Análise comparativa de métodos para estimativa de valores extremos de processos aleatórios não-gaussianos

This work makes a comparative study between four methods for extreme values estimation of non-Gaussian time series. The methods studied are: Hermite Moment Model, Shifted Generalized Lognormal Distribution (SGLD), Average Conditional Exceedance Rates (ACER) and Weibull Distribution Model. In the first two the process is transformed into an equivalent Standard Gaussian using the first four Statistical Moments of the time series. The last two procedures operate directly with the peaks observed in the time series regardless their statistical dependence, with only the ACER taking into account the statistical dependence between the peaks. Three case studies are presented to evaluate the performance of these methodologies and their accuracy as a function of the simulation time. In particular, the time series used are Utilization Factor series on the cross-section by the DnV-OS-F201 Standard for the steel risers design. It is shown that the Hermite Model has its applicability limited to some skewness-kurtosis combinations; the SGLD, due to its great versatility to cover the skewness-kurtosis combinations, is able to model any kind of distribution with high precision; the ACER and the Weibull models estimate efficiently the extreme values even for short simulation times. It is also observed that longer simulations are desirable to reduce the estimated values uncertainties.Este trabalho faz um estudo comparativo entre quatro métodos para estimativa de valores extremos de séries temporais não gaussianas. Os métodos estudados são: Modelo dos Polinômios de Hermite, Distribuição Lognormal Deslocada Generalizada (SGLD), Taxas Médias de Excedências Condicionadas (ACER) e Modelo da Distribuição de Weibull. Nos dois primeiros o processo é transformado em um gaussiano padrão equivalente utilizando os quatro primeiros momentos estatísticos da série temporal. Os dois últimos procedimentos operam diretamente com os picos observados na série temporal, sendo que somente o ACER leva em conta a dependência estatística entre eles. Três estudos de caso são apresentados para avaliar o desempenho destas metodologias e a sua precisão em função do tempo de simulação. Em particular, as séries temporais utilizadas são séries do fator de utilização da seção transversal obtidas segundo a norma DnV-OS-F201 para o projeto de risers de aço. Mostra-se que o modelo de Hermite tem sua aplicabilidade limitada somente a algumas combinações de skewness-kurtosis; a SGLD, devido à sua grande versatilidade para cobrir combinações de skewness-kurtosis, é capaz de modelar qualquer tipo de distribuição com boa precisão; os modelos ACER e Weibull estimam eficientemente os valores extremos, mesmo para tempos de simulação curtos. Observa-se também que simulações mais longas são desejáveis para reduzir as incertezas das aproximações

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Active Surveillance of Antimicrobial Resistance and Carbapenemase-Encoding Genes According to Sites of Care and Age Groups in Mexico: Results from the INVIFAR Network

We analyzed the antimicrobial resistance (AMR) data of 6519 clinical isolates of Escherichia coli (n = 3985), Klebsiella pneumoniae (n = 775), Acinetobacter baumannii (n = 163), Pseudomonas aeruginosa (n = 781), Enterococcus faecium (n = 124), and Staphylococcus aureus (n = 691) from 43 centers in Mexico. AMR assays were performed using commercial microdilution systems (37/43) and the disk diffusion susceptibility method (6/43). The presence of carbapenemase-encoding genes was assessed using PCR. Data from centers regarding site of care, patient age, and clinical specimen were collected. According to the site of care, the highest AMR was observed in E. coli, K. pneumoniae, and P. aeruginosa isolates from ICU patients. In contrast, in A. baumannii, higher AMR was observed in isolates from hospitalized non-ICU patients. According to age group, the highest AMR was observed in the ≥60 years age group for E. coli, E. faecium, and S. aureus, and in the 19–59 years age group for A. baumannii and P. aeruginosa. According to clinical specimen type, a higher AMR was observed in E. coli, K. pneumoniae, and P. aeruginosa isolates from blood specimens. The most frequently detected carbapenemase-encoding gene in E. coli was blaNDM (84%)