Новые тренды и вызовы популяционной кардиологии
Автор: Анфиногенова Я.Д., Трубачева И.А., Серебрякова В.Н., Попов С.В.
Журнал: Сибирский журнал клинической и экспериментальной медицины @cardiotomsk
Рубрика: Обзоры и лекции
Статья в выпуске: 4 т.34, 2019 года.
Бесплатный доступ
Целью статьи является обзор зарубежной литературы относительно современных трендов и вызовов в области эпидемиологии сердечно-сосудистых заболеваний (ССЗ), включая появление новых факторов риска. Рассмотрено трансформирующее влияние омиксных технологий на эпидемиологию, сильные и слабые стороны метаэпидемиологии, а также роль мобильных технологий и электронных медицинских карт в укреплении здоровья населения. Отмечена важность преемственности между результатами эпидемиологических исследований и программами, ориентированными на улучшение здоровья местного населения. Авторы делают вывод, что изменение образа жизни людей в индустриальном обществе, глобализация, процессы миграции, бурное развитие технологий и промышленности сопровождаются трансформацией старых и появлением новых факторов риска ССЗ, требующих последовательного изучения и контроля. Революционные изменения в области биомедицинских технологий и эпидемиологических методов находят отражение в расширении международной терминологии. Учитывая, что новые термины рождаются на стыке трансформирующих направлений науки, авторы считают необходимым обновление и расширение российской терминологии в области эпидемиологии и смежных дисциплин наряду с внедрением новых биомедицинских подходов.
Сердечно-сосудистые заболевания, эпидемиология, омиксные технологии, новые подходы, факторы риска
Короткий адрес: https://sciup.org/149125339
IDR: 149125339 | DOI: 10.29001/2073-8552-2019-34-4-24-38
Список литературы Новые тренды и вызовы популяционной кардиологии
- Vasan R.S., Benjamin E.J. The future of cardiovascular epidemiology. Circulation. 2016;133(25):2626-2633. DOI: 10.1161/CIRCULATIONA-HA.116.023528
- Manrai A.K., Ioannidis J.P.A., Patel C.J. Signals among signals: prioritizing nongenetic associations in massive data sets. American Journal of Epidemiology. 2019;188(5):846-850. DOI: 10.1093/aje/kwz031
- Epimonitor. The Voice of Epidemiology. Outgoing SER President Sees "Gross Failure" to improve population health and calls for a more "Consequential Epidemiology". Accessed on July 03, 2019. https://www.epimonitor.net/Consequential_Epidemiology.htm.
- Galea S. An argument for a consequential epidemiology. American Journal of Epidemiology. 2013;178(8):1185-1191. DOI: 10.1093/aje/kwt172
- Keyes K., Galea S. What matters most: quantifying an epidemiology of consequence. Annals of Epidemiology 2015;25(5):305-311. DOI: 10.1016/j.annepidem.2015.01.016
- Khoury M.J., Gwinn M., Ioannidis J.P. The emergence of translational epidemiology: from scientific discovery to population health impact. American Journal of Epidemiology. 2010;172(5):517-524.
- DOI: 10.1093/aje/kwq211
- Pang H., Jia W., Hu Z. Emerging applications of metabolomics in clinical pharmacology. Clinical Pharmacology&Therapeutics. 2019;106(3):544-556.
- DOI: 10.1002/cpt.1538
- Ge X., Zheng L., Zhuang R., Yu P., Xu Z., Liu G. et al. The gut microbial metabolite trimethylamine N-oxide and hypertension risk: a systematic review and dose-response meta-analysis. Advances in Nutrition. 2019; Jul. 3. 10.1093/advances/nmz064. Interventionist approaches to epidemiology.
- DOI: 10.1093/advances/nmz064.Interventionistapproachestoepidemiology
- Schiattarella G.G., Sannino A., Toscano E., Giugliano G., Gargiulo G., Franzone A. et al. Gut microbe-generated metabolite trimethyl-amine-N-oxide as cardiovascular risk biomarker: a systematic review and dose-response meta-analysis. Eur. Heart J. 2017;38(39):2948-2956.
- DOI: 10.1093/eurheartj/ehx342
- Zhuang R., Ge X., Han L., Yu P., Gong X., Meng Q. et al. Gut microbe-generated metabolite trimethylamine N-oxide and the risk of diabetes: A systematic review and dose-response meta-analysis. Obes. Rev. 2019;20(6):883-894.
