scholarly journals Disease Risk Factors Identified Through Shared Genetic Architecture and Electronic Medical Records

2014 ◽  
Vol 6 (234) ◽  
pp. 234ra57-234ra57 ◽  
Author(s):  
L. Li ◽  
D. J. Ruau ◽  
C. J. Patel ◽  
S. C. Weber ◽  
R. Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Genetic Architecture ◽  
Disease Risk ◽  
Shared Genetic

scholarly journals The Genetic Architecture of Alzheimer’s Disease Risk: A Genomic Structural Equation Modelling Study

2021 ◽  
Author(s):  
Isabelle F Foote ◽  
Benjamin M Jacobs ◽  
Georgina Mathlin ◽  
Cameron J Watson ◽  
Phazha LK Bothongo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Structural Equation Modelling ◽  
Structural Equation ◽  
Genetic Architecture ◽  
Disease Risk ◽  
Modifiable Risk Factors ◽  
Equation Modelling ◽  
Shared Genetic

AbstractBackgroundTargeting modifiable risk factors may have a role in the prevention of Alzheimer’s disease. However, the mechanisms by which these risk factors influence Alzheimer’s risk remain incompletely understood. Genomic structural equation modelling can reveal patterns of shared genetic architecture that provide insight into the pathophysiology of complex traits.MethodsWe identified genome-wide association studies for Alzheimer’s disease and its major modifiable risk factors: less education, hearing loss, hypertension, high alcohol intake, obesity, smoking, depression, social isolation, physical inactivity, type 2 diabetes, sleep disturbance and socioeconomic deprivation. We performed linkage disequilibrium score regression among these traits, followed by exploratory factor analysis, confirmatory factor analysis and structural equation modelling.ResultsWe identified complex networks of linkage disequilibrium among Alzheimer’s disease risk factors. The data were best explained by a bi-factor model, incorporating a Common Factor for Alzheimer’s risk, and three orthogonal sub-clusters of risk factors, which were validated across the two halves of the autosome. The first sub-cluster was characterised by risk factors related to sedentary lifestyle behaviours, the second by traits associated with reduced life expectancy and the third by traits that are possible prodromes of Alzheimer’s disease. Alzheimer’s disease was more genetically distinct and displayed minimal shared genetic architecture with its risk factors, which was robust to the exclusion of APOE.ConclusionShared genetic architecture may contribute to epidemiological associations between Alzheimer’s disease and its risk factors. Understanding the biology reflected by this communality may provide novel mechanistic insights that could help to prioritise targets for dementia prevention.

scholarly journals Comparing the Clinical Characteristics and Mortality of Residential and Non-Residential Older People with COVID-19: Retrospective Observational Study

2022 ◽  
Vol 19 (1) ◽  
pp. 483
Author(s):  
Francesc X. Marin-Gomez ◽  
Jacobo Mendioroz-Peña ◽  
Miguel-Angel Mayer ◽  
Leonardo Méndez-Boo ◽  
Núria Mora ◽  
...  
Keyword(s):  
Risk Factors ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Clinical Characteristics ◽  
Fold Increase ◽  
The Elderly ◽  
Health Administration ◽  
Epidemic Outbreak ◽  
Risk Of Death ◽  
Using Data

Nursing homes have accounted for a significant part of SARS-CoV-2 mortality, causing great social alarm. Using data collected from electronic medical records of 1,319,839 institutionalised and non-institutionalised persons ≥ 65 years, the present study investigated the epidemiology and differential characteristics between these two population groups. Our results showed that the form of presentation of the epidemic outbreak, as well as some risk factors, are different among the elderly institutionalised population with respect to those who are not. In addition to a twenty-fold increase in the rate of adjusted mortality among institutionalised individuals, the peak incidence was delayed by approximately three weeks. Having dementia was shown to be a risk factor for death, and, unlike the non-institutionalised group, neither obesity nor age were shown to be significantly associated with the risk of death among the institutionalised. These differential characteristics should be able to guide the actions to be taken by the health administration in the event of a similar infectious situation among institutionalised elderly people.

scholarly journals Identifying Risk Factors For Heart Disease in Electronic Medical Records: A Deep Learning Approach

2018 ◽  
Author(s):  
Thanat Chokwijitkul ◽  
Anthony Nguyen ◽  
Hamed Hassanzadeh ◽  
Siegfried Perez
Keyword(s):  
Risk Factors ◽  
Heart Disease ◽  
Deep Learning ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Learning Approach

scholarly journals Population prevalence and control of cardiovascular risk factors: What electronic medical records tell us

2014 ◽  
Vol 46 (1) ◽  
pp. 15-24 ◽  
Author(s):  
Arantxa Catalán-Ramos ◽  
Jose M. Verdú ◽  
María Grau ◽  
Manuel Iglesias-Rodal ◽  
José L. del Val García ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Population Prevalence ◽  
And Control

Abstract 16935: Cardiovascular Disease in Head Neck Squamous Cell Carcinoma Patients - A Case-Control Study Using Electronic Medical Records Data

