Evaluation of Single/Multiple Joint Effects of Lipid Profiles on Hypertension, Diabetes Mellitus and Obesity Accompanying Coronary Artery Disease
Öz
Objective: Although cardiovascular diseases are among the most prominent causes of mortality/morbidity in the world, they are even more important together with comorbidities. This study aims to reveal the single/multiple effects of total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), and triglyceride (TG) on hypertension (HT), type 2 diabetes mellitus (T2DM) and obesity accompanying coronary artery disease (CAD).
Method: The data were retrospectively achieved from the records of CAD patients undergoing coronary bypass surgery at the Department of Cardiovascular Surgery, Medical Center, University. The medical knowledge discovery process (MKDP) was applied to the data concerning HT, DM, obesity, TC, HDL-C, LDL-C, and TG variables. Different methods were used to determine the optimal cut-off points of lipid profiles. Logistic regression analysis (LRA) was examined the single/multiple effects of lipid profiles on HT, T2DM, and obesity.
Results: TC, LDL-C, TG, and HDL-C lipid profiles categorized according to the cut-off points determined in the current study were analyzed with LRA models. LDL-C (>117 mg/dL)*TC (>191 mg/dL)*HDL-C (>37.2 mg/dL) in HT and TC (>190 mg/dL)*TG (>197) mg/dL)*HDL-C (>36.3 mg/dL) in T2DM interaction terms had a moderate effect size. LDL-C (>115 mg/dL)*TG (>197 mg/dL)*HDL-C (>36.3 mg/dL) interaction terms in T2DM and TC (>192 mg/dL)*LDL-C (>117 mg/dL)*HDL-C (>36.8 mg/dL), TK (>192 mg/dL)*TG (>193 mg/dL)*HDL-C (>36.8 mg/dL) and LDL-C (>117 mg/dL)*TG (>193 mg/dL)*HDL-C (>36.8 mg/dL) interaction terms in obesity were reported as having a high effect size.
Conclusion: In conclusion, it is recommended to use the approach that analyzes the cut-off points proposed in this study for lipid profiles in predicting HT, T2DM, and obesity.
Anahtar Kelimeler
Coronary artery disease Risk factors Lipids Knowledge discovery
Destekleyen Kurum
TÜBİTAK
Proje Numarası
218S744
Teşekkür
This study was financially supported by TÜBİTAK for our 1001 project numbered 218S744. We would like to thank TÜBİTAK for its support in our 1001 project numbered 218S744.
Kaynakça
- Dülek H, Vural ZT, Gönenç I. Risk Factors in Cardiovascular Diseases. Jour Turk Fam Phy 2018; 9(2): 53-58.
- Aksoy DY, Gürlek A. Diabetes mellitus and primary healthcare. Journal of Clinical and Experimental Investigations 2004; 35: 123-26.
- Onat A, Uğur M, Çiçek G, Dogan Y, Kaya H, Can G. The Turkish Adult Risk Factor survey 2009: similar cardiovascular mortalityin rural and urban areas. Türk Kardiyol Dern Arş 2010; 38(3): 159-63.
- Abacı A. The current status of cardiovascular risk factors in Turkey. Turk Kardiyol Dern Ars 2011; 39(4): 1-5.
- Tekkeşin N, Kılınç C. Investigation of Framingham Risk Factors in Turkish adults. Journal of Clinical and Experimental Investigations 2011; 2(1): 42-49.
- Colak C, Colak MC, Orman MN. The comparison of logistic regression model selection methods for the prediction of coronary artery disease. Anadolu Kardiyol Derg 2007; 7(1): 6-12.
- Brown G, Albers JJ, Fisher LD, Schaefer SM, Lin JT, Kaplan C, et al. Regression of coronary artery disease as a result of intensive lipid-lowering therapy in men with high levels of apolipoprotein B. N Engl J Med 1990; 323(19): 1289-98.
