Final Multiple Linear Regression Model Research Articles

Reaction Time in Fibromyalgia Patients.

Fibromyalgia has unknown aetiology and is associated with reduced information processing speed and therefore prolonged reaction time. However, the processes underlying this are unknown. First, to compare the reaction time in a cohort of fibromyalgia patients and a matched group of normal controls. Second, to assess whether detailed symptoms of pain and autonomic function, as well as measures of tinnitus, fatigue, daytime sleepiness and Mycoplasma pneumoniae infection are predictors of reaction time in fibromyalgia. The between-groups mean serial five-choice reaction time difference was assessed in a cohort of fibromyalgia patients and in a matched group of normal controls in an analytical case-- controlled study. With the mean serial five-choice reaction time as the dependent variable for the fibromyalgia group, a mixed stepwise multiple linear regression was performed with inputs relating to pain, dysautonomia, tinnitus, fatigue, daytime sleepiness and Mycoplasma pneumoniae infection. The mean (standard error) serial five-choice reaction time for the fibromyalgia group was 448.4 (23.0) ms, compared with 386.3 (8.3) ms for the control group (p = 0.007). The final multiple linear regression model (p < 0.001; adjusted R2 = 0.772) contained 13 predictors: eight sensory pain and three affective pain parameters, and Mycoplasma pneumoniae IgG and IgA assay results. Certain sensory and affective pain parameters, as well as Mycoplasma pneumoniae infection, appear to be predictors of reaction time in fibromyalgia. Further research into the pathophysiological mechanisms by which they affect information processing is warranted and may shed light on the aetiology of fibromyalgia.

Machine-learning-based similarity meets traditional QSAR: “q-RASAR” for the enhancement of the external predictivity and detection of prediction confidence outliers in an hERG toxicity dataset

Recently, the concept of quantitative Read-Across Structure-Activity Relationship (q-RASAR) has been introduced by using various Machine Learning (ML) - derived similarity functions in the traditional quantitative structure-activity relationship (QSAR) modeling framework with the objective of enhancing the external predictivity of models while using the same available chemical information content. The present study uses the hERG K+ channel inhibition cardiotoxicity, a pharmaceutically relevant endpoint, as the modeling set for making predictions using the novel q-RASAR approach, as the approach combines the merits of QSAR and Read-Across, and generates simple and interpretable models using various similarity and error-based measures as descriptors. The cardiotoxicity data (in terms of pIC50 values) were collected from the literature. The curated data set was then divided into training and test sets using the sorted response-based division algorithm. The important set of features was identified based on the internal validation metrics of initial genetic algorithm models. Based on the features selected in the final Multiple Linear Regression (MLR) model, RASAR descriptors were computed using a tool available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home. The RASAR descriptors were then merged with the previously selected features, and an MLR q-RASAR model was generated using the grid search approach. The prediction outliers were then identified using the novel DTC Applicability Domain Plot, and the q-RASAR models were used for predictions after the removal of prediction outliers. A final Partial Least Squares (PLS) q-RASAR model was generated to obviate inter-correlation among descriptors. Various other Machine Learning approaches were also employed with the optimization of relevant hyperparameters based on the cross-validation approach, and the final test set prediction results were compared. Based on the performance in the test set predictions and interpretability, the PLS q-RASAR model was chosen as the final model which provided enhanced predictivity in comparison to previously reported models even without using 3-D descriptors. This model can thus be used for the quick screening of molecules, even before their synthesis, to estimate their cardiotoxic potential thus prioritizing molecules for further experimental testing in the drug discovery pipeline. A Java-based prediction tool has also been developed for the quick screening of cardiotoxic properties of query compounds and made available from https://sites.google.com/jadavpuruniversity.in/dtc-lab-software/home.

