Optimal linear ensemble of binary classifiers.

Motivation: The integration of vast, complex biological data with computational models offers profound insights and predictive accuracy. Yet, such models face challenges: poor generalization and limited labeled data. Results: To overcome these difficulties in binary classification tasks, we developed the Method for Optimal Classification by Aggregation (MOCA) algorithm, which addresses the problem of generalization by virtue of being an ensemble learning method and can be used in problems with limited or no labeled data. We developed both an unsupervised (uMOCA) and a supervised (sMOCA) variant of MOCA. For uMOCA, we show how to infer the MOCA weights in an unsupervised way, which are optimal under the assumption of class-conditioned independent classifier predictions. When it is possible to use labels, sMOCA uses empirically computed MOCA weights. We demonstrate the performance of uMOCA and sMOCA using simulated data as well as actual data previously used in Dialogue on Reverse Engineering and Methods (DREAM) challenges. We also propose an application of sMOCA for transfer learning where we use pre-trained computational models from a domain where labeled data are abundant and apply them to a different domain with less abundant labeled data. Availability and implementation: GitHub repository, https://github.com/robert-vogel/moca.

Automated Spot Counting in Microbiology.

Biological samples are routinely analyzed for microbe concentration. The samples are diluted, loaded onto established host cell cultures, and incubated. If infectious agents are present in the samples, they form circular spots that do not contain the host cells. Each spot is assumed to be originated from a single microbial unit such as a bacterial colony forming unit or viral plaque forming unit. The undiluted sample concentration is estimated by counting the spots and back-calculating. Counting the number of spots by trained technicians is currently the gold standard but it is laborious, subjective, and hard to scale. This paper presents a new automated algorithm for spot counting, Localized and Sequential Thresholding (LoST). Validation studies showed that LoST performance was comparable with manual counting and outperformed several existing tools on images with overlapping spots. The LoST algorithm employs sequential thresholding through a two-stage segmentation and borrows information across all images from the same dilution series to fine-tune the count and identify right censoring. The algorithm increases the efficiency of the spot counting and the quality of the downstream analysis, especially when coupled with an appropriate statistical serial dilution model to enhance the undiluted sample concentration estimation procedure.

Di-fluoro azepane HBV capsid assembly modulators.

The protein that forms the inner shell of the HBV virus, known as the capsid core protein, plays a crucial role in allowing chronic HBV infections to persist. Studies have shown that disrupting the assembly of the capsid can effectively combat the virus, and small molecule drugs that target the HBV capsid assembly modulator (CAM) process have been successful in clinical trials. Herein is described a distinct series of di-fluoro azepane CAMs with exceptional potency, pharmacokinetic, and solubility properties.

Physicochemical characterization and quantification of nanoplastics: applicability, limitations and complementarity of batch and fractionation methods.

A comprehensive physicochemical characterization of heterogeneous nanoplastic (NPL) samples remains an analytical challenge requiring a combination of orthogonal measurement techniques to improve the accuracy and robustness of the results. Here, batch methods, including dynamic light scattering (DLS), nanoparticle tracking analysis (NTA), tunable resistive pulse sensing (TRPS), transmission electron microscopy (TEM), and scanning electron microscopy (SEM), as well as separation/fractionation methods such as centrifugal liquid sedimentation (CLS) and field-flow fractionation (FFF)-multi-angle light scattering (MALS) combined with pyrolysis gas chromatography mass spectrometry (pyGC-MS) or Raman microspectroscopy (RM) were evaluated for NPL size, shape, and chemical composition measurements and for quantification. A set of representative/test particles of different chemical natures, including (i) polydisperse polyethylene (PE), (ii) (doped) polystyrene (PS) NPLs, (iii) titanium dioxide, and (iv) iron oxide nanoparticles (spherical and elongated), was used to assess the applicability and limitations of the selected methodologies. Particle sizes and number-based concentrations obtained by orthogonal batch methods (DLS, NTA, TRPS) were comparable for monodisperse spherical samples, while higher deviations were observed for polydisperse, agglomerated samples and for non-spherical particles, especially for light scattering methods. CLS and TRPS offer further insight with increased size resolution, while detailed morphological information can be derived by electron microscopy (EM)-based approaches. Combined techniques such as FFF coupled to MALS and RM can provide complementary information on physical and chemical properties by online measurements, while pyGC-MS analysis of FFF fractions can be used for the identification of polymer particles (vs. inorganic particles) and for their offline (semi)quantification. However, NPL analysis in complex samples will continue to present a serious challenge for the evaluated techniques without significant improvements in sample preparation.

