scholarly journals Systemic processes in influenza in fection, as a triggers of the development of somatic pathology in patients at risk

2015 ◽  
Vol 20 (4) ◽  
pp. 47-53
Author(s):  
E. G Deeva ◽  
T. G Zubkova ◽  
N. V Dunaeva ◽  
S. Zh Koltsebaeva ◽  
G. Yu Chelaeva ◽  
...  
Keyword(s):  
At Risk ◽  
Neurological Diseases ◽  
Influenza Infection ◽  
Critical Role ◽  
Risk Groups ◽  
Patients At Risk ◽  
Triggering Factor ◽  
Complicated Course ◽  
Severe Infections ◽  
The One

Pathogenetic mechanisms of influenza infection on the one hand are the triggering factor of certain diseases (asthma, neurological diseases and others.), on the other hand they worsen the course of concomitant somatic pathology, leading to severe, complicated course of infection and lethal outcomes in high-risk groups. The two components of the flu - a syndrome of systemic inflammation, which is manifested in the overproduction of cytokines and generalized vascular thrombosis syndrome (VTS) are the most important components of the pathogenesis of influenza and play a critical role in the development of severe infections, especially in patients with a history ofpremorbid background. Analysis of the pathogenic mechanisms of diseases, at risk, is necessary for the development of a comprehensive targeted tactics prevention, treatment and medical examination that will prevent mortality in these groups.

scholarly journals Sarcopenia and Malnutrition Screening in Female Osteoporosis Patients—A Cross-Sectional Study

2021 ◽  
Vol 10 (11) ◽  
pp. 2344
Author(s):  
Franca Genest ◽  
Dominik Rak ◽  
Elisa Bätz ◽  
Kerstin Ott ◽  
Lothar Seefried
Keyword(s):  
At Risk ◽  
Risk Groups ◽  
Cross Sectional Study ◽  
Mineral Density ◽  
Cross Sectional ◽  
Functional Deficits ◽  
Complementary Approach ◽  
Study Results ◽  
Patients At Risk ◽  
Not At Risk

Sarcopenia and malnutrition are important determinants of increased fracture risk in osteoporosis. SARC-F and MNA-SF are well-established questionnaires for identifying patients at risk for these conditions. We sought to evaluate the feasibility and potential added benefit of such assessments as well as the actual prevalence of these conditions in osteoporosis patients. We conducted a cross-sectional, single-center study in female osteoporosis patients ≥ 65 years (SaNSiBaR-study). Results of the sarcopenia (SARC-F) and malnutrition (MNA-SF) screening questionnaires were matched with a functional assessment for sarcopenia and data from patients’ medical records. Out of 107 patients included in the analysis, a risk for sarcopenia (SARC-F ≥ 4 points) and a risk for malnutrition (MNA-SF ≤ 11 points) was found in 33 (30.8%) and 38 (35.5%) patients, respectively. Diagnostic overlap with coincident indicative findings in both questionnaires was observed in 17 patients (16%). As compared to the respective not-at-risk groups, the mean short physical performance battery (SPPB) score was significantly reduced in both patients at risk for sarcopenia (7.0 vs. 10.9 points, p < 0.001) and patients at risk for malnutrition (8.7 vs. 10.5 points, p = 0.005). Still, confirmed sarcopenia according to EWGSOP2 criteria was present in only 6 (6%) of all 107 patients, with only 3 of them having an indicative SARC-F score. Bone mineral density was not significantly different in any of the at-risk groups at any site. In summary, applying SARC-F and MNA-SF in osteoporosis patients appears to be a complementary approach to identify individuals with functional deficits.

scholarly journals Identifying those at risk of reattendance at discharge from emergency departments using explainable machine learning

2020 ◽  
Author(s):  
F. P. Chmiel ◽  
M. Azor ◽  
F. Borca ◽  
M. J. Boniface ◽  
D. K. Burns ◽  
...  
Keyword(s):  
Machine Learning ◽  
At Risk ◽  
Emergency Departments ◽  
Risk Groups ◽  
Machine Learning Algorithms ◽  
Care Indicator ◽  
Number Of Patients ◽  
Increased Risk ◽  
Single Centre Study ◽  
Patients At Risk