- DOI: 10.1111/obr.12843
- Tang W.H., Wang Z., Kennedy D.J., Wu Y, Buffa J.A., Agatisa-Boyle B. et al. Gut microbiota-dependent trimethylamine N-oxide (TMAO) pathway contributes to both development of renal insufficiency and mortality risk in chronic kidney disease. Circ. Res. 2015;116(3):448-455.
- DOI: 10.1161/CIRCRESAHA.116.305360
- Halmos T., Suba I. Non-alcoholic fatty liver disease, as a component of the metabolic syndrome, and its causal correlations with other extrahepatic diseases. Orv. Hetil. 2017;158(52):2051-2061.
- DOI: 10.1556/650.2017.30936
- Naylor C.D. Meta-analysis and the meta-epidemiology of clinical research. BMJ. 1997;315(7109):617-619.
- Murad M.H., Wang Z. Guidelines for reporting meta-epidemiological methodology research. BMJ. Evidence-Based Medicine. 2017;22(4):139-142.
- DOI: 10.1136/ebmed-2017-110713
- Bae J.M. Meta-epidemiology. Epidemiol. Health. 2014;36:e2014019.
- DOI: 10.4178/epih/e2014019
- Trinquart L., Dechartres A., Ravaud P. Commentary: Meta-epidemiology, meta-meta-epidemiology or network meta-epidemiology? Int. J. Epidemiol. 2013;42(4):1131-1133.
- DOI: 10.1093/ije/dyt137
- Fortunato S., Bergstrom C.T., Borner K., Evans J.A., Helbing D., Milojevic S. et al. Science of science. Science. 2018;359(6379): eaao0185.
- DOI: 10.1126/science.aao0185
- Salanti G., Higgins J.P., Ades A.E., Ioannidis J.P. Evaluation of networks of randomized trials. Stat. Methods Med. Res. 2007;17(3):279-301.
- DOI: 10.1177/0962280207080643
- Damen J.A.A.G., Debray T.P.A., Pajouheshnia R., Reitsma J.B., Scholten R.J.P.M., Moons K.G.M. et al. Empirical evidence of the impact of study characteristics on the performance of prediction models: a meta-epidemiological study. BMJ Open. 2019;9(4):e026160.
- DOI: 10.1136/bm-jopen-2018-026160
- Held U., Kessels A., Garcia Aymerich J., Basagana X., Ter Riet G., Moons K.G. et al. Methods for handling missing variables in risk prediction models. American Journal of Epidemiology. 2016;184(7):545-551.
- DOI: 10.1093/aje/kwv346
- Janssen K.J., Vergouwe Y, Donders A.R., Harrell F.E. Jr., Chen Q., Grobbee D.E. et al. Dealing with missing predictor values when applying clinical prediction models. Clin. Chem. 2009;55(5):994-1001.
- DOI: 10.1373/clinchem.2008.115345
- Moons K.G., Altman D.G., Reitsma J.B., Ioannidis J.P., Macaskill P., Steyerberg E.W. et al. Transparent reporting of a multivariable prediction model for Individual prognosis or diagnosis (TRIPOD): explanation and elaboration. Ann. Intern. Med. 2015;162(1):W1-73.
- DOI: 10.7326/M14-0698
- Storz-Pfennig P. Potentially unnecessary and wasteful clinical trial research detected in cumulative meta-epidemiological and trial sequential analysis. J. Clin. Epidemiol. 2017;82:61-70. 10.1016/j. jclinepi.2016.11.003.
- DOI: 10.1016/j.jclinepi.2016.11.003
- Antman E.M., Loscalzo J. Precision medicine in cardiology. Nat. Rev. Cardiol. 2016;13(10):591-602.
- DOI: 10.1038/nrcardio.2016.101
- McManus D.D., Trinquart L., Benjamin E.J., Manders E.S., Fusco K., Jung L.S. et al. Design and Preliminary Findings From a New Electronic Cohort Embedded in the Framingham Heart Study. J. Med. Internet. Res. 2019;21(3):e12143.
- DOI: 10.2196/12143
- Vineis P., Chadeau-Hyam M., Gmuender H., Gulliver J., Herceg Z., Kleinjans J. et al. The exposome in practice: Design of the EXPOsOM-ICS project. Int. J. Hyg. Environ. Health. 2017;220(2):142-151.
- DOI: 10.1016/j.ijheh.2016.08.001
- Zhu Y, Gu X., Xu C. Effectiveness of telemedicine systems for adults with heart failure: a meta-analysis of randomized controlled trials. Heart Fail. Rev. 2019;May24.
