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3. World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions

Author

Angelantonio, E. di, Kaptoge, S., Pennells, L., Bacquer, D. de, Cooney, M.T., Kavousi, M., Stevens, G., Riley, L., Savin, S., Altay, S., Amouyel, P., Assmann, G., Bell, S., Ben-Shlomo, Y., Berkman, L., Beulens, J.W., Bjorkelund, C., Blaha, M.J., Blazer, D.G., Bolton, T., Bonita, R., Brenner, B.H., Brunner, E.J., Casiglia, E., Chamnan, P., Choi, Y.H., Chowdhury, R., Coady, S., Crespo, C.J., Cushman, M., Dagenais, G.R., D'Agostino, R.B., Daimon, M., Davidson, K.W., Engstrom, G., Fang, X.H., Ford, I., Gallacher, J., Gansevoort, R.T., Gaziano, T.A., Giampaoli, S., Grandits, G., Grimsgaard, S., Grobbee, D.E., Gudnason, V., Guo, Q., Humphries, S., Iso, H., Jukema, J.W., Kauhanen, J., Kengne, A.P., Khalili, D., Khan, T., Knuiman, M., Koenig, W., Kromhout, D., Krumholz, H.M., Lam, T.H., Laughlin, G., Ibanez, A.M., Moons, K.G.M., Nietert, P.J., Ninomiya, T., Nordestgaard, B.G., O'Donnell, C., Palmieri, L., Patel, A., Perel, P., Price, J.F., Costa, R.B.D.E., Ridker, P.M., Rodriguez, B., Rosengren, A., Roussel, R., Sakurai, M., Salomaa, V., Sato, S., Schottker, B., Shara, N., Shaw, J.E., Shin, H.C., Simons, L.A., Sofianopoulou, E., Sundstrom, J., Tolonen, H., Ueshima, H., Volzke, H., Wallace, R.B., Wareham, N.J., Willeit, P., Wood, D., Wood, A., Zhao, D., Onuma, O., Woodward, M., Danaei, G., Roth, G., Mendis, S., Graham, I., Varghese, C., Ezzati, M., Jackson, R., Danesh, J., Nambi, V., Matsushita, K., Couper, D., Diabetes, A., Zimmet, P.Z., Barr, E.L.M., Atkins, R., Whincup, P.H., Study, B., Kiechl, S., Willeit, J., Rungger, G., Sofat, R., Dale, C., Casas, J.P., Tikhonoff, V., Hunt, K.J., Sutherland, S.E., Psaty, B.M., Tracy, R., Frikke-Schmidt, R., Jensen, G.B., Schnohr, P., Donfrancesco, C., Vanuzzo, D., Panico, S., Balkau, B., Bonnet, F., Fumeron, F., Simons, J., McLachlan, S., Guralnik, J., Khaw, K.T., Brenner, H., Zhang, Y., Holleczek, B., Cohort, F., Vartiainen, E., Jousilahti, P., Harald, K., Massaro, J.J., Pencina, M., Ramachandran, V., Susa, S., Oizumi, T., Kayama, T., Wilhelmsen, L., Lissner, L., Hange, D., Mehlig, K., Hata, J., Yoshida, D., Hirakawa, Y., Rutters, F., Elders, P.J.M., Kyowa, I., Kiyama, M., Yamagishi, K., Tuomainen, T.P., Virtanen, J., Salonen, J.T., Meade, T.W., Nilsson, P.M., Melander, O., Boer, I.H. de, DeFilippis, A.P., Kuller, L.H., Juan, S.I., Gillum, R.F., Kirkland, S., Shimbo, D., Schwartz, J.E., Imano, H., Harst, P. van der, Hillige, J.L., Bakker, S.J., Dallongeville, J., Ferrieres, J., Moitry, M., Stott, D.J., Despres, J.P., Laughlin, G.A., Daniels, L.B., McEvoy, L.K., Aspelund, T., Thorsson, B., Gudmundsson, E.F., Aribas, E., Rueda-Ochoa, O.L., Ikram, M.K., Heshmatollah, A., Ikram, M.A., Dorr, M., Nauck, M., Howard, B., Can, G., Ishizaki, M., Wilsgaard, T., Mathiesen, E., Giedraitis, V., Ingelsson, M., Cook, N., Buring, J., Schouw, Y.T. van der, Claessen, H., Rothenbacher, D., Arndt, V., Study, W.I., Shipley, M., Packard, C., Robertson, M., Young, R., Feskens, E., Geleijnse, J.M., Fang, X., Gu, D.F., Huxley, R., Imai, Y., Kim, H.C., Pan, W.H., Rodgers, A., Suh, I., Town, A., Okayama, A., Maegawa, H., Nakamura, M., Aoki, N., Wu, Z.S., Yao, C.H., Luszcz, M., Tang, Z., Liu, L.S., Xie, J.X., Norton, R., Ameratunga, S., MacMahon, S., Whitlock, G., Knuiman, M.W., Christensen, H., Wu, X.G., Zhou, J., Yu, X.H., Tamakoshi, W.A., Wu, Z.L., Chen, L.Q., Shan, G.L., Sritara, P., Duan, X.F., Li, Y.H., Jiang, C.Q., Woo, J., Ho, S.C., Hong, Z., Huang, M.S., Zhou, B., Fuh, J.L., Kita, Y., Choudhury, S.R., Jee, S.H., Kim, Woodward, M, Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Epidemiology, Epidemiology and Data Science, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, and APH - Health Behaviors & Chronic Diseases

Subjects
Male, 10-YEAR RISK, BLOOD-PRESSURE, 0302 clinical medicine, Risk Factors, Medicine and Health Sciences, Medicine, Uganda, Cardiac and Cardiovascular Systems, Prospective Studies, 030212 general & internal medicine, Aged, 80 and over, Medicine(all), Kardiologi, lcsh:Public aspects of medicine, PRIMARY-CARE, Public Health, Global Health, Social Medicine and Epidemiology, General Medicine, Middle Aged, 3. Good health, Pooled analysis, Cardiovascular Diseases, Egypt, Female, Adult, PROSPECTIVE COHORTS, 030231 tropical medicine, 195 COUNTRIES, Primary care, World Health Organization, Risk Assessment, Article, World health, POOLED ANALYSIS, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Primary prevention, Environmental health, SYSTEMATIC ANALYSIS, Humans, Aged, CHINESE POPULATION, Chinese population, business.industry, Individual participant data, lcsh:RA1-1270, R1, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Disease risk, business, INDIVIDUAL PARTICIPANT DATA, PRIMARY PREVENTION
Abstract