Establishment of minimally invasive ventral hernia repair with extraperitoneal mesh placement in a primary care hospital using the robotic platform.

Background: The progressive availability of robotic surgical systems opens new perspectives in abdominal wall surgery due to excellent visibility and dexterity of instruments. While complex hernias until today were treated primarily through an open access, we evaluated if this promising technology is suitable for treating the entire spectrum of a hernia center, including complex hernias. Material/methods: In 2017, minimally invasive hernia surgery with extraperitoneal mesh placement was started in Kempten hospital. Since 2019, a Da Vinci X system has been available for this purpose. In order to observe the process of transition we retrospectively analyzed all patients who underwent ventral hernia repair in the department of general and visceral surgery at our hospital between January 2016 and December 2020 and were indicated for mesh implantation. Results: In 2016, the percentage of minimally invasive procedures was 37.3%. In all of these cases an intraperitoneal mesh was implanted into the abdominal cavity. Open surgery was performed in 62.7%, of which an a retromuscular mesh was implanted in 75.7%, an intraperitoneal mesh in 21.6%, and an onlay mesh in 2.7%. In 2020, minimally invasive surgery accounted for 87.5%, of which 85.7% were performed robotically and 14.3 laparoscopically. In 94.3% of these minimally invasively treated patients the mesh was implanted in extraperitoneal position (75.8% in retromuscular and 24.2% in preperitoneal position). The percentage of complex hernias increased from 20.3% to 35.0% during the same period. Conclusion: The majority of ventral hernia procedures can be performed safely using the robot in a minimally invasive technique with extraperitoneal mesh placement without leading to an increase in complications. Robotically-assisted hernia repair is a promising new technique that is also practical for complex hernias.

Diazepinone HBV capsid assembly modulators.

The HBV capsid core protein serves a number of important functions in the viral life cycle enabling chronic HBV infection to persist, and therefore is a promising drug target. Interfering with capsid assembly has shown efficacy in clinical trials with small molecule capsid assembly modulators (CAMs). Herein is described the further optimization of a progressive series of diazepinone HBV CAMs.

Multi-physics study of acoustofluidic delivery agents' clustering behavior.

Acoustofluidicly manipulated microbubbles (MBs) and echogenic liposomes (ELIPs) have been suggested as drug delivery systems for the 'on demand' release of drug in target tissue. This requires a clear understanding of their behaviour during ultrasonication and after ultrasonication stops. The main focus of this study is to investigate the behaviour of MBs and ELIPs clusters after ultrasonication stops and the underlaying cause of cluster diffusion considering electrostatic repulsion, steric repulsion and Brownian motion. It also examines the capability of existing models used to predict MBs' attraction velocity due to secondary radiation force, on predicting ELIPs' attraction velocity. Tunable resistive pulse sensing (TRPS) and phase analysis light scattering (PALS) techniques were used to measure zeta potentials of the agents and the size distributions were measured using TRPS. The zeta potentials were found to be -2.43 mV and -0.62 mV for Definity™ MBs, and -3.62 mV and -2.35 mV for ELIPs using TRPS and PALS, respectively. Both agents were shown to have significant cluster formation at pressures as low as 6 kPa. Clusters of both agents were shown to diffuse as sonication stops at a rate that approximately equals the sum of the diffusion coefficients of the agents forming them. The de-clustering behaviours are due to Brownian motion as no sign of electrostatic repulsion was observed and particles movements were observed to be faster for smaller diameters. These findings are important to design and optimise effective drug delivery systems using acoustofluidically manipulated MBs and ELIPs.

Oxadiazepinone HBV capsid assembly modulators.

The HBV core protein serves multiple essential functions in the viral life cycle that enable chronic HBV infection to persist, and as such, represents a promising drug target. Modulation of the HBV capsid assembly has shown efficacy in early clinical trials through use of small molecule capsid assembly modulators (CAMs). Herein is described the evolution and SAR of a novel pyrazolo piperidine lead series into advanced oxadiazepinone HBV CAMs.

The Fermi-Dirac distribution provides a calibrated probabilistic output for binary classifiers.

