Body mass index, smoking behavior, and depression mediated the effects of schizophrenia on chronic obstructive pulmonary disease: trans-ethnic Mendelian-randomization analysis.

Background: Previous studies have highlighted the association between schizophrenia (SCZ) and chronic obstructive pulmonary disease (COPD), yet the causal relationship remains unestablished. Methods: Under the genome-wide significance threshold (P<5×10-8), data from individuals of European (EUR) and East Asian (EAS) ancestries with SCZ were selected for analysis. Univariable Mendelian randomization (MR) explored the causal relationship between SCZ and COPD. Linkage disequilibrium score (LDSC) regression was used to calculate genetic correlation, while multivariable and mediation MR further investigated the roles of six confounding factors and their mediating effects. The primary method utilized was inverse-variance weighted (IVW), complemented by a series of sensitivity analyses and false discovery rate (FDR) correction. Results: LDSC analysis revealed a significant genetic correlation between SCZ and COPD within EUR ancestry (rg = 0.141, P = 6.16×10-7), with no such correlation found in EAS ancestry. IVW indicated a significant causal relationship between SCZ and COPD in EUR ancestry (OR = 1.042, 95% CI 1.013-1.071, P = 0.003, PFDR = 0.015). Additionally, replication datasets provide evidence of consistent causal associations(P < 0.05 & PFDR < 0.05). Multivariable and mediation MR analyses identified body mass index (BMI)(Mediation effect: 50.57%, P = 0.02), age of smoking initiation (Mediation effect: 27.42%, P = 0.02), and major depressive disorder (MDD) (Mediation effect: 60.45%, P = 6.98×10-5) as partial mediators of this causal relationship. No causal associations were observed in EAS (OR = 0.971, 95% CI 0.875-1.073, P = 0.571, PFDR = 0.761) ancestry. No causal associations were found in the reverse analysis across the four ancestries (P > 0.05 & PFDR > 0.05). Conclusions: This study confirmed a causal relationship between SCZ and the risk of COPD in EUR ancestry, with BMI, smoking, and MDD serving as key mediators. Future research on a larger scale is necessary to validate the generalizability of these findings across other ancestries.

Disease progression based feature screening for ultrahigh-dimensional survival-associated biomarkers.

The increased availability of ultrahigh-dimensional biomarker data and the high demand of identifying biomarkers importantly related to survival outcomes made feature screening methods commonplace in the analysis of cancer genome data. When survival outcomes include endpoints of overall survival (OS) and time-to-progression (TTP), a high concordance is typically found in both endpoints in cancer studies, namely, patients' OS would most likely be extended when tumour progression is delayed. Existing screening procedures are often performed on a single survival endpoint only and may result in biased selection of features for OS in ignorance of disease progression. We propose a novel feature screening method by incorporating information of TTP into the selection of important biomarker predictors for more accurate inference of OS subsequent to disease progression. The proposal is based on the rank of correlation between individual features and the conditional distribution of OS given observations of TTP. It is advantageous for its flexible model nature, which requires no marginal model assumption for each endpoint, and its minimal computational cost for implementation. Theoretical results show its ranking consistency, sure screening and false rate control properties. Simulation results demonstrate that the proposed screener leads to more accurate feature selection than the method without considering the prior observations of disease progression. An application to breast cancer genome data illustrates its practical utility and facilitates disease classification using selected biomarker predictors.

Minimally invasive pedicle screw fixation, including the fractured vertebra, combined with percutaneous vertebroplasty for treatment of acute thoracolumbar osteoporotic compression fracture in middle-age and elderly individuals: A prospective clinical study.

