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.
TÜBİTAK
218S744
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.
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.
218S744
Primary Language | English |
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Subjects | Clinical Sciences (Other) |
Journal Section | Original Articles |
Authors | |
Project Number | 218S744 |
Publication Date | April 30, 2024 |
Submission Date | January 4, 2024 |
Acceptance Date | April 13, 2024 |
Published in Issue | Year 2024 Volume: 11 Issue: 1 |