Surrogate Estimates Research Articles

Reduced neurovascular coupling of the visual network in migraine patients with aura as revealed with arterial spin labeling MRI: is there a demand-supply mismatch behind the scenes?

BackgroundAlthough neuroimaging investigations have consistently demonstrated that “hyperresponsive” and “hyperconnected” visual cortices may represent the functional substrate of cortical spreading depolarization in patients with migraine with aura, the mechanisms which underpin the brain “tendency” to ignite the cortical spreading depolarization and, consequently, aura phenomenon are still matter of debate. Considering that triggers able to induce aura phenomenon constrain brain to increase global (such as physical activity, stressors and sleep abnormalities) or local (such as bright light visual stimulations) energy demand, a vascular supply unable to satisfy the increased energy requirement could be hypothesized in these patients.MethodsTwenty-three patients with migraine with aura, 25 patients with migraine without aura and 20 healthy controls underwent a 3-Tesla MRI study. Cerebral blood flow and local functional connectivity (regional homogeneity) maps were obtained and registered to the MNI space where 100 cortical regions were derived using a functional local-global normative parcellation. A surrogate estimate of the regional neurovascular coupling for each subject was obtained at each parcel from the correlation coefficient between the z-scored ReHo map and the z-scored cerebral blood flow maps.ResultsA significantly higher regional cerebral blood flow across the visual cortex of both hemispheres (i.e. fusiform and lingual gyri) was detected in migraine with aura patients when compared to patients with migraine without aura (p < 0.05, corrected for multiple comparisons). Concomitantly, a significantly reduced neurovascular coupling (p < 0.05, false discovery rate corrected) in the primary visual cortex parcel (VIS-4) of the large-scale visual network was observed in the left hemisphere of patients with migraine with aura (0.23±0.03), compared to both patients with migraine without aura (0.32±0.05) and healthy controls (0.29±0.05).ConclusionsVisual cortex neurovascular “decoupling” might represent the “link” between the exposure to trigger factors and aura phenomenon ignition. While physiological vascular oversupply may compensate neurovascular demand-supply at rest, it becomes inadequate in case of increased energy demand (e.g. when patients face with trigger factors) paving the way to the aura phenomenon ignition in patients with migraine with aura. Whether preventive treatments may exert their therapeutic activity on migraine with aura restoring the energy demands and cerebral blood flow trade-off within the visual network should be further investigated.

Shared Decision-Making Communication and Prognostic Misunderstanding in the ICU

Surrogate misunderstanding of patient survival prognosis in the intensive care unit (ICU) is associated with poor patient and surrogate outcomes. Shared decision-making (SDM) may reduce misunderstanding. To evaluate the association between SDM-aligned communication and prognostic misunderstanding. This retrospective cohort study was conducted at 13 medical and surgical ICUs at 5 hospitals in North Carolina, Pennsylvania, and Washington between December 2012 and January 2017. Participants were surrogates of adult patients receiving prolonged mechanical ventilation and ICU physicians. Analysis was performed May to November 2023. SDM-aligned communication during ICU family meetings, defined as the presence of high-quality serious illness communication behaviors aligned with SDM principles. The primary outcome was postmeeting surrogate prognostic misunderstanding, defined as the absolute difference between the physician's estimate of survival prognosis and the surrogate's perception of that estimate (range, 0-100 percentage points). The secondary outcome was postmeeting physician misunderstanding, defined as the absolute difference between a surrogate's estimate of survival prognosis and the physician's perception of that estimate (range, 0-100 percentage points). Prognostic misunderstanding of 20 percentage points or greater was considered clinically significant as in prior work. Of 137 surrogates, most were female (102 [74.5%]), and there were 22 (16.1%) Black surrogates, 107 (78.1%) White surrogates, and 8 surrogates (5.8%) with other race and ethnicity. Of 100 physicians, most were male (64 [64.0%]), with 11 (11.0%) Asian physicians, 4 (4.0%) Black physicians, and 75 (75.0%) White physicians. Median (IQR) surrogate prognostic misunderstanding declined significantly after family meetings (before: 22.0 [10.0 to 40.0] percentage points; after: 15.0 [5.0 to 34.0] percentage points; P = .002), but there was no significant change in median (IQR) physician prognostic misunderstanding (before: 12.0 [5.0 to 30.0] percentage points; after: 15.0 [5.0 to 29.0] percentage points; P = .99). In adjusted analyses, SDM-aligned communication was not associated with prognostic misunderstanding among surrogates or physicians (surrogates: β = -0.74; 95% CI, -1.81 to 0.32; P = .17; physicians: β = -0.51; 95% CI, -1.63 to 0.62; P = .38). In a prespecified subgroup analysis of 78 surrogates (56.9%) with clinically significant premeeting prognostic misunderstanding, SDM-aligned communication was associated with reduced surrogate postmeeting prognostic misunderstanding (β = -1.71; 95% CI, -3.09 to -0.34; P = .01). In this retrospective cohort study, SDM-aligned communication was not associated with changes in prognostic misunderstanding for all surrogates or physicians, but it was associated with reduced prognostic misunderstanding among surrogates with clinically significant misunderstanding at baseline.

