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Background:Heart failure (HF) is a common condition that affects 1-3% of the general population. Its prevalence exhibits notable international and intranational disparities, partly explained by socioeconomic status, religion, ethnic diversity, and geographic factors. A comprehensive understanding of the epidemiological symptoms of HF in different regions of Türkiye has yet to be revealed.Aims:To examine epidemiological data from 2016 to 2022, focusing on crucial patient characteristics and geographical regions, to determine the incidence and prevalence of HF in Türkiye across seven diverse geographical regions.Study Design:A nationwide population-based retrospective cohort study.Methods:The comprehensive National Electronic Database of the Turkish Ministry of Health was used in this study to obtain data that covers the whole Turkish population from January 1, 2016, to December 31, 2022. The International Classification of Diseases-10 (ICD-10) codes were used to identify adults with HF (n = 2,701,099) and associated comorbidities. Türkiye is divided into seven geographically distinct regions. Epidemiological characteristics and survival data of these regions were analyzed separately. All-cause mortality was set as the primary outcome.Results:In , the total estimated prevalence of adult patients with HF is 2.939%, ranging from 2.442% in Southeastern Anatolia to 4.382% in the Black Sea Region. Except for the Eastern Anatolia Region, the three most often reported comorbidities were hypertension, dyslipidemia, and anxiety disorders. The rates of prescribing guideline-directed medical therapy (GDMT) for HF and other medications varied significantly. GDMT prescription rates were lowest in the Eastern Anatolia Region (82.6% for beta-blockers, 48.7% for RASi, 31.8% for mineralocorticoid receptor antagonists, and 9.4% for SGLT2i). The Mediterranean and Aegean regions had the highest median N-terminal brain natriuretic peptide (NT-proBNP) levels of 1,990,0 pg/ml (518.0-6,636,0) and 1,441,0 pg/ml (363.0-5,000,0), respectively. From 2016 to 2022, 915,897 (33.9%) of 2,701,099 patients died. The Eastern Anatolia Region had the lowest all-cause mortality rate of 26.5%, whereas the Black Sea Region had the highest all-cause mortality rate of 35.3%.Conclusion:Our real-world analysis revealed geographic disparities in HF characteristics, such as decreased mortality in socioeconomically challenged regions. Higher stress susceptibility in developed regions may increase the likelihood of adverse outcomes.

Objective: The aim of study is to introduce method of Soft Independent Modeling of Class Analogy (SIMCA), and to express whether the method is affected from the number of independent variables, the relationship between variables and sample size. Study Design: Simulation study. Material and Methods: SIMCA model is performed in two stages. In order to determine whether the method is influenced by the number of independent variables, the relationship between variables and sample size, simulations were done. Conditions in which sample sizes in both groups are equal, and where there are 30, 100 and 1000 samples; where the number of variables is 2, 3, 5, 10, 50 and 100; moreover where the relationship between variables are quite high, in medium level and quite low were mentioned. Results: Average classification accuracy of simulation results which were carried out 1000 times for each possible condition of trial plan were given as tables. Conclusion: It is seen that diagnostic accuracy results increase as the number of independent variables increase. SIMCA method is a method in which the relationship between variables are quite high, the number of independent variables are many in number and where there are outlier values in the data that can be used in conditions having outlier values.

Objective: The aim of study is to introduce method of Soft Independent Modeling of Class Analogy (SIMCA), and to express whether the method is affected from the number of independent variables, the relationship between variables and sample size. Study Design: Simulation study. Material and Methods: SIMCA model is performed in two stages. In order to determine whether the method is influenced by the number of independent variables, the relationship between variables and sample size, simulations were done. Conditions in which sample sizes in both groups are equal, and where there are 30, 100 and 1000 samples; where the number of variables is 2, 3, 5, 10, 50 and 100; moreover where the relationship between variables are quite high, in medium level and quite low were mentioned. Results: Average classification accuracy of simulation results which were carried out 1000 times for each possible condition of trial plan were given as tables. Conclusion: It is seen that diagnostic accuracy results increase as the number of independent variables increase. SIMCA method is a method in which the relationship between variables are quite high, the number of independent variables are many in number and where there are outlier values in the data that can be used in conditions having outlier values. [ABSTRACT FROM AUTHOR]