4 research outputs found
Modeling the Subsurface Structure of Sunspots
While sunspots are easily observed at the solar surface, determining their
subsurface structure is not trivial. There are two main hypotheses for the
subsurface structure of sunspots: the monolithic model and the cluster model.
Local helioseismology is the only means by which we can investigate
subphotospheric structure. However, as current linear inversion techniques do
not yet allow helioseismology to probe the internal structure with sufficient
confidence to distinguish between the monolith and cluster models, the
development of physically realistic sunspot models are a priority for
helioseismologists. This is because they are not only important indicators of
the variety of physical effects that may influence helioseismic inferences in
active regions, but they also enable detailed assessments of the validity of
helioseismic interpretations through numerical forward modeling. In this paper,
we provide a critical review of the existing sunspot models and an overview of
numerical methods employed to model wave propagation through model sunspots. We
then carry out an helioseismic analysis of the sunspot in Active Region 9787
and address the serious inconsistencies uncovered by
\citeauthor{gizonetal2009}~(\citeyear{gizonetal2009,gizonetal2009a}). We find
that this sunspot is most probably associated with a shallow, positive
wave-speed perturbation (unlike the traditional two-layer model) and that
travel-time measurements are consistent with a horizontal outflow in the
surrounding moat.Comment: 73 pages, 19 figures, accepted by Solar Physic
Delay in diagnosis of influenza A (H1N1)pdm09 virus infection in critically ill patients and impact on clinical outcome
Background: Patients infected with influenza A (H1N1)pdm09 virus requiring admission to the ICU remain an important source of mortality during the influenza season. The objective of the study was to assess the impact of a delay in diagnosis of community-acquired influenza A (H1N1)pdm09 virus infection on clinical outcome in critically ill patients admitted to the ICU. Methods: A prospective multicenter observational cohort study was based on data from the GETGAG/SEMICYUC registry (2009â2015) collected by 148 Spanish ICUs. All patients admitted to the ICU in which diagnosis of influenza A (H1N1)pdm09 virus infection had been established within the first week of hospitalization were included. Patients were classified into two groups according to the time at which the diagnosis was made: early (within the first 2 days of hospital admission) and late (between the 3rd and 7th day of hospital admission). Factors associated with a delay in diagnosis were assessed by logistic regression analysis. Results: In 2059 ICU patients diagnosed with influenza A (H1N1)pdm09 virus infection within the first 7 days of hospitalization, the diagnosis was established early in 1314 (63.8 %) patients and late in the remaining 745 (36.2 %). Independent variables related to a late diagnosis were: age (odds ratio (OR)â=â1.02, 95 % confidence interval (CI) 1.01â1.03, Pâ<â0.001); first seasonal period (2009â2012) (ORâ=â2.08, 95 % CI 1.64â2.63, Pâ<â0.001); days of hospital stay before ICU admission (ORâ=â1.26, 95 % CI 1.17â1.35, Pâ<â0.001); mechanical ventilation (ORâ=â1.58, 95 % CI 1.17â2.13, Pâ=â0.002); and continuous venovenous hemofiltration (ORâ=â1.54, 95 % CI 1.08â2.18, Pâ=â0.016). The intra-ICU mortality was significantly higher among patients with late diagnosis as compared with early diagnosis (26.9 % vs 17.1 %, Pâ<â0.001). Diagnostic delay was one independent risk factor for mortality (ORâ=â1.36, 95 % CI 1.03â1.81, Pâ<â0.001). Conclusions: Late diagnosis of community-acquired influenza A (H1N1)pdm09 virus infection is associated with a delay in ICU admission, greater possibilities of respiratory and renal failure, and higher mortality rate. Delay in diagnosis of flu is an independent variable related to death
Epidemiology of intra-abdominal infection and sepsis in critically ill patients: âAbSeSâ, a multinational observational cohort study and ESICM Trials Group Project
Purpose: To describe the epidemiology of intra-abdominal infection in an international cohort of ICU patients according to a new system that classifies cases according to setting of infection acquisition (community-acquired, early onset hospital-acquired, and late-onset hospital-acquired), anatomical disruption (absent or present with localized or diffuse peritonitis), and severity of disease expression (infection, sepsis, and septic shock). Methods: We performed a multicenter (n = 309), observational, epidemiological study including adult ICU patients diagnosed with intra-abdominal infection. Risk factors for mortality were assessed by logistic regression analysis. Results: The cohort included 2621 patients. Setting of infection acquisition was community-acquired in 31.6%, early onset hospital-acquired in 25%, and late-onset hospital-acquired in 43.4% of patients. Overall prevalence of antimicrobial resistance was 26.3% and difficult-to-treat resistant Gram-negative bacteria 4.3%, with great variation according to geographic region. No difference in prevalence of antimicrobial resistance was observed according to setting of infection acquisition. Overall mortality was 29.1%. Independent risk factors for mortality included late-onset hospital-acquired infection, diffuse peritonitis, sepsis, septic shock, older age, malnutrition, liver failure, congestive heart failure, antimicrobial resistance (either methicillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci, extended-spectrum beta-lactamase-producing Gram-negative bacteria, or carbapenem-resistant Gram-negative bacteria) and source control failure evidenced by either the need for surgical revision or persistent inflammation. Conclusion: This multinational, heterogeneous cohort of ICU patients with intra-abdominal infection revealed that setting of infection acquisition, anatomical disruption, and severity of disease expression are disease-specific phenotypic characteristics associated with outcome, irrespective of the type of infection. Antimicrobial resistance is equally common in community-acquired as in hospital-acquired infection. © 2019, The Author(s)