ABSTRACT: To evaluate the feasibility, efficacy, and safety of minimally invasive pedicle screw (MIPS) fixation, including the fractured vertebra, combined with percutaneous vertebroplasty (PVP) for the treatment of acute thoracolumbar osteoporotic compression fracture in middle-age and elderly individuals.Between January 2016 and August 2019, a total of 30 patients, with a mean age of 69.4 years (range, 58-75 years), who experienced thoracic or lumbar fracture without neurological deficits, underwent the MIPS procedure combined with PVP. Preoperative and postoperative pain were assessed using a visual analog scale and Oswestry Disability Index. Cobb angles and anterior column height were measured on lateral radiographs before surgery and at 3 days, 1, 3, and 6 months, and 1 and 2 years at final follow-up after surgery.All patients underwent surgery successfully, with a mean follow-up of 18.2 ±â€Š5.7 months (range, 12-45 months). Mean preoperative visual analog scale score decreased from 7.3 ±â€Š2.2 to 1.4 ±â€Š0.3 at the final follow-up (P < .05). Mean preoperative Oswestry Disability Index decreased from 84.2 ±â€Š10.3 to 18.8 ±â€Š7.5 (P < .05) at the final follow-up. The Kyphosis angle of operative segment was improved from preoperative (21.38 ±â€Š1.68)° to (4.01 ±â€Š1.38)° 3 days postoperatively and (5.02 ±â€Š1.09)° at final follow-up (P < .05). The anterior vertebral height was improved from preoperative (49.86 ±â€Š6.50)% to (94.01 ±â€Š1.79)% 3 days postoperatively and (91.80 ±â€Š1.88)% at final follow-up (P < .05). No significant changes in vertebral body height restoration were observed during 2 years of follow-up after surgery. In addition, there were no instrumentation failures or complications in any of the patients.MIPS, including the fractured vertebra, combined with PVP, was a reliable and safe procedure, with satisfactory clinical and radiological results for the treatment of thoracolumbar osteoporotic compression fracture in patients without neurological deficits.

Correlation-based joint feature screening for semi-competing risks outcomes with application to breast cancer data.

Ultrahigh-dimensional gene features are often collected in modern cancer studies in which the number of gene features p is extremely larger than sample size n. While gene expression patterns have been shown to be related to patients' survival in microarray-based gene expression studies, one has to deal with the challenges of ultrahigh-dimensional genetic predictors for survival predicting and genetic understanding of the disease in precision medicine. The problem becomes more complicated when two types of survival endpoints, distant metastasis-free survival and overall survival, are of interest in the study and outcome data can be subject to semi-competing risks due to the fact that distant metastasis-free survival is possibly censored by overall survival but not vice versa. Our focus in this paper is to extract important features, which have great impacts on both distant metastasis-free survival and overall survival jointly, from massive gene expression data in the semi-competing risks setting. We propose a model-free screening method based on the ranking of the correlation between gene features and the joint survival function of two endpoints. The method accounts for the relationship between two endpoints in a simply defined utility measure that is easy to understand and calculate. We show its favorable theoretical properties such as the sure screening and ranking consistency, and evaluate its finite sample performance through extensive simulation studies. Finally, an application to classifying breast cancer data clearly demonstrates the utility of the proposed method in practice.

Robotic Assisted Upper Limb Training Post Stroke: A Randomized Control Trial Using Combinatory Approach Toward Reducing Workforce Demands.

Post stroke upper limb rehabilitation is a challenging problem with poor outcomes as 40% of survivors have functionally useless upper limbs. Robot-aided therapy (RAT) is a potential method to alleviate the effort of intensive, task-specific, repetitive upper limb exercises for both patients and therapists. The present study aims to investigate how a time matched combinatory training scheme that incorporates conventional and RAT, using H-Man, compares with conventional training toward reducing workforce demands. In a randomized control trial (NCT02188628, www.clinicaltrials.gov), 44 subacute to chronic stroke survivors with first-ever clinical stroke and predominant arm motor function deficits were recruited and randomized into two groups of 22 subjects: Robotic Therapy (RT) and Conventional Therapy (CT). Both groups received 18 sessions of 90 min; three sessions per week over 6 weeks. In each session, participants of the CT group received 90 min of 1:1 therapist-supervised conventional therapy while participants of the RT group underwent combinatory training which consisted of 60 min of minimally-supervised H-Man therapy followed by 30 min of conventional therapy. The clinical outcomes [Fugl-Meyer (FMA), Action Research Arm Test and, Grip Strength] and the quantitative measures (smoothness, time efficiency, and task error, derived from two robotic assessment tasks) were independently evaluated prior to therapy intervention (week 0), at mid-training (week 3), at the end of training (week 6), and post therapy (week 12 and 24). Significant differences within group were observed at the end of training for all clinical scales compared with baseline [mean and standard deviation of FMA score changes between baseline and week 6; RT: Δ4.41 (3.46) and CT: Δ3.0 (4.0); p < 0.01]. FMA gains were retained 18 weeks post-training [week 24; RT: Δ5.38 (4.67) and week 24 CT: Δ4.50 (5.35); p < 0.01]. The RT group clinical scores improved similarly when compared to CT group with no significant inter-group at all time points although the conventional therapy time was reduced to one third in RT group. There were no training-related adverse side effects. In conclusion, time matched combinatory training incorporating H-Man RAT produced similar outcomes compared to conventional therapy alone. Hence, this study supports a combinatory approach to improve motor function in post-stroke arm paresis. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT02188628.