Background: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. Methods: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40–80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. Findings: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629–0·741) to 0·833 (0·783–0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40–64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. Interpretation: We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. Funding: World Health Organization, British Heart Foundation (BHF), BHF Cambridge Centre for Research Excellence, UK Medical Research Council, and National Institute for Health Research. The WHO CVD Risk Chart Working Group, for complete list of authors see http://dx.doi.org/10.1016/S2214-109X(19)30318-3

Published
2019
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4. Survival After Uncomplicated EVAR in Octogenarians is Similar to the General Population of Octogenarians Without an Abdominal Aortic Aneurysm

Author

Rueda-Ochoa, O.L. (Oscar), van Bakel, P. (Pieter), Hoeks, S.E. (Sanne), Verhagen, H.J.M. (Hence), Deckers, J. (Jaap), Rizopoulos, D. (Dimitris), Ikram, M.A. (Arfan), Rouwet, E.V. (Ellen), Ultee, K.H.J. (Klaas), Raa, S. (Sander) ten, Franco, O.H. (Oscar), Kavousi, M. (Maryam), Rijn, M.J.E. (Marie Josee) van, Rueda-Ochoa, O.L. (Oscar), van Bakel, P. (Pieter), Hoeks, S.E. (Sanne), Verhagen, H.J.M. (Hence), Deckers, J. (Jaap), Rizopoulos, D. (Dimitris), Ikram, M.A. (Arfan), Rouwet, E.V. (Ellen), Ultee, K.H.J. (Klaas), Raa, S. (Sander) ten, Franco, O.H. (Oscar), Kavousi, M. (Maryam), and Rijn, M.J.E. (Marie Josee) van

Abstract

Objective: Long term survival after endovascular aortic aneurysm repair (EVAR) in octogenarians remains unclear. This was evaluated by comparing octogenarians after EVAR with a matched group of octogenarians without an abdominal aortic aneurysm (AAA) from the Rotterdam Study (RS). The influence of complications after EVAR on survival was also studied with the aim of identifying risk factors for the development of complications in octogenarians. Methods: Using propensity score matching (PSM), 83 EVAR octogenarians were matched for comorbidities with 83 octogenarians from the RS, and survival was compared between these two groups using Cox proportional hazard analysis. Then, complications were studied, defined as cardiac or pulmonary, renal deterioration, access site bleeding, acute limb ischaemia or bowel ischaemia, within 30 days of surgery between 83 EVAR octogenarians and 475 EVAR non-octogenarians. Also, the difference in baseline characteristics between the octogenarians with and without complications after EVAR were studied, and survival was compared between the RS controls and the complicated and uncomplicated EVAR octogenarians separately. Results: The total EVAR octogenarian population did not show an increased mortality risk compared with RS octogenarian controls (hazard ratio [HR] 1.28, 95% confidence interval [CI] 0.84–1.97). Post-operative complications occurred in 22 octogenarians (27%) and 59 non-octogenarians (12.4%, p < .001), mainly cardiac, pulmonary, and bleeding complications. All baseline characteristics were similar in the complicated EVAR octogenarians compared with the uncomplicated EVAR octogenarians. After uncomplicated EVAR, octogenarians had a similar survival compared with the RS controls (HR 1.0

Published
2020
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5. Methodological and Epidemiological Studies of Cardiovascular Structure and Function

Author

Rueda-Ochoa, O.L. (Oscar) and Rueda-Ochoa, O.L. (Oscar)

Abstract

Three methodological aspects were the thematic axis of this thesis: 1. The analysis of repeated measures of variables such as electrocardiogram in neonates, changes in echocardiographic variables that evaluate left ventricular diastolic function in adults of the Rotterdam Study and dynamic changes in systolic blood pressure over time and its association with clinical outcomes in the participants of the Systolic blood PRessure INTervention Trial (SPRINT trial). 2. The application of advanced statistical methods for the analysis of causal inference such as: i) Propensity score matching, applied in the selection of the best control group in quasi-experiments involving vascular interventions in octogenarians diagnosed with abdominal aortic aneurysm and in patients with coronary heart disease undergoing Fractional Flow Reserve (FFR) to guide the best therapy and, ii) Mendelian randomization analysis to assess the causal relationship between serum levels of dehydroepiandrostenedione sulfate (DHEAs) and N-terminal type B natriuretic pro-peptide (NT-pro-BNP), hormones directly related to changes in the structure and function of the cardiovascular system associated with heart failure and aging. 3. Finally, the dynamics changes in thoracic aortic diameters and their associated risk factors, the implication of these changes in the development of clinical events and, the evaluation of the hypothesis that atherosclerosis is a systemic condition affecting different vascular beds in a similar manner was explored.

Published
2020

6. The cardiovascular risk profile of middle age women previously diagnosed with premature ovarian insufficiency: A case-control study

Author

Gunning, M.N. (Marlise N.), Meun, C. (Cindy), Rijn, B.B. (Bas) van, Daan, N.M.P. (Nadine M.P.), Van Lennep, J.E.R. (Jeanine E. Roeters), Appelman, Y.E.A. (Yolande), Boersma, H. (Eric), Hofstra, L. (Leo), Fauser, C.G.K.M. (Clemens G. K. M.), Rueda-Ochoa, O.L. (Oscar L.), Ikram, M.A. (Arfan), Kavousi, M. (Maryam), Lambalk, C.B. (Cornelius), Eijkemans, M.J.C. (Marinus J. C.), Laven, J.S.E. (Joop), Fauser, B.C.J.M. (Bart), Gunning, M.N. (Marlise N.), Meun, C. (Cindy), Rijn, B.B. (Bas) van, Daan, N.M.P. (Nadine M.P.), Van Lennep, J.E.R. (Jeanine E. Roeters), Appelman, Y.E.A. (Yolande), Boersma, H. (Eric), Hofstra, L. (Leo), Fauser, C.G.K.M. (Clemens G. K. M.), Rueda-Ochoa, O.L. (Oscar L.), Ikram, M.A. (Arfan), Kavousi, M. (Maryam), Lambalk, C.B. (Cornelius), Eijkemans, M.J.C. (Marinus J. C.), Laven, J.S.E. (Joop), and Fauser, B.C.J.M. (Bart)