A control-oriented load surrogate model based on sector-averaged inflow quantities: capturing damage for unwaked, waked, wake-steering and curtailed wind turbines

This paper presents a novel approach to constructing a load surrogate model. The surrogate estimates the damage equivalent loads (DELs) of a wind turbine of a given type regardless of its position within a wind farm, and under various farm control actions. The model relies solely on local inflow quantities (sector-averaged wind speeds and turbulence intensities) and local control parameters (rotor speed, pitch angle, and yaw misalignment). Despite its highly simplified representation of the complex behavior of the turbulent wind field, wake effects, and controller dynamics, these quantities prove sufficient to characterize DELs. The paper demonstrates the training of this load model within a simulation environment. Validation results using a different wind farm configuration indicate that the surrogate can accurately predict fatigue loads for both unwaked and waked turbines, encompassing scenarios of wake steering and induction control.

A simple medical device development according to normative values of calf circumference across ages: results from the Italian Longevity Check-up 7+ (Lookup 7+) project.

Wide consensus exists on the notion that low muscle mass is a predictor of negative health-related events, such as disability, morbidity, and mortality. Indeed, the European Working Group on Sarcopenia in Older People 2 had identified muscle mass as the key component to confirm the diagnosis of sarcopenia. However, the lack of normative values for muscle mass across ages hampers the practical assessment of this important parameter. The aim of the present study was to produce cross-sectional centile and normative values for calf circumference (a surrogate estimation of muscle mass) across a wide spectrum of ages using a large and unselected sample of community-dwellers enrolled in the Longevity Check-up 7+ (Lookup 7+) project. This is a cross-sectional study using the data of Lookup 7+ project, an ongoing study started in June 2015 and conducted in unconventional settings (i.e., exhibitions, malls, and health promotion campaigns). Candidate participants were considered eligible for enrolment if they were at least 45years of age and provided written informed consent. Calf circumference was measured using an inextensible but flexible plastic tape in a sitting position with the knee and ankle at a right angle and the feet resting on the floor. Normative values for calf circumference from ages 45 to 80+years were generated. A total of 11814 participants were enrolled from 1 June 2015 to 30 September 2022. The mean age of participants included in the analyses was 61.8years (standard deviation; 10.2years; range: 45-98years), and 6686 (57%) were women. Normative values for calf circumference were obtained for men and women, stratified by age groups. Accordingly, a calf circumference tape, with colour bands that demarcate the centiles range into which the patient falls, was created and validated. Our study established age- and gender-specific centile reference values for calf circumference. The calf circumference tape can be used to easily interpret the assessment in every-day practice for the early detection of individuals with or at risk of sarcopenia and malnutrition.

Communication‐efficient low‐dimensional parameter estimation and inference for high‐dimensional Lp$$ {L}^p $$‐quantile regression

AbstractThe ‐quantile regression generalizes both quantile regression and expectile regression, and has become popular for its robustness and effectiveness especially when . In this paper, we consider the data that are inherently distributed and propose two distributed ‐quantile regression estimators for a preconceived low‐dimensional parameter in the presence of high‐dimensional extraneous covariates. To handle the impact of high‐dimensional nuisance parameters, we first investigate regularized projection score for estimating low‐dimensional parameter of main interest in ‐quantile regression. To deal with the distributed data, we further propose two communication‐efficient surrogate projection score estimators and establish their theoretical properties. The finite‐sample performance of the proposed estimators is studied through simulations and an application to Communities and Crime data set is also presented.

