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Curation and Phenotyping of Cardiovascular Case Reports Achieved by ICD Based Index System and MeSH Supported Query Platform
Abstracts
remodeling. Results: No significant differences in cardiac function were identified in Atrogin-1 Tg+ mice compared to sibling wildtype controls at four months of age. However, at 12 months of age, Atrogin1 Tg+ hearts were significantly larger, with anterior wall thickness 1.40+/-0.6 mm (diastole) and 1.38+/-0.03 mm (systole) compared to wildtype (1.10+/-0.02 mm diastole, 1.15+/-0.04 mm systole). Histological analysis of trichrome-stained wildtype hearts at 18 months of age revealed ~ 4.5+/-0.5% collagen deposition; in contrast, Atrogin-1 Tg+ hearts had significantly less collagen deposition (~1.5%+/-0.25%). By RT-qPCR, Atrogin-1 Tg + had increased MMP-9 mRNA, suggesting a role for Atrogin-1 in regulating MMP-9 transcriptionally. Conclusions: Chronic increased Atrogin-1 in cardiomyocytes alters age-associated function, which reducing fibrosis detected histologically, which may be related to alterations in MMP-9. These findings indicate a novel role of muscle-specific Atrogin-1 in preventing fibrosis, identifying for the first time a muscle-specific anti-fibrotic target in the aging heart.
doi:10.1016/j.yjmcc.2017.07.107
096 Curation and Phenotyping of Cardiovascular Case Reports Achieved by ICD Based Index System and MeSH Supported Query Platform Yijiang Zhoua,b, David Liema,b, Quan Caoa,b, Jessica Leea,b, Wei Wanga,c, Alex Buia,d, Karol Watsona,b, Jiawei Hane, Peipei Pinga,b a
The NIH BD2K Center of Excellence at UCLA, Los Angeles, California, USA Departments of Physiology, Medicine/Cardiology, Bioinformatics, University of California at Los Angeles, Los Angeles, California, USA c Department of Computer Science, University of California at Los Angeles, Los Angeles, California, USA d Department of Radiology, University of California at Los Angeles, Los Angeles, California, USA e NIH BD2K KnowEng Center, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA b
Background: Accurate phenotyping of patients and efficient extraction of detailed clinical information from large amounts of accumulated case reports in open resources have been challenging, in part, due to inadequate Medical Subjects Headings (MeSH) term and insufficient indexing systems. To overcome this challenge, we have created a novel indexing system integrating MeSH terms together with the current edition of the International Classification of Diseases (ICD-10). Methods: We have manually selected case reports using a combination of four MeSH terms: "myocardial Infarction", "coronary angiography", "echocardiography" and "shock, cardiogenic". In parallel, we extracted clinical features using ICD-10based indexing, which combines the codes from ICD-10 and from International Classification of Health Interventions (ICHI). An evaluation metrics (100 total) consisting of key clinical information was assembled; including 1) symptoms; 2) demographics; 3) lifestyle, 4) family history; 5) medical history; 6) diagnostic tests; 7) pathology; 8) treatment interventions; 9) drug therapies; 10) diagnosis; and 11) outcomes. Subsequently, we compared the ICD based index with that of MeSH supported query applying this metrics (11 components) using Wilcoxon Signed-Rank Test. Results: A total of 46 case reports were identified using the aforementioned indexing strategy. Ten case reports on “ST-segment elevation acute myocardial infarction” were analyzed. Our results show that ICD-10-based indexing scored higher than MeSH-supported indexing in overall setting (51.8 vs 38.3, pb0.05). Furthermore, ICD-10 based indexing also exhibits better accuracy in components of “symptoms and signs” (pb0.05), “past
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medical history” (pb0.05), “treatment interventions” (pb0.05) and “diagnosis” (pb0.05). However, MeSH indexing scored higher in “demographics” (pb0.05), “pathology and pathophysiology” (pb0.05) and “outcomes” (pb0.05). Conclusion: ICD-10-based indexing scored higher than MeSH for extracting key clinical information; the two systems emphasize on distinct clinical features. Integration of ICD-10 and MeSH terms would offer better precision and comprehensiveness to accurately phenotype and curate case reports.
