Log-likelihood Ratio Test Research Articles

Benford’s law analysis to evaluate the quality data of COVID-19 epidemiological surveillance in Indonesia

Countries worldwide, including Indonesia, grappled with the unprecedented challenges brought about by the coronavirus disease (COVID-19) pandemic. Surveillance data vividly illustrates the profound effect of the COVID-19 pandemic in Indonesia. Both daily cases and deaths were raised, revealing the rapid transmission of the virus within communities. A quantitative study using a statistical approach was accomplished with secondary data to evaluate the quality of COVID-19 epidemiological surveillance data in Indonesia during the period between March 2020 to January 2021. The data was sourced from the World Health Organization (WHO) website using data reports on COVID-19 confirmed cases and deaths. A rapid tool called the first digit law or the fulfillment of Benford’s law was used to suggest good data quality for epidemiological surveillance. Data analysis used the Chi-squared test and the log-likelihood ratio test. Also, it displayed the difference in mean absolute deviation (MAD) to identify the proximity of the data and Benford’s law distribution. The results showed that both confirmed, and death case distributions were statistically non-conformity with Benford’s law distribution. In terms of quality data regarding the COVID-19 pandemic, the epidemiological surveillance system falls short of Benford’s law assumption. Benford's law has been acknowledged as an initial analysis that can expeditiously assess the performance of a surveillance system. The next phase of this study would be to conduct a complete evaluation suitably, especially in post-pandemic COVID-19.

Non-linear relationship between pulse pressure and the risk of prediabetes: a 5-year cohort study in Chinese adults

Previous research has established a strong link between pulse pressure (PP) and diabetes, but there is limited investigation into the connection between PP and prediabetes. This study aims to explore the potential association between PP and prediabetes. A retrospective cohort study encompassed 202,320 Chinese adults who underwent health check-ups between 2010 and 2016. Prediabetes was defined in accordance with the World Health Organization criteria, indicating impaired fasting glucose, with fasting blood glucose levels ranging from 6.1 to 6.9 mmol/L. To assess the PP-prediabetes relationship, we employed Cox regression analysis, sensitivity analysis, and subgroup analysis. Cox proportional hazards regression, coupled with cubic spline functions and smooth curve fitting, helped elucidate the non-linear PP-prediabetes relationship. Upon adjusting for confounding factors, we observed a positive association between PP and prediabetes (HR 1.15, 95% CI 1.11–1.18, P < 0.0001). Participants in the fourth quartile (PP ≥ 51 mmHg) had a 73% higher likelihood of developing prediabetes compared to those in the first quartile (PP < 36 mmHg) (HR 1.73, 95% CI 1.52–1.97, P < 0.0001). Moreover, the relationship between PP and prediabetes was non-linear. A two-piece Cox proportional hazards regression model identified an inflection point at 40 mmHg for PP (P for log-likelihood ratio test = 0.047). Sensitivity and subgroup analyses corroborated the robustness of our findings. Our study reveals a non-linear correlation between PP and prediabetes, signifying an increased risk of prediabetes when PP levels exceed 40 mmHg. This discovery has significant clinical implications for early prediabetes prevention and intervention, ultimately contributing to improved patient outcomes and quality of life.

Direct Link Interference Suppression for Bistatic Backscatter Communication in Distributed MIMO

Backscatter communication (BC) is a promising technique for future Internet-of-Things (IoT) owing to its low complexity, low cost, and potential for energy-efficient operation in sensor networks. There are several network infrastructure setups that can be used for BC with IoT nodes. One of them is the bistatic setup where typically there is a need for high dynamic range and high-resolution analog-to-digital converters at the reader. In this paper, we investigate a bistatic BC setup with multiple antennas. We propose a novel transmission scheme, which includes a protocol for channel estimation at the carrier emitter (CE) as well as a transmit beamformer construction that suppresses the direct link interference between the two ends of a bistatic link (namely CE and reader), and increases the detection performance of the backscatter device (BD) symbol. Further, we derive a generalized log-likelihood ratio test (GLRT) to detect the symbol/presence of the BD. We also provide an iterative algorithm to estimate the unknown parameters in the GLRT. Finally, simulation results show that the required dynamic range of the system is significantly decreased, and the detection performance of the BD symbol is increased, by the proposed algorithm compared to a system not using beamforming at the CE.