Binary classification is one of the central problems in machine-learning research and, as such, investigations of its general statistical properties are of interest. We studied the ranking statistics of items in binary classification problems and observed that there is a formal and surprising relationship between the probability of a sample belonging to one of the two classes and the Fermi-Dirac distribution determining the probability that a fermion occupies a given single-particle quantum state in a physical system of noninteracting fermions. Using this equivalence, it is possible to compute a calibrated probabilistic output for binary classifiers. We show that the area under the receiver operating characteristics curve (AUC) in a classification problem is related to the temperature of an equivalent physical system. In a similar manner, the optimal decision threshold between the two classes is associated with the chemical potential of an equivalent physical system. Using our framework, we also derive a closed-form expression to calculate the variance for the AUC of a classifier. Finally, we introduce FiDEL (Fermi-Dirac-based ensemble learning), an ensemble learning algorithm that uses the calibrated nature of the classifier's output probability to combine possibly very different classifiers.

Robotically assisted enhanced-view totally extraperitoneal repair (eTEP) of a recurrent umbilical hernia in a patient with peritoneal dialysis.

Background: Abdominal wall hernias are frequent in patients with peritoneal dialysis. Guidelines recommend an open hernia repair with extraperitoneal mesh placement to avoid access to the abdominal cavity. Method: We performed a lateral docking robotically assisted enhanced-view totally extraperitoneal repair (eTEP) of a recurrent umbilical hernia with diastasis recti in a patient with peritoneal dialysis due to polycystic kidney disease. After suturing of the midline a 20 x 28 cm mesh was placed in the retrorectus space, covering the whole area of preparation while also overlapping all trocar sites. A drainage was left in the retrorectus space until the first session of PD did not sample any form of leakage. Result: Robotically assisted totally extraperitoneal hernia repair was feasible. The patient was able to continue peritoneal dialysis without intermittent hemodialysis. There was no leakage of the dialysate to the retrorectus space. Postoperative recovery was uneventful. 6 months after surgery the patient was free from pain and showed no signs of recurrence. Conclusion: Robotically assisted totally extraperitoneal hernia repair in patients with umbilical hernia and peritoneal dialysis could be a promising surgical technique to combine the advantages of minimally-invasive surgery with totally extraperitoneal mesh placement without access to the abdominal cavity.

Identification of a new class of HBV capsid assembly modulator.

The HBV core protein is a druggable target of interest due to the multiple essential functions in the HBV life cycle to enable chronic HBV infection. The core protein oligomerizes to form the viral capsid, and modulation of the HBV capsid assembly has shown efficacy in clinical trials. Herein is described the identification and hit to lead SAR of a novel series of pyrazolo piperidine HBV capsid assembly modulators.

Shell properties and concentration stability of acoustofluidic delivery agents.

This paper investigates the shell elastic properties and the number-concentration stability of a new acoustofluidic delivery agent liposome in comparison to Definity™, a monolayer ultrasonic contrast agent microbubble. The frequency dependent attenuation of an acoustic beam passing through a microbubble suspension was measured to estimate the shell parameters. The excitation voltage was adjusted to ensure constant acoustic pressure at all frequencies. The pressure was kept at the lowest possible magnitude to ensure that effects from nonlinear bubble behaviour which are not considered in the analytical model were minimal. The acoustofluidic delivery agent shell stiffness Sp and friction Sf parameters were determined as (Sp = 0.11 N/m, Sf = 0.31 × 10-6 Kg/s at 25 °C) in comparison to the Definity™ monolayer ultrasound contrast agent which were (Sp = 1.53 N/m, Sf = 1.51 × 10-6 Kg/s at 25 °C). When the temperature was raised to physiological levels, the friction coefficient Sf decreased by 28% for the monolayer microbubbles and by only 9% for the liposomes. The stiffness parameter Sp of the monolayer microbubble decreased by 23% while the stiffness parameter of the liposome increased by a similar margin (27%) when the temperature was raised to 37 °C. The size distribution of the bubbles was measured using Tunable Resistive Pulse Sensing (TRPS) for freshly prepared microbubbles and for bubble solutions at 6 h and 24 h after activation to investigate their number-concentration stability profile. The liposome maintained >80% of their number-concentration for 24 h at physiological temperature, while the monolayer microbubbles maintained only 27% of their number-concentration over the same period. These results are important input parameters for the design of effective acoustofluidic delivery systems using the new liposomes.

Measuring particle concentration of multimodal synthetic reference materials and extracellular vesicles with orthogonal techniques: Who is up to the challenge?