- Perk J, De Backer G, Gohlke H, Graham I, Reiner Z, Verschuren M, et al. European Guidelines on cardiovascular disease prevention in clinical practice (version 2012) The Fifth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of nine societies and by invited experts) Developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). European heart journal 2012; 33(13): 1635-701.
- Grundy SM, Cleeman JI, Merz CNB, Brever HB, Clark LT, Hunninghake DB, Pasternak RC, et al. Implications of recent clinical trials for the national cholesterol education program adult treatment panel III guidelines. Circulation 2004; 110(2): 227-39.
- Berneis KK, Krauss RM. Metabolic origins and clinical significance of LDL heterogeneity. Journal of lipid research 2002; 43(9): 1363-79.
- Hirayama S, Miida T. Small dense LDL: an emerging risk factor for cardiovascular disease. Clinica Chimica Acta 2012; 414: 215-24.
- Bos M, Agyemang C. Prevalence and complications of diabetes mellitus in Northern Africa, a systematic review. BMC public health 2013; 13(1): 387-93.
- Haffner SM. Management of dyslipidemia in adults with diabetes. Diabetes care 1998; 21(1): 160-78.
- Colak C, Karaman E, Turtay MG. Application of knowledge discovery process on the prediction of stroke. Computer methods and programs in biomedicine 2015; 119(3): 181-85.
- Akgöbek Ö, Kaya S. Knowledge Discovery From Data Sets Through Data Mining Techniques: Application to Medical Data Mining. E-Journal of New World Sciences Academy 2011; 6(1): 237-45.
- Belard A, Buchman T, Forsberg J, Potter PK, Dente CJ, Kirk A, et al. Precision diagnosis: a view of the clinical decision support systems (CDSS) landscape through the lens of critical care. Journal of clinical monitoring and computing 2017; 31(2): 261-71.
- Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Bulletin of the World Health Organization 2007; 85: 867-72.
- Erdil N, Nisanoğlu V, Battaloğlu B, Cihan HB, Gülcan, Ö, Ege E, et al. Early Results of Surgıcal Treatment in Patıents with Left ventricular Aneurysm. Turkish J Thorac Cardiovasc Surg 2003; 11(4): 219-23.
- Arsenault BJ, Rana JS, Stroes ES, Despres JP, Shah PK, Kastelein JJP, et al. Beyond low-density lipoprotein cholesterol: respective contributions of non–high-density lipoprotein cholesterol levels, triglycerides, and the total cholesterol/high-density lipoprotein cholesterol ratio to coronary heart disease risk in apparently healthy men and women. Journal of the American College of Cardiology 2009; 55(1): 35-41.
- Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clinical chemistry 1972; 18(6): 499-502. 1972/06/01.
- Jun KR, Park H-i, Chun S, Park H, Min W-K. Effects of total cholesterol and triglyceride on the percentage difference between the low-density lipoprotein cholesterol concentration measured directly and calculated using the Friedewald formula. Clinical Chemical Laboratory Medicine 2008; 46(3): 371-75.
- Arslan A, Yasar S, Colak C, Yologlu S. WSSPAS: web-based sample size & power analysis software. J Turkiye Klinikleri J Biostatistics 2018; 3: 1-34.
- Chen H, Cohen P, Chen S. How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. J Communications in Statistics—Simulation Computation 2010; 39(4): 860-64.
- Tomczak M, Tomczak E. The need to report effect size estimates revisited. An overview of some recommended measures of effect size. Trends in Sport Sciences 2014; 21(1).
- Keskin B. Does Statistical Power Affect a Study’s Results? How Many Sample Size? Manisa Celal Bayar University Journal of Social Sciences 2020; 18: 157-74.
- Shiny R. Shiny. Web application framework for R 2018.
- Perrier V, Meyer F, Granjon D. shinyWidgets: Custom inputs widgets for Shiny. R package version 2019.
- Dumas J. shinyLP: Bootstrap Landing Home Pages for Shiny Applications. R package version 2019; 1: 2.
