{"title":"The war against the resistance of Acinetobacter baumannii: A Meta-Analysis in Turkey","authors":"Imdat Kilbas","doi":"10.14744/etd.2022.94770","DOIUrl":"https://doi.org/10.14744/etd.2022.94770","url":null,"abstract":"","PeriodicalId":43995,"journal":{"name":"Erciyes Medical Journal","volume":"6 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78744774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluation of serum growth arrest specific-6/sAXL levels in type 2 diabetes mellitus","authors":"Merve Özel","doi":"10.14744/etd.2022.45403","DOIUrl":"https://doi.org/10.14744/etd.2022.45403","url":null,"abstract":"","PeriodicalId":43995,"journal":{"name":"Erciyes Medical Journal","volume":"1 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79346357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Differences between chronological age and height age in goiter interpretation","authors":"S. Koca","doi":"10.14744/etd.2022.56687","DOIUrl":"https://doi.org/10.14744/etd.2022.56687","url":null,"abstract":"","PeriodicalId":43995,"journal":{"name":"Erciyes Medical Journal","volume":"14 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82631381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluation of Subclinical Inflammation in children with Premature Adrenarche","authors":"Gözde Köylü","doi":"10.14744/etd.2022.39699","DOIUrl":"https://doi.org/10.14744/etd.2022.39699","url":null,"abstract":"","PeriodicalId":43995,"journal":{"name":"Erciyes Medical Journal","volume":"12 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83464332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Review of the Effects of Probiotics and Their Metabolites in the Treatment of Liver Cancer: an Update on Probiotics as a New Treatment","authors":"R. Bakhtiari","doi":"10.14744/etd.2022.25477","DOIUrl":"https://doi.org/10.14744/etd.2022.25477","url":null,"abstract":"","PeriodicalId":43995,"journal":{"name":"Erciyes Medical Journal","volume":"69 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89373382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Historical Perspective of the Management of Scoliosis","authors":"G. Yagci","doi":"10.14744/etd.2022.23682","DOIUrl":"https://doi.org/10.14744/etd.2022.23682","url":null,"abstract":"","PeriodicalId":43995,"journal":{"name":"Erciyes Medical Journal","volume":"116 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79658690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: The primary aim of this study was to use metagenomic next-generation sequencing (mNGS) data to identify coronavirus 2019 (COVID-19)-related biomarker genes and to construct a machine learning model that could successfully differentiate patients with COVID-19 from healthy controls. Materials and Methods: The mNGS dataset used in the study demonstrated expression of 15,979 genes in the upper airway in 234 patients who were COVID-19 negative and COVID-19 positive. The Boruta method was used to select qualitative biomarker genes associated with COVID-19. Random forest (RF), gradient boosting tree (GBT), and multi-layer perceptron (MLP) models were used to predict COVID-19 based on the selected biomarker genes. Results: The MLP (0.936) model outperformed the GBT (0.851), and RF (0.809) models in predicting COVID-19. The three most important biomarker candidate genes associated with COVID-19 were IFI27, TPTI, and FAM83A. Conclusion: The proposed model (MLP) was able to predict COVID-19 successfully. The results showed that the generated model and selected biomarker candidate genes can be used as diagnostic models for clinical testing or potential therapeutic targets and vaccine design.