- DOI: 10.1007/s10741-019-09801-5
- Omboni S., Posokhov I., Parati G., Rogoza A., Kotovskaya Y, Arystan A. et al. Ambulatory blood pressure and arterial stiffness web-based telemonitoring in patients at cardiovascular risk. First results of the VASOTENS (Vascular health ASsessment Of The hypertENSive patients) Registry. J. Clin. Hypertens. (Greenwich). 2019;21(8):1155-1168.
- DOI: 10.1111/jch.13623
- Fox C.S., Hwang S.J., Nieto K., Valentino M., Mutalik K., Massaro J.M. et al. Digital Connectedness in the Framingham Heart Study. J. Am. Heart Assoc. 2016;5(4):e003193.
- DOI: 10.1161/JAHA.116.003193
- Schofield P., Shaw T., Pascoe M. Toward comprehensive patient-centric care by integrating digital health technology with direct clinical contact in Australia. J. Med. Internet Res. 2019;21(6):e12382.
- DOI: 10.2196/12382
- Treskes R.W., Wildbergh T.X., Schalij M.J., Scherptong R.W.C. Expectations and perceived barriers to widespread implementation of e-Health in cardiology practice: Results from a national survey in the Netherlands. Neth. Heart J. 2019;27(1):18-23.
- DOI: 10.1007/s12471-018-1199-9
- Hemingway H., Asselbergs F.W., Danesh J., Dobson R., Maniadakis N., Maggioni A. et al. Big data from electronic health records for early and late translational cardiovascular research: challenges and potential. Eur. Heart J. 2018;39(16):1481-1495.
- DOI: 10.1093/eurheartj/ehx487
- Puska P. From Framingham to North Karelia: from descriptive epidemiology to public health action. Prog. Cardiovasc. Dis. 2010;53(1):15-20.
- DOI: 10.1016/j.pcad.2010.01.003
- Pearson T.A., Palaniappan L.P., Artinian N.T., Carnethon M.R., Criqui M.H., Daniels S.R. et al. American Heart Association Guide for Improving Cardiovascular Health at the Community Level, 2013 update: a scientific statement for public health practitioners, healthcare providers, and health policy makers. Circulation. 2013;127(16):1730-1753.
- DOI: 10.1161/CIR.0b013e31828f8a94
- Andersson C., Johnson A.D., Benjamin E.J., Levy D., Vasan R.S. 70-year legacy of the Framingham Heart Study. Nat. Rev. Cardiol. 2019;May 7.
- DOI: 10.1038/s41569-019-0202-5
- Muhlack D.C., Hoppe L.K., Weberpals J., Brenner H., Schottker B. The Association of Potentially Inappropriate Medication at Older Age with Cardiovascular Events and Overall Mortality: A Systematic Review and Meta-Analysis of Cohort Studies. J. Am. Med. Dir. Assoc. 2017;18(3):211-220.
- DOI: 10.1016/j.jamda.2016.11.025
- Grina D., Briedis V. The use of potentially inappropriate medications among the Lithuanian elderly according to Beers and EU(7)-PIM list -a nationwide cross-sectional study on reimbursement claims data. J. Clin. Pharm. Ther. 2017;42(2):195-200.
- DOI: 10.1111/jcpt.12494
- Beers M.H., Ouslander J.G., Rollingher I., Reuben D.B., Brooks J., Beck J.C. Explicit criteria for determining inappropriate medication use in nursing home residents. UCLA Division of Geriatric Medicine. Arch. Intern. Med. 1991;151:1825-1832.
- DOI: 10.1001/archinte.1991.00400090107019
- Beers M.H. Explicit criteria for determining potentially inappropriate medication use by the elderly. An update. Arch. Intern. Med. 1997;157(14):1531-1536.
- DOI: 10.1001/archinte.1997.00440350031003
- The National Committee for Quality Assurance. HEDIS 2016 final NDC lists - Use of high-risk medications in the elderly (DAE). Accessed August 1, 2016. http://www.ncqa.org/hedis-quality-measurement/hedis-mea-sures/hedis-2016/hedis-2016-ndclicense/hedis-2016-final-ndc-lists.
- Stolar M.H. Drug use review: Operational definitions. American Journal Hospital Pharmacy. 1978;35(1):76-78.
- DOI: 10.1093/ajhp/35.1.76
- Fastbom J., Johnell K. National indicators for quality of drug therapy in older persons: The Swedish experience from the first 10 years. Drugs Aging. 2015;32(3):189-199.