A longitudinal complex likelihood ratio test for pleiotropy

. To test pleiotropy based on longitudinal data, two main difficulties are the construction of test statistics and the formulation of decision-making criteria. In particular, the commonly used log-likelihood ratio test is not available since there does not exist a likelihood function and the estimation is based on estimating equations in general. To address this and construct a statistic similar to the -2 log-likelihood ratio test statistic, we propose a new concept, a complex log-likelihood function, such that its first derivative is equal to a given estimating function. In consequence, the -2 complex log-likelihood ratio test is constructed for testing genetic pleiotropy, and the validity of the test procedure is established. An extensive simulation study is performed, which suggests that the proposed method works well for practical situations. Furthermore, it is applied to a set of longitudinal data on tropical storms.

Association between triglyceride glucose index and all-cause mortality in patients with cerebrovascular disease: a retrospective study

BackgroundTriglyceride glucose (TyG) is associated with stroke, atherosclerosis, and adverse clinical outcomes. However, its correlation with cerebrovascular disease (CVD) mortality remains unclear. This study aimed to investigate the relationship between TyG index and mortality in patients with CVD.MethodsPatient data sourced from the Medical Information Mart for Intensive Care -IV database were categorized based on TyG quartiles. Kaplan–Meier survival analysis was used to estimate survival disparities among the TyG subgroups. Cox proportional risk modeling was used to examine the association between the TyG index and mortality. Generalized summation models were applied to fit the smoothed curves. log-likelihood ratio test were used to analyze the non-linear relationship.ResultsThe study comprised 1,965 patients (50.18% were male). The 28-day and 90-day mortality rates were 20.10% and 24.48%, respectively. The TyG index exhibited a linear relationship with the 28-day mortality (Hazards ratio (HR), 1.16; 95% confidence interval (CI), 0.99–1.36) and the 90-day mortality (HR, 1.18; 95% CI, 1.02–1.37). In the TyG Q4 group, each 1 mg/dl increase was linked to a 35% rise in the risk of 28-day mortality and a 38% increase in the risk of 90-day mortality. Subgroup analyses highlighted a more substantial association between TyG index and 90-day mortality in the diabetic group.ConclusionOur findings underscore the positive association between TyG and the 28- and 90-day mortality rates in patients with CVD. This insight may prove pivotal for identifying at-risk populations and enhancing risk prediction in the clinical management of CVD.

Impact of Anomalous Diffusion Phenomenon on Molecular Information Delivery in Bounded Environment.

Through this paper, a three-dimensional molecular communication (MC) inside a cuboid container is considered. Instead of normal diffusion phenomenon, the anomalous diffusion phenomenon is incorporated which enhances the practicability of the model. The Fick's law is re-defined for the considering rectangular coordinate system in which information carrying molecules (ICMs) diffuse anomalously in the environment. The impact of flow of the fluid along the +x direction in the environment is also considered. Moreover, considering free propagator phenomenon, the expressions of spatio-temporal probability density function (PDF) of the ICMs is derived for the considered model. Further, the novel closed-form expressions for first arrival time density (FATD) of the ICM, survival probability (SP) at any time, and its corresponding first arrival probability (FAP) are also derived. Furthermore, the considered MC model is also analyzed in terms of minimum bit-error-rate (BER) using log-likelihood ratio test (LLRT) optimal detector. The derived expressions are verified using MATLAB based particle-based and Monte-Carlo simulations.

Association between serum uric acid and homocysteine levels among adults in the United States: a cross-sectional study

BackgroundMany studies have shown that both elevated serum uric acid (SUA) levels and hyperhomocysteinemia are risk factors for atherosclerosis. However, the relationship between the two has not been thoroughly investigated.ObjectiveThis study aimed to explore the possible link between SUA levels and homocysteine (Hcy) levels.MethodsIn this cross-sectional study, 17,692 adults aged > 19 years in National Health and Nutrition Examination Survey from 1999 to 2006 were analyzed. Multivariable linear regression analysis was performed to assess the association between SUA and Hcy levels. In addition, smooth curve fitting (penalized spline method) and threshold effect analysis were performed.ResultsMultivariable linear analysis showed that Hcy levels increased by 0.48 µmol/L (β = 0.48, 95%CI: 0.43–0.53) for every 1 mg/dL increase in SUA levels. We found a nonlinear relationship between SUA and Hcy levels. The results of threshold effect analysis showed that the inflection point for SUA levels was 7.1 mg/dL (β = 0.29, 95% CI: 0.23–0.36 and β = 1.05, 95% CI: 0.67–1.43 on the left and right sides of the inflection point, respectively). The p-values was less than 0.001 when using the log likelihood ratio test. This nonlinear relationship was also found in both sexes. The inflection point for SUA levels was 5.4 mg/dL in males and 7.3 mg/dL in females, respectively.ConclusionsThis cross-sectional study showed that the SUA levels were positively correlated with Hcy levels. And we found a nonlinear relationship between SUA and Hcy levels.

