Shared component modelling as an alternative to assess geographical variations in medical practice: gender inequalities in hospital admissions for chronic diseases

<p>Abstract</p> <p>Background</p> <p>Small area analysis is the most prevalent methodological approach in the study of unwarranted and systematic variation in medical practice at geographical level. Several of its limitations drive researchers to use disease mapping methods -deemed as a valuable alternative. This work aims at exploring these techniques using - as a case of study- the gender differences in rates of hospitalization in elderly patients with chronic diseases.</p> <p>Methods</p> <p>Design and study setting: An empirical study of 538,358 hospitalizations affecting individuals aged over 75, who were admitted due to a chronic condition in 2006, were used to compare Small Area Analysis (SAVA), the Besag-York-Mollie (BYM) modelling and the Shared Component Modelling (SCM). Main endpoint: Gender spatial variation was measured, as follows: SAVA estimated gender-specific utilization ratio; BYM estimated the fraction of variance attributable to spatial correlation in each gender; and, SCM estimated the fraction of variance shared by the two genders, and those specific for each one.</p> <p>Results</p> <p>Hospitalization rates due to chronic diseases in the elderly were higher in men (median per area 21.4 per 100 inhabitants, interquartile range: 17.6 to 25.0) than in women (median per area 13.7 per 100, interquartile range: 10.8 to 16.6). Whereas Utilization Ratios showed a similar geographical pattern of variation in both genders, BYM found a high fraction of variation attributable to spatial correlation in both men (71%, CI95%: 50 to 94) and women (62%, CI95%: 45 to 77). In turn, SCM showed that the geographical admission pattern was mainly shared, with just 6% (CI95%: 4 to 8) of variation specific to the women component.</p> <p>Conclusions</p> <p>Whereas SAVA and BYM focused on the magnitude of variation and on allocating where variability cannot be due to chance, SCM signalled discrepant areas where latent factors would differently affect men and women.</p

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Overrepresentation of Glutamate Signaling in Alzheimer's Disease: Network-Based Pathway Enrichment Using Meta-Analysis of Genome-Wide Association Studies

Genome-wide association studies (GWAS) have successfully identified several risk loci for Alzheimer's disease (AD). Nonetheless, these loci do not explain the entire susceptibility of the disease, suggesting that other genetic contributions remain to be identified. Here, we performed a meta-analysis combining data of 4,569 individuals (2,540 cases and 2,029 healthy controls) derived from three publicly available GWAS in AD and replicated a broad genomic region (>248,000 bp) associated with the disease near the APOE/TOMM40 locus in chromosome 19. To detect minor effect size contributions that could help to explain the remaining genetic risk, we conducted network-based pathway analyses either by extracting gene-wise p-values (GW), defined as the single strongest association signal within a gene, or calculated a more stringent gene-based association p-value using the extended Simes (GATES) procedure. Comparison of these strategies revealed that ontological sub-networks (SNs) involved in glutamate signaling were significantly overrepresented in AD (p<2.7×10(-11), p<1.9×10(-11); GW and GATES, respectively). Notably, glutamate signaling SNs were also found to be significantly overrepresented (p<5.1×10(-8)) in the Alzheimer's disease Neuroimaging Initiative (ADNI) study, which was used as a targeted replication sample. Interestingly, components of the glutamate signaling SNs are coordinately expressed in disease-related tissues, which are tightly related to known pathological hallmarks of AD. Our findings suggest that genetic variation within glutamate signaling contributes to the remaining genetic risk of AD and support the notion that functional biological networks should be targeted in future therapies aimed to prevent or treat this devastating neurological disorder

O papel da lipemia pós-prandial na gênese da aterosclerose: particularidades do diabetes mellitus

A aterosclerose é uma doença multifatorial e complexa, que determina eventos clínicos causadores de morbi-mortalidade significativa, representada pela ocorrência de infarto agudo do miocárdio, angina e morte súbita. Está associada a anormalidades lipídicas, ativação plaquetária, trombose, inflamação, disfunção endotelial, estresse oxidativo e alterações metabólicas da matriz, entre outros distúrbios. Todas essas anormalidades são mais comuns e acentuadas no paciente com diabetes, assim como no estado pós-prandial. Dentre os fatores de risco para doença arterial coronariana que ainda não são efetivamente empregados nas estratégias de prevenção da doença em grandes populações destaca-se a hiperlipemia pós-prandial, possível marcador precoce de anormalidades metabólicas e disfunção vascular não observadas em jejum. Recentes resultados mostram que as alterações que ocorrem após uma única sobrecarga lipídica se relacionam negativamente à função endotelial, sendo que as alterações na reatividade vascular estão fortemente associadas à progressão da aterosclerose e aos eventos cardiovasculares. Essas alterações podem revelar um estado de intolerância às gorduras que já são detectadas em indivíduos saudáveis, antes mesmo que anormalidades em jejum sejam percebidas. Esta revisão aborda a fisiopatologia envolvida na lipemia pós-prandial e sua relação com a aterogênese, com ênfase no diabetes mellitus.Atherosclerosis is a complex and multifactorial disease, which determines clinical events that cause significant morbi-mortality, represented by acute myocardial infarction, angina and sudden death. It is associated with lipid disturbances, platelet activation, thrombosis, endothelial dysfunction, inflammation, oxidative stress, altered matrix metabolism, among other disturbances. All these abnormalities are usual and more pronounced in diabetic patients, as well as in the post-prandial state. Among the coronary artery disease risk factors that are not usually employed in clinical practice in the whole population, postprandial hyperlipemia plays a major role, being a possible early marker of metabolic abnormalities and vascular dysfunction not yet seen in the fasting state. Recent results showed that post-oral lipid overload changes are negatively associated with endothelial dysfunction, and vascular reactivity abnormalities are strongly related to atherosclerosis progression and cardiovascular events. These abnormalities could disclose a lipid intolerance state that can be detected in apparently healthy subjects even before fasting abnormalities are seen. This review will deal with the pathophysiology changes involved in post-prandial hyperlipemia and its relationship with atherogenesis, with particular emphasis to diabetes mellitus

A gamma-ray burst at a redshift of z approximate to 8.2

Long-duration gamma-ray bursts (GRBs) are thought to result from the explosions of certain massive stars(1), and some are bright enough that they should be observable out to redshifts of z > 20 using current technology(2-4). Hitherto, the highest redshift measured for any object was z = 6.96, for a Lyman-alpha emitting galaxy(5). Here we report that GRB 090423 lies at a redshift of z approximate to 8.2, implying that massive stars were being produced and dying as GRBs similar to 630 Myr after the Big Bang. The burst also pinpoints the location of its host galaxy