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Amrita Mukherjee ◽  
Howard Wiener ◽  
Russell Griffin ◽  
Lisle M Nabell ◽  
Carrie G Lenneman ◽  
...  
Keyword(s):  
Risk Factors ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Cancer Site ◽  
Cancer Stage ◽  
Cvd Risk Factors ◽  
Cvd Risk ◽  
Related Factors ◽  
Traditional Risk Factors ◽  
Head Neck

Introduction: Cancer survivors have higher rates of cardiovascular disease (CVD) compared to age-adjusted general population. However, traditional CVD risk factors alone do not fully explain increased CVD risk in cancer patients. Cancer-related factors like cancer site, stage and chemotherapy may also contribute to CVD. Despite increase in head neck squamous cell carcinoma (HNSCC) cases in recent years, little is known about CVD risk in HNSCC patients. We aim to assess association of traditional risk factors and cancer-related factors with CVD in HNSCC patients. Methods: Electronic medical records data of 2391 HNSCC patients diagnosed between 2012-2018 at the UAB O’Neal Comprehensive Cancer Center, were included. ICD-9/10 codes were used to identify HNSCC patients, CVD cases and traditional risk factors. CVD cases were defined as those with composite events of ischemic heart disease and/ or heart failure; controls were without any CVD diagnosis. Cancer site, stage and treatment were included. Logistic regression [OR(95%CI)] was used to assess association of risk factors with CVD, adjusting for age, race, and gender. Results: HNSCC patients were mostly white (82.7%), male (74.7%) and had Stage III/IV cancer (46.6%). Oral cavity was the most common cancer site (32.9%), followed by oropharynx (31.7%); 55.4% patients had hypertension, 23.0% had dyslipidemia, and 16.1% had diabetes. CVD was diagnosed in 16.1% patients, who were more likely to be older [median age 67.0 vs 60.0 years, p<0.0001]. In the multivariable model, hypertension [2.08(1.54-2.80)], diabetes [2.03(1.52-2.70)] and dyslipidemia [2.36(1.82-3.07)] were associated with CVD. Smoking status was not associated. Association of cancer stage with CVD varied by cancer site. Stage III/IV oropharynx cancer patients had lower odds of CVD than stage I/II oropharynx patients [0.38(0.30-0.92)]. No association with cancer stage was observed in oral cavity patients. Compared to chemotherapy, surgery [0.85(0.63-1.14)] and other treatments {0.61(0.41-0.89)] had lower odds of CVD. Conclusions: Traditional CVD risk factors remain associated with CVD in HNSCC patients. In addition, cancer-related factors (oropharynx cancer, advanced cancer stage and chemotherapy) are also associated with CVD.

Risk Factors for Unnecessary Antibiotic Therapy: A Major Role for Clinical Management

2018 ◽  
Vol 69 (3) ◽  
pp. 466-472 ◽  
Author(s):  
Pierre-Marie Roger ◽  
Eve Montera ◽  
Diane Lesselingue ◽  
Nathalie Troadec ◽  
Patrick Charlot ◽  
...  
Keyword(s):  
Risk Factors ◽  
Antibiotic Therapy ◽  
Electronic Medical Records ◽  
Medical Records ◽  
Modifiable Risk Factors ◽  
Comorbid Conditions ◽  
Prospective Multicenter Study ◽  
Diagnostic Difficulties ◽  
Microbial Samples ◽  
Diagnosis Of Infection

Abstract Background Assessment of antimicrobial use places an emphasis on therapeutic aspects of infected patients. Our aim was to determine the risk factors for unnecessary antibiotic therapy (UAT). Methods This was a prospective, multicenter study evaluating all curative antibiotic therapies prescribed over 2 consecutive days through the same electronic medical records. Each item that could participate in these prescriptions was collected from the computerized file (reason for hospitalization, comorbid conditions, suspected or definitive diagnosis of infection, microbial analyses). UAT was defined as the recognition of noninfectious sydromes (NIS), nonbacterial infections, use of redundant antimicrobials, and continuation of empirical broad-spectrum antimicrobials. Results Four hundred fifty-three antibiotic therapies were analyzed at 17 institutions. An infectious disease was the reason for hospitalization in 201 cases (44%). An unspecified diagnosis of infection was observed in 104 cases (23%). Microbial samples were taken in 296 cases (65%), allowing isolation of a pathogen in 156 cases (53%). Unspecified diagnosis was associated with the absence of a microbial sample compared to patients with a diagnosis: (56/104 [54%] vs 240/349 [69%]; P = .005). A total of 158 NIS were observed (35%). UAT was observed in 169 cases (37%), due to NIS in 106 cases. In multivariate analysis, the modifiable risk factors for UAT were unspecified diagnosis (adjusted odds ratio [AOR], 1.83; 95% confidence interval [CI], 1.04–3.20) and absence of a blood culture (AOR, 5.26; 95% CI, 2.56–10.00). Conclusions UAT is associated with an unspecified diagnosis and the absence of microbial testing. Antimicrobial stewardship programs should focus on diagnostic difficulties and microbial testing, the latter facilitating antibiotic reassessment and therapeutic interruption.

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