doi:10.1016/j.yjmcc.2017.07.108
097 Construction a Standardized Metadata Template to Extract Relevant Biomedical Insights from Clinical Case Reports Yijiang Zhoua, David A. Liema, Quan Caoa, Jessica Leea, Wei Wangb, Alex Buic, Karol Watsond, Jiawei Hane, Peipei Pingf a
The NIH BD2K Center of Excellence at UCLA, Departments of Physiology, Los Angeles, California, USA b The NIH BD2K Center of Excellence at UCLA, Department of Computer Science, University of California at Los Angeles, CA 90095, USA, Los Angeles, California, USA c The NIH BD2K Center of Excellence at UCLA, Departments of Radiology, University of California at Los Angeles, CA 90095, USA, Los Angeles, California, USA d The NIH BD2K Center of Excellence at UCLA, Departments of Medicine/ Cardiology, University of California at Los Angeles, CA 90095, USA, Los Angeles, California, USA e NIH BD2K KnowEng Center, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Urbana-Champaign, Illinois, USA f The NIH BD2K Center of Excellence at UCLA, Departments of Physiology, Medicine/Cardiology, Bioinformatics, Computer Science, and Radiology, University of California at Los Angeles, CA 90095, USA, Los Angeles, California, USA Background: Clinical case reports (CR) have a time-honored tradition in serving as an important means of sharing clinical experiences on patients presenting with atypical disease phenotypes or receiving new therapies. However, the huge amount of accumulated case reports are isolated, unstructured, and heterogeneous data, posing a great challenge to clinicians and researchers in mining relevant information through existing indexing tools. In this investigation, we analyzed the current publication trends of case reports, their disease specific citation impact, and summarized the merits and limitations of CR genre with respect to their utilities to future knowledge production in cardiovascular medicine. Importantly, the results of our analysis highlight the importance of a standardized metadata template and metrics to guide and evaluate case report contents and metadata; as wel as to better index, annotate, and curate online case reports to support innovations and discoveries in the biomedical community. Methods: To construct a metadata template and metrics we categorized three major metadata components: (i) case report identification; e.g., title, author, PMID/DOI numbers; (ii) medical content; e.g., disease diagnosis, signs and symptoms, diagnostic procedures, and therapies; and (iii) other; e.g., references, funding source, award numbers, and disclosures. We analyzed the CR metadata retrieved from MeSH term & Pubmed indexing using these metrics. Results and Conclusion: Among the 100 manually screened CRs, 65% of them are missing key metadata components with the majority missing in the “medical content” category (51% from key “medical content” components). Taken together, our study on the evalution and quantification of the exhisting metadata for
remodeling. Results: No significant differences in cardiac function were identified in Atrogin-1 Tg+ mice compared to sibling wildtype controls at four months of age. However, at 12 months of age, Atrogin1 Tg+ hearts were significantly larger, with anterior wall thickness 1.40+/-0.6 mm (diastole) and 1.38+/-0.03 mm (systole) compared to wildtype (1.10+/-0.02 mm diastole, 1.15+/-0.04 mm systole). Histological analysis of trichrome-stained wildtype hearts at 18 months of age revealed ~ 4.5+/-0.5% collagen deposition; in contrast, Atrogin-1 Tg+ hearts had significantly less collagen deposition (~1.5%+/-0.25%). By RT-qPCR, Atrogin-1 Tg + had increased MMP-9 mRNA, suggesting a role for Atrogin-1 in regulating MMP-9 transcriptionally. Conclusions: Chronic increased Atrogin-1 in cardiomyocytes alters age-associated function, which reducing fibrosis detected histologically, which may be related to alterations in MMP-9. These findings indicate a novel role of muscle-specific Atrogin-1 in preventing fibrosis, identifying for the first time a muscle-specific anti-fibrotic target in the aging heart.
