Lipid-Lowering Therapy in Patients with Coronary Heart Disease and Prior Stroke: Mission Impossible?

Prevalence of chronic diabetic complications and associated risk factors among follow-up diabetic patients: estimates from a referral national diabetes center in Yemen

BACKGROUND

Emergence and progression of diabetic complications are associated with several risk factors. Identifying these risk factors related to diabetes helps avoid such complications and develop preventive measures to protect patients and improve their quality of life. This study aimed to estimate the prevalence of chronic complications among Yemeni diabetic patients and investigate the associations between these complications, sociodemographic characteristics, and diabetic risk factors.

METHODS

This cross-sectional study was conducted at the National Diabetic Referral Center in Sana'a, Yemen, from September 1 to October 30, 2023. Of the 228 respondents, 222 were considered valid for analysis. Data for this study were collected using the World Health Organization (WHO) STEPS Surveillance questionnaire and a simple physical assessment. IBM SPSS version 24.0 was utilized to manage and analyze the data. Descriptive statistics were used to determine the prevalence of diabetes complications. The chi-square test and binary logistic regression were used to determine the associations and risk factors. A p-value of less than 0.05 was used to determine statistical significance.

RESULTS

Diabetes-related complications were reported by 62.6% of respondents, with females having a greater risk of diabetic foot, nephropathy, and retinopathy, while males had an increased risk of neuropathy complications. Unemployment, obesity, non-adherence to diabetes regimens, uncontrolled hypertension, longer duration of type 1 diabetes (T1DM), and irregular physician check-ups were identified as key predictors of diabetes-related complications. Administration of statins as lipid-lowering medications was associated with a reduced risk of coronary artery disease (CAD) or ischemic stroke complications.

CONCLUSION

Chronic complications related to diabetes were common among patients in Yemen. Factors such as unemployment, obesity, non-adherence to diabetes regimens, uncontrolled hypertension, longer duration of T1DM, and irregular physician check-ups were identified as key predictors of these complications. Implementation of the WHO non-communicable disease package is strongly recommended. This package comprises comprehensive measures aimed at detecting, treating, preventing, and controlling diabetic complications and ultimately improving the overall management of diabetes in Yemen.

CLINICAL TRIAL NUMBER

Not applicable.

Development and validation of risk prediction model for recurrent cardiovascular events among Chinese: the Personalized CARdiovascular DIsease risk Assessment for Chinese model

Aims

Cardiovascular disease (CVD) is a leading cause of mortality, especially in developing countries. This study aimed to develop and validate a CVD risk prediction model, Personalized CARdiovascular DIsease risk Assessment for Chinese (P-CARDIAC), for recurrent cardiovascular events using machine learning technique.

Methods and results

Three cohorts of Chinese patients with established CVD were included if they had used any of the public healthcare services provided by the Hong Kong Hospital Authority (HA) since 2004 and categorized by their geographical locations. The 10-year CVD outcome was a composite of diagnostic or procedure codes with specific International Classification of Diseases, Ninth Revision, Clinical Modification. Multivariate imputation with chained equations and XGBoost were applied for the model development. The comparison with Thrombolysis in Myocardial Infarction Risk Score for Secondary Prevention (TRS-2°P) and Secondary Manifestations of ARTerial disease (SMART2) used the validation cohorts with 1000 bootstrap replicates. A total of 48 799, 119 672 and 140 533 patients were included in the derivation and validation cohorts, respectively. A list of 125 risk variables were used to make predictions on CVD risk, of which 8 classes of CVD-related drugs were considered interactive covariates. Model performance in the derivation cohort showed satisfying discrimination and calibration with a C statistic of 0.69. Internal validation showed good discrimination and calibration performance with C statistic over 0.6. The P-CARDIAC also showed better performance than TRS-2°P and SMART2.

Conclusion

Compared with other risk scores, the P-CARDIAC enables to identify unique patterns of Chinese patients with established CVD. We anticipate that the P-CARDIAC can be applied in various settings to prevent recurrent CVD events, thus reducing the related healthcare burden.