Abstract

Background: Cardiovascular disease (CVD) is the leading cause of death in women worldwide. The cardiovascular risk profile deteriorates after women enter menopause. By definition, women diagnosed with premature ovarian insufficiency (POI) experience menopause before 40 years of age, which may render these women even more susceptible to develop CVD later in life. However, prospective long-term follow up data of well phenotyped women with POI are scarce. In the current study we compare the CVD profile and risk of middle aged women previously diagnosed with POI, to a population based reference group matched for age and BMI. Methods and findings: We compared 123 women (age 49.0 (± 4.3) years) and diagnosed with POI 8.1 (IQR: 6.8- 9.6) years earlier, with 123 population controls (age 49.4 (± 3.9) years). All women underwent an extensive standardized cardiovascular screening. We assessed CVD risk factors including waist circumference, BMI, blood pressure, lipid profile, pulse wave velocity (PWV), and the prevalence of diabetes mellitus, metabolic syndrome (MetS) and carotid intima media thickness (cIMT), in both women with POI and controls. We calculated the 10-year CVD Framingham Risk Score (FRS) and the American Heart Association's suggested cardiovascular health score (CHS). Waist circumference (90.0 (IQR: 83.0-98.0) versus 80.7 (IQR: 75.1-86.8), p < 0.01), waist-to-hip ratio (0.90 (IQR: 0.85-0.93) versus 0.79 (IQR: 0.75-0.83), p < 0.01), systolic blood pressure (124 (IQR 112-135) versus 120 (IQR109- 131), p < 0.04) and diastolic blood pressure (81 (IQR: 76-89) versus 78 (IQR: 71-86), p < 0.01), prevalence of hypertension (45 (37%) versus 21 (17%), p < 0.01) and MetS (19 (16%) versus 4 (3%), p < 0.01) were all significantly increased in women with POI compared to healthy controls. Other risk factors, however, such as lipids, glucose levels and prevalence of diabetes were similar comparing women with POI versus controls. The arterial stiffness assessed by PWV was also s

Published
2020
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7. Development and external validation of a deep learning algorithm for prognostication of cardiovascular outcomes

Author

Cho, I.-J. (In-Jeong), Sung, J.M. (Ji Min), Kim, H.C. (Hyeon Chang), Lee, S.-E. (Sang-Eun), Chae, M.-H. (Myeong-Hun), Kavousi, M. (Maryam), Rueda-Ochoa, O.L. (Oscar), Ikram, M.A. (Arfan), Franco, O.H. (Oscar), Min, J.K. (James K.), Chang, H.-J. (Hyuk-Jae), Cho, I.-J. (In-Jeong), Sung, J.M. (Ji Min), Kim, H.C. (Hyeon Chang), Lee, S.-E. (Sang-Eun), Chae, M.-H. (Myeong-Hun), Kavousi, M. (Maryam), Rueda-Ochoa, O.L. (Oscar), Ikram, M.A. (Arfan), Franco, O.H. (Oscar), Min, J.K. (James K.), and Chang, H.-J. (Hyuk-Jae)

Abstract

Background and Objectives: We aim to explore the additional discriminative accuracy of a deep learning (DL) algorithm using repeated-measures data for identifying people at high risk for cardiovascular disease (CVD), compared to Cox hazard regression. Methods: Two CVD prediction models were developed from National Health Insurance Service-Health Screening Cohort (NHIS-HEALS): A Cox regression model and a DL model. Performance of each model was assessed in the internal and 2 external validation cohorts in Koreans (National Health Insurance Service-National Sample Cohort; NHIS-NSC) and in Europeans (Rotterdam Study). A total of 412,030 adults in the NHIS-HEALS; 178,875 adults in the NHIS-NSC; and the 4,296 adults in Rotterdam Study were included. Results: Mean ages was 52 years (46% women) and there were 25,777 events (6.3%) in NHIS-HEALS during the follow-up. In internal validation, the DL approach demonstrated a C-statistic of 0.896 (95% confidence interval, 0.886-0.907) in men and 0.921 (0.908-0.934) in women and improved reclassification compared with Cox regression (net reclassification index [NRI], 24.8% in men, 29.0% in women). In external validation with NHIS-NSC, DL demonstrated a C-statistic of 0.868 (0.860-0.876) in men and 0.889 (0.876-0.898) in women, and improved reclassification compared with Cox regression (NRI, 24.9% in men, 26.2% in women). In external validation applied to the Rotterdam Study, DL demonstrated a C-statistic of 0.860 (0.824-0.897) in men and 0.867 (0.830-0.903) in women, and improved reclassification compared with Cox regression (NRI, 36.9% in men, 31.8% in women). Conclusions: A DL algorithm exhibited greater discriminative accuracy than Cox model approaches.

Published
2020
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8. The cardiovascular risk profile of middle-aged women with polycystic ovary syndrome

Author

Meun, C. (Cindy), Gunning, M.N. (Marlise N), Louwers, Y.V. (Yvonne), Peters, H. (Henrike), Roos-Hesselink, J.W. (Jolien), Roeters van Lennep, J.E. (Jeanine), Rueda-Ochoa, O.L. (Oscar), Appelman, Y.E.A. (Yolande), Lambalk, N. (Nils), Boersma, H. (Eric), Kavousi, M. (Maryam), Fauser, B.C.J.M. (Bart), Laven, J.S.E. (Joop), Baart, S.J. (Sara), Benschop, H.A.M. (Laura), Brouwers, L. (Laura), Budde, R.P.J. (Ricardo), Cannegieter, S.C. (Suzanne), Dam, V. (Veerle), Eijkemans, M.J.C. (René), Ferrari, M. (Michel), Franx, A. (Arie), Groot, C.J.M. (Christianne) de, Hoek, A. (Annemieke), Koffijberg, E. (Erik), Koster, W. (Wendy), Kruit, M. (Mark), Lagerweij, G. (Giske), Linstra, K. (Katie), Lugt, A. (Aad) van der, Maas, A.H.E.M. (Angela H.E.M.), Maassen van den Brink, A. (Antoinette), Middeldorp, S. (Saskia), Moons, K.G.M. (Karel), Rijn, B.B. (Bas) van, Scheres, L. (Luuk), Schouw, Y.T. (Yvonne) van der, Steegers, E.A.P. (Eric), Steegers, R. (Regine), Terwindt, G.M. (Gisela), Velthuis, B.K. (Birgitta), Wermer, M.J.H. (Marieke), Zick, B. (Bart), Zoet, G. (Gerbrand), Meun, C. (Cindy), Gunning, M.N. (Marlise N), Louwers, Y.V. (Yvonne), Peters, H. (Henrike), Roos-Hesselink, J.W. (Jolien), Roeters van Lennep, J.E. (Jeanine), Rueda-Ochoa, O.L. (Oscar), Appelman, Y.E.A. (Yolande), Lambalk, N. (Nils), Boersma, H. (Eric), Kavousi, M. (Maryam), Fauser, B.C.J.M. (Bart), Laven, J.S.E. (Joop), Baart, S.J. (Sara), Benschop, H.A.M. (Laura), Brouwers, L. (Laura), Budde, R.P.J. (Ricardo), Cannegieter, S.C. (Suzanne), Dam, V. (Veerle), Eijkemans, M.J.C. (René), Ferrari, M. (Michel), Franx, A. (Arie), Groot, C.J.M. (Christianne) de, Hoek, A. (Annemieke), Koffijberg, E. (Erik), Koster, W. (Wendy), Kruit, M. (Mark), Lagerweij, G. (Giske), Linstra, K. (Katie), Lugt, A. (Aad) van der, Maas, A.H.E.M. (Angela H.E.M.), Maassen van den Brink, A. (Antoinette), Middeldorp, S. (Saskia), Moons, K.G.M. (Karel), Rijn, B.B. (Bas) van, Scheres, L. (Luuk), Schouw, Y.T. (Yvonne) van der, Steegers, E.A.P. (Eric), Steegers, R. (Regine), Terwindt, G.M. (Gisela), Velthuis, B.K. (Birgitta), Wermer, M.J.H. (Marieke), Zick, B. (Bart), and Zoet, G. (Gerbrand)