295 Topical Tranexamic Acid in Burn Surgery – A Randomized Controlled Trial

Abstract Introduction Early excision and grafting of large burn wounds can result in considerable bleeding. Systemic use of tranexamic acid (TXA) generally reduces surgical bleeding by 30-40%, but its safety in burn surgery has not been studied. Topical use may provide a sufficient wound concentration with negligible risk of systemic adverse events. However, it is unclear whether topical use may delay wound re-epithelialization. This pilot double-blinded randomized controlled trial aimed to evaluate the therapeutic potential of topical TXA for reducing blood loss and the effect on wound re-epithelialization in burn surgery. Methods Between Jan 2021 – April 2022, burn patients at a single national burn center who needed at least two separate donor sites for split-thickness skin grafting were included. In total, 36 wound pairs in similar anatomical areas were made in 23 patients. Donor sites were infiltrated with tumescence containing epinephrine before harvesting. Paired wounds were randomized to topical application of standard epinephrine solution, with or without added TXA 25 mg/ml, before coverage with vaseline and dry gauze. Endpoints were time to re-epithelialization and surrogate bleeding estimates defined as net weight gain of dressings per cm2 wound area, bloodstain area per wound area, and visual rating of the amount of blood in dressings on the first postoperative day. Results There was no difference in healing time between wounds. The results trended towards less increase in dressing weight gain per cm2 of wound area in the TXA group, though not significant (p=0.12). However, when dividing the results in two at the median bleeding volume, there was a significant reduction in bleeding in the high-bleed group (p=0.012). Similar observations were made for the other two bleeding endpoints, but the differences did not reach statistical significance. Conclusions Moistening a superficial wound surface with TXA 25 mg/ml does not impair wound re-epithelialization. Topical TXA may reduce bleeding from graft donor sites with low risk of systemic complications. Applicability of Research to Practice This pilot study suggests that topical TXA is of value in reducing bleeding in burn surgery without delaying donor site healing. The effect may be larger in wounds not prepared with epinephrine infiltration. More research is warranted regarding the optimal mode of topical drug delivery and systemic concentrations after topical application in burns. Furthermore, it remains to investigate whether topical TXA affects graft take.

Postural and Gestural Synchronization, Sequential Imitation, and Mirroring Predict Perceived Coupling of Dancing Dyads

Body movement is a primary nonverbal communication channel in humans. Coordinated social behaviors, such as dancing together, encourage multifarious rhythmic and interpersonally coupled movements from which observers can extract socially and contextually relevant information. The investigation of relations between visual social perception and kinematic motor coupling is important for social cognition. Perceived coupling of dyads spontaneously dancing to pop music has been shown to be highly driven by the degree of frontal orientation between dancers. The perceptual salience of other aspects, including postural congruence, movement frequencies, time-delayed relations, and horizontal mirroring remains, however, uncertain. In a motion capture study, 90 participant dyads moved freely to 16 musical excerpts from eight musical genres, while their movements were recorded using optical motion capture. A total from 128 recordings from 8 dyads maximally facing each other were selected to generate silent 8-s animations. Three kinematic features describing simultaneous and sequential full body coupling were extracted from the dyads. In an online experiment, the animations were presented to 432 observers, who were asked to rate perceived similarity and interaction between dancers. We found dyadic kinematic coupling estimates to be higher than those obtained from surrogate estimates, providing evidence for a social dimension of entrainment in dance. Further, we observed links between perceived similarity and coupling of both slower simultaneous horizontal gestures and posture bounding volumes. Perceived interaction, on the other hand, was more related to coupling of faster simultaneous gestures and to sequential coupling. Also, dyads who were perceived as more coupled tended to mirror their pair's movements.

