For a long time, high-density lipoprotein cholesterol (HDL-C) has been regarded as a cardiovascular disease (CVD) protective factor. Recently, several epidemiological studies, while confirming low plasma levels of HDL-C as an established predictive biomarker for atherosclerotic CVD, indicated that not only people at the lowest levels but also those with high HDL-C levels are at increased risk of cardiovascular (CV) mortality. This “U-shaped” association has further fueled the discussion on the pathophysiological role of HDL in CVD. In fact, genetic studies, Mendelian randomization approaches, and clinical trials have challenged the notion of HDL-C levels being causally linked to CVD protection, independent of the cholesterol content in low-density lipoproteins (LDL-C). These findings have prompted a reconsideration of the biological functions of HDL that can be summarized with the word “HDL functionality”, a term that embraces the many reported biological activities beyond the so-called reverse cholesterol transport, to explain this lack of correlation between HDL levels and CVD. All these aspects are summarized and critically discussed in this review, in an attempt to provide a background scenario for the “HDL story”, a lipoprotein still in search of a role.

Chronic low-degree inflammation is a hallmark of atherosclerotic cardiovascular (CV) disease. To assess the effect of lipid-lowering therapies on C-reactive protein (CRP), a biomarker of inflammation, we conducted a meta-analysis according to the PRISMA guidelines. Databases were searched from inception to July 2023. Inclusion criteria were: (i) randomized controlled trials (RCTs) in human, Phase II, III, or IV; (ii) English language; (iii) comparing the effect of lipid-lowering drugs vs. placebo; (iv) reporting the effects on CRP levels; (v) with intervention duration of more than 3 weeks; (vi) and sample size (for both intervention and control group) over than 100 subjects. The between-group (treatment-placebo) CRP absolute mean differences and 95% confidence intervals were calculated for each drug class separately. A total of 171 668 subjects from 53 RCTs were included. CRP levels (mg/L) were significantly decreased by statins [−0.65 (−0.87 to −0.43), bempedoic acid; −0.43 (−0.67 to −0.20), ezetimibe; −0.28 (−0.48 to −0.08)], and omega-3 fatty acids [omega3FAs, −0.27 (−0.52 to −0.01)]. CRP was reduced by −0.40 (−1.17 to 0.38) with fibrates, although not statistically significant. A slight increase of CRP concentration was observed for proprotein convertase subtilisin/kexin type 9 inhibitors [0.11 (0.07–0.14)] and cholesteryl-ester transfer protein inhibitors [0.10 (0.00–0.21)], the latter being not statistically significant. Meta-regression analysis did not show a significant correlation between changes in CRP and LDL cholesterol (LDL-C) or triglycerides. Statins, bempedoic acid, ezetimibe, and omega3FAs significantly reduce serum CRP concentration, independently of LDL-C reductions. The impact of this anti-inflammatory effect in terms of CV prevention needs further investigation.

Polypharmacy, defined as the concurrent use of multiple medications, increases the risk of various adverse outcomes. However, the variability in definitions across the literature contributes to substantial heterogeneity. Building on the published literature, this study aimed to identify a set of operational definitions of polypharmacy applicable to administrative databases and to assess their association with all-cause hospitalization. Data from the pharmacy refill and hospitalization databases of the Local Health Unit (LHU) of Bergamo, Lombardy, were analyzed. Patients aged ≥40 with at least one reimbursed drug prescription in 2017 were included. Prescription coverage was evaluated using total defined daily doses (DDDs), and all-cause hospitalizations from January to June 2018 were considered. Definitions explored included (i) the WHO’s criterion of ≥5 medications by ATC fourth-level code; (ii) the exclusion of prescriptions usually for short-term treatments; and (iii) drugs with cumulative annual DDD ≥ 60. Approaches were assessed annually, quarterly, and monthly, and logistic regression was used to estimate odds ratios (ORs) for hospitalization risk. Among 431,620 patients, the DDD ≥ 60 definition showed the least variability (20.47–21.16%) and identified an older more complex cohort. All definitions showed a dose-dependent association with hospitalization risk. Different definitions of polypharmacy result in varying prevalence, with DDD ≥ 60 being the most consistent. A patient-centric approach is crucial to assess the appropriateness of polypharmacy.

We conducted a meta-analysis to compare the lipid-lowering effects of fibratesLiterature was searched up to December 2024. Absolute changes in triglycerides (TG), LDL-cholesterol (LDL‑C), apolipoprotein B (ApoB), and non-HDL cholesterol (non-HDL-C) were analyzed using both fixed and random effects models. We included 63 randomized controlled trials. Compared to placebo, all fibrates significantly reduced TG levels. Fenofibrate and bezafibrate significantly reduced LDL-C (–15.12 and –15.04 mg/dL, respectively), while only fenofibrate significantly lowered ApoB (–24.88 mg/dL) and non-HDL-C (–46.38 mg/dL), followed by gemfibrozil and pemafibrate for non-HDL-C. In combination with statins, no fibrates significantly reduced LDL-C, while fenofibrate remained the only fibrate to significantly lower ApoB (–10.42 mg/dL) and non-HDL-C (–12.02 mg/dL). Overall, we found that fibrates differ substantially in their lipid effects. Fenofibrate shows the most consistent and comprehensive lipid-lowering profile.

Background: Lipoprotein(a) [Lp(a)] is a relatively new but underutilized biomarker in the context of atherosclerotic cardiovascular disease (ASCVD). Objectives: To explore the clinical implementation of Lp(a) measurement and current practices in hospital and specialised settings in Italy. Methods: An anonymous online questionnaire was distributed to Italian physicians to examine the habits of Italian clinicians regarding Lp(a) measurement. The survey covered three topics: 1) information on the clinical setting of the physicians, 2) questions for physicians who reported not measuring Lp(a), to understand the reasons for not requesting the test, and 3) questions for physicians who measure Lp(a), to investigate its use in patient management. Results: A total of 978 responses were received. Overall, 63.1% of physicians reported working in a hospital; 12.2% reported being a territorial specialist. Regular Lp(a) measurement was reported by 32.1% of clinicians. Among those who do not measure Lp(a), the main barriers to implementation include high cost and limited availability of the test. The threshold value for defining elevated Lp(a) levels varies significantly among professionals, with 36.7% considering levels above 30 mg/dL to be elevated and 32.7% considering levels above 50 mg/dL to be elevated. Clinical management of patients with elevated Lp(a) primarily includes intensification of lipid-lowering therapy (69.2%), management of cardiovascular risk factors (48.7%), and lifestyle recommendations (37.4%). Conclusions: The survey highlights the heterogeneity in the approach to managing elevated Lp(a) levels among Italian clinicians, underscoring the importance of clear guidelines and greater accessibility to the test to optimize cardiovascular risk stratification and improve clinical outcomes.