Abstract

Objectives: Contradictory results have been reported regarding the association between polycystic ovary syndrome (PCOS) and cardiovascular disease (CVD). We assessed the cardiometabolic phenotype and prevalence of CVD in middle-aged women with PCOS, compared with age-matched controls from the general population, and estimated 10-year CVD risk and cardiovascular health score. Design: A cross-sectional study. Participants: 200 women aged >45 with PCOS, and 200 age-matched controls. Measurements: Anthropometrics, insulin, lipid levels, prevalence of metabolic syndrome and type II diabetes. Ten-year Framingham risk score and the cardiovascular health score were calculated, and carotid intima-media thickness (cIMT) was measured. Results: Mean age was 50.5 years (SD = 5.5) in women with PCOS and 51.0 years (SD = 5.2) in controls. Increased waist circumference, body mass index and hypertension were more often observed in women with PCOS (P <.001). In women with PCOS, the prevalence of type II diabetes and metabolic syndrome was not significantly increased and lipid levels were not different from controls. cIMT was lower in women with PCOS (P <.001). Calculated cardiovascular health and 10-year CVD risk were similar in women with PCOS and controls. Conclusions: Middle-aged women with PCOS exhibit only a moderately unfavourable cardiometabolic profile compared to age-matched controls, even though they present with an increased BMI and waist circumference. Furthermore, we found no evidence for increased (10-year) CVD risk or more severe atherosclerosis compared with controls from the general population. Long-term follow-up of women with PCOS is necessary to provide a definitive answer concerning long

Published
2019
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9. Development and verification of prediction models for preventing cardiovascular diseases

Author

Sung, J.M. (Ji Min), Cho, I.-J. (In-Jeong), Sung, D. (David), Kim, S. (Sunhee), Kim, H.C. (Hyeon Chang), Chae, M.-H. (Myeong-Hun), Kavousi, M. (Maryam), Rueda-Ochoa, O.L. (Oscar), Ikram, M.A. (Arfan), Franco, O.H. (Oscar), Chang, H.-J. (Hyuk-Jae), Sung, J.M. (Ji Min), Cho, I.-J. (In-Jeong), Sung, D. (David), Kim, S. (Sunhee), Kim, H.C. (Hyeon Chang), Chae, M.-H. (Myeong-Hun), Kavousi, M. (Maryam), Rueda-Ochoa, O.L. (Oscar), Ikram, M.A. (Arfan), Franco, O.H. (Oscar), and Chang, H.-J. (Hyuk-Jae)

Abstract

Objectives Cardiovascular disease (CVD) is one of the major causes of death worldwide. For improved accuracy of CVD prediction, risk classification was performed using national time-series health examination data. The data offers an opportunity to access deep learning (RNN-LSTM), which is widely known as an outstanding algorithm for analyzing time-series datasets. The objective of this study was to show the improved accuracy of deep learning by comparing the performance of a Cox hazard regression and RNN-LSTM based on survival analysis. Methods and findings We selected 361,239 subjects (age 40 to 79 years) with more than two health examination records from 2002–2006 using the National Health Insurance System-National Health Screening Cohort (NHIS-HEALS). The average number of health screenings (from 2002–2013) used in the analysis was 2.9 ± 1.0. Two CVD prediction models were developed from the NHIS-HEALS data: a Cox hazard regression model and a deep learning model. In an internal validation of the NHIS-HEALS dataset, the Cox regression model showed a highest time-dependent area under the curve (AUC) of 0.79 (95% CI 0.70 to 0.87) for in females and 0.75 (95% CI 0.70 to 0.80) in males at 2 years. The deep learning model showed a highest time-dependent AUC of 0.94 (95% CI 0.91 to 0.97) for in females and 0.96 (95% CI 0.95 to 0.97) in males at 2 years. Layer-wise Relevance Propagation (LRP) revealed that age was the variable that had the greatest effect on CVD, followed by systolic blood pressure (SBP) and diastolic blood pressure (DBP), in that order. Conclusion The performance of the deep learning model for predicting CVD occurrences was better than that of the Cox regression model. In addition, it was confirmed that the known risk factors shown to be important by previous clinical studies were extracted from the study results using LRP.

Published
2019
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10. Impact of cumulative SBP and serious adverse events on efficacy of intensive blood pressure treatment: a randomized clinical trial

Author

Rueda-Ochoa, O.L. (Oscar), Rojas, L.Z. (Lyda), Ahmad, S. (Shahzad), Duijn, C.M. (Cornelia) van, Ikram, M.A. (Arfan), Deckers, J.W. (Jaap), Franco, O.H. (Oscar), Rizopoulos, D. (Dimitris), Kavousi, M. (Maryam), Rueda-Ochoa, O.L. (Oscar), Rojas, L.Z. (Lyda), Ahmad, S. (Shahzad), Duijn, C.M. (Cornelia) van, Ikram, M.A. (Arfan), Deckers, J.W. (Jaap), Franco, O.H. (Oscar), Rizopoulos, D. (Dimitris), and Kavousi, M. (Maryam)