Transformational leadership and predictors of resilience among registered nurses: a cross-sectional survey in an underserved area

BackgroundHigh resilience increases nurses' ability to cope with job-related stressors and enhances job satisfaction and, consequently, their retention. The study aims to identify resilience predictors and perceptions of transformational leadership in a convenience sample of registered nurses in Lebanon.MethodsAn anonymous cross-sectional survey of a convenience sample of 240 registered nurses working for more than a year at three private hospitals in an underserved area in South Lebanon was used. The survey instrument included demographic questions, the True Resilience Scale ©, and the Global Transformational Leadership Scale. Multiple linear regression was used to assess the predictors of resilience after a descriptive analysis of the study variables.ResultsThe survey response rate was 85%. The nurses' mean resilience score was 119.4 (SD 15.3), and their perception of transformational leadership score was M = 25.0, SD = 6.8. Compared to bedside nurses, nurse managers, nurses with more than five years of experience, and nurses in critical nursing units had statistically significant higher resilience scores (p < 0.05). Resilience scores and perception of global transformational leadership were moderately correlated (r = 0.53, p < 0.05). In the final multiple linear regression model, 30% of the variation in resilience scores was explained by designation (p < 0.05) and perception of Global Transformational Leadership (p < 0.01). Perception of global transformational leadership scores explained 29% of the variance in resilience scores. Designation and perception of global transformational leadership predicted resilience in this sample.ConclusionsA national survey of the Lebanese nursing workforce is needed to achieve an improved predictive model and support policy developments to increase resilience among bedside nurses and retain them in the nursing workforce. Nurse administrators can help by strengthening their transformational leadership behaviors. Consistent use of transformational leadership styles will strengthen bedside nurses' resilience, increase nurse retention, and help sustain the Lebanese nursing workforce.

Correlation between three-dimensional transperineal ultrasound and pelvic floor electromyography in women with stress urinary incontinence.

To investigate the relationships among pelvic floor myoelectric level, ultrasound and stress urinary incontinence in women. 218 women with SUI and 300 normal women were studied. The main outcomes were to determine the relationship between SUI and high-risk factors, PFM intensity, pelvic floor EMG value, and pelvic floor ultrasound data. In the pelvic floor EMG data, the abnormal rate of type I muscle fibre strength, type I muscle fibre fatigue, type II muscle fibre strength and type II muscle fibre endurance in the SUI group reached more than 50%. The abnormal rates of type I muscle fibre strength and type II muscle fibre strength in the severe SUI group were more significant than those in the mild and moderate SUI. The funnelization of the black neck urethra, bladder neck mobility, posterior angle of the black neck urethra, urinary increment angle and urinary rotation angle of the SUI group were significantly increased. The levator ani muscle in the SUI group was thinner, and the difference was statistically significant. The analysis of the variance results of the overall significance of the regression model were tested, and the final multiple linear regression model was statistically significant. With the help of a convenient and economic means of the early detection of SUI, the diagnosis rate can be improved so that SUI tendency can achieve a diagnosis and treatment through nonsurgical treatment with fewer complications and a low risk and improve the quality of life of middle-aged and elderly women.

Machine Learning-Assisted Identification and Quantification of Hydroxylated Metabolites of Polychlorinated Biphenyls in Animal Samples.

Laboratory studies of the disposition and toxicity of hydroxylated polychlorinated biphenyl (OH-PCB) metabolites are challenging because authentic analytical standards for most unknown OH-PCBs are not available. To assist with the characterization of these OH-PCBs (as methylated derivatives), we developed machine learning-based models with multiple linear regression (MLR) or random forest regression (RFR) to predict the relative retention times (RRT) and MS/MS responses of methoxylated (MeO-)PCBs on a gas chromatograph-tandem mass spectrometry system. The final MLR model estimated the retention times of MeO-PCBs with a mean absolute error of 0.55 min (n = 121). The similarity coefficients cos θ between the predicted (by RFR model) and experimental MS/MS data of MeO-PCBs were >0.95 for 92% of observations (n = 96). The levels of MeO-PCBs quantified with the predicted MS/MS response factors approximated the experimental values within a 2-fold difference for 85% of observations and 3-fold differences for all observations (n = 89). Subsequently, these model predictions were used to assist with the identification of OH-PCB 95 or OH-PCB 28 metabolites in mouse feces or liver by suggesting candidate ranking information for identifying the metabolite isomers. Thus, predicted retention and MS/MS response data can assist in identifying unknown OH-PCBs.