The measurement of physicochemical properties of polydisperse complex biological samples, for example, extracellular vesicles, is critical to assess their quality, for example, resulting from their production and isolation methods. The community is gradually becoming aware of the need to combine multiple orthogonal techniques to perform a robust characterization of complex biological samples. Three pillars of critical quality attribute characterization of EVs are sizing, concentration measurement and phenotyping. The repeatable measurement of vesicle concentration is one of the key-challenges that requires further efforts, in order to obtain comparable results by using different techniques and assure reproducibility. In this study, the performance of measuring the concentration of particles in the size range of 50-300 nm with complementary techniques is thoroughly investigated in a step-by step approach of incremental complexity. The six applied techniques include multi-angle dynamic light scattering (MADLS), asymmetric flow field flow fractionation coupled with multi-angle light scattering (AF4-MALS), centrifugal liquid sedimentation (CLS), nanoparticle tracking analysis (NTA), tunable resistive pulse sensing (TRPS), and high-sensitivity nano flow cytometry (nFCM). To achieve comparability, monomodal samples and complex polystyrene mixtures were used as particles of metrological interest, in order to check the suitability of each technique in the size and concentration range of interest, and to develop reliable post-processing data protocols for the analysis. Subsequent complexity was introduced by testing liposomes as validation of the developed approaches with a known sample of physicochemical properties closer to EVs. Finally, the vesicles in EV containing plasma samples were analysed with all the tested techniques. The results presented here aim to shed some light into the requirements for the complex characterization of biological samples, as this is a critical need for quality assurance by the EV and regulatory community. Such efforts go with the view to contribute to both, set-up reproducible and reliable characterization protocols, and comply with the Minimal Information for Studies of Extracellular Vesicles (MISEV) requirements.

Lipoprotein(a) lowering by alirocumab reduces the total burden of cardiovascular events independent of low-density lipoprotein cholesterol lowering: ODYSSEY OUTCOMES trial.

AIMS: Lipoprotein(a) concentration is associated with first cardiovascular events in clinical trials. It is unknown if this relationship holds for total (first and subsequent) events. In the ODYSSEY OUTCOMES trial in patients with recent acute coronary syndrome (ACS), the proprotein convertase subtilisin/kexin type 9 inhibitor alirocumab reduced lipoprotein(a), low-density lipoprotein cholesterol (LDL-C), and cardiovascular events compared with placebo. This post hoc analysis determined whether baseline levels and alirocumab-induced changes in lipoprotein(a) and LDL-C [corrected for lipoprotein(a) cholesterol] independently predicted total cardiovascular events. METHODS AND RESULTS: Cardiovascular events included cardiovascular death, non-fatal myocardial infarction, stroke, hospitalization for unstable angina or heart failure, ischaemia-driven coronary revascularization, peripheral artery disease events, and venous thromboembolism. Proportional hazards models estimated relationships between baseline lipoprotein(a) and total cardiovascular events in the placebo group, effects of alirocumab treatment on total cardiovascular events by baseline lipoprotein(a), and relationships between lipoprotein(a) reduction with alirocumab and subsequent risk of total cardiovascular events. Baseline lipoprotein(a) predicted total cardiovascular events with placebo, while higher baseline lipoprotein(a) levels were associated with greater reduction in total cardiovascular events with alirocumab (hazard ratio Ptrend = 0.045). Alirocumab-induced reductions in lipoprotein(a) (median -5.0 [-13.6, 0] mg/dL) and corrected LDL-C (median -51.3 [-67.1, -34.0] mg/dL) independently predicted lower risk of total cardiovascular events. Each 5-mg/dL reduction in lipoprotein(a) predicted a 2.5% relative reduction in cardiovascular events. CONCLUSION: Baseline lipoprotein(a) predicted the risk of total cardiovascular events and risk reduction by alirocumab. Lipoprotein(a) lowering contributed independently to cardiovascular event reduction, supporting the concept of lipoprotein(a) as a treatment target after ACS.

Long-term exposure to particulate air pollution and brachial artery flow-mediated dilation in the Old Order Amish.

