Current Search: Institute for Successful Longevity (x)
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- Title
- Assessing the Comorbidity Gap between Clinical Studies and Prevalence in Elderly Patient Populations.
- Creator
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He, Zhe, Charness, Neil, Bian, Jiang, Hogan, William R
- Abstract/Description
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Well-designed and well-conducted clinical studies represent gold standard approaches for generating medical evidence. However, elderly populations are systematically underrepresented in studies across major chronic medical conditions, which has hampered the generalizability (external validity) of studies to the real-world patient population. It is the norm that intervention studies often require a homogeneous cohort to test their hypotheses; therefore older adults with co-medications and...
Show moreWell-designed and well-conducted clinical studies represent gold standard approaches for generating medical evidence. However, elderly populations are systematically underrepresented in studies across major chronic medical conditions, which has hampered the generalizability (external validity) of studies to the real-world patient population. It is the norm that intervention studies often require a homogeneous cohort to test their hypotheses; therefore older adults with co-medications and comorbidities are often excluded. The purpose of this study is to assess the gap between clinical studies on comorbidities and prevalence in elderly populations derived from the National Health and Nutrition Examination Survey (NHANES) and the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) dataset. A comorbidity gap between them was observed and reported in this work.
Show less - Date Issued
- 2016-02-01
- Identifier
- FSU_pmch_27738664, 10.1109/BHI.2016.7455853, PMC5058342, 27738664, 27738664
- Format
- Citation
- Title
- Diabetic Indicators Are The Strongest Predictors For Cardiovascular Disease Risk In African American Adults.
- Creator
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Carter, Ashley N., Ralston, Penny A., Young-Clark, Iris, Ilich, Jasminka Z.
- Abstract/Description
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African Americans have higher risk of developing type 2 diabetes and cardiovascular disease (CVD) compared to other racial groups. Modifiable and non-modifiable factors play a role in the development of both diseases. This study assessed diabetes indicators in relation to other CVD risk factors taking into account confounders, among African American adults. This was a cross-sectional study in mid-life and older African Americans (>= 45 years) who were recruited from the local churches....
Show moreAfrican Americans have higher risk of developing type 2 diabetes and cardiovascular disease (CVD) compared to other racial groups. Modifiable and non-modifiable factors play a role in the development of both diseases. This study assessed diabetes indicators in relation to other CVD risk factors taking into account confounders, among African American adults. This was a cross-sectional study in mid-life and older African Americans (>= 45 years) who were recruited from the local churches. Fasting blood was collected and serum analyzed for diabetes indicators, apolipoproteins, adipokines, and lipid profile. CVD risk scores were determined using the American Heart Association and Framingham Risk Score assessments. Homeostasis Model Assessments (HOMAs) were calculated using glucose and insulin concentrations. Confounding variables were assessed by questionnaires. Data were analyzed using SPSS software, version 21, and p<0.05 was deemed significant. Descriptive statistics was used to analyze continuous variables. Frequencies and percentages were used to examine categorical variables. T-tests compared different groups while Pearson correlations provided preliminary relationships and determined variables for multiple regression analyses. A total of n=79 participants were evaluated (69% women), 59.3+/-9.2 years, BMI=34.7+/-8.3 (mean+/-SD). As expected, AA men had higher fasting blood glucose than women (123.6+/-54.9 mg/dL versus 99.0+/-21.8 mg/dL), and AA women had higher insulin (11.8+/-13.1 mg/dL versus 7.6+/-6.0 mg/dL). Our study confirmed that it is likely for AA men to have significantly lower adiponectin concentrations in comparison to AA women. Based on the CVD risk assessments, men had a significantly higher risk of developing CVD than women, which has been shown previously. Apolipoproteins, adipokines, and lipid profile also negatively influenced the cardiovascular health outcomes in men. Dietary intake, probably by influencing participants' weight/adiposity, contributed to the differences in cardiovascular outcomes between men and women. In conclusion, the findings of this study revealed that diabetes and serum glucose appeared to be the leading factors for high CVD risk, on the contrary to some other indicators reported in some studies, e.g. hypertension or dyslipidemia.
