Comparação entre duas estratégias para a detecção precoce do hipotiroidismo congênito Comparison between two strategies for the precocious detection of congenital hypothyroidism

OBJETIVO: Comparar em recém-nascidos (RN) duas estratégias diferentes para o rastreamento do hipotiroidismo congênito (HC), a dosagem primária de TSH no sangue colhido do cordão umbilical (método 1) e a dosagem primária de T4 no sangue colhido por punção de calcanhar no 2º dia de internação (método 2). MÉTODOS: Os autores compararam as duas estratégias em 10.000 RN. Dosaram o TSH por método imunofluorimétrico sensível em papel de filtro e o T4 por radioimunoensaio em papel de filtro. A coleta de sangue do calcanhar foi realizada no 2º dia de vida RESULTADOS: Os dois programas diagnosticaram todos os casos de HC nos RN (4 casos, 1/2.500 RN). O índice de rechamada por coleta inadequada foi nulo no método 1 e de 8,5% (850 RN) no método 2. O índice de reconvocação para confirmação de resultados foi de 0,06% (6 RN) no método 1 e de 2,25% (225 RN) no método 2; quando este método incluía também a dosagem suplementar de TSH, o índice baixou para 1,63% (163 RN). CONCLUSÃO: Os dados dos autores evidenciam a superioridade técnica da coleta de sangue a partir do cordão umbilical em relação à punção de calcanhar, assim como da dosagem primária de TSH em relação à de T4, uma vez que apresentam índices muito menores de reconvocação.<br>OBJECTIVE: Compare two different strategies in newborn screening for congenital hypothyroidism, primary TSH in the umbilical cord blood (method 1) and primary T4 in blood collected from the heel in the 2nd day of life (method 2). METHODS: We compared both strategies in 10,000 newborns, measuring TSH by a sensitive immunofluorimetric assay and T4 by a radioimmunoassay. RESULTS: Both strategies detected all cases of hypothyroidism (4 cases, 1/2,500 newborns). The recalling index owing to insufficient amount of blood to perform the assays was zero in method 1 and 8.5% (850 newborns) in method 2. The recalling index for confirmation of the results was 0.06% (6 newborns) in method 1 and 2.25% (225 newborns) in method 2; when method 2 included supplementary TSH, the recalling index was reduced to 1.63% (163 newborns). CONCLUSION: Our data indicate the technical superiority of the umbilical cord blood compared to heel and primary TSH compared to primary T4 in the neonatal thyroid screening for congenital hypothyroidism

Modelos matemáticos para predição da chuva de projeto para regiões do Estado de Minas Gerais Mathematical models for the estimation of rainfall in selected regions of Minas Gerais State, Brazil

O uso de modelos matemáticos para predição da chuva é uma forma prática e precisa para determinação do valor a ser aplicado em projetos, sendo útil para localidades desprovidas de informações pluviométricas. Objetivou-se ajustar o método de Bell, que possui características de regionalização para a chuva de projeto, com base em equações de chuvas intensas e modelos de probabilidade de Gumbel de estações meteorológicas do Estado de Minas Gerais ajustando, também, um modelo para cada região do estado. Avaliaram-se os modelos considerando-se o coeficiente de determinação e os erros médios em relação aos dados originais. Para validação, trabalhou-se com três estações meteorológicas da região Norte não usadas para ajuste do respectivo modelo. Foram analisadas três metodologias para estimativa da chuva intensa padrão (h(60,2)), que pondera o método usado, ressaltando-se a média aritmética, a média ponderada pelo inverso do quadrado da distância e a predição geoestatística (krigagem). Observou-se que os modelos possuem bons indicadores estatísticos e a validação produziu erros baixos, mostrando que os modelos podem ser aplicados, especialmente se a krigagem for usada para estimativa do parâmetro h(60,2).<br>The use of mathematical models for predicting rainfall is a practical and accurate way of determining this parameter to be applied to regions which do not have any precipitation data. Based on the intense rainfall equations and Gumbel's probability model for maximum daily precipitation of meteorological stations in Minas Gerais State, the objective of this work was to adjust the Bell's Method, with regional features, for rainfall, adjusting one model for each region. The regional parameters were estimated by non-linear multiple regression, using Gauss-Newton's method. The goodness of the models was evaluated by the coefficient of determination and mean errors of prediction as compared to the original data. Data from three meteorological stations in the Northern region, which were not used to adjust the respective model, were used for validation purposes. The most frequent precipitation was tested by the arithmetic mean, the weighted mean by the inverse-square-distance and the geo-statistical prediction (kriging). The models produced good statistical parameters, with low mean errors, showing their accuracy, specially when the kriging method for estimating the most frequent precipitation was used

How well do covariates perform when adjusting for sampling bias in online COVID-19 research? Insights from multiverse analyses

COVID-19 research has relied heavily on convenience-based samples, which—though often necessary—are susceptible to important sampling biases. We begin with a theoretical overview and introduction to the dynamics that underlie sampling bias. We then empirically examine sampling bias in online COVID-19 surveys and evaluate the degree to which common statistical adjustments for demographic covariates successfully attenuate such bias. This registered study analysed responses to identical questions from three convenience and three largely representative samples (total N = 13,731) collected online in Canada within the International COVID-19 Awareness and Responses Evaluation Study (www.icarestudy.com). We compared samples on 11 behavioural and psychological outcomes (e.g., adherence to COVID-19 prevention measures, vaccine intentions) across three time points and employed multiverse-style analyses to examine how 512 combinations of demographic covariates (e.g., sex, age, education, income, ethnicity) impacted sampling discrepancies on these outcomes. Significant discrepancies emerged between samples on 73% of outcomes. Participants in the convenience samples held more positive thoughts towards and engaged in more COVID-19 prevention behaviours. Covariates attenuated sampling differences in only 55% of cases and increased differences in 45%. No covariate performed reliably well. Our results suggest that online convenience samples may display more positive dispositions towards COVID-19 prevention behaviours being studied than would samples drawn using more representative means. Adjusting results for demographic covariates frequently increased rather than decreased bias, suggesting that researchers should be cautious when interpreting adjusted findings. Using multiverse-style analyses as extended sensitivity analyses is recommended