P-063 Multivariate analysis identifies oxidative stress levels and acrosome status of motile spermatozoa as independent predictors of motile sperm hyaluronan binding ability

Abstract Study question Is it possible to predict motile sperm hyaluronan binding ability (HBA) from motile sperm functional parameters? Summary answer Using multivariate analysis, oxidative stress levels and acrosome status of motile spermatozoa, derived from semen swim-up, were identified as predictors of sperm HBA. What is known already Semen analysis is a gold standard practice for fertility evaluation. However, motility and morphology of spermatozoa are not always indicative of the molecular makeup of sperm cells. In this context, several sperm functional tests were developed to enhance our understanding of spermatozoa biology. Interestingly, several studies have shown that the plasma membrane of mature sperm cells contain hyaluronan binding sites. HBA was associated with intact acrosome, decreased DNA damage, and high viability. Nevertheless, it has not been demonstrated yet if hyaluronan binding ability can be predicted solely by swim-up derived- motile spermatozoa functional parameters. Study design, size, duration A prospective study was performed at Al-Hadi Medical Center, beirut, Lebanon, between January and July 2020. Freshly ejaculated semen samples obtained from infertile men with concentration of ≥ 20 x 106/ml and with total sperm motility of ≥ 30% were included. The primary outcome was to assess if the motile sperm functional parameters may influence HBA. A sample size of 54 was calculated using power = 85% and alpha = 5% for multiple linear regression. Participants/materials, setting, methods 54 semen samples were assessed according to WHO guidelines (2010). Thereafter, samples were processed using the semen swim-up technique. Supernatants containing motile spermatozoa were collected for further analysis. In motile spermatozoa-enriched fractions, chromatin integrity was assessed using toluidine blue (TB) staining. Oxidative stress levels were detected using a nitroblue tetrazolium (NBT) test. Acrosome status was determined using triple staining technique. HBA was evaluated via a commercially available hyaluronan binding assay (HBA® Assay). Main results and the role of chance In the motile spermatozoa-enriched fractions, mean ± standard deviations for concentration, progressive motility, non-progressive motility and normal morphology were 26.17±11.48, 76±18.97, 20.94±12.61 and 0.75 ± 1.4, respectively. In addition, mean ± standard deviations for TB + cells, NBT + cells, living spermatozoa with intact acrosome, and HBA were 16.42 ± 13.4, 57.4 ± 9.4, 93.9 ±3.2, and 48.98±11.95, respectively. The values of the HBA had a non-normal distribution; therefore, these values were first linearized by taking the logarithm of the outcome. Afterwards, multiple linear regression (MLR) was used to predict the outcome. The overall regression of the final model was statistically significant (R2 = 0.346), F(4.43) =5.962, p = 0.001. The results of the final MLR model indicated that a unit increase in non-progressive motility (%) (p = 0.002) and NBT + cells (%) (p = 0.009) increased the HBA by 1.505 units and 1.409 units, respectively. However, a unit increase in dead spermatozoa with unreacted acrosome (%) (p = 0.032) and living spermatozoa with reacted acrosome (%) (p = 0.026) decreased the HBA by 1.317 units and 1.342 units, respectively. Limitations, reasons for caution This is an interim study and these results should be taken as preliminary. In order to confirm these findings, further studies including larger sample size and motile spermatozoa derived from semen samples with abnormal parameters (such as severe asthenozoospermia, leukocytospermia, severe oligozoospermia) are required. Wider implications of the findings Several studies indicated that using damaged spermatozoa may affect the intracytoplasmic sperm injection (ICSI) outcomes. In addition, using damaged spermatozoa during fertilization may predispose the offspring to various diseases later in life. These results may be considered as an impetus to reconsider sperm selection during ICSI. Trial registration number Not applicable

Compassion fatigue, burnout, compassion satisfaction and depression among emergency department physicians and nurses: a cross-sectional study

ObjectivesEmergency department physicians and nurses are at high risk of compassion fatigue, burnout and depression. The purpose of this study was to examine the inter-relationship between compassion fatigue, burnout, compassion...

An Experimental Urban Case Study with Various Data Sources and a Model for Traffic Estimation.