ABSTRACTShort-term reattendances to emergency departments are a key quality of care indicator. Identifying patients at increased risk of early reattendance can help reduce the number of patients with missed or undertreated illness or injury, and could support appropriate discharges with focused interventions. In this manuscript we present a retrospective, single-centre study where we create and evaluate a machine-learnt classifier trained to identify patients at risk of reattendance within 72 hours of discharge from an emergency department. On a patient hold-out test set, our highest performing classifier obtained an AUROC of 0.748 and an average precision of 0.250; demonstrating that machine-learning algorithms can be used to classify patients, with moderate performance, into low and high-risk groups for reattendance. In parallel to our predictive model we train an explanation model, capable of explaining predictions at an attendance level, which can be used to help inform the design of interventional strategies.

scholarly journals Challenges and opportunities to understanding genetics of fungal diseases: towards a functional genomics approach

2021 ◽  
Author(s):  
Mariolina Bruno ◽  
Vasiliki Matzaraki ◽  
Frank L van de Veerdonk ◽  
Vinod Kumar ◽  
Mihai G. Netea
Keyword(s):  
Infectious Diseases ◽  
Fungal Infections ◽  
Critical Role ◽  
Treatment Strategies ◽  
Risk Groups ◽  
Fungal Diseases ◽  
Human Pathogens ◽  
Challenges And Opportunities ◽  
Patients At Risk ◽  
Immune Related Genes

Infectious diseases are a leading cause of morbidity and mortality worldwide and human pathogens have long been recognized as one of the main sources of evolutionary pressure, resulting in a high variable genetic background in immune-related genes. The study of the genetic contribution to infectious diseases has undergone tremendous advances over the last decades. Here, focusing on genetic predisposition to fungal diseases, we provide an overview of the available approaches for studying human genetic susceptibility to infections, reviewing current methodological and practical limitations. We describe how the classical methods available, such as family-based studies and candidate-gene studies, have contributed to the discovery of crucial susceptibility factors for fungal infections. We will also discuss the contribution of novel unbiased approaches to the field, highlighting their success but also their limitations for the fungal immunology field. Finally, we show how a systems genomics approach can overcome those limitations and can lead to efficient prioritization and identification of genes and pathways with a critical role in susceptibility to fungal diseases. This knowledge will help stratify patients at risk groups and, subsequently, develop early appropriate prophylactic and treatment strategies.

scholarly journals Identifying patients at risk of readmission for heart failure in the French national claim database

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
P Constantinou ◽  
N Pelletier-Fleury ◽  
V Olié ◽  
C Gastaldi-Ménager ◽  
Y Juillière ◽  
...  
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Administrative Data ◽  
Mortality Risk ◽  
Risk Groups ◽  
Claim Database ◽  
Health State ◽  
Hazard Ratios ◽  
Patients At Risk ◽  
Competing Mortality

Abstract Background To reduce readmissions for heart failure (HF) among HF patients, most at-risk individuals could be targeted to benefit from adapted interventions. A better understanding of HF readmission predictors could help clinicians and regulators identify patients most at-risk. We focused, in particular, on distinguishing HF severity from overall health-state severity. Methods We studied predictors of HF readmission available in administrative data in a nationwide cohort of patients aged 65 years or older surviving an index hospitalization for HF in 2015 (N = 70 657). To take into account the competing mortality risk, we estimated subdistribution hazard ratios (sdHRs) of HF readmission and cause-specific hazard ratios (csHRs) for HF readmission and for death without HF readmission, over a 1-year follow-up period. We then computed cumulative incidences and daily rates of HF readmission for specific risk-groups. Results 31.8% of patients were readmitted at least once for HF, among which 27.2% (8.6% of study cohort) were readmitted 30 days after discharge. 17.6% of patients died without any HF readmission. HF severity and overall health-state severity were the strongest HF readmission predictors (sdHRs 2.66 [95% CI: 2.52-2.81] and 1.37 [1.30-1.45] respectively, when comparing extreme categories). HF severity and length of index stay were more strongly associated with the rate (csHRs) of HF readmissions, whereas overall health-state severity and age were more strongly associated with the competing rate of death without HF readmission. Risk-groups defined upon HF severity and overall health-state severity had approximately 40% of separation in HF readmission proportion (21.9% versus 60.4%). Conclusions Our results stress the importance of considering both HF severity and overall morbidity and of accounting for the competing mortality risk to identify patients at-risk of HF readmission. Such patients could benefit from targeted transitional or post-discharge HF care. Key messages Heart failure patients can be stratified into risk-groups of readmission using administrative data. Identifying at-risk patients could help clinicians and regulators to target interventions.