- Chang W, Park T, Dziedzic L, Willis N, McInerney M. shinythemes: Themes for Shiny. R package version 1.1. 2. 2018.
- Chang W, Ribeiro BB, Studio A, Chang MW. Package ‘shinydashboard’. 2022.
- TEMD Working Group. TEMD Dyslipidemia Diagnosis and Treatment Guideline. Turkish Society of Endocrinology and Metabolism, 2019.
- Zamora A, Masana L, Comas-Cufí M, et al. Familial hypercholesterolemia in a European Mediterranean population—Prevalence and clinical data from 2.5 million primary care patients. Journal of clinical lipidology 2017; 11(4): 1013-22.
- Mach F, Baigent C, Catapano AL, Koskinas KC, Badimon MCL, Chapman MJ, et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk: the Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS). European heart journal 2020; 41(1): 111-88.
- Petrie JR, Guzik TJ, Touyz RM. Diabetes, Hypertension, and Cardiovascular Disease: Clinical Insights and Vascular Mechanisms. Can J Cardiol 2018; 34(5): 575-84. 2017/12/11.
- Manninen V, Tenkanen L, Koskinen P, Huttunen, JK, Mänttäri M, Heinonen OP, et al. Joint effects of serum triglyceride and LDL cholesterol and HDL cholesterol concentrations on coronary heart disease risk in the Helsinki Heart Study. Implications for treatment. Circulation 1992; 85(1): 37-45. 1992/01/01.
Lipid Profilinin Hipertansiyon, Diabetes Mellitus ve Obezite ile Birlikte Gelen Koroner Arter Hastalığı Üzerindeki Tekli/Çoklu Etkilerinin Değerlendirilmesi
Öz
Amaç: Kardiyovasküler hastalıklar dünya genelindeki önde gelen ölüm/morbidite nedenleri arasında olmasına rağmen, eşlik eden hastalıklarla birlikte daha da önemlidirler. Bu çalışma, total kolesterol (TK), yüksek dansiteli lipoprotein-kolesterol (HDL-C), düşük dansiteli lipoprotein-kolesterol (LDL-C) ve trigliserit (TG)'nin hipertansiyon (HT), tip 2 diabetes mellitus (T2DM) ve obezite üzerindeki tekli/çoklu etkilerini ortaya çıkarmayı amaçlamaktadır.
Yöntem: Üniversitesi Tıp Merkezi … Kardiyovasküler Cerrahi Bölümü'nde koroner bypass cerrahisi geçiren koroner arter hastalarının kayıtlarından retrospektif olarak elde edilmiştir. Hipertansiyon, DM, obezite, TK, HDL-C, LDL-C ve TG değişkenlerine ilişkin veriler için tıbbi bilgi keşfi süreci (TBKS) uygulanmıştır. Lipid profillerinin optimal kesme noktalarını belirlemek için farklı yöntemler kullanılmıştır. Tekli/çoklu etkilerini belirlemek için lojistik regresyon analizi (LRA) lipid profilleri incelenmiştir.
Bulgular: Bu çalışmada belirlenen kesme noktalarına göre kategorize edilen TK, LDL-C, TG ve HDL-C lipid profilleri LRA modelleri ile analiz edilmiştir. HT'de LDL-C (>117 mg/dL)*TK (>191 mg/dL)*HDL-C (>37.2 mg/dL) ve T2DM'de TK (>190 mg/dL)*TG (>197 mg/dL)*HDL-C (>36.3 mg/dL) etkileşim terimleri orta etki büyüklüğüne sahipti. T2DM'de LDL-C (>115 mg/dL)*TG (>197 mg/dL)*HDL-C (>36.3 mg/dL) etkileşim terimleri ve obezitede TK (>192 mg/dL)*LDL-C (>117 mg/dL)*HDL-C (>36.8 mg/dL), TK (>192 mg/dL)*TG (>193 mg/dL)*HDL-C (>36.8 mg/dL) ve LDL-C (>117 mg/dL)*TG (>193 mg/dL)*HDL-C (>36.8 mg/dL) etkileşim terimleri yüksek etki büyüklüğü olarak rapor edilmiştir.