Abstract

Background: Intensive blood pressure lowering is increasingly gaining attention. In addition to higher baseline blood pressure, cumulative SBP, visit-to-visit variability, and treatment-induced serious adverse events (SAEs) could impact treatment efficacy over time. Our aim was to assess the impact of cumulative SBP and SAEs on intensive hypertension treatment efficacy in the Systolic Blood Pressure Intervention Trial (SPRINT) population during follow-up. Methods: Secondary analysis of the SPRINT study: a randomized, controlled, open-label trial including 102 clinical sites in the United States. We included 9068 SPRINT participants with 128 139 repeated SBP measurements. Participants were randomly assigned to intensive (target SBP < 120 mmHg) versus standard treatment (target SBP between 135 and 139 mmHg). We used cumulative joint models for longitudinal and survival data analysis. Primary outcome was a composite outcome of myocardial infarction, other acute coronary syndromes, acute decompensated heart failure, stroke, and cardiovascular mortality. Results: Although intensive treatment decreased the risk for the primary SPRINT outcome at the start of follow-up, its effect lost significance after 3.4 years of follow-up in the total SPRINT population and after 1.3, 1.3, 1.1, 1.8, 2.1, 1.8, and 3.4 years among participants with prevalent chronic kidney disease, prevalent cardiovascular disease, women, black individuals, participants less than 75 years, those with baseline SBP more than 132 mmHg, and individuals who suffered SAEs during follow-up, respectively. Conclusion: The initial beneficial impact of intensive hypertension treatment might be offset by cumulative SBP and development of SAEs during follow-up.

Published
2019
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11. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes

Author

Franceschini, N. (Nora), Giambartolomei, C. (Claudia), Vries, P.S. (Paul) de, Finan, C. (Chris), Bis, J.C. (Joshua), Huntley, R.P. (Rachael P.), Lovering, R.C. (Ruth C.), Tajuddin, S.M. (Salman M.), Winkler, T.W. (Thomas W.), Graff, M. (Misa), Kavousi, M. (Maryam), Dale, C. (Caroline), Smith, A.V. (Albert), Hofer, E. (Edith), Leeuwen, E.M. (Elisa) van, Nolte, I.M. (Ilja), Lu, L. (Lingyi), Scholz, M. (Markus), Sargurupremraj, M. (Muralidharan), Pitkanen, N. (Niina), Franzén, O. (Oscar), Joshi, P.K. (Peter), Noordam, R. (Raymond), Marioni, R.E. (Riccardo), Hwang, S.-J. (Shih-Jen), Musani, S.K. (Solomon K.), Schminke, U. (Ulf), Palmas, W. (Walter), Isaacs, A.J. (Aaron), Correa, D.D., Zonderman, A.B., Hofman, A. (Albert), Teumer, A. (Alexander), Cox, A.J. (Amanda J.), Uitterlinden, A.G. (André), Wong, A. (Andrew), Smit, A.J. (Andries), Newman, A.B. (Anne B.), Britton, A.R., Ruusalepp, A. (Arno), Sennblad, B. (Bengt), Hedblad, B. (Bo), Pasaniuc, B. (Bogdan), Penninx, B.W.J.H. (Brenda), Langefeld, C.D. (Carl D.), Wassel, C.L. (Christina), Tzourio, C. (Christophe), Fava, C. (Cristiano), Baldassarre, D. (Damiano), O’Leary, D.H. (Daniel H.), Teupser, D. (Daniel), Kuh, D. (Diana), Tremoli, E. (Elena), Mannarino, E. (Elmo), Grossi, E. (Enzo), Boerwinkle, E.A. (Eric), Schadt, E.E. (Eric E.), Ingelsson, E. (Erik), Veglia, F. (Fabrizio), Rivadeneira Ramirez, F. (Fernando), Beutner, F. (Frank), Chauhan, G. (Ganesh), Heiss, G. (Gerardo), Snieder, H. (Harold), Campbell, H. (Harry), Völzke, H. (Henry), Markus, H.S. (Hugh), Deary, I.J. (Ian), Jukema, J.W. (Jan Wouter), Graaf, J. (Jacqueline) de, Price, J. (Jacqueline), Pott, J. (Janne), Hopewell, J., Liang, J. (Jingjing), Thiery, J.P. (Joachim), Engmann, J. (Jorgen), Gertow, K. (Karl), Rice, K.M. (Kenneth), Taylor, K.D. (Kent), Dhana, K. (Klodian), Kiemeney, L.A.L.M. (Lambertus A. L. M.), Kao, W.H.L. (Wen), Raffield, L.M. (Laura M.), Launer, L.J. (Lenore), Holdt, L.M. (Lesca), Dörr, M. (Marcus), Kubisch, C. (Christian), Traylor, M. (Matthew), Sitzer, M. (Matthias), Kumari, M. (Meena), Kivimaki, M. (Mika), Nalls, M.A. (Michael), Melander, O. (Olle), Raitakari, O. (Olli), Franco, O.H. (Oscar), Rueda-Ochoa, O.L. (Oscar), Roussos, A. (Alexandra), Whincup, P.H. (Peter), Amouyel, P. (Philippe), Giral, P. (Philippe), Anugu, P. (Pramod), Wong, Q. (Quenna), Malik, R. (Rainer), Rauramaa, R. (Rainer), Burkhardt, R. (Ralph), Hardy, R. (Rebecca), Schmidt, R. (Reinhold), Mutsert, R. (Reneé) de, Strawbridge, R.J. (Rona), Wannamethee, S.G. (Goya), Hägg, S. (Sara), Shah, S. (Sonia), McLachlan, S. (Stela), Trompet, S. (Stella), Seshadri, S. (Sudha), Kurl, S. (Sudhir), Heckbert, S.R. (Susan), Ring, S.M. (Susan), Harris, T.B. (Tamara B.), Lehtimäki, T. (Terho), Galesloot, T.E. (Tessel), Shah, T. (Tina), Faire, U. (Ulf) de, Plagnol, V. (Vincent), Rosamond, W.D. (Wayne), Post, W.S. (Wendy S.), Zhu, X. (Xiaofeng), Zhang, X. (Xiaoling), Guo, X. (Xiuqing), Saba, Y. (Yasaman), Okada, Y. (Yukinori), Mishra, A. (Aniket), Rutten-Jacobs, L. (Loes), Giese, A.-K. (Anne-Katrin), van der Laan, S.W. (Sander W.), Gretarsdottir, S. (Solveig), Anderson, C.D. (Christopher D.), Chong, M. (Michael), Adams, H.H.H. (Hieab), Ago, T. (Tetsuro), Almgren, P. (Peter), Ay, H. (Hakan), Bartz, T.M. (Traci M.), Benavente, O.R. (Oscar R.), Bevan, S. (Steve), Boncoraglio, G. (Giorgio Battista), Brown, R.D. (Robert D.), Butterworth, A.S. (Adam S.), Carrera, C. (Caty), Carty, C.L. (Cara L.), Chasman, D.I. (Daniel), Chen, W-M., Cole, J.W. (John W.), Cotlarciuc, I. (Ioana), Cruchaga, C. (Carlos), Danesh, J. (John), Bakker, P.I.W. (Paul) de, DeStefano, A.L. (Anita), Hoed, M. (Marcel) den, Duan, Q. (Qing), Engelter, S.T. (Stefan), Falcone, G.J. (Guido J.), Gottesman, R.F. (Rebecca), Grewal, R.P. (Raji P.), Gustafsson, S. (Stefan), Haessler, J. (Jeff), Harris, T.B. (Tamara), Hassan, A. (Ahamad), Havulinna, A.S. (Aki), Holliday, E.G. (Elizabeth), Howard, G. (George), Hsu, F.-C. (Fang-Chi), Hyacinth, H.I. (Hyacinth I.), Ikram, M.A. (Arfan), Irvin, M.R. (Marguerite R.), Jian, X. (Xueqiu), Jimenez-Conde, J. (Jordi), Johnson, J.A. (Julie A.), Jukema, J.W. (J. Wouter), Kanai, M. (Masahiro), Keene, K.L. (Keith), Kissela, B.M. (Brett M.), Kleindorfer, D.O. (Dawn O.), Kooperberg, C. (Charles), Kubo, M. (Michiaki), Lange, L.A. (Leslie), Langefeld, C.D. (Carl), Langenberg, C. (Claudia), Lee, J.-M. (Jin-Moo), Lemmens, R. (Robin), Leys, D. (Didier), Lewis, C.M. (Cathryn), Lin, W.-Y. (Wei-Yu), Lindgren, A.G. (Arne G.), Lorentzen, E. (Erik), Magnusson, P.K. (Patrik), Maguire, J.M. (Jane), Manichaikul, A. (Ani), McArdle, P.F. (Patrick), Meschia, J.F. (James F.), Mosley, T.H. (Thomas H.), Ninomiya, T. (Toshiharu), O’Donnell, M.J. (Martin J.), Pulit, S.L. (Sara), Rannikmäe, K. (Kristiina), Reiner, A.P. (Alexander P.), Rexrode, K. (Kathryn), Rich, S.S. (Stephen), Ridker, P.M. (Paul), Rost, N.S. (Natalia), Rothwell, P.M. (Peter), Rundek, T. (Tatjana), Muir, K.W. (Keith), Sakaue, S. (Saori), Sale, M.M. (Michele M.), Salomaa, V. (Veikko), Sapkota, B.R. (Bishwa R.), Schmidt, C.O. (Carsten O.), Sharma, P. (Pankaj), Slowik, A. (Agnieszka), Sudlow, C. (Cathie), Tanislav, C. (Christian), Tatlisumak, T. (Turgut), Thijs, V. (Vincent), Thorleifsson, G. (Gudmar), Thorsteinsdottir, U. (Unnur), Tiedt, S. (Steffen), Walters, M. (Matthew), Wareham, N.J. (Nick), Wassertheil-Smoller, S. (Sylvia), Wiggins, K.L. (Kerri), Yang, Q. (Qiong Fang), Yusuf, S. (Salim), Pastinen, T. (Tomi), Schadt, E.E. (Eric), Koplev, S. (Simon), Codoni, V. (Veronica), Civelek, M. (Mete), Smith, N.L. (Nicholas), Tregouet, D.-A. (David-Alexandre), Christophersen, I.E. (Ingrid E.), Roselli, C. (Carolina), Lubitz, S.A. (Steven A.), Ellinor, P.T. (Patrick), Tai, E.S. (E. Shyong), Kooner, J.S. (Jaspal S.), Kato, N. (Norihiro), He, J. (Jiang), Harst, P. (Pim) van der, Elliott, P. (Paul), Chambers, J.C. (John C.), Takeuchi, F. (Fumihiko), Johnson, A.D. (Andrew), Sanghera, D.K. (Dharambir K.), Jern, C. (Christina), Strbian, D. (Daniel), Fernandez-Cadenas, I. (Israel), Longstreth Jr, W.T., Rolfs, A. (Arndt), Hata, J. (Jun), Woo, D. (Daniel), Rosand, J. (Jonathan), Pare, G. (Guillame), Saleheen, D. (Danish), Zwart, J-A. (John-Anker), Worrall, B.B. (Bradford B.), Kittner, T. (Thomas), Howson, J.M.M. (Joanna M. M.), Kamatani, Y. (Yoichiro), Dehghan, A. (Abbas), Seldenrijk, K.A. (Kees), Morrison, A.C. (Alanna), Hamsten, A. (Anders), Psaty, B.M. (Bruce), Duijn, C.M. (Cornelia) van, Lawlor, D.A. (Debbie), Mook-Kanamori, D.O. (Dennis O.), Bowden, D.W. (Donald), Schmidt, H. (Helena), Wilson, J.F. (James F.), Wilson, J.F. (James), Rotter, J.I. (Jerome I.), Wardlaw, J.M. (J.), Deanfield, J. (John), Halcox, J. (Julian), Lyytikäinen, L.