A reliable estimation of the traffic state in a network is essential, as it is the input of any traffic management strategy. The idea of using the same type of sensors along large networks is not feasible; as a result, data fusion from different sources for the same location should be performed. However, the problem of estimating the traffic state alongside combining input data from multiple sensors is complex for several reasons, such as variable specifications per sensor type, different noise levels, and heterogeneous data inputs. To assess sensor accuracy and propose a fusion methodology, we organized a video measurement campaign in an urban test area in Zurich, Switzerland. The work focuses on capturing traffic conditions regarding traffic flows and travel times. The video measurements are processed (a) manually for ground truth and (b) with an algorithm for license plate recognition. Additional processing of data from established thermal imaging cameras and the Google Distance Matrix allows for evaluating the various sensors’ accuracy and robustness. Finally, we propose an estimation baseline MLR (multiple linear regression) model (5% of ground truth) that is compared to a final MLR model that fuses the 5% sample with conventional loop detector and traffic signal data. The comparison results with the ground truth demonstrate the efficiency and robustness of the proposed assessment and estimation methodology.

Impaired Lower Extremity Biomechanics, Hip External Rotation Muscle Weakness, and Proximal Femoral Morphology Predict Impaired Single-Leg Squat Performance in People With FAI Syndrome

Background: Impairments in squat depth have been reported in patients with femoroacetabular impingement syndrome (FAIS). However, little is known about single-leg squat (SLS) performance in these patients, despite this task being commonly used in the rehabilitation and training settings. Purpose/Hypothesis: The aims of this study were (1) to investigate whether patients with FAIS demonstrate differences in SLS performance compared with healthy controls and (2) to determine whether dynamic range of motion (ROM), muscle strength, hip morphologic measures, hip pain, and hip-specific function predict SLS performance in patients with FAIS. We hypothesized that patients with FAIS would demonstrate impaired SLS performance and that impaired hip biomechanics, muscle strength, and hip-specific function would predict squat performance in patients with FAIS. Study Design: Controlled laboratory study. Methods: Three-dimensional (3D) kinematic data were collected at 100 Hz using a 20-camera 3D motion capture system during 3 SLS trials in 34 patients with FAIS and 26 healthy controls. Isometric muscle strength was tested with a stationary handheld dynamometer in all participants. Squat performance was quantified by squat depth (in meters), and the biomechanical variables of dynamic ROM of the pelvis, the hip, the knee, and the ankle in all planes were calculated. In patients with FAIS, femoral and acetabular morphology were measured using radiographic alpha angles and lateral center-edge angles. Hip pain and hip-specific function were measured using the visual analog scale for pain and the Hip Outcome Score Activities of Daily Living subscale, respectively. Two-tailed independent-samples t tests were used to determine between-group differences for squat depth, dynamic ROM variables, and muscle strength. A hierarchical multiple linear regression (MLR) model was used to determine whether biomechanical variables, muscle strength, hip morphology measures, hip pain, and hip-specific function were predictors of squat depth. All statistical analyses were performed using SPSS Version 26. Results: There were no between-group differences in age (FAIS, 30.0 ± 7.0 years vs controls, 27.3 ± 7.0 years; P = .18) or body mass index (FAIS, 23.1 ± 2.8 vs controls, 22.6 ± 3.2; P = .51). Squat depth was less in patients with FAIS compared with healthy controls (FAIS, 0.24 ± 0.4 m vs controls, 0.29 ± 0.05 m; P < .001). In the sagittal plane, patients with FAIS demonstrated less dynamic ROM of the hip (FAIS, 67.8°± 12.4° vs controls, 79.2°± 12.5°; P = .001) and the knee (FAIS, 71.9°± 9.4° vs controls, 78.9°± 13.2°; P = .02) compared with controls. Patients with FAIS also demonstrated a less dynamic coronal plane pelvis ROM (FAIS, 11.3°± 5.0° vs controls, 14.4°± 6.7°; P = .044). Patients with FAIS had reduced hip muscle strength of the hip external rotator (FAIS, 1 ± 0.3 N/kg vs controls, 1.2 ± 0.3 N/kg; P = .034), hip internal rotator (FAIS, 0.8 ± 0.3 N/kg vs controls 1 ± 0.3 N/kg; P = .03), and hip flexor (FAIS, 4 ± 1.1 N/kg vs controls, 4.8 ± 1.2 N/kg; P = .013) muscle groups. The hierarchical MLR revealed that the dynamic ROM of the hip, the knee, and the pelvis, the hip external rotation muscle strength, and the femoral alpha angles were all significant predictors of squat performance, and the final MLR model explained 92.4% of the total variance in squat depth in patients with FAIS. Conclusion: Patients with FAIS demonstrate impaired SLS squat performance compared with healthy controls. This impaired squat performance is predominantly predicted by sagittal plane knee and hip biomechanics and hip external rotator strength, and less by frontal plane pelvic ROM and hip morphology in patients with FAIS. Clinical Relevance: Clinicians should focus treatment on improving dynamic ROM and hip external rotator muscle strength to improve squat performance; however, femoral morphology should also be considered in the treatment paradigm.

