Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. MethodsIn this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2•5% (95% CI 1•4-4•3) for patients with phenotype A, 30•5% (28•5-32•6) for patients with phenotype B, and 60•7% (53•7-67•2) for patients with phenotype C (log-rank test p<0•0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5•3% [95% CI 3•4-8•1] for phenotype A, 31•3% [28•5-34•2] for phenotype B, and 59•5% [48•8-69•3] for phenotype C; external validation cohort: 3•7% [2•0-6•4] for phenotype A, 23•7% [21•8-25•7] for phenotype B, and 51•4% [41•9-60•7] for phenotype C).Interpretation Patients admitted to hospital with COVID-19 can be classified into three...

Objectives The majority of available scores to assess mortality risk of coronavirus disease 19 (COVID-19) patients in the emergency department have high risk of bias. Therefore, our aim was to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients, and to compare this score with other existing ones. Methods Consecutive patients (≥18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March-July, 2020. The model was validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. Results Median (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO 2 /FiO 2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833 to 0.885]) and Spanish (0.894 [95% CI 0.870 to 0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions We designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19.

A retrospective study was carried out of the ten cases of osteopoikilosis seen at this Orthopedic Unit over a 15-year period in order to determine the reasons why patients seek consultation, preliminary diagnosis, and associated lesions. Eight patients consulted for problems not related to the locomotor apparatus, and diagnosis was by chance; the other two presented joint pain. The preliminary diagnosis was osteoblastic metastasis in five patients and osteopoikilosis in the other five. None of the patients displayed skin or visceral involvement, but three presented bone alterations. Definitive diagnosis was made by measurement of biochemical markers of bone remodeling, radiography of both hands, and bone scan. Bone biopsy was performed in one case. Although rare, the radiographic symptoms of osteopoikilosis are sufficiently specific to avoid false diagnoses, which may give rise to rigorous and expensive studies for other important disorders.

The guidelines of Decree No. 7508 -June 28, 2011 -have contributed to enhance the capacity of governance of small municipalities in health regions. The objective of this study was to identify the potential and the obstacles in the process of integrated regional planning in health region 29, Rio Grande do Sul. This is a case study carried out through information from semi-structured interviews, field observations, and documentary records, analyzed according to Content Analysis method. The study had participation of health managers of five municipalities and three state public servants linked to the 16th Regional Health Coordination, selected intentionally. Five categories of analysis emerged: the Regional Intermanagers Committee (CIR) as a space of coordination; the strengthening of the Brazilian Unified Health System; the weakness of the management; individualism in observing the process; and what has guided the meetings of the CIR. Results indicate that the integrated regional planning process has advanced, in the sense of CIR being constituted as a space of mutual support between the municipal and state management. However, decisions are made with more political than technical basis, with little monitoring of the access to health actions and health services, hindering the ability of control and negotiation in relation to service providers. It is considered that the CIR needs to be strengthened and consolidated through improvement of the management and through effective participation of state and municipal health managers in order to enable regional governance.

Papel do agente comunitário de saúde no controle do estoque domiciliar de medicamentos em comunidades atendidas pela estratégia de saúde da família

Objective: To develop and validate a rapid scoring system at hospital admission for predicting in-hospital mortality in patients hospitalized with coronavirus disease 19 (COVID-19), and to compare this score with other existing ones. Design: Cohort study Setting: The Brazilian COVID-19 Registry has been conducted in 36 Brazilian hospitals in 17 cities. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients that were admitted between March-July, 2020. The model was then validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. Participants: Consecutive symptomatic patients (≥18 years old) with laboratory confirmed COVID-19 admitted to participating hospitals. Patients who were transferred between hospitals and in whom admission data from the first hospital or the last hospital were not available were excluded, as well those who were admitted for other reasons and developed COVID-19 symptoms during their stay. Main outcome measures: In-hospital mortality Results: Median (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, 53.8% were men, in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. From 20 potential predictors, seven significant variables were included in the in-hospital mortality risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859) and Spanish (0.899) validation cohorts. Our ABC2-SPH score showed good calibration in both Brazilian cohorts, but, in the Spanish cohort, mortality was somewhat underestimated in patients with very high (>25%) risk. The ABC2-SPH score is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions: We designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19.

OBJECTIVE:To analyze the relationship between the health promotion conditions in schools and the consumption of alcohol and other drugs by students.METHODS:This is a cross-sectional study with a probabilistic sample of 3,464 students aged 12 to 17 from all schools of the cities of Lajeado and Sapiranga, state of Rio Grande do Sul, Brazil, and 53 managers from the same schools; the data was collected in 2012. Reports of the use of tobacco, alcohol, and illicit drugs in 2012 were used as outcomes, and the health promotion score in the school environment was used as the exposure of interest. We submitted the data to multilevel analysis.RESULTS:The prevalence of the annual use of tobacco was 9.8% (95%CI 8.8-10.8), alcohol was 46.2% (95%CI 44.5-47.8), and other drugs was 10.9% (95%CI 9.9-12.0). In the crude analysis, only the use of tobacco was associated with less health promoting schools (OR = 1.89, 95%CI 1.16-3.09) when compared to those with better conditions. This association lost statistical significance in the adjusted analysis (OR = 1.27, 95%CI 0.74-2.19).CONCLUSIONS:The effects of the school environment on the use of drugs, especially tobacco and alcohol, are manifested mainly by the individual and family conditions of the adolescents.

This paper provides a direct test of how fixed export costs and productivity jointly determine firm-level export behavior. Using Chilean data, we construct indices of fixed export costs for each industry-region-year triplet and match them to domestic firms. Our empirical results show that firms facing higher fixed export costs are less likely to export, while those with higher productivity export more. These outcomes are the foundation of the widely-used sorting mechanism in trade models with firm heterogeneity. A particularly novel finding is that high-productivity nonexporters face greater fixed export costs than low-productivity exporters. We also find that the substitution between fixed export costs and productivity in determining export decisions is weaker for firms with higher productivity. Finally, both larger fixed export costs and greater within-triplet productivity dispersion raise the export volume of the average exporter.JEL codes: F10, F12, F14.