Surrogate Endpoints in Clinical Trials

Surrogate markers are often used in clinical trials settings when obtaining a final outcome to evaluate the effectiveness of a treatment requires a long wait, is expensive to obtain, or both. Formal definitions of surrogate marker quality resulting from a large variety of estimation approaches have been proposed over the years. I review this work, with a particular focus on approaches that use the causal inference paradigm, as these conceptualize a good marker as one in the causal pathway between the treatment and outcome. I also focus on efforts to evaluate the risk of a surrogate paradox, a damaging situation where the surrogate is positively associated with the outcome, and the causal effect of the treatment on the surrogate is in a helpful direction, but the ultimate causal effect of the treatment on the outcome is harmful. I then review some recent work in robust surrogate marker estimation and conclude with a discussion and suggestions for future research.

The relation of whole grain surrogate estimates and food definition to total whole grain intake in the Finnish adult population

ObjectivesChallenges in estimating total whole grain intake have led to the use of surrogate estimates, of which accuracy has not been assessed. We examined the suitability of five potential surrogates (dietary fiber; bread; rye bread; rye, oat and barley combined; rye) and a whole grain food definition to measure total whole grain intake in the Finnish adult population.MethodsOur data comprised 5094 Finnish adults participating in the national FinHealth 2017 Study. Dietary intake was assessed by a validated FFQ. Food and nutrient intakes, including total whole grain, were calculated utilizing the Finnish Food Composition Database. The Healthgrain Forum whole grain food definition was applied to examine definition-based whole grain intake. Spearman correlations and quintile cross-classifications were calculated.ResultsDefinition-based whole grain intake and consumption of rye, oat and barley combined had consistently the strongest correspondence with total whole grain intake. Rye and rye bread consumption also corresponded well with total whole grain intake. The correspondences of dietary fiber and bread with total whole grain were lower and more affected by the exclusion of energy under-reporters. Furthermore, their correlations with total whole grain intake varied the most between population subgroups.ConclusionsRye-based estimates, especially rye, oat and barley combined, and definition-based whole grain intake appeared suitable surrogate estimates of total whole grain intake for epidemiological research of Finnish adults. The variation between surrogate estimates in their correspondence with total whole grain intake demonstrated the need for further evaluation of their accuracy in different populations and regarding specific health outcomes.

Metabolically unhealthy phenotype in adults with normal weight: Is cardiometabolic health worse off when compared to adults with obesity?

The concept of metabolically healthy vs. unhealthy obese (MHO vs. MUO) was expanded to non-obese individuals as obesity-related comorbidities exist in a sub-group of normal weight (NW), i.e., MHNW vs. MUNW. It is unclear if MUNW differs from MHO with respect to cardiometabolic health. PurposeThe purpose of this study was to compare cardiometabolic disease risk factors between MH vs. MU across weight status, NW, and obesity. MethodA total of 8160 adults were included in the study from both the 2019 and 2020 Korean National Health and Nutrition Examination Surveys. Individuals with NW vs. obesity were further stratified as MH vs. MU by using AHA/NHLBI criterion for metabolic syndrome. A retrospective pair-matched analysis with respect to sex (male/female) and age ( ± 2 years) was performed to verify our total cohort analyses/results. ResultsDespite a gradual increase in BMI and waist circumference from MHNW to MUNW to MHO to MUO, the surrogate estimates of insulin resistance and arterial stiffness were higher in MUNW vs. MHO. When compared to the MHNW, MUNW and MUO showed higher odds of hypertension (MUNW: 512%, MUO: 784%), dyslipidemia (MUNW: 210%, MUO: 245%), and diabetes (MUNW: 920%, MUO: 4012%), with no difference between MHNW and MHO. ConclusionIndividuals with MUNW vs. MHO have greater vulnerability to cardiometabolic disease. Our data indicate that cardiometabolic risk is not solely dependent on adiposity, suggesting that early preventive efforts for chronic disease are needed for individuals with NW yet MU.

Global sensitivity study for irreversible electroporation: Towards treatment planning under uncertainty.