doi:10.1016/j.yjmcc.2017.07.107
096 Curation and Phenotyping of Cardiovascular Case Reports Achieved by ICD Based Index System and MeSH Supported Query Platform Yijiang Zhoua,b, David Liema,b, Quan Caoa,b, Jessica Leea,b, Wei Wanga,c, Alex Buia,d, Karol Watsona,b, Jiawei Hane, Peipei Pinga,b a
The NIH BD2K Center of Excellence at UCLA, Los Angeles, California, USA Departments of Physiology, Medicine/Cardiology, Bioinformatics, University of California at Los Angeles, Los Angeles, California, USA c Department of Computer Science, University of California at Los Angeles, Los Angeles, California, USA d Department of Radiology, University of California at Los Angeles, Los Angeles, California, USA e NIH BD2K KnowEng Center, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA b
Background: Accurate phenotyping of patients and efficient extraction of detailed clinical information from large amounts of accumulated case reports in open resources have been challenging, in part, due to inadequate Medical Subjects Headings (MeSH) term and insufficient indexing systems. To overcome this challenge, we have created a novel indexing system integrating MeSH terms together with the current edition of the International Classification of Diseases (ICD-10). Methods: We have manually selected case reports using a combination of four MeSH terms: "myocardial Infarction", "coronary angiography", "echocardiography" and "shock, cardiogenic". In parallel, we extracted clinical features using ICD-10based indexing, which combines the codes from ICD-10 and from International Classification of Health Interventions (ICHI). An evaluation metrics (100 total) consisting of key clinical information was assembled; including 1) symptoms; 2) demographics; 3) lifestyle, 4) family history; 5) medical history; 6) diagnostic tests; 7) pathology; 8) treatment interventions; 9) drug therapies; 10) diagnosis; and 11) outcomes. Subsequently, we compared the ICD based index with that of MeSH supported query applying this metrics (11 components) using Wilcoxon Signed-Rank Test. Results: A total of 46 case reports were identified using the aforementioned indexing strategy. Ten case reports on “ST-segment elevation acute myocardial infarction” were analyzed. Our results show that ICD-10-based indexing scored higher than MeSH-supported indexing in overall setting (51.8 vs 38.3, pb0.05). Furthermore, ICD-10 based indexing also exhibits better accuracy in components of “symptoms and signs” (pb0.05), “past
167
medical history” (pb0.05), “treatment interventions” (pb0.05) and “diagnosis” (pb0.05). However, MeSH indexing scored higher in “demographics” (pb0.05), “pathology and pathophysiology” (pb0.05) and “outcomes” (pb0.05). Conclusion: ICD-10-based indexing scored higher than MeSH for extracting key clinical information; the two systems emphasize on distinct clinical features. Integration of ICD-10 and MeSH terms would offer better precision and comprehensiveness to accurately phenotype and curate case reports.
doi:10.1016/j.yjmcc.2017.07.108
097 Construction a Standardized Metadata Template to Extract Relevant Biomedical Insights from Clinical Case Reports Yijiang Zhoua, David A. Liema, Quan Caoa, Jessica Leea, Wei Wangb, Alex Buic, Karol Watsond, Jiawei Hane, Peipei Pingf a
The NIH BD2K Center of Excellence at UCLA, Departments of Physiology, Los Angeles, California, USA b The NIH BD2K Center of Excellence at UCLA, Department of Computer Science, University of California at Los Angeles, CA 90095, USA, Los Angeles, California, USA c The NIH BD2K Center of Excellence at UCLA, Departments of Radiology, University of California at Los Angeles, CA 90095, USA, Los Angeles, California, USA d The NIH BD2K Center of Excellence at UCLA, Departments of Medicine/ Cardiology, University of California at Los Angeles, CA 90095, USA, Los Angeles, California, USA e NIH BD2K KnowEng Center, Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA, Urbana-Champaign, Illinois, USA f The NIH BD2K Center of Excellence at UCLA, Departments of Physiology, Medicine/Cardiology, Bioinformatics, Computer Science, and Radiology, University of California at Los Angeles, CA 90095, USA, Los Angeles, California, USA Background: Clinical case reports (CR) have a time-honored tradition in serving as an important means of sharing clinical experiences on patients presenting with atypical disease phenotypes or receiving new therapies. However, the huge amount of accumulated case reports are isolated, unstructured, and heterogeneous data, posing a great challenge to clinicians and researchers in mining relevant information through existing indexing tools. In this investigation, we analyzed the current publication trends of case reports, their disease specific citation impact, and summarized the merits and limitations of CR genre with respect to their utilities to future knowledge production in cardiovascular medicine. Importantly, the results of our analysis highlight the importance of a standardized metadata template and metrics to guide and evaluate case report contents and metadata; as wel as to better index, annotate, and curate online case reports to support innovations and discoveries in the biomedical community. Methods: To construct a metadata template and metrics we categorized three major metadata components: (i) case report identification; e.g., title, author, PMID/DOI numbers; (ii) medical content; e.g., disease diagnosis, signs and symptoms, diagnostic procedures, and therapies; and (iii) other; e.g., references, funding source, award numbers, and disclosures. We analyzed the CR metadata retrieved from MeSH term & Pubmed indexing using these metrics. Results and Conclusion: Among the 100 manually screened CRs, 65% of them are missing key metadata components with the majority missing in the “medical content” category (51% from key “medical content” components). Taken together, our study on the evalution and quantification of the exhisting metadata for