-P. (Leo-Pekka), Loeffler, M. (Markus), Evans, M.K. (Michele), Debette, S. (Stéphanie), Humphries, S.E. (Steve), Völker, U. (Uwe), Gudnason, V. (Vilmundur), Hingorani, A. (Aroon), Björkegren, J.L.M. (Johan L.M.), Casas, J.P. (Juan), Ódonnell, C.J. (Christopher), Morris, R.W. (Richard), Franceschini, N. (Nora), Giambartolomei, C. (Claudia), Vries, P.S. (Paul) de, Finan, C. (Chris), Bis, J.C. (Joshua), Huntley, R.P. (Rachael P.), Lovering, R.C. (Ruth C.), Tajuddin, S.M. (Salman M.), Winkler, T.W. (Thomas W.), Graff, M. (Misa), Kavousi, M. (Maryam), Dale, C. (Caroline), Smith, A.V. (Albert), Hofer, E. (Edith), Leeuwen, E.M. (Elisa) van, Nolte, I.M. (Ilja), Lu, L. (Lingyi), Scholz, M. (Markus), Sargurupremraj, M. (Muralidharan), Pitkanen, N. (Niina), Franzén, O. (Oscar), Joshi, P.K. (Peter), Noordam, R. (Raymond), Marioni, R.E. (Riccardo), Hwang, S.-J. (Shih-Jen), Musani, S.K. (Solomon K.), Schminke, U. (Ulf), Palmas, W. (Walter), Isaacs, A.J. (Aaron), Correa, D.D., Zonderman, A.B., Hofman, A. (Albert), Teumer, A. (Alexander), Cox, A.J. (Amanda J.), Uitterlinden, A.G. (André), Wong, A. (Andrew), Smit, A.J. (Andries), Newman, A.B. (Anne B.), Britton, A.R., Ruusalepp, A. (Arno), Sennblad, B. (Bengt), Hedblad, B. (Bo), Pasaniuc, B. (Bogdan), Penninx, B.W.J.H. (Brenda), Langefeld, C.D. (Carl D.), Wassel, C.L. (Christina), Tzourio, C. (Christophe), Fava, C. (Cristiano), Baldassarre, D. (Damiano), O’Leary, D.H. (Daniel H.), Teupser, D. (Daniel), Kuh, D. (Diana), Tremoli, E. (Elena), Mannarino, E. (Elmo), Grossi, E. (Enzo), Boerwinkle, E.A. (Eric), Schadt, E.E. (Eric E.), Ingelsson, E. (Erik), Veglia, F. (Fabrizio), Rivadeneira Ramirez, F. (Fernando), Beutner, F. (Frank), Chauhan, G. (Ganesh), Heiss, G. (Gerardo), Snieder, H. (Harold), Campbell, H. (Harry), Völzke, H. (Henry), Markus, H.S. (Hugh), Deary, I.J. (Ian), Jukema, J.W. (Jan Wouter), Graaf, J. (Jacqueline) de, Price, J. (Jacqueline), Pott, J. (Janne), Hopewell, J., Liang, J. (Jingjing), Thiery, J.P. (Joachim), Engmann, J. (Jorgen), Gertow, K. (Karl), Rice, K.M. (Kenneth), Taylor, K.D. (Kent), Dhana, K. (Klodian), Kiemeney, L.A.L.M. (Lambertus A. L. M.), Kao, W.H.L. (Wen), Raffield, L.M. (Laura M.), Launer, L.J. (Lenore), Holdt, L.M. (Lesca), Dörr, M. (Marcus), Kubisch, C. (Christian), Traylor, M. (Matthew), Sitzer, M. (Matthias), Kumari, M. (Meena), Kivimaki, M. (Mika), Nalls, M.A. (Michael), Melander, O. (Olle), Raitakari, O. (Olli), Franco, O.H. (Oscar), Rueda-Ochoa, O.L. (Oscar), Roussos, A. (Alexandra), Whincup, P.H. (Peter), Amouyel, P. (Philippe), Giral, P. (Philippe), Anugu, P. (Pramod), Wong, Q. (Quenna), Malik, R. (Rainer), Rauramaa, R. (Rainer), Burkhardt, R. (Ralph), Hardy, R. (Rebecca), Schmidt, R. (Reinhold), Mutsert, R. (Reneé) de, Strawbridge, R.J. (Rona), Wannamethee, S.G. (Goya), Hägg, S. (Sara), Shah, S. (Sonia), McLachlan, S. (Stela), Trompet, S. (Stella), Seshadri, S. (Sudha), Kurl, S. (Sudhir), Heckbert, S.R. (Susan), Ring, S.M. (Susan), Harris, T.B. (Tamara B.), Lehtimäki, T. (Terho), Galesloot, T.E. (Tessel), Shah, T. (Tina), Faire, U. (Ulf) de, Plagnol, V. (Vincent), Rosamond, W.D. (Wayne), Post, W.S. (Wendy S.), Zhu, X. (Xiaofeng), Zhang, X. (Xiaoling), Guo, X. (Xiuqing), Saba, Y. (Yasaman), Okada, Y. (Yukinori), Mishra, A. (Aniket), Rutten-Jacobs, L. (Loes), Giese, A.-K. (Anne-Katrin), van der Laan, S.W. (Sander W.), Gretarsdottir, S. (Solveig), Anderson, C.D. (Christopher D.), Chong, M. (Michael), Adams, H.H.H. (Hieab), Ago, T. (Tetsuro), Almgren, P. (Peter), Ay, H. (Hakan), Bartz, T.M. (Traci M.), Benavente, O.R. (Oscar R.), Bevan, S. (Steve), Boncoraglio, G. (Giorgio Battista), Brown, R.D. (Robert D.), Butterworth, A.S. (Adam S.), Carrera, C. (Caty), Carty, C.L. (Cara L.), Chasman, D.I. (Daniel), Chen, W-M., Cole, J.W. (John W.), Cotlarciuc, I. (Ioana), Cruchaga, C. (Carlos), Danesh, J. (John), Bakker, P.I.W. (Paul) de, DeStefano, A.L. (Anita), Hoed, M. (Marcel) den, Duan, Q. (Qing), Engelter, S.T. (Stefan), Falcone, G.J. (Guido J.), Gottesman, R.F. (Rebecca), Grewal, R.P. (Raji P.), Gustafsson, S. (Stefan), Haessler, J. (Jeff), Harris, T.B. (Tamara), Hassan, A. (Ahamad), Havulinna, A.S. (Aki), Holliday, E.G. (Elizabeth), Howard, G. (George), Hsu, F.-C. (Fang-Chi), Hyacinth, H.I. (Hyacinth I.), Ikram, M.A. (Arfan), Irvin, M.R. (Marguerite R.), Jian, X. (Xueqiu), Jimenez-Conde, J. (Jordi), Johnson, J.A. (Julie A.), Jukema, J.W. (J. Wouter), Kanai, M. (Masahiro), Keene, K.L. (Keith), Kissela, B.M. (Brett M.), Kleindorfer, D.O. (Dawn O.), Kooperberg, C. (Charles), Kubo, M. (Michiaki), Lange, L.A. (Leslie), Langefeld, C.D. (Carl), Langenberg, C. (Claudia), Lee, J.-M. (Jin-Moo), Lemmens, R. (Robin), Leys, D. (Didier), Lewis, C.M. (Cathryn), Lin, W.-Y. (Wei-Yu), Lindgren, A.G. (Arne G.), Lorentzen, E. (Erik), Magnusson, P.K. (Patrik), Maguire, J.M. (Jane), Manichaikul, A. (Ani), McArdle, P.F. (Patrick), Meschia, J.F. (James F.), Mosley, T.H. (Thomas H.), Ninomiya, T. (Toshiharu), O’Donnell, M.J. (Martin J.), Pulit, S.L. (Sara), Rannikmäe, K. (Kristiina), Reiner, A.P. (Alexander P.), Rexrode, K. (Kathryn), Rich, S.S. (Stephen), Ridker, P.M. (Paul), Rost, N.S. (Natalia), Rothwell, P.M. (Peter), Rundek, T. (Tatjana), Muir, K.W. (Keith), Sakaue, S. (Saori), Sale, M.M. (Michele M.), Salomaa, V. (Veikko), Sapkota, B.R. (Bishwa R.), Schmidt, C.O. (Carsten O.), Sharma, P. (Pankaj), Slowik, A. (Agnieszka), Sudlow, C. (Cathie), Tanislav, C. (Christian), Tatlisumak, T. (Turgut), Thijs, V. (Vincent), Thorleifsson, G. (Gudmar), Thorsteinsdottir, U. (Unnur), Tiedt, S. (Steffen), Walters, M. (Matthew), Wareham, N.J. (Nick), Wassertheil-Smoller, S. (Sylvia), Wiggins, K.L. (Kerri), Yang, Q. (Qiong Fang), Yusuf, S. (Salim), Pastinen, T. (Tomi), Schadt, E.E. (Eric), Koplev, S. (Simon), Codoni, V. (Veronica), Civelek, M. (Mete), Smith, N.L. (Nicholas), Tregouet, D.-A. (David-Alexandre), Christophersen, I.E. (Ingrid E.), Roselli, C. (Carolina), Lubitz, S.A. (Steven A.), Ellinor, P.T. (Patrick), Tai, E.S. (E. Shyong), Kooner, J.S. (Jaspal S.), Kato, N. (Norihiro), He, J. (Jiang), Harst, P. (Pim) van der, Elliott, P. (Paul), Chambers, J.C. (John C.), Takeuchi, F. (Fumihiko), Johnson, A.D. (Andrew), Sanghera, D.K. (Dharambir K.), Jern, C. (Christina), Strbian, D. (Daniel), Fernandez-Cadenas, I. (Israel), Longstreth Jr, W.T., Rolfs, A. (Arndt), Hata, J. (Jun), Woo, D. (Daniel), Rosand, J. (Jonathan), Pare, G. (Guillame), Saleheen, D. (Danish), Zwart, J-A. (John-Anker), Worrall, B.B. (Bradford B.), Kittner, T. (Thomas), Howson, J.M.M. (Joanna M. M.), Kamatani, Y. (Yoichiro), Dehghan, A. (Abbas), Seldenrijk, K.A. (Kees), Morrison, A.C. (Alanna), Hamsten, A. (Anders), Psaty, B.M. (Bruce), Duijn, C.M. (Cornelia) van, Lawlor, D.A. (Debbie), Mook-Kanamori, D.O. (Dennis O.), Bowden, D.W. (Donald), Schmidt, H. (Helena), Wilson, J.F. (James F.), Wilson, J.F. (James), Rotter, J.I. (Jerome I.), Wardlaw, J.M. (J.), Deanfield, J. (John), Halcox, J. (Julian), Lyytikäinen, L.-P. (Leo-Pekka), Loeffler, M. (Markus), Evans, M.K. (Michele), Debette, S. (Stéphanie), Humphries, S.E. (Steve), Völker, U. (Uwe), Gudnason, V. (Vilmundur), Hingorani, A. (Aroon), Björkegren, J.L.M. (Johan L.M.), Casas, J.P. (Juan), Ódonnell, C.J. (Christopher), and Morris, R.W. (Richard)

