Innlandet Hospital Trust

About: Innlandet Hospital Trust is a healthcare organization based out in Brumunddal, Norway. It is known for research contribution in the topics: Population & Dementia. The organization has 387 authors who have published 1302 publications receiving 37753 citations.

Correlation between the human fecal microbiota and depression

Abstract: Background Depression is a chronic syndrome with a pathogenesis linked to various genetic, biological, and environmental factors. Several links between gut microbiota and depression have been established in animal models. In humans, however, few correlations have yet been demonstrated. The aim of our work was therefore to identify potential correlations between human fecal microbiota (as a proxy for gut microbiota) and depression. Methods We analyzed fecal samples from 55 people, 37 patients, and 18 non-depressed controls. Our analyses were based on data generated by Illumina deep sequencing of 16S rRNA gene amplicons. Key Results We found several correlations between depression and fecal microbiota. The correlations, however, showed opposite directions even for closely related Operational Taxonomic Units (OTU's), but were still associated with certain higher order phylogroups. The order Bacteroidales showed an overrepresentation (p = 0.05), while the family Lachnospiraceae showed an underrepresentation (p = 0.02) of OTU's associated with depression. At low taxonomic levels, there was one clade consisting of five OTU's within the genus Oscillibacter, and one clade within Alistipes (consisting of four OTU's) that showed a significant association with depression (p = 0.03 and 0.01, respectively). Conclusions & Inferences The Oscillibacter type strain has valeric acid as its main metabolic end product, a homolog of neurotransmitter GABA, while Alistipes has previously been shown to be associated with induced stress in mice. In conclusion, the taxonomic correlations detected here may therefore correspond to mechanistic models.

Use of GRADE for assessment of evidence about prognosis: rating confidence in estimates of event rates in broad categories of patients.

Abstract: Introduction The term prognosis refers to the likelihood of future health outcomes in people with a given disease or health condition or with particular characteristics such as age, sex, or genetic profile. Patients and healthcare providers may be interested in prognosis for several reasons, so prognostic studies may have a variety of purposes,1–4 including establishing typical prognosis in a broad population, establishing the effect of patients’ characteristics on prognosis, and developing a prognostic model (often referred to as a clinical prediction rule) (Table 1). Considerations in determining the trustworthiness of estimates of prognosis arising from these types of studies differ. This article covers studies answering questions about the prognosis of a typical patient from a broadly defined population; we will consider prognostic studies assessing risk factors and clinical prediction guides in subsequent papers. Knowing the likely course of their disease may help patients to come to terms with, and plan for, the future. Knowledge of the risk of adverse outcomes or the likelihood of spontaneous resolution of symptoms is critical in predicting the likely effect of treatment and planning diagnostic investigations.5 If the probability of facing an adverse outcome is very low or the spontaneous remission of the disease is high (“good prognosis”), the possible absolute benefits of treatment will inevitably be low and serious adverse effects related to treatment or invasive diagnostic tests, even if rare, will loom large in any decision. If instead the probability of an adverse outcome is high (“bad prognosis”), the impact of new diagnostic information or of effective treatment may be large and patients may be ready to accept higher risks of diagnostic investigation and treatment related adverse effects. Inquiry into the credibility or trustworthiness of prognostic estimates has, to date, largely focused on individual studies of prognosis. Systematic reviews of the highest quality evidence including all the prognostic studies assessing a particular clinical situation are, however, gaining increasing attention, including the Cochrane Collaboration’s work (in progress) to define a template for reviews of prognostic studies (http://prognosismethods.cochrane.org/scope-ourwork). Trustworthy systematic reviews will not only ensure comprehensive collection, summarization, and critique of the primary studies but will also conduct optimal analyses. Matters that warrant consideration in such analyses include the method used to pool rates and whether analyses account for all the relevant covariates; the literature provides guidance on both questions.6 7 In this article, we consider how to establish degree of confidence in estimates from such bodies of evidence. The guidance in this article is directed primarily at researchers conducting systematic reviews of prognostic studies. It will also be useful to anyone interested in prognostic estimates and their associated confidence (including guideline developers) when evaluating a body of evidence (for example, a guideline panel using baseline risk estimates to estimate the absolute effect of Summary poIntS