Real-World Data and Machine Learning to Predict Cardiac Amyloidosis

(1) Background: Cardiac amyloidosis or “stiff heart syndrome” is a rare condition that occurs when amyloid deposits occupy the heart muscle. Many patients suffer from it and fail to receive a timely diagnosis mainly because the disease is a rare form of restrictive cardiomyopathy that is difficult to diagnose, often associated with a poor prognosis. This research analyses the characteristics of this pathology and proposes a statistical learning algorithm that helps to detect the disease. (2) Methods: The hospitalization clinical (medical and nursing ones) records used for this study are the basis of the learning and training techniques of the algorithm. The approach consisted of using the information generated by the patients in each admission and discharge episode and treating it as data vectors to facilitate their aggregation. The large volume of clinical histories implied a high dimensionality of the data, and the lack of diagnosis led to a severe class imbalance caused by the low prevalence of the disease. (3) Results: Although there are few patients with amyloidosis in this study, the proposed approach demonstrates that it is possible to learn from clinical records despite the lack of data. In the validation phase, the algorithm first acted on data from the general study population. It then was applied to a sample of patients diagnosed with heart failure. The results revealed that the algorithm detects disease when data vectors profile each disease episode. (4) Conclusions: The prediction levels showed that this technique could be useful in screening processes on a specific population to detect the disease.

Laboratory testing and screening for SARS-CoV-2: A review of current methods

In a relatively short period of time new coronavirus disease (COVID-19) has become a global threat, both to human health and to the functioning of human society in general. This pandemic is certainly neither the first nor is it likely to be the last disease episode in human history. At the moment, it is still too early to make a reliable assessment of its total effect on human civilization, but it can already be stated that this disease, and its causative agent SARS-CoV-2 virus, have caused a strong scientific response all around the World. For the first time in this magnitude, it has united the resources of large scientific institutions and companies with the aim of finding solutions for fast and accurate virus detection procedures, effective and safe vaccine, reliable medical treatments, etc. It is astonishing that only a month has passed from the first officially detected case to the complete sequencing of the SARS-CoV-2 virus genome and the creation of the first detection systems based on RT-PCR method. After that, numerous scientific teams and companies worked together, or independently, to improve the detection methods. Their work included further optimization of PCR and other genetic approaches, as well as the development of detection methods based on the analysis of specific antibodies and viral antigens. The aim of this paper is to review the results that were achieved in this area so far, analyze the strategies currently used in the world and the region, and to predict future steps in the process of optimizing and improving methods for SARS CoV-2 detection in individual patients and the global human population.

The differences between referred and non-referred patients to a psychiatric consultation-liaison service in a general hospital

Objective The primary aim of this study was to investigate whether there are clinical differences between patients who are referred or not referred for psychiatric consultation and liaison service. The secondary aim was to compare the perspectives of doctors, nurses and patients. Methods This naturalistic, prospective and comparative study (N = 294) utilised a control sample of non-referrals (n = 177, consenting 81) and referrals (n = 177, consenting 49). The normality of the data was examined with the Shapiro-Wilk test; bivariate group comparisons were made using Mann-Whitney, Wilcoxon tests and bivariate regression analyses. Statistically adjusted group comparisons were performed with multivariate median regressions. Results The sample presented limited representativeness. Referred patients were predominantly women, mostly living alone and not working. Compared to the non-referred patients, their disease episode and length of hospital stay were significantly longer, self-efficacy and quality of life lower and psychological stress was higher. For referred patients, there were no differences between the estimations of mental burden and the need for care among doctors, nurses and patients. Self-efficacy and appraisal of one's own burden were the best predictors of the extent of mental symptoms. Discussion Patients in an admission ward for internal medicine referred to a psychiatric consultation-liaison service displayed a more adverse psychosocial profile and were more psychologically burdened than non-referred patients, but they are also relevantly subsyndromal burdened. Identifying and supporting burdened patients is an endeavour that requires collaborative care, especially in the transition to specialised mental health and to primary care.

Capturing heterogeneous infectiousness in transmission dynamic models of tuberculosis: a compartmental modelling approach

Infectiousness heterogeneity among individuals with tuberculosis (TB) is substantial and is likely to have a significant impact on the long-term dynamics of TB and the effectiveness of interventions. However, there is a gap in capturing heterogeneous infectiousness and evaluating its impact on the effectiveness of interventions.Informed by observed distribution of secondary infections, we constructed a deterministic model of TB transmission using ordinary differential equations. The model incorporated assumption of heterogeneous infectiousness with three levels of infectivity, namely non-spreaders, low-spreaders and super-spreaders. We evaluated the effectiveness of dynamic transmission untargeted and targeted implementation of an intervention intended to represent active case finding with a point-of-care diagnostic tool. The simulated intervention detected 20% of all TB patients who would otherwise have been missed by the health system during their disease episode and was compared across four epidemiological scenarios.Our model suggested that targeting the active case finding intervention towards super-spreaders was more effective than untargeted intervention in all setting scenarios, with more effectiveness in settings with low case detection and high transmission intensity. For instance, a targeted intervention achieved a 42.2% reduction in TB incidence, while the untargeted intervention achieved only a 20.7% reduction over 20 years, given the same number of people treated. Although the most marked impact on equilibrium TB incidence came from the rate of late reactivation, the proportion of super-spreaders and their relative infectiousness had shown substantial impact.Targeting active case-finding interventions to highly infectious cases likely to be particularly beneficial in settings where case detection is poor. Heterogeneity-related parameters had an equivalent effect to several other parameters that have been established as being very important to TB transmission dynamics.