140 Targhee Sire Benchmarking at the U.S. Sheep Experiment Station

Abstract The Targhee breed was developed at the U.S. Sheep Experiment Station (USSES) starting in 1926, and has become an established range breed used commercially in the Western U.S. Our objective was to benchmark the performance of industry-based (external) Targhee sires with those currently in use at USSES. Nineteen Targhee sires from 12 flocks were incorporated into the USSES breeding flock starting with the 2015 breeding season. Data were measured through 2022 for 3 production and 12 wool traits with a range of 180 to 1,967 records per trait. Externally sourced sires averaged 38.3 progeny (7 to 78), with 0 to 4 ram lambs (15 total) and 0 to 15 (106 total) ewe lambs retained per sire in the flock. They were ancestors of 984 grand-progeny. USSES sires averaged 25.0 progeny (5 to 52), with 0 to 1 ram lambs (2 total) and 0 to 8 (53 total) ewe lambs retained per sire. They had 275 grand-progeny. Pedigree data was used to compute the marginal genetic contributions for each sire to the current flock using ENDOG. External sires had a cumulative contribution of 31.9 percent (0.4 to 3.9) while the USSES sires contributed 1.4 percent (0.0 to 0.9). Using R, fixed effects examined were age of dam, lamb sex, lamb birth year, grazing group, and type of birth/rearing. Significant variation explained in a trait by main effects (P &amp;lt; 0.005), and their two-way interactions (P &amp;lt; 0.001), were included in the final linear mixed models fitted. Externally sourced and USSES sires were assigned to separate genetic groups to account for the anticipated differences in genetic base. Using WOMBAT, a univariate animal model was fitted to estimate variance components and predict estimated breeding values for each lamb trait. Selection of random effects was based on log-likelihood ratio tests. Final models fitted and estimated heritabilities are summarized in Table 1. Total litter weight at 120 days per ewe lambing (TW120) was evaluated using a repeated measures model with direct additive and permanent environmental random effects of the ewe. Genetic group solutions were not significantly different (P &amp;gt; 0.05) for any traits evaluated. Since both sire groups originated from the same population, this suggests significant selection divergence had not occurred between industry and USSES flocks. Incorporation of external Targhee sires increased the genetic diversity of the USSES flock. It also strengthened industry ties to the USSES flock, which will benefit the commercial genetic evaluation conducted by the National Sheep Improvement Program. USDA is an equal opportunity provider and employer.

A time-varying Copula-based approach to quantify the effects of antecedent drought on hot extremes

Hot extremes may adversely impact human health and agricultural production. Owing to anthropogenic and climate changes, the close and dynamic interaction between drought and hot extremes in most areas of China need to be revisited from the perspective of nonstationarity. This study therefore proposes a time-varying Copula-based model to describe the nonstationary dependence structure of summer extreme temperature (SET) and antecedent soil moisture condition to quantify the dynamic risk of hot extremes conditioned on dry/wet condition. A general statistical inspection procedure which was composed of maximum likelihood (ML)-based estimation, nonstationary Goodness-of-fit (GOF) tests, the log likelihood ratio (LR) tests and minimum corrected Akaike information criterion-based selection was promoted to select the best-fitted nonstationary models efficiently. This study proposed a new approach to identify the soil moisture driving law over extreme temperature from the point view of tail monotonicity and nonstationary risk assessment. Owing to the LTI-RTD (left tail increasing and right tail decreasing) tail monotonicity for dependence structure of these two extremes derived from most areas, two kinds of the driving laws of soil moisture over SET were detected. Because of the spatiotemporal divergence of sensitivity index derived from tail monotonicity (SITM), we can conclude that the spatial and temporal heterogeneity of response degree of ET over the variations of antecedent dry/wet conditions is evident. Incorporation of nonstationarity and tail monotonicity helps identify the changes of driving mechanism (laws) between soil moisture and hot extremes.