Abstract

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.

Published
2018
Full Text
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12. Electrocardiographic abnormalities in Chagas disease in the general population

Author

Rojas, L.Z. (Lyda), Glisic, M. (Marija), Pletsch-Borba, L. (Laura), Echeverría, L.E. (Luis E.), Bramer, W.M. (Wichor), Bano, A. (Arjola), Stringa, N. (Najada), Zaciragic, A. (Asija), Kraja, B. (Bledar), Asllanaj, E. (Eralda), Chowdhury, R. (Rajiv), Morillo, C.A. (Carlos), Rueda-Ochoa, O.L. (Oscar), Franco, O.H. (Oscar), Muka, T. (Taulant), Rojas, L.Z. (Lyda), Glisic, M. (Marija), Pletsch-Borba, L. (Laura), Echeverría, L.E. (Luis E.), Bramer, W.M. (Wichor), Bano, A. (Arjola), Stringa, N. (Najada), Zaciragic, A. (Asija), Kraja, B. (Bledar), Asllanaj, E. (Eralda), Chowdhury, R. (Rajiv), Morillo, C.A. (Carlos), Rueda-Ochoa, O.L. (Oscar), Franco, O.H. (Oscar), and Muka, T. (Taulant)

Abstract

Background: Chagas disease (CD) is a major public health concern in Latin America and a potentially serious emerging threat in non-endemic countries. Although the association between CD and cardiac abnormalities is widely reported, study design diversity, sample size and quality challenge the information, calling for its update and synthesis, which would be very useful and relevant for physicians in non-endemic countries where health care implications of CD are real and neglected. We performed to systematically review and meta-analyze population-based studies that compared prevalence of overall and specific ECG abnormalities between CD and non-CD participants in the general population. Methods: Six databases (EMBASE, Ovid Medline, Web of Science, Cochrane Central, Google Scholar and Lilacs) were searched systematically. Observational studies were included. Odds ratios (OR) were computed using random-effects model. Results: Forty-nine studies were selected, including 34,023(12,276 CD and 21,747 non-CD). Prevalence of overall ECG abnormalities was higher in participants with CD (40.1%; 95%CIs=39.2-41.0) compared to non-CD (24.1%; 95%CIs=23.5-24.7) (OR=2.78; 95%CIs=2.37-3.26). Among specific ECG abnormalities, prevalence of complete right bundle branch block (RBBB) (OR=4.60; 95%CIs=2.97-7.11), left anterior fascicular block (LAFB) (OR=1.60; 95%CIs=1.21-2.13), combination of complete RBBB/LAFB (OR=3.34; 95%CIs=1.76-6.35), first-degree atrioventricular block (A-V B) (OR=1.71; 95%CIs=1.25-2.33), atrial fibrillation (AF) or flutter (OR=2.11; 95%CIs=1.40-3.19) and ventricular extrasystoles (VE) (OR=1.62; 95%CIs=1.14-2.30) was higher in CD compared to non-CD participants. Conclusions: This systematic review and meta-analysis provides an update and synthesis in this field. This research of observational studies indicates a significant excess in prevalence of ECG abnormalities (40.1%) related to T. cruzi infection in the general population from Chagas endemic regions, being th

Published
2018
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13. P3413Prevalence of cardiac abnormalities in Chagas disease in the general population: a systematic review and meta-analysis

Author

Rojas Sanchez, L.Z., primary, Glisic, M., additional, Pletsch, L., additional, Rueda-Ochoa, O.L., additional, Echeverria, L.E., additional, Bramer, W., additional, Bano, A., additional, Stringa, N., additional, Zaciragic, A., additional, Kraja, B., additional, Asllanaj, E., additional, Franco, O.H., additional, and Muka, T., additional

Published
2017
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