Electroporation-based cancer treatments are minimally invasive, nonthermal interventional techniques that leverage cell permeabilization to ablate the target tumor. However, the amount of permeabilization is susceptible to the numerous uncertainties during treatment, such as patient-specific variations in the tissue, type of the tumor, and the resolution of imaging equipment. These uncertainties can reduce the extent of ablation in the tissue, thereby affecting the effectiveness of thetreatment. The aim of this work is to understand the effect of these treatment uncertainties on the treatment outcome for irreversible electroporation (IRE) in the case of colorectal liver metastasis (CRLM). Understanding the nature and extent of these effects can help us identify the influential treatment parameters and build better models for predicting the treatmentoutcome. This is an in silico study using a static computational model with a custom applicator design, spherical tissue, and tumor geometry. A nonlinear electrical conductivity, dependent on the local electric field, is considered. Morris analysis is used to identify the influential treatment parameters on the treatment outcome. Seven treatment parameters pertaining to the relative tumor location with respect to the applicator, the tumor growth pattern, and the electrical conductivity of tissue are analyzed. The treatment outcome is measured in terms of the relative tumor ablation with respect to the target ablation volume and total ablationvolume. The Morris analysis was performed with 800 model evaluations, sampled from the seven dimensional input parameter space. Electrical properties of the tissue, especially the electrical conductivity of the tumor before ablation, were found to be the most influential parameter for relative tumor ablation and total ablation volume. This parameter was found to be about 4-15 times more influential than the least influential parameter, depending on the tumor size. The tumor border configuration was identified as the least important parameter for treatment effectiveness. The most desired treatment outcome is obtained by a combination of high healthy liver conductivity and low tumor conductivity. This information can be used to tackle worst-case scenarios in treatment planning. Finally, when the safety margins used in the clinical applications are accounted for, the effects of uncertainties in the treatment parameters reducedrastically. The results of this work can be used to create an efficient surrogate estimator for uncertainty quantification in the treatment outcome, that can be utilized in optimal real-time treatment planning solutions.

Combining Reduced-Order Model With Data-Driven Model for Parameter Estimation of Lithium-Ion Battery

The parameters of a lithium-ion battery are important to construct an effective battery management system. Parameter estimation assisted by the pseudo-two-dimensional (P2D) model is much more cost-effective than direct measurement methods. However, this is a nontrivial task, because the simulation of the P2D model is time-consuming. Alternatively, surrogate models such as reduced-order/data-driven models are often used to accelerate the parameter estimation process. Each category of surrogate models has its own strengths and weaknesses. Traditionally, reduced-order models run faster than data-driven models, while data-driven models are more accurate than reduced-order models. To leverage the complementary advantages of these two kinds of surrogate models, we make an interesting attempt to combine them compactly, thus proposing a two-phase surrogate model-assisted parameter estimation algorithm (TPSMA-PEAL). In the first phase, a fast reduced-order model is designed for parameter prescreening. In the second phase, a high-fidelity data-driven model is developed for fine estimation. In TPSMA-PEAL, except the time-consuming simulation, the other two challenges (i.e., the overfitting problem and the low observability of some parameters) are also considered from the perspective of optimization. Note that TPSMA-PEAL takes advantage of differential evolution and parameter sensitivity analysis to address them. Simulations and experiments verify that TPSMA-PEAL is efficient and accurate.

The Associations between Accelerometer-measured Physical Activity and Cardiometabolic Disease Risk Factors and Metabolic Syndrome in Korean Adults : Results from 2014-2016 KNHANES DATA

PURPOSE This study aimed to examine the associations between accelerometer-measured physical activity and both cardiometabolic disease risk factors and metabolic syndrome in Korean adults. METHODS We performed a retrospective cohort study with age-sex matched case-control using data from the 2014-2016 Korea National Health and Nutrition Examination Survey, which was administered to South Korean adults (n=320). Individuals were categorized into quartiles based on accelerometer-measured moderate-to-vigorous physical activity (MVPA). Demographic and physical characteristics, waist circumference, visceral adiposity index, blood pressure, lipid profiles, and TG/HDL-C were observed. The associations between MVPA status and cardiometabolic disease risk factors as well as metabolic syndrome were determined using multiple logistic regression. RESULTS For the waist circumference, SBP, DBP, MBP, visceral adiposity, triglyceride, and a surrogate estimate of insulin resistance, the Q1 and Q2 groups had higher means compared with the Q3 and Q4 groups. HDL-C was higher in the Q3 and Q4 groups compared to the Q1 and Q2 groups. Odds ratios for cardiometabolic disease risk factors and metabolic syndrome decreased in a curvilinear manner with the increasing quartile of MVPA. CONCLUSIONS Adults with higher MVPA participation were strongly associated with cardiometabolic disease risk factors and metabolic syndrome.