Unveiling differential mechanisms of chuanxiong cortex and pith in the treatment of coronary heart disease using SPME-GC×GC-MS and network pharmacology

Ligusticum chuanxiong Hort (LCH) is a well-known traditional Chinese medicinal herb for treating coronary heart disease (CHD). This study investigated the differential preventive mechanisms of Rhizome Cortex (RC) and Rhizome Pith (RP) of LCH. Solid-phase microextraction combined with comprehensive two-dimensional gas chromatography-tandem mass spectrometry analysis identified 32 differential components, and network pharmacology revealed 11 active ingredients and 191 gene targets in RC, along with 12 active ingredients and 318 gene targets in RP. Primary active ingredients in RC were carotol, epicubenol, fenipentol, and methylisoeugenol acetate, while 3-undecanone, (E)- 5-decen-1-ol acetate, linalyl acetate, and (E)- 2-Methoxy-4-(prop-1-enyl) phenol were dominant in RP. KEGG mapping analysis associated 27 pathways with RC targets and 116 pathways with RP targets. Molecular docking confirmed the efficient activation of corresponding targets by these active ingredients. This study provides valuable insights into the preventive and therapeutic effects of RC and RP in CHD.

Exploring the Mechanism of Hawthorn Leaves Against Coronary Heart Disease Using Network Pharmacology and Molecular Docking

Hawthorn leaves, which is a traditional Chinese medicine (TCM), has been used for treating coronary heart disease (CHD) for a long time in China. But the limited understanding of the main active components and molecular mechanisms of this traditional medicine has restricted its application and further research. The active compounds of hawthorn leaves were obtained from TCMSP database and SymMap database. The targets of it were predicted based on TCMSP, PubChem, Swiss Target Prediction, and SymMap database. The putative targets of CHD were gathered from multi-sources databases including the Online Mendelian Inheritance in Man (OMIM) database, the DrugBank database, the GeneCards database and the DisGeNet database. Network topology analysis, GO and KEGG pathway enrichment analyses were performed to select the key targets and pathways. Molecular docking was performed to demonstrate the binding capacity of the key compounds to the predicted targets. Furthermore, RAW264.7 cells stimulated by lipopolysaccharides (LPS) were treated with three effective compounds of hawthorn leaves to assess reliability of prediction. Quercetin, isorhamnetin and kaempferol were main active compounds in hawthorn leaves. Forty four candidate therapeutic targets were identified to be involved in protection of hawthorn leaves against CHD. Additionally, the effective compounds of it had good binding affinities to PTGS2, EGFR, and MMP2. Enrichment analyses suggested that immune inflammation related biological processes and pathways were possibly the potential mechanism. Besides, we found that three predicted effective compounds of hawthorn leaves decreased protein expression of PTGS2, MMP2, MMP9, IL6, IL1B, TNFα and inhibited activation of macrophage. In summary, the present study demonstrates that quercetin, kaempferol and isorhamnetin are proved to be the main effective compounds of hawthorn leaves in treatment of CHD, possibly by suppressing expression of PTGS2, MMP2, MMP9, inflammatory cytokines and macrophages viability. This study provides a new understanding of the active components and mechanisms of hawthorn leaves treating CHD from the perspective of network pharmacology.

Current and Developing Liquid Biopsy Techniques for Breast Cancer

Breast cancer is the most commonly diagnosed cancer and leading cause of cancer mortality among woman worldwide. The techniques of diagnosis, prognosis, and therapy monitoring of breast cancer are critical. Current diagnostic techniques are mammography and tissue biopsy; however, they have limitations. With the development of novel techniques, such as personalized medicine and genetic profiling, liquid biopsy is emerging as the less invasive tool for diagnosing and monitoring breast cancer. Liquid biopsy is performed by sampling biofluids and extracting tumor components, such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), cell-free mRNA (cfRNA) and microRNA (miRNA), proteins, and extracellular vehicles (EVs). In this review, we summarize and focus on the recent discoveries of tumor components and biomarkers applied in liquid biopsy and novel development of detection techniques, such as surface-enhanced Raman spectroscopy (SERS) and microfluidic devices.