23 Latent Profiles of Children Referred for Possible Autism

Objective:Autism is a neurodevelopmental disorder characterized by impairments in social communication and the presence of restricted and repetitive behaviors (RRBs). Clinical diagnosis of autism is often complicated by heterogeneity in core autism traits and other individual characteristics (e.g., cognition). Previous literature suggests that degree of autism characteristics, cognitive ability, and age contribute to identifying homogenous subgroups of autism, which facilitates prognosis and treatment planning. The present study extends these findings by examining profiles of cognition, age, and autism characteristics (measured by the Autism Diagnostic Observation Schedule, Second Edition [ADOS-2]) in a clinical sample of school-aged children presenting with concern for possible autism. Profiles are also described according to whether children received an autism diagnosis and clinician ratings of emotional/behavioral problems, which have been shown to influence diagnostic clarity when assessing for autism.Participants and Methods:We conducted a retrospective chart review of 188 children (68% male) ages 4-17 years (M=8.9) who were referred for an autism evaluation. Latent profile analysis was conducted using age, ADOS-2 Social Affect (SA) and RRB scores, and verbal and non-verbal intelligence quotients (VIQ/NVIQ). Model fit comparing 2, 3, 4, and 5-class models was assessed using log-likelihood, AIC, BIC, SABIC, entropy, and Lo, Mendell, and Rubin (LMR) and bootstrap likelihood ratio (BLRT) tests. The frequency of clinical autism diagnosis and ADOS-2 emotional/behavioral problems were calculated across profiles in the best-fitting model.Results:The 5-class model demonstrated the best fit. The following characteristics were observed across five profiles: 1) mean age = 9.5 years, Low Average VIQ/NVIQ, and low SA (M=5.2) and RRB (M=0.7) scores; 2) mean age = 7.3 years, Average VIQ/NVIQ, and low SA (M=3.1) and RRB (M=0.8) scores; 3) mean age = 10.1 years, Low Average VIQ/NVIQ, and high SA (M=11.3) and RRB (M=4.2) scores; 4) mean age = 8.8 years, Average VIQ/NVIQ, and moderately high SA (M=9.6) and RRB (M=3.4) scores; and 5) Exceptionally High VIQ, Above Average NVIQ, and comparatively mid-level SA (M=6.6) and RRB (M=3.6) scores. Autism diagnosis and emotional/behavioral problems varied across profiles. Profiles 1 and 2 contained lower diagnosis rates (33% and 10%, respectively). Profiles 3 and 4 contained the highest diagnosis rates (97% in both), followed by profile 5 (75%). In terms of emotional/behavioral problems, Profile 2 exhibited the highest overactivity (56%). Profile 3 demonstrated the highest rate of tantrums/disruptive behaviors (20%).Conclusions:Findings revealed distinct profiles of IQ and autism characteristics within a clinical sample of school-aged children referred for possible autism. Children with the highest scoring ADOS profile were older compared to other profiles. Higher and lower scoring ADOS profiles exhibited both lower and higher IQ scores. Descriptive analyses suggested that the frequency of autism diagnosis was notably higher in moderate and high-scoring ADOS profiles; however, emotional/behavioral problems were salient in only one low and one high-scoring ADOS profile. The findings suggest that higher-scoring ADOS profiles consistently demonstrated high autism diagnosis rates but varied across IQ and behavioral problems. These results have implications for interpreting these characteristics during clinical autism diagnosis.

Investigating the spatial heterogeneity of factors influencing speeding-related crash severities using correlated random parameter order models with heterogeneity-in-means

ABSTRACT Speeding has been acknowledged as a critical determinant in increasing the risk of crashes and their resulting injury severities. This paper employs Global Moran’s I coefficient and local Getis – Ord G* indexes to systematically account for the spatial distribution feature of speeding-related crashes, study the global spatial pattern of speeding-related crashes, and identify severe crash cluster districts. The findings demonstrate that severe speeding-related crashes within the state of Pennsylvania have a spatial clustering trend, where four crash datasets are extracted from four hotspot districts. Two log-likelihood ratio (LR) tests were conducted to determine whether speeding-related crashes classified by hotspot districts should be modeled separately. The results suggest that separate modeling is necessary. To capture the unobserved heterogeneity, four correlated random parameter order models with heterogeneity in means are employed to explore the factors contributing to crash severity involving at least one vehicle speeding.