BACKGROUND: Atmospheric particulate matter (PM) has been associated with endothelial dysfunction, an early marker of cardiovascular risk. Our aim was to extend this research to a genetically homogenous, geographically stable rural population using location-specific moving-average air pollution exposure estimates indexed to the date of endothelial function measurement. METHODS: We measured endothelial function using brachial artery flow-mediated dilation (FMD) in 615 community-dwelling healthy Amish participants. Exposures to PM < 2.5 µm (PM2.5) and PM < 10 µm (PM10) were estimated at participants' residential addresses using previously developed geographic information system-based spatio-temporal models and normalized. Associations between PM exposures and FMD were evaluated using linear mixed-effects regression models, and polynomial distributed lag (PDL) models followed by Bayesian model averaging (BMA) were used to assess response to delayed effects occurring across multiple months. RESULTS: Exposure to PM10 was consistently inversely associated with FMD, with the strongest (most negative) association for a 12-month moving average (- 0.09; 95% CI: - 0.15, - 0.03). Associations with PM2.5 were also strongest for a 12-month moving average but were weaker than for PM10 (- 0.07; 95% CI: - 0.13, - 0.09). Associations of PM2.5 and PM10 with FMD were somewhat stronger in men than in women, particularly for PM10. CONCLUSIONS: Using location-specific moving-average air pollution exposure estimates, we have shown that 12-month moving-average estimates of PM2.5 and PM10 exposure are associated with impaired endothelial function in a rural population.

R/PY-SUMMA: An R/Python Package for Unsupervised Ensemble Learning for Binary Classification Problems in Bioinformatics.

The increasing availability of complex data in biology and medicine has promoted the use of machine learning in classification tasks to address important problems in translational and fundamental science. Two important obstacles, however, may limit the unraveling of the full potential of machine learning in these fields: the lack of generalization of the resulting models and the limited number of labeled data sets in some applications. To address these important problems, we developed an unsupervised ensemble algorithm called strategy for unsupervised multiple method aggregation (SUMMA). By virtue of being an ensemble method, SUMMA is more robust to generalization than the predictions it combines. By virtue of being unsupervised, SUMMA does not require labeled data. SUMMA receives as input predictions from a diversity of models and estimates their classification performance even when labeled data are unavailable. It then uses these performance estimates to combine these different predictions into an ensemble model. SUMMA can be applied to a variety of binary classification problems in bioinformatics including but not limited to gene network inference, cancer diagnostics, drug response prediction, somatic mutation, and differential expression calling. In this application note, we introduce the R/PY-SUMMA packages, available in R or Python, that implement the SUMMA algorithm.

Effect of Alirocumab on Lipoprotein(a) and Cardiovascular Risk After Acute Coronary Syndrome.

BACKGROUND: Lipoprotein(a) concentration is associated with cardiovascular events. Alirocumab, a proprotein convertase subtilisin/kexin type 9 inhibitor, lowers lipoprotein(a) and low-density lipoprotein cholesterol (LDL-C). OBJECTIVES: A pre-specified analysis of the placebo-controlled ODYSSEY Outcomes trial in patients with recent acute coronary syndrome (ACS) determined whether alirocumab-induced changes in lipoprotein(a) and LDL-C independently predicted major adverse cardiovascular events (MACE). METHODS: One to 12 months after ACS, 18,924 patients on high-intensity statin therapy were randomized to alirocumab or placebo and followed for 2.8 years (median). Lipoprotein(a) was measured at randomization and 4 and 12 months thereafter. The primary MACE outcome was coronary heart disease death, nonfatal myocardial infarction, ischemic stroke, or hospitalization for unstable angina. RESULTS: Baseline lipoprotein(a) levels (median: 21.2 mg/dl; interquartile range [IQR]: 6.7 to 59.6 mg/dl) and LDL-C [corrected for cholesterol content in lipoprotein(a)] predicted MACE. Alirocumab reduced lipoprotein(a) by 5.0 mg/dl (IQR: 0 to 13.5 mg/dl), corrected LDL-C by 51.1 mg/dl (IQR: 33.7 to 67.2 mg/dl), and reduced the risk of MACE (hazard ratio [HR]: 0.85; 95% confidence interval [CI]: 0.78 to 0.93). Alirocumab-induced reductions of lipoprotein(a) and corrected LDL-C independently predicted lower risk of MACE, after adjustment for baseline concentrations of both lipoproteins and demographic and clinical characteristics. A 1-mg/dl reduction in lipoprotein(a) with alirocumab was associated with a HR of 0.994 (95% CI: 0.990 to 0.999; p = 0.0081). CONCLUSIONS: Baseline lipoprotein(a) and corrected LDL-C levels and their reductions by alirocumab predicted the risk of MACE after recent ACS. Lipoprotein(a) lowering by alirocumab is an independent contributor to MACE reduction, which suggests that lipoprotein(a) should be an independent treatment target after ACS. (ODYSSEY Outcomes: Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab; NCT01663402).

Community-Based Upper Extremity Power Training for Youth with Cerebral Palsy: A Pilot Study.