Social Determinants of Health and Parenting Self-Efficacy Among Mothers of Preterm Infants.

To explore the relationships between social and environmental factors and parenting self-efficacy (PSE) among mothers of preterm infants hospitalized in neonatal intensive care units (NICUs) using a social determinants of health (SDoH) framework. We analyzed data from a prospective cohort study that included 187 mother-infant dyads admitted to four NICUs in the Mountain West region between June 2017 and December 2019. We used multivariable linear regression models to assess the independent associations between maternal and infant characteristics and PSE. Our final multiple linear regression model predicting the efficacy score including maternal race/ethnicity, age, insurance, employment status before giving birth, gestational age, depression, and having other children was significant (F(12,160) = 3.17, p = .0004, adjusted R¬2 = .131). Significant predictors of PSE were race/ethnicity (β= 3.3, p = .022), having another child/children (β= 4.2, p = .005), and depression (β= -4.2, p = .004). Findings suggest that social workers and medical practitioners should consider SDoH, such as insurance type, household income, and employment, along with traditional clinical indicators when assessing families' infant care needs. Social workers, medical practitioners, and researchers should be mindful of how implicit bias may influence the allocation of care and parental supports.

Mental Symptoms and Stress of Hospitalized Schizophrenia Patients With 2019 Novel Coronavirus Disease: An Observation Study.

Background: The 2019 novel coronavirus disease (COVID-19) is an extremely rapidly spreading respiratory infection caused by SARS-CoV-2. Many schizophrenic patients were infected with COVID-19 in Wuhan City, Hubei Province. This study took hospitalized schizophrenia patients with COVID-19 as the research subjects and observed the changes in psychopathology and stress of patients with COVID-19 and the accompanying social isolation.Methods: To sort and isolate potential COVID-19-infected patients, an isolated ward was set up from January 30, 2020, to March 30, 2020. Schizophrenia patients with COVID-19 were referred to this ward, and long-term hospitalized cases were included in this study. The Positive and Negative Syndrome Scale and Perceived Stress Scale were used to evaluate the severity of mental symptoms and psychological stress in the early stage of the outbreak of COVID-19, after the diagnosis of COVID-19 and after recovery. At the time of diagnosis, we also extracted the patient's routine blood, biochemical and other indicators and asked the patient's perception of COVID-19.Results: 21 hospitalized schizophrenia patients with COVID-19 were recruited in this study. The changes in PANSS scores were not significant (p = 0.225 baseline vs. diagnosed, p = 0.399 cured vs. diagnosed). The CPSS scores increased significantly after diagnosis and transfer to the isolation ward (p < 0.001 baseline vs. diagnosed, p < 0.001 cured vs. diagnosed). The course of schizophrenia was a protective factor of stress levels to cases (t = −3.25, p = 0.006), and patients' perception of COVID-19 was a risk factor (t = 2.48, p = 0.038). The final multiple linear regression model was statistically significant (F = 8.16, p < 0.001).Conclusion: Hospitalized schizophrenia patients with COVID-19 had increased stress levels and negative symptoms but alleviated positive symptoms after medical isolated treatment. This reminds us that in the face of major epidemics, we must specifically alleviate the psychological burden at the peak of the epidemic and improve the prognosis of patients after the epidemic.

AMPAr GluA1 Phosphorylation at Serine 845 in Limbic System Is Associated with Cardiac Autonomic Tone.