Short-range multispectral imaging is an inexpensive, fast, and accurate approach to estimate biodiversity in a temperate calcareous grassland.

Image sensing technologies are rapidly increasing the cost-effectiveness of biodiversity monitoring efforts. Species differences in the reflectance of electromagnetic radiation can be used as a surrogate estimate plant biodiversity using multispectral image data. However, these efforts are often hampered by logistical difficulties in broad-scale implementation. Here, we investigate the utility of multispectral imaging technology from commercially available unmanned aerial vehicles (UAVs, or drones) in estimating biodiversity metrics at a fine spatial resolution (0.1-0.5cm pixel resolution) in a temperate calcareous grassland in Oxfordshire, UK. We calculate a suite of moments (coefficient of variation, standard deviation, skewness, and kurtosis) for the distribution of radiance from multispectral images at five wavelength bands (Blue 450 ± 16 nm; Green 560 ± 16 nm; Red 650 ± 16 nm; Red Edge 730 ± 16 nm; Near Infrared 840 ± 16 nm) and test their effectiveness at estimating ground-truthed biodiversity metrics from in situ botanical surveys for 37-1 × 1m quadrats. We find positive associations between the average coefficient of variation in spectral radiance and both the Shannon-Weiner and Simpson's biodiversity indices. Furthermore, the average coefficient of variation in spectral radiance is consistent and highly repeatable across sampling days and recording heights. Positive associations with biodiversity indices hold irrespective of the image recording height (2-8m), but we report reductions in estimates of spectral diversity with increases to UAV recording height. UAV imaging reduced sampling time by a factor of 16 relative to in situ botanical surveys. We demonstrate the utility of multispectral radiance moments as an indicator of biodiversity in this temperate calcareous grassland at a fine spatial resolution using a widely available UAV monitoring system with a coarse spectral resolution. The use of UAV technology with multispectral sensors has far-reaching potential to provide cost-effective and high-resolution monitoring of biodiversity.

A Novel Approach of Combining Methylene Blue Photodynamic Inactivation, Photobiomodulation and Oral Ingested Methylene Blue in COVID-19 Management: A Pilot Clinical Study with 12-Month Follow-Up.

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 virus was first recognized in late 2019 and remains a significant threat. We therefore assessed the use of local methylene blue photodynamic viral inactivation (MB-PDI) in the oral and nasal cavities, in combination with the systemic anti-viral, anti-inflammatory and antioxidant actions of orally ingested methylene blue (MB) and photobiomodulation (PBM) for COVID-19 disease. The proposed protocol leverages the separate and combined effects of MB and 660nm red light emitted diode (LED) to comprehensively address the pathophysiological sequelae of COVID-19. A total of eight pilot subjects with COVID-19 disease were treated in the Bahamas over the period June 2021-August 2021, using a remote care program that was developed for this purpose. Although not a pre-requisite for inclusion, none of the subjects had received any COVID-19 vaccination prior to commencing the study. Clinical outcome assessment tools included serial cycle threshold measurements as a surrogate estimate of viral load; serial online questionnaires to document symptom response and adverse effects; and a one-year follow-up survey to assess long-term outcomes. All subjects received MB-PDI to target the main sites of viral entry in the nose and mouth. This was the central component of the treatment protocol with the addition of orally ingested MB and/or PBM based on clinical requirements. The mucosal surfaces were irradiated with 660 nm LED in a continuous emission mode at energy density of 49 J/cm2 for PDI and 4.9 J/cm2 for PBM. Although our pilot subjects had significant co-morbidities, extremely high viral loads and moderately severe symptoms during the Delta phase of the pandemic, the response to treatment was highly encouraging. Rapid reductions in viral loads were observed and negative PCR tests were documented within a median of 4 days. These laboratory findings occurred in parallel with significant clinical improvement, mostly within 12-24 h of commencing the treatment protocol. There were no significant adverse effects and none of the subjects who completed the protocol required in-patient hospitalization. The outcomes were similarly encouraging at one-year follow-up with virtual absence of "long COVID" symptoms or of COVID-19 re-infection. Our results indicate that the protocols may be a safe and promising approach to challenging COVID-19 disease. Moreover, due its broad spectrum of activity, this approach has the potential to address the prevailing and future COVID-19 variants and other infections transmitted via the upper respiratory tract. Extensive studies with a large cohort are warranted to validate our results.