{"title":"Prediction of COVID-19 Based on Genomic Biomarkers of Metagenomic Next-Generation Sequencing Data Using Artificial Intelligence Technology","authors":"S. Akbulut","doi":"10.14744/etd.2022.00868","DOIUrl":"https://doi.org/10.14744/etd.2022.00868","url":null,"abstract":"Objective: The primary aim of this study was to use metagenomic next-generation sequencing (mNGS) data to identify coronavirus 2019 (COVID-19)-related biomarker genes and to construct a machine learning model that could successfully differentiate patients with COVID-19 from healthy controls. Materials and Methods: The mNGS dataset used in the study demonstrated expression of 15,979 genes in the upper airway in 234 patients who were COVID-19 negative and COVID-19 positive. The Boruta method was used to select qualitative biomarker genes associated with COVID-19. Random forest (RF), gradient boosting tree (GBT), and multi-layer perceptron (MLP) models were used to predict COVID-19 based on the selected biomarker genes. Results: The MLP (0.936) model outperformed the GBT (0.851), and RF (0.809) models in predicting COVID-19. The three most important biomarker candidate genes associated with COVID-19 were IFI27, TPTI, and FAM83A. Conclusion: The proposed model (MLP) was able to predict COVID-19 successfully. The results showed that the generated model and selected biomarker candidate genes can be used as diagnostic models for clinical testing or potential therapeutic targets and vaccine design.","PeriodicalId":43995,"journal":{"name":"Erciyes Medical Journal","volume":"36 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80663257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Objective: The coronavirus disease 2019 (COVID-19) has placed huge strains on medical systems. Therefore, it is essential to determine the predictors of the long hospital stay. We sought to investigate whether alterations in left ventricular (LV) geometry in COVID-19 patients are associated with the length of stay (LoS) and a long hospital stay. Materials and Methods: 108 consecutive hospitalized COVID-19 patients were incorporated in the study and 89 patients remained for statistical analysis. All participants underwent standard two-dimensional (2D) and Doppler echocardiographic examinations. Patients were classified according to LV geometry characteristics namely normal geometry (NG), concentric remodeling, concentric hypertrophy and eccentric hypertrophy. Results: Multiple binary logistic regression model adjusted for clinical and laboratory variables yielded significant and independent association of LV mass index (LVMI) (OR: 1.12, 95% CI: 1.06-1.19, p<0.001), 10 g/m(2) increase in LVMI (OR: 3.63, 95% CI: 2.00-6.59, p<0.001), LV geometry patterns (OR: 2.92, 95% CI: 1.46-5.34, p=0.002), and altered geometric patterns compared to NG (OR: 3.97, 95% CI: 1.08-14.5, p=0.037) with long hospital stay. Correlation analysis of LVMI and LoS demonstrated significant and moderate correlation (rho=0.58, p<0.001). Conclusion: LVMI and LV geometric patterns independently predict long hospital stays in COVID-19 patients. The significant correlation between LoS and LVMI underlies the significance of LV geometry in this infection.
{"title":"The Impact of Left Ventricle Geometry Patterns on Length of Hospital Stay in COVID-19 Patients","authors":"M. Erdoğan","doi":"10.14744/etd.2022.08365","DOIUrl":"https://doi.org/10.14744/etd.2022.08365","url":null,"abstract":"Objective: The coronavirus disease 2019 (COVID-19) has placed huge strains on medical systems. Therefore, it is essential to determine the predictors of the long hospital stay. We sought to investigate whether alterations in left ventricular (LV) geometry in COVID-19 patients are associated with the length of stay (LoS) and a long hospital stay. Materials and Methods: 108 consecutive hospitalized COVID-19 patients were incorporated in the study and 89 patients remained for statistical analysis. All participants underwent standard two-dimensional (2D) and Doppler echocardiographic examinations. Patients were classified according to LV geometry characteristics namely normal geometry (NG), concentric remodeling, concentric hypertrophy and eccentric hypertrophy. Results: Multiple binary logistic regression model adjusted for clinical and laboratory variables yielded significant and independent association of LV mass index (LVMI) (OR: 1.12, 95% CI: 1.06-1.19, p<0.001), 10 g/m(2) increase in LVMI (OR: 3.63, 95% CI: 2.00-6.59, p<0.001), LV geometry patterns (OR: 2.92, 95% CI: 1.46-5.34, p=0.002), and altered geometric patterns compared to NG (OR: 3.97, 95% CI: 1.08-14.5, p=0.037) with long hospital stay. Correlation analysis of LVMI and LoS demonstrated significant and moderate correlation (rho=0.58, p<0.001). Conclusion: LVMI and LV geometric patterns independently predict long hospital stays in COVID-19 patients. The significant correlation between LoS and LVMI underlies the significance of LV geometry in this infection.","PeriodicalId":43995,"journal":{"name":"Erciyes Medical Journal","volume":"74 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85340834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detection of Novel NF1 Variants with Next Generation-based DNA Sequencing Technology, and Genotype-Phenotype Characteristics of Neurofibromatosis","authors":"A. Kiraz","doi":"10.14744/etd.2022.90023","DOIUrl":"https://doi.org/10.14744/etd.2022.90023","url":null,"abstract":"","PeriodicalId":43995,"journal":{"name":"Erciyes Medical Journal","volume":"17 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90470286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Duration of oral antioxidant therapy in male infertility with increased DNA damage: 3 month versus 6 month","authors":"E. Hasırcı","doi":"10.14744/etd.2022.49404","DOIUrl":"https://doi.org/10.14744/etd.2022.49404","url":null,"abstract":"","PeriodicalId":43995,"journal":{"name":"Erciyes Medical Journal","volume":"36 1","pages":""},"PeriodicalIF":0.4,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74057916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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