- DOI: 10.1007/s40266-015-0242-4
- Fick D.M., Cooper J.W., Wade W.E., Waller J.L., Maclean J.R., Beers M.H. Updating the Beers criteria for potentially inappropriate medication use in older adults: results of a US consensus panel of experts. Arch. Intern. Med. 2003;163(22):2716-2724.
- DOI: 10.1001/archinte.163.22.2716
- McLeod PJ., Huang A.R., Tamblyn R.M., Gayton D.C. Defining inappropriate practices in prescribing for elderly people: A national consensus panel. CMAJ. 1997;156(3):385-391.
- Elliott R.A. Problems with medication use in the elderly: An Australian perspective. J. Pharm. Pract. Res. 2006;36(1):58-66.
- DOI: 10.1002/j.2055-2335.2006.tb00889.x
- Roughead E.E., Anderson B., Gilbert A.L. Potentially inappropriate prescribing among Australian veterans and war widows/wid-owers. Intern. Med. J. 2007;37(6):402-405.
- DOI: 10.1111/j.1445-5994.2007.01316.x
- American Geriatrics Society 2012 Beers Criteria Update Expert Panel. American Geriatrics Society updated Beers Criteria for potentially inappropriate medication use in older adults. J. Am. Geriatr. Soc. 2012;60(4):616-631.
- DOI: 10.1111/j.1532-5415.2012.03923.x
- American Geriatrics Society 2015 Beers Criteria Update Expert Panel. American Geriatrics Society 2015 Updated Beers criteria for potentially inappropriate medication use in older adults. J. Am. Geriatr. Soc. 2015;63(11):2227-2246.
- DOI: 10.1111/jgs.13702
- Renom-Guiteras A., Meyer G., Th'rmann P.A. The EU(7)-PIM list: a list of potentially inappropriate medications for older people consented by experts from seven European countries. Eur. J. Clin. Pharmacol. 2015;71(7):861-875.
- DOI: 10.1007/s00228-015-1860-9
- Ivanova I., Elseviers M., Wettermark B., Schmidt Mende K., Vander Stichele R., Christiaens T. Electronic assessment of cardiovascular potentially inappropriate medications in an administrative population database. BCPT. 2019;124(1):62-73.
- DOI: 10.1111/bcpt.13095
- Jin K., Gullick J., Neubeck L., Koo F., Ding D. Acculturation is associated with higher prevalence of cardiovascular disease risk-factors among Chinese immigrants in Australia: Evidence from a large population-based cohort. Eur. JPrev. Cardiol. 2017;24(18):2000-2008.
- DOI: 10.1177/2047487317736828
- Guo S., Lucas R.M., Joshy G., Banks E. Cardiovascular disease risk factor profiles of 263,356 older Australians according to region of birth and acculturation, with a focus on migrants born in Asia. PLoS One. 2015;10(2):e0115627.
- DOI: 10.1371/journal.pone.0115627
- Tavares L., Calhau C., Polonia J. Assessment of cardiovascular risk and social framework of Cape Verdean university students studying in Portugal. Rev. Port. Cardiol. 2018;37(7):577-582.
- DOI: 10.1016/j.repc.2017.09.027
- Choi M., Mesa-Frias M., Nuesch E., Hargreaves J., Prieto-Merino D., Bowling A. et al. Social capital, mortality, cardiovascular events and cancer: a systematic review of prospective studies. Int. J. Epidemiol. 2014;43(6):1895-1920.
- DOI: 10.1093/ije/dyu212
- Hamad R., Nguyen T.T., Bhattacharya J., Glymour M.M., Rehkopf D.H. Educational attainment and cardiovascular disease in the United States: A quasi-experimental instrumental variables analysis. PLoS Med. 2019;16(6):e1002834.
- DOI: 10.1371/journal.pmed.1002834
- Braveman P., Gottlieb L. The social determinants of health: it's time to consider the causes of the causes. Public Health Rep. 2014;129(2):19-31.
- DOI: 10.1177/00333549141291S206
- Currie D.J., Smith C., Jagals P. The application of system dynamics modelling to environmental health decision-making and policy - a scoping review. BMC Public Health. 2018;18(1):402.
- DOI: 10.1186/s12889-018-5318-8
- Alderwick H., Gottlieb L.M. Meanings and misunderstandings: a social determinants of health lexicon for health care systems. Milbank Quarterly. 2019;97(2):407-419.
- DOI: 10.1111/1468-0009.12390