scholarly journals Predicting Persistent Opioid Use, Abuse, and Toxicity Among Cancer Survivors

2019 ◽  
Vol 112 (7) ◽  
pp. 720-727 ◽  
Author(s):  
Lucas K Vitzthum ◽  
Paul Riviere ◽  
Paige Sheridan ◽  
Vinit Nalawade ◽  
Rishi Deka ◽  
...  
Keyword(s):  
Risk Factors ◽  
At Risk ◽  
Cancer Survivors ◽  
Critical Role ◽  
Multivariable Analysis ◽  
Area Under The Curve ◽  
Opioid Abuse ◽  
Opioid Use ◽  
Multivariable Logistic Regression Model ◽  
Patients At Risk

Abstract Background Although opioids play a critical role in the management of cancer pain, the ongoing opioid epidemic has raised concerns regarding their persistent use and abuse. We lack data-driven tools in oncology to understand the risk of adverse opioid-related outcomes. This project seeks to identify clinical risk factors and create a risk score to help identify patients at risk of persistent opioid use and abuse. Methods Within a cohort of 106 732 military veteran cancer survivors diagnosed between 2000 and 2015, we determined rates of persistent posttreatment opioid use, diagnoses of opioid abuse or dependence, and admissions for opioid toxicity. A multivariable logistic regression model was used to identify patient, cancer, and treatment risk factors associated with adverse opioid-related outcomes. Predictive risk models were developed and validated using a least absolute shrinkage and selection operator regression technique. Results The rate of persistent opioid use in cancer survivors was 8.3% (95% CI = 8.1% to 8.4%); the rate of opioid abuse or dependence was 2.9% (95% CI = 2.8% to 3.0%); and the rate of opioid-related admissions was 2.1% (95% CI = 2.0% to 2.2%). On multivariable analysis, several patient, demographic, and cancer and treatment factors were associated with risk of persistent opioid use. Predictive models showed a high level of discrimination when identifying individuals at risk of adverse opioid-related outcomes including persistent opioid use (area under the curve [AUC] = 0.85), future diagnoses of opioid abuse or dependence (AUC = 0.87), and admission for opioid abuse or toxicity (AUC = 0.78). Conclusion This study demonstrates the potential to predict adverse opioid-related outcomes among cancer survivors. With further validation, personalized risk-stratification approaches could guide management when prescribing opioids in cancer patients.

Application of Viscosity Volume Screening Tool as a screening tool in swallowing disorders diagnosis

2018 ◽  
Vol 7 (2) ◽  
pp. 6-10
Author(s):  
Barbara Jamróz ◽  
Magdalena Milewska ◽  
Pere Clave ◽  
Joanna Chmielewska
Keyword(s):  
At Risk ◽  
Treatment Cost ◽  
Screening Tool ◽  
Risk Groups ◽  
Swallowing Disorders ◽  
Screening Tests ◽  
Non Invasive ◽  
Risk Of Mortality ◽  
Patients At Risk ◽  
Instrumental Methods

It is commonly known that dysphagia is associated with primary (malnutrition, dehydration, aspiration pneumonia) as well as secondary consequences (longer hospital stay, increased treatment cost, higher risk of mortality). Therefore screening tests in swallowing disorders, especially at risk groups are essential. The aim of screening is identification of patients at risk of dysphagia and referring patient to further instrumental methods. Test should be non invasive, quick, easy to perform by medical staff, with highest sensitivity and specifity. One of the test is Viscosity – Volume Screening Test (VVST) with 3 different consistencies at 3 volumes (5, 10 and 20 ml), what wider possibilities of these tool in safe consistency and volume indication.