Investigating the difference in factors influencing the injury severity between daytime and nighttime speeding-related crashes

This study investigates the differences in the factors affecting the injury severity of speeding-related crashes occurring in the daytime and nighttime. Two log-likelihood ratio tests are conducted to validate whether speeding-related crashes classified by daytime and nighttime should be modeled separately. The result proves that separate modeling is necessary. Two correlated random parameter order probit models with heterogeneity in means are conducted using the data collected from 2018 to 2020 in the United States. Model estimation results show that urban areas, speed limits, and young and older drivers are temporal instability. Angle crashes, head-on crashes, intersections, downhill, exceeding the speed limit, drunk driving, and motorcycles are statistically significant in both models with an increased crash severity. Interaction and heterogeneity effects between random parameters are also reported. For instance, large trucks driving above the speed limit are more likely to increase the probability of severe injury.

Comparative evaluation for alternative variable importance rankings for pedestrian injury severities

Little research is dedicated to evaluating the performance difference of various metrics in ranking predictor importance in the traffic safety field. To this end, the main objective of the current paper is to evaluate and quantify different methods for sorting the variable importance related to crash severity. A comprehensive database for pedestrian-related crashes in the state of California was developed. Four popular measurement metrics used in the past were chosen for evaluation purpose: Mean Decrease Accuracy (MDA), Mean Decrease Gini (MDG), log-likelihood ratio test associated with multinomial logit model, and Principal Component Analysis (PCA). The former two metrics come under the same umbrella of the Random Forest (RF) technique, while the latter two are methods belonging to different domains. The results show the alternative methods yield different variable importance rankings with PCA being isolated from others. The two methods under the same domain of the random forest, or MDG and MDA, have the most common results, but still reveal a 17% ranking difference. It is anticipated that the results could raise more awareness of the importance of selecting the appropriate metrics to evaluate the predictor importance from different perspectives.

Nonlinear relationship between atherogenic index of plasma and the risk of prediabetes: a retrospective study based on Chinese adults

BackgroundThe atherogenic index of plasma (AIP) can reflect the burden of atherosclerosis. Hyperglycemia is one of the leading causes of atherosclerosis. However, the relationship between AIP and prediabetes is rarely studied. Therefore, we aimed to explore the relationship between AIP and prediabetes.MethodsThis retrospective cohort study recruited 100,069 Chinese adults at the Rich Healthcare Group from 2010 to 2016. AIP was calculated according to Log10 (triglyceride/high-density lipoprotein cholesterol) formula. Cox regression method, sensitivity analyses and subgroup analyses were used to examine the relationship between AIP and prediabetes. Cox proportional hazards regression with cubic spline functions and smooth curve fitting was performed to explore the non-linearity between AIP and prediabetes. The two-piece Cox proportional hazards regression model was used to determine the inflection point of AIP on the risk of prediabetes.ResultsAfter adjusting for confounding covariates, AIP was positively associated with prediabetes (HR: 1.41, 95%CI: 1.31–1.52, P < 0.0001). The two-piecewise Cox proportional hazards regression model discovered that the AIP’s inflection point was 0.03 (P for log-likelihood ratio test < 0.001). AIP was positively associated with the risk of prediabetes when AIP ≤ 0.03 (HR: 1.90, 95%CI: 1.66–2.16, P < 0.0001). In contrast, When AIP > 0.03, their association was not significant (HR: 1.04, 95%CI: 0.91–1.19, P = 0.5528).ConclusionThis study shows that AIP was positively and non-linearly associated with the risk of prediabetes after adjusting for other confounding factors. When AIP ≤ 0.03, AIP was positively associated with the risk of prediabetes.

Wide dynamic range signal detection for underwater optical wireless communication using a PMT detector.

