Statins for hemodialysis patients with diabetes? Long-term follow-up endorses the original conclusions of the 4D Study

The prevalence of dyslipidemia in patients on hemodialysis: a cross-sectional study from Syria

Dyslipidemia is an established risk factor for cardiovascular disease (CVD), which is the main cause of mortality among haemodialysis (HD) patients. We investigate the prevalence and characteristics of dyslipidemia in HD patients. Also, we aimed to study the prediction scores; Framingham risk score (FRS), and the atherosclerotic cardiovascular disease risk score; among this population.

METHODS

One hundred fifty-three HD patients were enroled in this retrospective cross-sectional study from two HD centres in Syria, from March 2021 to March 2022. Dyslipidemia is considered as follows; hyper-total cholesterol (TC) (≥200 mg/dl), hyper-triglycerides (TG), (≥150 mg/dl), hyper-low-density lipoprotein (LDL) (≥100 mg/dl), hypo-high-density lipoprotein (HDL) (<40 mg/dl), hyper-Non-HDL (≥130 mg/dl).

RESULTS

The most prevalent dyslipidemic parameter was low HDL (72.50%) followed by increased TGs (37.30%). TC, LDL, HDL, and Non-HDL showed differences between males and females (P=0.001, 0.015, 0.024, and 0.025; respectively). These parameters were higher in females. History of CVD showed associations with TC, LDL, HDL, and non-HDL (P=0.003, 0.007, 0.004, and 0.004; respectively). Additionally, statins showed effects on TC, LDL, and non-HDL (P=0.003, 0.0002, and 0.002; respectively); however, no relation with TG and HDL (P=0.9 and 0.4). HDL level showed differences in low (7.5%) and intermediate (10%) FRS (P=0.01 and 0.028; respectively); however, it did not show a difference in high (20%) FRS (P=0.68). The lipids profile did not show differences in different thresholds of atherosclerotic cardiovascular disease scores.

CONCLUSION

The prevalence of dyslipidemia was high in HD patients in Syria. All lipid parameters except TG showed differences between males and females. Comparisons of lipid parameters with CVD risk stratifications support the need for further studies to prove the benefits of these scores in CVD prediction among the dialysis population.

A scoring system for predicting individual treatment effects of statins in type 2 diabetes patients on haemodialysis

AIMS

Haemodialysis patients have high cardiovascular disease risk. Although statins reduce this risk in chronic kidney disease, randomised trials in haemodialysis patients show no benefit. Post-hoc analyses of the German Diabetes Dialysis (4D) study identified patient-specific markers associated with heterogeneous treatment effects. We combined these markers to develop a score for predicting individual effects of statins in these patients.

METHODS AND RESULTS

We used data from the 4D study, enrolling 1255 haemodialysis patients with type 2 diabetes mellitus, randomised to atorvastatin or placebo and followed for a composite cardiovascular endpoint. We calculated two scores: score 1 based on all 23 predictive markers and score 2 based on 17 clinically accessible markers. Groups stratified by score 1 showed differential treatment effects: for score <26 (458 patients; 36%), the hazard ratio (95% confidence interval) was 1.54 (1.16-2.03), suggesting harm; for 26-31 (331 patients; 26%), it was 1.03 (0.72-1.48), suggesting a neutral effect; and for >31 (466 patients; 38%), it was 0.43 (0.30-0.60), suggesting a benefit. Statins also significantly reduced all-cause mortality in the benefit group. Stratification by score 2 yielded similar results but a smaller group gaining benefit (360 patients).

CONCLUSION

Statin effects in haemodialysis patients can be predicted by markers associated with plausible relevant mechanisms including cholesterol metabolism, atherosclerosis, protein energy wasting, or competing risks. In clinical practice, the score could aid in risk stratification, not only to select patients who benefit from statins but also to identify those whom treatment could harm.

Acute Coronary Syndromes in Chronic Kidney Disease: Clinical and Therapeutic Characteristics

Background and Objectives: This study evaluated the clinical characteristics of the acute coronary syndromes (ACS) in chronic kidney disease (CKD) patients and established prognostic values of the biomarkers and echocardiography. Materials and Methods: 273 patients admitted to the cardiology department of the Clinical County Emergency Hospital of Oradea, Romania, with ACS diagnosis were studied. Two study groups were formed according to the presence of CKD (137 patients with ACS + CKD and 136 with ACS without CKD). Kidney Disease: Improving Global Outcomes (KDIGO) threshold was used to assess the stages of CKD. Results: Data regarding the medical history, laboratory findings, biomarkers, echocardiography, and coronary angiography were analysed for both groups. ACS parameters were represented by ST-segment elevation myocardial infarction (STEMI), which revealed a greater incidence in subjects without CKD (43.88%); non-ST-segment elevation myocardial infarction (NSTEMI), characteristic for the CKD group (28.47%, with statistically significance p = 0.04); unstable angina and myocardial infarction with nonobstructive coronary arteries (MINOCA). Diabetes mellitus, chronic heart failure, previous stroke, and chronic coronary syndrome were more prevalent in the ACS + CKD group (56.93%, p < 0.01; 41.61%, p < 0.01; 18.25%, p < 0.01; 45.26%, p < 0.01). N-terminal pro b-type natriuretic peptide (NT-proBNP) was statistically higher (p < 0.01) in patients with CKD; Killip class 3 was evidenced more frequently in the same group (p < 0.01). Single-vessel coronary artery disease (CAD) was statistically more frequent in the ACS without CKD group (29.41%, p < 0.01) and three-vessel CAD or left main coronary artery disease (LMCA) were found more often in the ACS + CKD group (27.01%, 14.6%). Conclusions: Extension of the CAD in CKD subjects revealed an increased prevalence of the proximal CAD, and the involvement of various coronary arteries is characteristic in these patients. Biomarkers and echocardiographic elements can outline the evolution and outcomes of ACS in CKD patients.