The central autonomic network, which is connected to the limbic system structures including the amygdala (AMY) and anterior hippocampus (aHIP), regulates the sympathetic and parasympathetic modulation of visceromotor, neuroendocrine, pain, and behavior manifestations during stress responses. Heart rate variability (HRV) is useful to estimate the cardiac autonomic tone. The levels of phosphorylation on the Ser831 and Ser845 sites of the GluA1 subunit of the AMPAr (P-GluA1-Ser845 and P-GluA1-Ser831) are useful markers of synaptic plasticity. The relation between synaptic plasticity in the human limbic system structures and autonomic regulation in humans is unknown. This study investigated the association between HRV and neurochemistry biomarkers of synaptic plasticity in AMY and aHIP. HRV indices were obtained from the resting state electrocardiogram of patients with drug-resistant mesial temporal lobe epilepsy (MTLE, n = 18) and the levels of P-GluA1-Ser845 and P-GluA1-Ser831 in the AMY and aHIP resected during the epilepsy surgery. A backward stepwise multiple linear regression models were used to analyze the association between HRV and synaptic plasticity biomarkers controlling for imbalances in the distribution of sociodemographic, clinical, neuroimaging, and neurosurgical variables. P-GluA1-Ser845 levels in AMY show a negative association (p < 0.05) with the 3 investigated parasympathetic autonomic HRV indices (SDNN, rMSSD, and HF) predicting 24 to 40% of their variation. The final multiple linear regression models include disease duration and levels of P-GluA1-Ser845 and predict 24 to 56% of cardiac autonomic tone variation (p < 0.01). P-GluA1-Ser845 levels in AMY and aHIP are negatively associated with the resting HRV in MTLE-HS indicating that increased synaptic efficiency in amygdala is associated with a parasympathetic cardiac autonomic tone impairment. The results suggest that specific changes in synaptic plasticity may be involved in the brain-heart axis regulation by the limbic system.

In Silico Modeling of Small Molecule Carboxamides as Inhibitors of SARS-CoV 3CL Protease: An Approach Towards Combating COVID-19.

The quantitative structure-activity relationship (QSAR) approach is most widely used for the prediction of biological activity of potential medicinal compounds. A QSAR model is developed by correlating the information obtained from chemical structures (numerical descriptors/ independent variables) with the experimental response values (the dependent variable). In the current study, we have developed a QSAR model to predict the inhibitory activity of small molecule carboxamides against severe acute respiratory syndrome coronavirus (SARS-- CoV) 3CLpro enzyme. Due to the structural similarity of this enzyme with SARS-CoV-2, the causative organism of the recent pandemic, the former may be used for the development of therapies against coronavirus disease 19 (COVID-19). The final multiple linear regression (MLR) model was based on four two-dimensional descriptors with definite physicochemical meaning. The model was strictly validated using different internal and external quality metrics. The model showed significant statistical quality in terms of determination coefficient (R2=0.748, adjusted R2 or R2 adj = 0.700), cross-validated leave-one-out Q2 (Q2=0.628) and external predicted variance R2 pred = 0.723. The final validated model was used for the prediction of external set compounds as well as to virtually design a new library of small molecules. We have also performed a docking analysis of the most active and least active compounds present in the dataset for comparative analysis and to explain the features obtained from the 2D-QSAR model. The derived model may be useful to predict the inhibitory activity of small molecules within the applicability domain of the model only based on the chemical structure information prior to their synthesis and testing.

Health equity and the usage of atypical antipsychotics within the Brazilian national health system: findings and implications

ABSTRACT Background There is a need to evaluate the health equity of atypical antipsychotics users who obtain their medicines from the Brazilian National Health System (SUS) through the identification of key factors that influence their health status due to concerns with equity of care. Research design and methods Cross-sectional study among patients attending state pharmacies in Brazil. Individuals were included if they used atypical antipsychotics, aged ≥18 years, and answered the EQ-5D-3 L questionnaire. Sociodemographic, behavioral, and clinical data were collected. The dependent variable was health status. Associations between the independent variables and the dependent variable were analyzed by adjusting a linear regression model. Results Overall, 388 individuals met the eligibility criteria and were included in the analysis. The final multiple linear regression model demonstrated a statistically significant association between VAS and suicide attempts, private care, current antipsychotics, comorbidities, and perceived family support. Expert Commentary The study identified several factors both individual and collective that correlate with the health status of atypical antipsychotic users and confirmed the importance of providing medicines for treating psychotic disorders. However, other factors are involved including social support. Our results suggest additional activities and policies are necessary including strategies to address the differences in private and public health care.