Sonuç: Sonuç olarak, HT, T2DM ve obeziteyi öngörmede lipid profilleri için bu çalışmada önerilen kesme noktalarını analiz eden bir yaklaşımın kullanılması önerilir.
Anahtar Kelimeler
Koroner arter hastalığı Risk faktörleri Lipitler Bilgi keşfi
Proje Numarası
218S744
Kaynakça
- Dülek H, Vural ZT, Gönenç I. Risk Factors in Cardiovascular Diseases. Jour Turk Fam Phy 2018; 9(2): 53-58.
- Aksoy DY, Gürlek A. Diabetes mellitus and primary healthcare. Journal of Clinical and Experimental Investigations 2004; 35: 123-26.
- Onat A, Uğur M, Çiçek G, Dogan Y, Kaya H, Can G. The Turkish Adult Risk Factor survey 2009: similar cardiovascular mortalityin rural and urban areas. Türk Kardiyol Dern Arş 2010; 38(3): 159-63.
- Abacı A. The current status of cardiovascular risk factors in Turkey. Turk Kardiyol Dern Ars 2011; 39(4): 1-5.
- Tekkeşin N, Kılınç C. Investigation of Framingham Risk Factors in Turkish adults. Journal of Clinical and Experimental Investigations 2011; 2(1): 42-49.
- Colak C, Colak MC, Orman MN. The comparison of logistic regression model selection methods for the prediction of coronary artery disease. Anadolu Kardiyol Derg 2007; 7(1): 6-12.
- Brown G, Albers JJ, Fisher LD, Schaefer SM, Lin JT, Kaplan C, et al. Regression of coronary artery disease as a result of intensive lipid-lowering therapy in men with high levels of apolipoprotein B. N Engl J Med 1990; 323(19): 1289-98.
- Perk J, De Backer G, Gohlke H, Graham I, Reiner Z, Verschuren M, et al. European Guidelines on cardiovascular disease prevention in clinical practice (version 2012) The Fifth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of nine societies and by invited experts) Developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). European heart journal 2012; 33(13): 1635-701.
- Grundy SM, Cleeman JI, Merz CNB, Brever HB, Clark LT, Hunninghake DB, Pasternak RC, et al. Implications of recent clinical trials for the national cholesterol education program adult treatment panel III guidelines. Circulation 2004; 110(2): 227-39.
- Berneis KK, Krauss RM. Metabolic origins and clinical significance of LDL heterogeneity. Journal of lipid research 2002; 43(9): 1363-79.
- Hirayama S, Miida T. Small dense LDL: an emerging risk factor for cardiovascular disease. Clinica Chimica Acta 2012; 414: 215-24.
- Bos M, Agyemang C. Prevalence and complications of diabetes mellitus in Northern Africa, a systematic review. BMC public health 2013; 13(1): 387-93.
- Haffner SM. Management of dyslipidemia in adults with diabetes. Diabetes care 1998; 21(1): 160-78.
- Colak C, Karaman E, Turtay MG. Application of knowledge discovery process on the prediction of stroke. Computer methods and programs in biomedicine 2015; 119(3): 181-85.
- Akgöbek Ö, Kaya S. Knowledge Discovery From Data Sets Through Data Mining Techniques: Application to Medical Data Mining. E-Journal of New World Sciences Academy 2011; 6(1): 237-45.
- Belard A, Buchman T, Forsberg J, Potter PK, Dente CJ, Kirk A, et al. Precision diagnosis: a view of the clinical decision support systems (CDSS) landscape through the lens of critical care. Journal of clinical monitoring and computing 2017; 31(2): 261-71.
- Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Bulletin of the World Health Organization 2007; 85: 867-72.