scholarly journals A35 MICROBIAL PROTEOLYTIC SIGNATURE IN ULCERATIVE COLITIS INDUCES AN INFLAMMATORY SIGNATURE IN MICROBIOTA-HUMANIZED MICE

2020 ◽  
Vol 3 (Supplement_1) ◽  
pp. 42-43
Author(s):  
H J Galipeau ◽  
W Turpin ◽  
A Caminero Fernandez ◽  
A Santiago ◽  
J Libertucci ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
At Risk ◽  
Proteolytic Activity ◽  
Intestinal Microbiota ◽  
Inflammatory Responses ◽  
Critical Role ◽  
Low Grade ◽  
Polymorphonuclear Cells ◽  
Fecal Samples ◽  
Patients At Risk

Abstract Background Altered gut microbiota composition has been associated with inflammatory bowel diseases (IBD) including ulcerative colitis (UC), but causality and bacterially-driven mechanisms, are unclear. Proteases within the gastrointestinal tract play a critical role in maintaining homeostasis and are tightly regulated by anti-proteases. Host-derived proteolytic imbalances have been described in IBD, including UC, however, the role of intestinal microbiota as a source of proteases and anti-proteases has largely been ignored. Aims To study microbial proteolytic activity and intestinal microbiota profiles in a cohort of individuals at-risk for IBD, and in those individuals that develop UC at follow-up. Methods Fecal samples were collected from healthy individuals at-risk for IBD and who went on to develop UC (pre-UC; n=14) and again after UC diagnosis (post-UC, n=10). Fecal samples from matched at-risk individuals that did not develop UC were used as healthy controls (n=52). Overall fecal proteolytic and elastolytic activity was measured. We performed metagenomics sequencing in 4 UC subjects (pre and post) and 4 matched HC using Illumina Hi-Seq from stool DNA. To investigate bacterial origin and functional significance, pregnant germ-free (GF) mice were colonized with a fecal sample from a selected UC subject (pre and post) and a matched HC. Naturally colonized litters were followed for 12 weeks, after which proteolytic activities and signs of inflammation were measured. Results Fecal proteolytic and elastase activity was increased in pre- and post-UC samples compared to HCs. Metagenomics revealed over 20k genes were significantly different between HC and pre-UC samples, and of these, 440 related to proteases and peptidases. Increased fecal proteolytic activity, higher lipocalin levels, and increased colonic polymorphonuclear cells in colonic H&E sections was observed in pre- and post-UC colonized mice compared to HC colonized mice. Mice colonized with pre-UC microbiota showed increased mRNA expression of genes linked to immunological disease, antimicrobial and inflammatory responses (ie. Tlr2, Tlr5, Nod2, and Il1b) as compared to HC colonized mice. Conclusions These results suggest increased fecal proteolytic activity is observed prior to the onset and clinical diagnosis of UC in patients at-risk for IBD, and upon transfer to mice born from colonized GF dams, low-grade inflammation develops. These pathways could be developed as novel non-invasive biomarkers to monitor at-risk populations. Submitted on behalf of the CCC-GEM Project consortium. Supported by CCC GIA to EF Verdu Funding Agencies CCC

scholarly journals INFECTION AND IMMUNITY IN PATIENTS WITH RISK GROUPS

2018 ◽  
pp. 109-119
Author(s):  
A. M. Zemskov ◽  
V. M. Zemskov ◽  
V. A. Zemskova ◽  
R. I. Sepiashvili ◽  
V. I. Zoloedov
Keyword(s):  
At Risk ◽  
Pregnant Women ◽  
Risk Groups ◽  
Elderly Persons ◽  
Immune Disorders ◽  
Infectious Morbidity ◽  
Patients At Risk ◽  
Pathological Pregnancy

Based on the data of the literature and their own studies, the features of infectious morbidity, immune disorders, the principles of their directed correction in patients at risk: pregnant women, puerperas, children born at physiological and pathological pregnancy, elderly persons are analyzed.

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