Assessing the relationship between non-motor symptoms and health-related quality of life in Parkinson's disease: a retrospective observational cohort study.

Non-motor symptoms (NMSs) negatively impact the health-related quality of life (HrQOL) of patients with Parkinson's disease (PD). The Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is a comprehensive scale for evaluating PD. It remains unclear whether the NMSs evaluated with MDS-UPDRS are predictive of HrQOL. This study aimed to investigate whether NMSs, as evaluated with the MDS-UPDRS, could predict the HrQOL of patients with PD. We conducted a 2-year retrospective observational cohort study assessing 108 patients with PD who were recruited from a single tertiary center between January 2015 and December 2017. MDS-UPDRS was used to assess NMSs and motor symptoms and Parkinson's Disease Questionnaire-39 (PDQ-39) to measure patients' HrQOL. The median age of patients was 69years, and 65.7% were female. The median MDS-UPDRS part I, part II, part III, and PDQ-39-summary index scores were 8, 10, 22, and 25, respectively. The final stepwise multiple linear regression model showed that female sex (standard partial regression coefficient β = 0.131, P < 0.05) and baseline MDS-UPDRS part I (β = 0.272, P < 0.01) and part II (β = 0.571, P < 0.01) scores significantly predicted the PDQ-39-SI scores at the 2-year follow-up. In addition to motor symptoms, NMSs at the 2-year follow-up may be useful for predicting the HrQOL of patients with PD. In clinical practice, MDS-UPDRS-guided assessment and treatment of motor symptoms and NMSs may contribute to improving HrQOL in patients with PD.

Impact of Sensory Processing on School Performance Outcomes in High Functioning Individuals with Autism Spectrum Disorder.

Difficulty processing sensory information may impede progress in school for students with autism spectrum disorder (ASD). We explore the relationship between sensory processing and school performance in 26 high-functioning youths with ASD and 26 controls (age 8-14) using measures of sensory, social, cognitive, and academic functioning. In the ASD group, bivariate Pearson correlations indicated a significant positive relationship between intelligence quotient (IQ) and the School Competence Scale (SCS) of the Child Behavior Checklist (CBCL), and a significant negative relationship between Dunn's Sensory Processing Framework and SCS scores. Final hierarchical multiple linear regression model accounting for SCS scores in ASD included IQ, ADHD symptoms, and sensory features. An interaction between increased sensory sensitivity with reduced sensory avoidance behaviors explained the greatest amount of variance in SCS, meaning school performance is lowest for children with greater hypersensitivity and fewer avoidance behaviors. Results indicate a strong impact of sensory processing on school performance in ASD.

Normative data for verbal fluency in healthy Latin American adults: Letter M, and fruits and occupations categories.

To generate normative data for the verbal fluency tests (VFT-letter M, fruits, and occupations categories) in Spanish-speaking adult populations, with country-specific adjustments for age, education, and sex when appropriate. The sample consisted of 3,977 healthy adults from 11 countries in Latin America (Argentina, Bolivia, Chile, Cuba, El Salvador, Guatemala, Honduras, Mexico, Paraguay, Peru, and Puerto Rico; sample size per country ranged between n = 184 and n = 1,300). Each participant was administered the VFT as part of a larger neuropsychological battery. Scores for letter M, fruits, and occupations categories were normed using multiple linear regressions. The country-specific regression models included age, age2, education, education2, and sex as predictors. The final multiple linear regression models showed that age affected the performance on these tests but not uniformly. For example, M letter scores decrease linearly with age except for Argentina, Guatemala, and Mexico, in which quadratic age effect was found. Scores also increase linearly as a function of education but not in all countries. For example, a quadratic education effect was found for the fruits category in Bolivia, Honduras, and Paraguay. Sex had a significant impact on the M letter category fluency in Guatemala, fruits category in Guatemala and Peru, and occupations' category in Mexico. This study presents verbal fluency test normative data across 11 countries in Latin America. These norms are expected to be useful for neuropsychologists of these countries. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Lifestyle factors during acute Epstein-Barr virus infection in adolescents predict physical activity six months later.

