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SIMPLE MORTALITY PROGNOSTIC RISK CALCULATOR FOR PATIENTS WITH ACUTE CORONARY SYNDROME
Zagidullin, N., Travnikova, E., Zagidullin, B., Zulkarneev, R., Zagidullin, S. (2016)
(survivors) and group 2 (nonsurvivors). Firstly, the risk factor were evaluated using the binary model
A Combined Effect of Polygenic Scores and Environmental Factors on Individual Differences in Depression Level
Kazantseva, Anastasiya, Davydova, Yuliya, Enikeeva, Renata, Mustafin, Rustam, Malykh, Sergey, Lobaskova, Marina, Kanapin, Alexander, Prokopenko, Inga, Khusnutdinova, Elza (2023)
-specific effect estimates in such modeling is important for individual risk assessment. © 2023 by the authors.
Using a Polygenic Score to Predict the Risk of Developing Primary Osteoporosis
Yalaev, Bulat, Tyurin, Anton, Prokopenko, Inga, Karunas, Aleksandra, Khusnutdinova, Elza, Khusainova, Rita (2022)
models to predict the risk of low fractures in women from the Volga-Ural region of Russia with efficacy
ПРЕДИКТОРНАЯ МОДЕЛЬ ИСХОДОВ ОСТРОГО КОРОНАРНОГО СИНДРОМА
PREDICTOR MODEL OF ACUTE CORONARY SYNDROME OUTCOMES
ЗАГИДУЛЛИН, Н.Ш., ТРАВНИКОВА, Е.О., ЛАКМАН, И.А., ЗАГИДУЛЛИН, Б.И., ЗАГИДУЛЛИН, Ш.З., ZAGIDULLIN, N. S., TRAVNIKOVA, E.O., LAKMAN, I.A., ZAGIDULLIN, B.I., ZAGIDULLIN, Sh.Z. (2016)
PREDICTOR MODEL OF ACUTE CORONARY SYNDROME OUTCOMES
STATISTICAL MODELS OF ECONOMIC BURDEN: A CASE STUDY IN MEDICINE
LAKMAN, I.A., MAKSIMENKO, Z.V., SHANGAREEVA, R.KH., GINDULLIN, R.V. (2019)
-37 weeks were used as input data. Cox’s proportional hazards model was used as a survival tool. Findings
Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes
Timasheva, Y., Balkhiyarova, Z., Avzaletdinova, D., Rassoleeva, I., Morugova, T.V., Korytina, G., Prokopenko, I., Kochetova, O. (2023)
ability of the model containing polygenic scores for the variants associated with T2D in our dataset
Incidence of adhesive small bowel obstruction after gastrectomy for gastric cancer and its risk factors: a long-term retrospective cohort study from a high-volume institution in China
Tao, Pan, Galiullin, D, Chen, X.L., Zhang, W.H., Yang, K, Liu, K, Zhao, L.Y., Chen, X.Z., Hu, J.K. (2021)
performed to determine risk factors for ASBO. A nomogram for the prediction of ASBO was generated using
Многофакторная прогностическая модель у пациентов с инфарктом миокарда в отдаленном периоде на основе современных биомаркеров
MULTIFACTOR PREDICTIVE MODEL IN PATIENTS WITH MYOCARDIAL INFARCTION BASED ON MODERN BIOMARKERS
Khamitova, A.F., Lakman, I.A., Akhmetvaleev, R.R., Tulbaev, E.L., Gareeva, D.F., Zagidullin, Sh.Z, Zagidullin, NS, Хамитова А. Ф., Лакман И. А., Ахметвалеев Р. Р., Тулбаев Э. Л., Гареева Д. Ф., Загидуллин Ш. З.,, Загидуллин Н. Ш. (2020)
infarction (MI) by constructing a multifactorial model for prediction of cardiovascular complications (CVC
Evaluation of Polygenic Risk Score for Prediction of Childhood Onset and Severity of Asthma
Savelieva, Olga, Karunas, Alexandra, Prokopenko, Inga, Balkhiyarova, Zhanna, Gilyazova, Irina, Khidiyatova, Irina, Khusnutdinova, Elza (2025)
and respective response to drug therapy. PGS models could help to predict the individual risk of asthma using 26
Polygenic Score Approach to Predicting Risk of Metabolic Syndrome
Timasheva, Yanina, Kochetova, Olga, Balkhiyarova, Zhanna, Korytina, Gulnaz, Prokopenko, Inga, Nouwen, Arie (2025)
, we evaluated the prognostic capability of a polygenic score model for MetS risk, both independently

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