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Supplemental Digital Content is available in the text., Background: A continuous relationship between reductions in low-density lipoprotein cholesterol (LDL-C) and major adverse cardiovascular events (MACE) has been observed in statin and ezetimibe outcomes trials down to achieved levels of 54 mg/dL. However, it is uncertain whether this relationship extends to LDL-C levels

Background: The majority of ODYSSEY Phase 3 clinical trials of the PCSK9 inhibitor alirocumab (ALI) utilized a dose increase strategy designed to individualize LDL-C lowering therapy. Objective: To describe dose response in patients on background statin whose ALI dose was increased from 75 to 150 mg every 2 wks (Q2W) at wk 12. Methods: This analysis included 6 Phase 3, randomized, double-blind, double-dummy trials of 24-104 wks duration (N=1291): ALI vs placebo (COMBO I, FH I+II) or vs ezetimibe 10 mg/day (COMBO II, OPTIONS I+II). Patients on background statin with an initial dose of ALI 75 mg Q2W had dose increase to 150 mg SQ Q2W at wk 12, if at wk 8 LDL-C was ≥70 mg/dL (or >100 mg/dl in OPTIONS studies for patients without prior CHD but other risk factors). LDL-C % reductions from baseline were compared at wk 12 (before dose increase) vs wk 24, including only patients receiving study treatment (on-treatment analysis). Results: Majority of FH and high-risk patients (73.7%) achieved LDL-C Conclusions: The 75 mg Q2W dose is sufficient for most patients to achieve risk-specific LDL-C goals. Increasing ALI dose from 75 to 150 mg Q2W at wk 12 was associated with a 14.2% additional reduction in LDL-C at wk 24, more than double the additional LDL-C reduction achieved by doubling a statin dose. The flexible dosing strategy allows the majority of patients to get to LDL-C goals without affecting the safety profile.

Background —Enhanced nocturnal heart rate variability (HRV) has been evoked in sleep-related breathing disorders. However, its capacity to detect obstructive sleep apnea syndrome (OSAS) has not been systematically determined. Thus, we evaluated the discriminant power of HRV parameters in a first group of patients (G1) and validated their discriminant capacity in a second group (G2). Methods and Results —In G1, 39 of 91 patients (42.8%) were identified as diseased by polysomnography, as were 24 of 52 patients (46%) in G2. Time-domain HRV variables (SD of NN intervals [SDNN], mean of the standard deviations of all NN intervals for all consecutive 5-minute segments of the recording [SDNN index], square root of the mean of the sum of the squares of differences between adjacent normal RR intervals [r-MSSD], and SD of the averages of NN intervals in all 5-minute segments of the recording [SDANN]) were calculated for daytime and nighttime periods, as well as the differences between daytime and nighttime values (Δ[D/N]). Correlations between HRV variables and OSAS status were analyzed in G1 by use of receiver-operating characteristic (ROC) curves and logistic regression analysis. By ROC curve analysis, 7 variables were significantly associated with OSAS. After adjustment for other variables through multiple logistic regression analysis, Δ[D/N]SDNN index and Δ[D/N] r-MSSD remained significant independent predictors of OSAS, with ORs of 8.22 (95% CI, 3.16 to 21.4) and 2.86 (95% CI, 1.21 to 6.75), respectively. The classification and regression tree methodology demonstrated a sensitivity reaching 89.7% (95% CI, 73.7 to 97.7) with Δ[D/N] SDNN index and a specificity of 98.1% (95% CI, 86.4 to 100) with Δ[D/N] SDNN using appropriate thresholds. These thresholds, applied to G2, yielded a sensitivity of 83% using Δ[D/N] SDNN index and a specificity of 96.5% using Δ[D/N] SDNN. Conclusions —Time-domain HRV analysis may represent an accurate and inexpensive screening tool in clinically suspected OSAS patients and may help focus resources on those at the highest risk.

Background The interpretation of exercise stress testing for coronary artery disease detection is affected by the many differences in chosen variables and mathematical methods. We conducted a prospective trial to evaluate a global muscle fatigue parameter—the blood lactate level achieved at maximal exercise—as a method of distinguishing between diseased and nondiseased coronary status. Methods and Results We evaluated 236 consecutive male patients without previous myocardial infarction who had been referred for the diagnosis of coronary artery disease. None of the patients had cardiomyopathy, severe cardiac heart failure, or valvular heart disease. Blood lactate concentration at maximal exercise was measured as well as other classic variables. Correlations between variables and coronary status as assessed by coronary arteriography were described using receiver operating characteristic (ROC) curves and logistic regression analysis. The first four most powerful variables (lactate level, maximal power output, exercise duration, and percentage of maximal predicted heart rate), which are directly representative of the global functional capacity, showed values of 0.777, 0.775, 0.760, and 0.740, respectively, by ROC curve analysis. Mean±SD blood lactate level at peak exercise reached 7.68±2.70 mmol/L in the 153 diseased and 10.56±2.75 mmol/L in the 83 nondiseased patients ( P Conclusions Global muscle fatigue as assessed by lactate levels in the blood at maximal exercise appears to be a powerful distinguisher of diseased and nondiseased coronary status.