Show less - Date Issued
- 2016
- Identifier
- FSU_libsubv1_wos_000384819900006
- Format
- Citation
- Title
- Enriching consumer health vocabulary through mining a social Q&A site: A similarity-based approach..
- Creator
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He, Zhe, Chen, Zhiwei, Oh, Sanghee, Hou, Jinghui, Bian, Jiang
- Abstract/Description
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The widely known vocabulary gap between health consumers and healthcare professionals hinders information seeking and health dialogue of consumers on end-user health applications. The Open Access and Collaborative Consumer Health Vocabulary (OAC CHV), which contains health-related terms used by lay consumers, has been created to bridge such a gap. Specifically, the OAC CHV facilitates consumers' health information retrieval by enabling consumer-facing health applications to translate between...
Show moreThe widely known vocabulary gap between health consumers and healthcare professionals hinders information seeking and health dialogue of consumers on end-user health applications. The Open Access and Collaborative Consumer Health Vocabulary (OAC CHV), which contains health-related terms used by lay consumers, has been created to bridge such a gap. Specifically, the OAC CHV facilitates consumers' health information retrieval by enabling consumer-facing health applications to translate between professional language and consumer friendly language. To keep up with the constantly evolving medical knowledge and language use, new terms need to be identified and added to the OAC CHV. User-generated content on social media, including social question and answer (social Q&A) sites, afford us an enormous opportunity in mining consumer health terms. Existing methods of identifying new consumer terms from text typically use ad-hoc lexical syntactic patterns and human review. Our study extends an existing method by extracting n-grams from a social Q&A textual corpus and representing them with a rich set of contextual and syntactic features. Using K-means clustering, our method, simiTerm, was able to identify terms that are both contextually and syntactically similar to the existing OAC CHV terms. We tested our method on social Q&A corpora on two disease domains: diabetes and cancer. Our method outperformed three baseline ranking methods. A post-hoc qualitative evaluation by human experts further validated that our method can effectively identify meaningful new consumer terms on social Q&A.
Show less - Date Issued
- 2017-05-01
- Identifier
- FSU_pmch_28359728, 10.1016/j.jbi.2017.03.016, PMC5488691, 28359728, 28359728, S1532-0464(17)30065-5
- Format
- Citation
- Title
- Topological-Pattern-Based Recommendation of UMLS Concepts for National Cancer Institute Thesaurus.
- Creator
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He, Zhe, Chen, Yan, de Coronado, Sherri, Piskorski, Katrina, Geller, James
- Abstract/Description
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The National Cancer Institute Thesaurus (NCIt) is a reference terminology used to support clinical, translational and basic research as well as administrative activities. As medical knowledge evolves, concepts that might be missing from a particular needed subdomain are regularly added to the NCIt. However, terminology development is known to be labor-intensive and error-prone. Therefore, cost-effective semi-automated methods for identifying potentially missing concepts would be useful to...
Show moreThe National Cancer Institute Thesaurus (NCIt) is a reference terminology used to support clinical, translational and basic research as well as administrative activities. As medical knowledge evolves, concepts that might be missing from a particular needed subdomain are regularly added to the NCIt. However, terminology development is known to be labor-intensive and error-prone. Therefore, cost-effective semi-automated methods for identifying potentially missing concepts would be useful to terminology curators. Previously, we have developed a structural method leveraging the native term mappings of the Unified Medical Language System to identify potential concepts in several of its source vocabularies to enrich the SNOMED CT. In this paper, we tested an analogous method for NCIt. Concepts from eight UMLS source terminologies were identified as possibilities to enrich NCIt's conceptual content.
Show less - Date Issued
- 2017-02-10
- Identifier
- FSU_pmch_28269858, PMC5333219, 28269858, 28269858
- Format
- Citation