Aim: To examine the effects of an upper-extremity, community-based, and power-training intervention.Methods: Twelve participants with cerebral palsy (CP) [8 males, 4 females; mean age 14 years 6 months (SD 5 years 4 months), range 7-24] were randomly assigned to a rest-training (RT; n = 6) or training-rest (n = 6) group in this randomized, cross-over design. Training took place in participants' home or school, three times per week for 6 weeks. We examined changes in upper extremity average power output (Pavg) in watts (W) and changes in function via the Pediatric Outcomes Data Collection Instrument (PODCI).Results: Each participant completed at least 15 of the 18 total training sessions (91.2% adherence). Pavg increased 92.2% on average among participants (p < .05). There was a significant three-way interaction among treatment, sequence, and period with the data stratified by (Bimanual Fine Motor Function [BFMF]) level on the pain subscale of the PODCI (p = 0.0118). All participants decreased pain after training with the exception of individuals with lower functioning (BFMF II-V) in the RT group.Conclusion: A community-based upper extremity power-training intervention was feasible and effective at improving power among young people with CP and has the potential to improve pain.

Critical slowing down in biochemical networks with feedback.

Near a bifurcation point, the response time of a system is expected to diverge due to the phenomenon of critical slowing down. We investigate critical slowing down in well-mixed stochastic models of biochemical feedback by exploiting a mapping to the mean-field Ising universality class. We analyze the responses to a sudden quench and to continuous driving in the model parameters. In the latter case, we demonstrate that our class of models exhibits the Kibble-Zurek collapse, which predicts the scaling of hysteresis in cellular responses to gradual perturbations. We discuss the implications of our results in terms of the tradeoff between a precise and a fast response. Finally, we use our mapping to quantify critical slowing down in T cells, where the addition of a drug is equivalent to a sudden quench in parameter space.

Risk Categorization Using New American College of Cardiology/American Heart Association Guidelines for Cholesterol Management and Its Relation to Alirocumab Treatment Following Acute Coronary Syndromes.

BACKGROUND: The 2018 US cholesterol management guidelines recommend additional lipid-lowering therapies for secondary prevention in patients with low-density lipoprotein cholesterol ≥70 mg/dL or non-high-density lipoprotein cholesterol ≥100 mg/dL despite maximum tolerated statin therapy. Such patients are considered at very high risk (VHR) based on a history of >1 major atherosclerotic cardiovascular disease (ASCVD) event or a single ASCVD event and multiple high-risk conditions. We investigated the association of US guideline-defined risk categories with the occurrence of ischemic events after acute coronary syndrome and reduction of those events by alirocumab, a PCSK9 (proprotein convertase subtilisin/kexin type 9) inhibitor. METHODS: In the ODYSSEY OUTCOMES trial (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab), patients with recent acute coronary syndrome and residual dyslipidemia despite optimal statin therapy were randomly assigned to alirocumab or placebo. The primary trial outcome (major adverse cardiovascular events, ie, coronary heart disease death, nonfatal myocardial infarction, ischemic stroke, or hospitalization for unstable angina) was examined according to American College of Cardiology/American Heart Association risk category. RESULTS: Of 18 924 participants followed for a median of 2.8 years, 11 935 (63.1%) were classified as VHR: 4450 (37.3%) had multiple prior ASCVD events and 7485 (62.7%) had 1 major ASCVD event and multiple high-risk conditions. Major adverse cardiovascular events occurred in 14.4% of placebo-treated patients at VHR versus 5.6% of those not at VHR. In the VHR category, major adverse cardiovascular events occurred in 20.4% with multiple prior ASCVD events versus 10.7% with 1 ASCVD event and multiple high-risk conditions. Alirocumab was associated with consistent relative risk reductions in both risk categories (hazard ratio=0.84 for VHR; hazard ratio=0.86 for not VHR; Pinteraction=0.820) and by stratification within the VHR group (hazard ratio=0.86 for multiple prior ASCVD events; hazard ratio=0.82 for 1 major ASCVD event and multiple high-risk conditions; Pinteraction=0.672). The absolute risk reduction for major adverse cardiovascular events with alirocumab was numerically greater (but not statistically different) in the VHR group versus those not at VHR (2.1% versus 0.8%; Pinteraction=0.095) and among patients at VHR with multiple prior ASCVD events versus a single prior ASCVD event (2.4% versus 1.8%; Pinteraction=0.661). CONCLUSIONS: The US guideline criteria identify patients with recent acute coronary syndrome and dyslipidemia who are at VHR for recurrent ischemic events and who may derive a larger absolute benefit from treatment with alirocumab. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01663402.