed. Tailored screening, vaccination and prevention strategies in potentially vulnerable migrant groups should be designed.