Impact of estimated pulse wave velocity on cardiovascular outcomes in a general population

Abstract Background Estimated pulse wave velocity (ePWV), a simple surrogate estimate of carotid-femoral pulse wave velocity which was gold standard for measuring aortic stiffness, has been demonstrated to predict cardiovascular (CV) outcome. However, there was limited data on its predictive capacity for CV outcomes in the general population. The study aim was to investigate the independent association between ePWV and CV outcomes in general population. Methods A total of 10,030 subjects aged between 40 and 69 years were followed over 18-year period in the Ansan-Ansung cohort study. Levels of ePWV, which was calculated from an equation based on age and mean blood pressure, were categorized according to quartiles. A major adverse cardiovascular event (MACE) was defined as a composite of myocardial infarction, coronary artery disease, stroke, heart failure, peripheral artery disease, and cardiovascular death. Results The incidence rates of CV death, and MACE were 7.0% and 22.1% in the fourth (highest) quartile of ePWV and 0.1% and 4.5% in the first (lowest) quartile of ePWV. After adjusting for relevant covariates, patients with third and fourth quartile of ePWV showed significantly higher risk of CV death (hazard ratio [HR] 3.92; 95% confidence intervals [CI] 1.09–14.15 in third quartile and HR 8.53; 95% CI 2.13–34.10 in fourth quartile), and MACE (HR 1.54; 95% CI 1.15–2.08 in third quartile and HR 1.56; 95% CI 1.05–2.32) compared to the reference of first (lowest) quartile of ePWV. However, there were no improvement of C statistic for CV death and MACE when adding ePWV to the Cox regression models with 10-year atherosclerotic cardiovascular disease (ASCVD) risk. Conclusion These results suggest that ePWV predicted CV death and MACE in general population. The value of ePWV, a simple and useful indicator of aortic stiffness, is expected to serve as a potential marker to identify high risk groups of CV event in general population. Funding Acknowledgement Type of funding sources: None.

Robust sequential experimental strategy for black‐box optimization with application to hyperparameter tuning

AbstractGlobal optimization of expensive, noisy black‐box functions is a problem of significant interest and is used extensively in applications such as hyperparameter optimization (HPO) of machine learning models. Response Surface Optimization (RSO) and Bayesian Optimization (BO) are two highly efficient model‐based experimentation strategies for optimizing expensive, noisy black‐box functions. The run‐size efficiency of both RSO and BO is critically dependent on the fitness of the surrogate model in approximating the true response function. In this regard, both RSO and BO deliberately choose initial designs that are optimal for estimating the assumed surrogate model and their sequential design strategy is aimed at further refining the surrogate model estimate. As a result, a design strategy that is optimal for one is not necessarily optimal for the other. In this study, we propose Compound‐RSO, a model‐robust, three‐stage experimental strategy for optimizing noisy black‐box functions with continuous experimental factors. Compound‐RSO is a hybrid strategy between RSO and BO which empirically estimates the complexity of the black‐box function and chooses the appropriate strategy between them. We propose robust designs that are highly efficient for estimating a second‐order polynomial model and that simultaneously maximize the power of the Lack‐of‐Fit test to determine the inadequacies of a second‐order approximation. Additionally, we propose a trust‐region‐based‐adaptive experimentation strategy for optimizing a second‐order response function. Through our simulation study we illustrate that the proposed Compound‐RSO strategy is more efficient than BO when the response function is second‐order, and performs comparably to BO when the response function is complex. Lastly, a case study on HPO of Deep Neural Networks (DDNs) in the context of visual quality inspections at a medical device manufacturer further illustrates the utility of the proposed Compound‐RSO strategy.