Acute Epstein-Barr virus (EBV) infection is a trigger of prolonged fatigue. This study investigated baseline predictors of physical activity six months after an acute EBV infection. A total of 200 adolescents (12-20years old) with acute EBV infection were assessed for 149 possible baseline predictors and followed prospectively. In this exploratory study, we performed linear regression analysis to assess possible associations between baseline predictors and steps per day at six months. In the final multiple linear regression model, physical activity six months after acute EBV infection was significantly and independently predicted by baseline physical activity (steps per day), substance use (alcohol and illicit drugs) and human growth hormone (adjusted R2 =0.20). Baseline physical activity, substance use and plasma growth hormone are independent predictors of physical activity six months after an acute EBV infection in adolescents, whereas markers of the infection and associated immune response do not seem to be associated with physical activity six months later.

Impact of Co-Morbidities on the Cost of Care in Primary Elective Joint Arthroplasty

BackgroundThe Comprehensive Care for Joint Replacement model is the newest iteration of the bundled payment methodology introduced by the Centers for Medicare and Medicaid Services. Comprehensive Care for Joint Replacement model, while incentivizing providers to deliver care at a lower cost, does not incorporate any patient-level risk stratification. Our study evaluated the impact of specific medical co-morbidities on the cost of care in total joint arthroplasty (TJA) patients. MethodsA retrospective study was conducted on 1258 Medicare patients who underwent primary elective TJA between January 2015 and July 2016 at a single institution. There were 488 males, 552 hips, and the mean age was 71 years. Cost data were obtained from the Centers for Medicare and Medicaid Services. Co-morbidity information was obtained from a manual review of patient records. Fourteen co-morbidities were included in our final multiple linear regression models. ResultsThe regression models significantly predicted cost variation (P < .001). For index hospital costs, a history of cardiac arrhythmias (P < .001), valvular heart disease (P = .014), and anemia (P = .020) significantly increased costs. For post-acute care costs, a history of neurological conditions like Parkinson’s disease or seizures (P < .001), malignancy (P = .001), hypertension (P = .012), depression (P = .014), and hypothyroidism (P = .044) were associated with increases in cost. Similarly, for total episode cost, a history of neurological conditions (P < .001), hypertension (P = .012), malignancy (P = .023), and diabetes (P = .029) were predictors for increased costs. ConclusionThe cost of care in primary elective TJA increases with greater patient co-morbidity. Our data provide insight into the relative impact of specific medical conditions on cost of care and may be used in risk stratification in future reimbursement methodologies.

Association between internet gaming addiction and leukocyte telomere length in Korean male adolescents

Internet gaming addiction (IGA) has been associated with many negative health outcomes, especially for youth. In particular, the potential association between IGA and leukocyte telomere length (LTL) has yet to be examined. In this study we compared LTL in Korean male adolescents with and without IGA and examined the association between LTL and autonomic functions. Specifically, plasma catecholamine, serum cortisol, and psychological stress levels were measured as autonomic functions. Data were collected using participant blood samples analyzed for LTL, catecholamine, and cortisol levels and a set of questionnaires to assess IGA and psychological stress levels of the participants. The LTL measurements were made using a qPCR-based technique, and the relative LTL was calculated as the telomere/single copy (T/S) ratio. T/S ratio was significantly shorter in the IGA group than in the non-IGA group (150.43 ± 6.20 and 187.23 ± 6.42, respectively; p < .001) after adjusting for age. In a univariate regression analysis, age, daily Internet gaming time, IGA score, and catecholamine level (epinephrine and norepinephrine) were significantly associated with T/S ratio. However, duration of Internet gaming exposure, dopamine, cortisol, and psychological stress levels were not found to be associated with T/S ratio. In the final multiple linear regression model, age, daily Internet gaming time, and epinephrine level showed statistically significant relationships with T/S ratio. Our results indicate that in addition to age, involvement in excessive Internet gaming may induce LTL shortening in male adolescents, which may be partially attributable to changes in autonomic function such as catecholamine level. These findings further understanding of the health effects of IGA and highlight the need for screening and intervention strategies for male adolescents with IGA.