In the underwater optical wireless communication (UOWC) scenario, a photomultiplier tube (PMT) with higher sensitivity, lower noise, and a larger receiver area is employed as the photon detector to further extend the transmission distance. Due to the complex underwater environment, the high directionality of the light beam, and the vibration of a transceiver, the incident optical power usually spans a very wide dynamic range, and the PMT may operate in any one of the three regimes: pulse, transition, and waveform. While it is difficult to obtain the analytical characterization of the output electric signals across these regimes, this paper resorts to experimental measurements of the upsampled discrete samples within a training symbol duration. Among different statistical distribution fitting options, generalized extreme value (GEV) distribution is found to show excellent performance in fitting the probability density function (PDF) of either multiple samples or the superimposition of all samples within a symbol duration. Then joint sample distribution (JSD) based and superimposed sample distribution (SSD) based symbol detection methods are proposed by adopting the GEV distribution and log-likelihood ratio (LLR) testing criterion. The proposed methods are experimentally evaluated under different received signal optical powers, data rates, and sampling rates. They are shown to outperform the Poisson and Gaussian based maximum likelihood detection methods which are employed for the pulse regime and waveform regime respectively. Furthermore, the effectiveness of the proposed methods in alleviating strong ambient radiation is experimentally verified.

Genetic evaluation of growth rate and efficiency-related traits in Dorper × local crossbred sheep population.

The present study was carried out to estimate genetic and phenotypic parameters for growth rate and efficiency-related traits in Dorper crossbred sheep population. Data on body weight collected from 2012 to 2021 at Debre Birhan Agricultural Research Center, Amhara Regional State, Ethiopia, were used to estimate phenotypic and genetic parameters for daily gain from birth to weaning (DG0-3), daily gain from weaning to 6 months (DG3-6), and daily gain from 6 months to yearling (DG6-12) and corresponding Kleiber ratios (KR0-3, KR3-6, KR6-12), efficiency of growth (GE0-3, GE3-6, GE6-12), and relative growth rate (RG0-3, RG3-6, RG6-12). Genetic parameters were estimated by restricted maximum likelihood (REML) procedure fitting six different univariate animal models and the most appropriate model for each trait was determined by log-likelihood ratio test. Multivariate analysis was carried out to estimate correlations between traits. Year and season of birth had a significant effect (p<0.001) in all studied traits. Direct heritability estimates for DG0-3, DG3-6, DG6-12, KR0-3, KR3-6, KR6-12, GE0-3, GE3-6, GE6-12, GR0-3, GR3-6, and GR6-12 were 0.45±0.15, 0.04±0.06, 0.15±0.11, 0.30±0.08, 0.13±0.11, 0.14±0.12, 0.34±0.15, 0.39±0.17, 0.31±0.14, 0.25±0.08, 0.23±0.13, and 0.23±0.13 respectively. Genetic correlation estimates between DG3-6 and other traits were positive and high in magnitude to their respective growth phase (0.95, 0.86, and 0.91 for KR3-6, GE3-6, and GR3-6 respectively). As the Dorper crossbred sheep are reaches market weight at about 6 months of age, focusing on improving traits measured during weaning to 6 months of age is more feasible. Selection based on DG3-6 is recommended to improve efficiency-related traits.

Asymptotic distributions for likelihood ratio tests for the equality of covariance matrices

Consider k independent random samples from p-dimensional multivariate normal distributions. We are interested in the limiting distribution of the log-likelihood ratio test statistics for testing for the equality of k covariance matrices. It is well known from classical multivariate statistics that the limit is a chi-square distribution when k and p are fixed integers. Jiang and Qi (Scand J Stat 42:988–1009, 2015) and Jiang and Yang (Ann Stat 41(4):2029–2074, 2013) have obtained the central limit theorem for the log-likelihood ratio test statistics when the dimensionality p goes to infinity with the sample sizes. In this paper, we derive the central limit theorem when either p or k goes to infinity. We also propose adjusted test statistics which can be well approximated by chi-squared distributions regardless of values for p and k. Furthermore, we present numerical simulation results to evaluate the performance of our adjusted test statistics and the log-likelihood ratio statistics based on classical chi-square approximation and the normal approximation.

Relationship Between Plasma Aldosterone Concentrations and Non-Alcoholic Fatty Liver Disease Diagnosis in Patients with Hypertension: A Retrospective Cohort Study.