Beyond “sex prediction”: Estimating and interpreting multivariate sex differences and similarities in the brain

Previous studies have shown that machine-learning (ML) algorithms can “predict” sex based on brain anatomical/ functional features. The high classification accuracy achieved by ML algorithms is often interpreted as revealing large differences between the brains of males and females and as confirming the existence of “male/female brains”. However, classification and estimation are different concepts, and using classification metrics as surrogate estimates of between-group differences may result in major statistical and interpretative distortions. The present study avoids these distortions and provides a novel and detailed assessment of multivariate sex differences in gray matter volume (GMVOL) that does not rely on classification metrics. Moreover, appropriate regression methods were used to identify the brain areas that contribute the most to these multivariate differences, and clustering techniques and analyses of similarities (ANOSIM) were employed to empirically assess whether they assemble into two sex-typical profiles. Results revealed that multivariate sex differences in GMVOL: (1) are “large” if not adjusted for total intracranial volume (TIV) variation, but “small” when controlling for this variable; (2) differ in size between individuals and also depends on the ML algorithm used for their calculation (3) do not stem from two sex-typical profiles, and so describing them in terms of “male/female brains” is misleading.

Multi-Hazard Fragility Analysis of Offshore Wind Turbine Portfolios using Surrogate Models

This paper deals with a surrogate modeling-based fragility estimate of monopile offshore wind turbine (OWT) towers subjected to wind and wave loadings. The monopile 5-MW OWT specified by the National Renewable Energy Laboratory (NREL), United States was used as the base model for this study. Aero- and hydrodynamic simulations of the OWT were first performed via Fatigue, Aerodynamics, Structures, and Turbulence (FAST) developed by the NREL to determine its critical wave-and-wind responses, to determine peak tower top deflections, flexural moments, and shear forces. Through least squares regression with the simulation data, two surrogate models, Response Surface Metamodel (RSM) and Stepwise Multiple Linear Regression (SMLR) were developed to predict the critical OWT responses caused by both wind and wave loads and to develop its fragility curves at a low computational cost. Responses and fragility curves resulting from each of the surrogate models were compared to those from the FAST simulation, demonstrating the effectiveness of the RSM in terms of accuracy to replicate the FAST results. As a result of the comparison, the RSM was adopted as the final model to estimate the multi-wind-and-wave vulnerability of the OWT in terms of fragility surfaces considering uncertainties in a broad spectrum of its loads and capacities. Major findings indicated that the wind speed was observed to be the most critical load parameter for peak tower top deflections with response observed in the range of 2.2 5 m at a wind speed of 5 m/s to 5.5 m at 70 m/s, while the wave height appeared to be the major contributor to the vulnerability on flexural moments with the observed peak value of 1.75 × 108 Nm at a wave height of 1 m increased to 5.75 × 108 Nm at 20 m. It was also found that structural characteristics parameters related to the OWT's capacities, including hub height, rotor diameter, and monopile thickness have a significant impact on the overall vulnerability with one-quarter exceeding probability for mudline flexure was noted at 83.26 m, 151 m, and 0.133 m, respectively.

A novel hybrid adaptive scheme for Kriging-based reliability estimation – A comparative study

Over the past decade, researches on adaptive Kriging-based reliability estimation have been focused on enhancing its performance from three aspects including the simulation methods, learning functions, and stopping criteria, whereas few efforts have been dedicated to give a comprehensive guidance on design of experiment of the initial sampling methods, which directly influences the performance of the surrogate and surrogate-based reliability estimation. This paper presents a comparative study on the adaptive modeling schemes for Kriging-based reliability estimation. Comparison on six common sampling methods for the single step Kriging is conducted with a typical numerical example, to find an optimal initial sampling scheme for the surrogates. A comparative study on the performance of the hybrid adaptive schemes for the adaptive Kriging, each of which includes the initial sampling method, the learning scheme and the corresponding stop criterion, is then implemented on three typical examples, in order to heuristically provide a unique hybrid adaptive scheme for Kriging-based structural reliability estimation. It can synthetically consider the dimension of the input variables, the nonlinearity of the limit-state function and the application scenarios.