- Erdil N, Nisanoğlu V, Battaloğlu B, Cihan HB, Gülcan, Ö, Ege E, et al. Early Results of Surgıcal Treatment in Patıents with Left ventricular Aneurysm. Turkish J Thorac Cardiovasc Surg 2003; 11(4): 219-23.
- Arsenault BJ, Rana JS, Stroes ES, Despres JP, Shah PK, Kastelein JJP, et al. Beyond low-density lipoprotein cholesterol: respective contributions of non–high-density lipoprotein cholesterol levels, triglycerides, and the total cholesterol/high-density lipoprotein cholesterol ratio to coronary heart disease risk in apparently healthy men and women. Journal of the American College of Cardiology 2009; 55(1): 35-41.
- Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clinical chemistry 1972; 18(6): 499-502. 1972/06/01.
- Jun KR, Park H-i, Chun S, Park H, Min W-K. Effects of total cholesterol and triglyceride on the percentage difference between the low-density lipoprotein cholesterol concentration measured directly and calculated using the Friedewald formula. Clinical Chemical Laboratory Medicine 2008; 46(3): 371-75.
- Arslan A, Yasar S, Colak C, Yologlu S. WSSPAS: web-based sample size & power analysis software. J Turkiye Klinikleri J Biostatistics 2018; 3: 1-34.
- Chen H, Cohen P, Chen S. How big is a big odds ratio? Interpreting the magnitudes of odds ratios in epidemiological studies. J Communications in Statistics—Simulation Computation 2010; 39(4): 860-64.
- Tomczak M, Tomczak E. The need to report effect size estimates revisited. An overview of some recommended measures of effect size. Trends in Sport Sciences 2014; 21(1).
- Keskin B. Does Statistical Power Affect a Study’s Results? How Many Sample Size? Manisa Celal Bayar University Journal of Social Sciences 2020; 18: 157-74.
- Shiny R. Shiny. Web application framework for R 2018.
- Perrier V, Meyer F, Granjon D. shinyWidgets: Custom inputs widgets for Shiny. R package version 2019.
- Dumas J. shinyLP: Bootstrap Landing Home Pages for Shiny Applications. R package version 2019; 1: 2.
- Chang W, Park T, Dziedzic L, Willis N, McInerney M. shinythemes: Themes for Shiny. R package version 1.1. 2. 2018.
- Chang W, Ribeiro BB, Studio A, Chang MW. Package ‘shinydashboard’. 2022.
- TEMD Working Group. TEMD Dyslipidemia Diagnosis and Treatment Guideline. Turkish Society of Endocrinology and Metabolism, 2019.
- Zamora A, Masana L, Comas-Cufí M, et al. Familial hypercholesterolemia in a European Mediterranean population—Prevalence and clinical data from 2.5 million primary care patients. Journal of clinical lipidology 2017; 11(4): 1013-22.
- Mach F, Baigent C, Catapano AL, Koskinas KC, Badimon MCL, Chapman MJ, et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk: the Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS). European heart journal 2020; 41(1): 111-88.
- Petrie JR, Guzik TJ, Touyz RM. Diabetes, Hypertension, and Cardiovascular Disease: Clinical Insights and Vascular Mechanisms. Can J Cardiol 2018; 34(5): 575-84. 2017/12/11.
- Manninen V, Tenkanen L, Koskinen P, Huttunen, JK, Mänttäri M, Heinonen OP, et al. Joint effects of serum triglyceride and LDL cholesterol and HDL cholesterol concentrations on coronary heart disease risk in the Helsinki Heart Study. Implications for treatment. Circulation 1992; 85(1): 37-45. 1992/01/01.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Klinik Tıp Bilimleri (Diğer) |
| Bölüm | Orjinal makale |
| Yazarlar | |
| Proje Numarası | 218S744 |
| Yayımlanma Tarihi | 30 Nisan 2024 |
| Gönderilme Tarihi | 4 Ocak 2024 |
| Kabul Tarihi | 13 Nisan 2024 |
| Yayımlandığı Sayı | Yıl 2024 Cilt: 11 Sayı: 1 |