To investigate the association between plasma aldosterone concentration (PAC) and non-alcoholic fatty liver disease (NAFLD) diagnosis in Chinese hypertensive patients. We conducted a retrospective study of all patients diagnosed with hypertension between January 1, 2010, and December 31, 2021. We included 3713 hypertensive patients based on the criteria for inclusion and exclusion. PAC measurement was performed using a radioimmunoassay. NAFLD was diagnosed using abdominal ultrasonography. Cox regression analysis was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for univariable and multivariable models. A generalized additive model was used to identify nonlinear relationships between PAC and NAFLD diagnosis. A total of 3713 participants were included in the analysis. Over a median follow-up of 30 months, 1572 hypertensive individuals developed new-onset NAFLD. When PAC was used as a continuous variable, the risk of NAFLD increased by 1.04 and 1.24-fold for each 1 ng/dL and 5 ng/dL increase in PAC, respectively. When PAC was considered a categorical variable, the HR for tertile 3 was 1.71 (95% CI, 1.47-1.98, P < 0.001) compared to tertile 1. Overall, there was a J-shaped relationship between PAC and new-onset NAFLD. By fitting a two-piecewise linear regression model and using a recursive algorithm, we identified a PAC inflection point at 13 ng/dL (log-likelihood ratio test, P = 0.005). In adjusted model 3, for PAC ≥ 13 ng/dL, a 5 ng/dL increase in PAC was associated with a 30% increase in the risk of new-onset NAFLD (95% CI, 1.25-1.35, P < 0.001). The study revealed a non-linear relationship between elevated PAC levels and the incidence of NAFLD in hypertensive patients. Notably, the risk of new-onset NAFLD was significantly increased when PAC levels were ≥13 ng/dL. Larger, prospective studies are necessary to confirm these findings.

Approach to Quantify Eye Movements to Augment Stroke Diagnosis With a Non-Calibrated Eye-Tracker.

We investigated 1) the need for calibration to measure eye movement symmetry in healthy controls and 2) the potential of eye movement symmetry to distinguish between healthy controls and patients. We analyzed fixations, smooth pursuits, saccades, and conjugacy measured by a Spearman correlation coefficient and utilized a linear mixed-effects model to estimate the effect of calibration. Healthy participants (n = 18) did not differ in correlations between calibrated and non-calibrated conditions for all tests. The calibration condition did not improve the linear mixed effects model (log-likelihood ratio test p = 0.426) in predicting correlation coefficients. Interestingly, the patient group (n = 17) differed in correlations for the DOT (0.844 [95% CI 0.602, 0.920] vs. 0.98 [95% CI 0.976, 0.985]), H (0.903 [95% CI 0.746, 0.958] vs. 0.979 [95% CI 0.971, 0.986]), and OKN (0.898 [95% CI 0.785, 0.958] vs. 0.993 [95% CI 0.987, 0.996]) tests compared to healthy controls along the x-axis. These differences were not observed along the y-axis. This study suggests that automated eye tracking can be deployed without calibration to measure eye movement symmetry. It may be a good discriminator between normal and abnormal eye movement symmetry. Validation of these findings in larger populations is required.

Sparsity-Based Classification Approaches for Radar Data in the Presence of Clutter Edges and Discretes

Modern radars face challenging scenarios characterized by high levels of heterogeneity that make conventional detection/estimation algorithms no longer effective since most of them rely on the well-known homogeneous environment. In this paper, we propose innovative classification schemes capable of identifying the radar operating scenario in terms of clutter properties. To this end, different situations are accounted for at the design stage ranging from the homogeneous environment to the simultaneous presence of clutter edges and clutter discretes/outliers. Then, we conceive decision rules based upon the so-called penalized log-likelihood ratio test that exploits the inherent sparse nature of the observed scene. In this context, two different sparsity-promoting priors are used to model the behavior of clutter discretes/outliers and the unknown parameters are estimated by means of cyclic procedures. The performance analysis, conducted on both simulated and real-recorded data, highlights the effectiveness of the proposed classifiers at least for the considered operating parameter values. Remarkably, radar systems can take advantage of such classification results by selecting homogeneous data that can yield reliable estimates (namely, that are functions of homogeneous data) of the unknown interference parameters and, hence, enhanced detection performance with respect to the case where unclassified heterogeneous data are used.