Dynamic Gill and Mucous Microbiomes Track an Amoebic Gill Disease Episode in Farmed Atlantic Salmon

Background Amongst gill disorders in Atlantic salmon, amoebic gill disease (AGD) is currently one of the most common and virulent, resulting in large losses for the aquaculture industry. However, our understanding of the role of the gill microbiome during AGD development is limited. Thus, we undertook a longitudinal study with the main objective of characterising the microbiome of gill, and mucous, samples from farmed Atlantic salmon before, and during, an AGD episode. Using a newly optimised DNA extraction protocol, we sequenced rRNA genes from 90 Atlantic salmon gill microbiomes from a fish farm (West coast of Ireland) over the course of a summer season. The first aetiological agent of AGD, Neoparamoeba perurans , was quantified using PCR targeting 18S rRNA genes. The same analyses were done using mucous samples as suitable, non-lethal alternatives to gill samples. Microbiome features across the sampling campaign were distinguished, focusing on patterns before and during the AGD episode. Results The richness and balance of the prokaryotic community on gills were trending upwards prior to the first appearance of AGD symptoms. The microbiome changed significantly, with reduced diversity and balance, after the AGD episode was confirmed, and the changing bacterial community was driven by competitive exclusion. However, this trend was reversed with the application of a first, and a second, freshwater bath treatment. Mucous samples behaved similarly. The variance of the entire prokaryotic community from both gill and mucous samples was significantly affected by the abundance of N. perurans . Rubritalea sp. were abundant in every gill and mucous sample; however, other genera ( Dyadobacter, Shewanella and Pedobacter ) were maximally abundant in gill and mucous samples 12 days prior to the first detection of AGD symptoms. Conclusions Gill and mucous microbiomes changed significantly after the first AGD symptoms were evident, correlating with N. perurans concentrations and supporting a connection between the development of the AGD and the gill microbiome. Those changes, however, were reversed by the application of multiple freshwater treatments, which returned gills to a more healthy state. Despite differences between microbiome features from gill and mucous samples, the data establish mucous scrapings as suitable, non-lethal substitutes for partial characterisation of the whole prokaryotic community from fish gills. The genus Shewanella was widely present, and significantly more abundant, immediately before the first AGD symptoms than during the AGD episode, marking this out as a feasible, putative target in identifying proxies for early detection of AGD.

Mucosal infection rewires TNFɑ signaling dynamics to skew susceptibility to recurrence

A mucosal infectious disease episode can render the host either more or less susceptible to recurrent infection, but the specific mechanisms that tip the balance remain unclear. We investigated this question in a mouse model of recurrent urinary tract infection and found that a prior bladder infection resulted in an earlier onset of tumor necrosis factor-alpha (TNFɑ)-mediated bladder inflammation upon subsequent bacterial challenge, relative to age-matched naive mice. However, the duration of TNFɑ signaling activation differed according to whether the first infection was chronic (Sensitized) or self-limiting (Resolved). TNFɑ depletion studies revealed that transient early-phase TNFɑ signaling in Resolved mice promoted clearance of bladder-colonizing bacteria via rapid recruitment of neutrophils and subsequent exfoliation of infected bladder cells. In contrast, sustained TNFɑ signaling in Sensitized mice prolonged damaging inflammation, worsening infection. This work reveals how TNFɑ signaling dynamics can be rewired by a prior infection to shape diverse susceptibilities to future mucosal infections.

Can We Trust the Literature on Risk Factors and Triggers for Low Back Pain? A Systematic Review of a Sample of Contemporary Literature

Background. Risk factors (RFs) for the “disease” of low back pain (LBP) are probably different from the triggers of new episodes of LBP. Investigating RFs for the onset of the “disease” and the triggers of LBP is problematic if researchers fail to discern the different types of pain-free status of participants at and before baseline. There is a difference between never having had LBP and having been pain-free for a certain period only. In this review, we assessed the dependability of contemporary literature on RFs and triggers of LBP, in relation to the “disease” and the episodes, respectively.Methods. A literature search from 2010 until 2017 was performed. Information on the definitions of LBP, potential RFs/triggers, and study design was extracted. Studies were reclassified based on the type of LBP concerning the “disease,” episode, or mixed/unclear/chronic. RFs and triggers were grouped into major domains, and positive associations listed, respectively, for the “disease” and episodes.Results. In 42 of the included 47 articles, it was not clear if the authors investigated RFs for the “disease” of LBP or triggers of new episodes. Only one study properly reported RFs for the onset of the “disease” of LBP, and four studies were deemed suitable to investigate triggers for a new episode of LBP. No study reproduced the results of other included studies.Conclusion. Trustworthy information regarding RFs and triggers of LBP is rare in the current literature. Future research needs to use precise definitions of LBP (onset of the “disease” vs. episodes) and nominate the timing of the associated factors in relation to the types of LBP as these are two critical factors when studying causes of LBP.