Quantile regression for survival data with covariates subject to detection limits.

With advances in biomedical research, biomarkers are becoming increasingly important prognostic factors for predicting overall survival, while the measurement of biomarkers is often censored due to instruments' lower limits of detection. This leads to two types of censoring: random censoring in overall survival outcomes and fixed censoring in biomarker covariates, posing new challenges in statistical modeling and inference. Existing methods for analyzing such data focus primarily on linear regression ignoring censored responses or semiparametric accelerated failure time models with covariates under detection limits (DL). In this paper, we propose a quantile regression for survival data with covariates subject to DL. Comparing to existing methods, the proposed approach provides a more versatile tool for modeling the distribution of survival outcomes by allowing covariate effects to vary across conditional quantiles of the survival time and requiring no parametric distribution assumptions for outcome data. To estimate the quantile process of regression coefficients, we develop a novel multiple imputation approach based on another quantile regression for covariates under DL, avoiding stringent parametric restrictions on censored covariates as often assumed in the literature. Under regularity conditions, we show that the estimation procedure yields uniformly consistent and asymptotically normal estimators. Simulation results demonstrate the satisfactory finite-sample performance of the method. We also apply our method to the motivating data from a study of genetic and inflammatory markers of Sepsis.

Frailty modelling approaches for semi-competing risks data.

In the semi-competing risks situation where only a terminal event censors a non-terminal event, observed event times can be correlated. Recently, frailty models with an arbitrary baseline hazard have been studied for the analysis of such semi-competing risks data. However, their maximum likelihood estimator can be substantially biased in the finite samples. In this paper, we propose effective modifications to reduce such bias using the hierarchical likelihood. We also investigate the relationship between marginal and hierarchical likelihood approaches. Simulation results are provided to validate performance of the proposed method. The proposed method is illustrated through analysis of semi-competing risks data from a breast cancer study.

A two-part mixed-effects model for analyzing clustered time-to-event data with clumping at zero.

BACKGROUND AND OBJECTIVE: In longitudinal epidemiological studies consisting of a baseline stage and a follow-up stage, observations at the baseline stage may contain a countable proportion of negative responses. The time-to-event outcomes of those observations corresponding to negative responses at baseline can be denoted as zeros, which are excluded from standard survival analysis. Consequently, some important information on these subjects is therefore lost in the analysis. Furthermore, subjects are often clustered within hospitals, communities or health service centers, resulting in correlated observations. The framework of the two-part model has been developed and utilized widely to analyze semi-continuous data or count data with excess zeros, but its application to clustered time-to-event data with clumping at zero remains sparse. METHODS: A two-part mixed-effects modeling approach was proposed. A logistic mixed-effects regression model was used in the first part to determine factors associated with the prevalence of the baseline event of interest. Parametric frailty models (including Weibull, exponential, log-logistic and log-normal) were used in the second part to assess associations between exposures and time-to-event outcomes. Correlated random effects were incorporated within the two regression models to accommodate the inherent correlation within each clustering unit and the correlation between the two parts. As an illustrative example, the method was applied to exclusive breastfeeding data from a community-based prospective cohort study in Nepal. RESULTS: A significantly positive correlation between the baseline prevalence of exclusive breastfeeding and exclusive breastfeeding duration was confirmed (ρ = 0.67, P < 0.001). The correlated two-part model outperformed the independent two-part model (likelihood ratio test statistic = 8.6, df = 1, P = 0.003). CONCLUSIONS: The proposed approach makes full use of all available information at baseline and during the follow-up, compared to the conventional survival analysis. In addition to breastfeeding studies, the method can be applied to other research areas where clustered time-to-event data with clumping at zero arise.

A preliminary study on the relationship between proprioceptive deficits and motor functions in chronic stroke patients.

Although motor and sensory impairments of the upper limb after stroke have been widely studied, the relationship between sensory deficits and motor functions has been less thoroughly explored. In this ongoing study, we investigated the relationship between proprioceptive impairments and motor functions with 20 chronic stroke survivors. Their proprioceptive abilities were assessed with a passive joint position matching test using H-Man and their motor functions were assessed with ARAT (Action Research Arm Test) and FMA (Fugl Meyer Upper Extremity Assessment) clinical scores. The assessments were conducted before, during and after the therapy. Results indicated a significant difference between the proprioceptive outcomes of healthy and stroke participants (at baseline) in both matching accuracy (absolute error, p=0.02) and precision (variability of the signed error, p=0.03). Significant correlations were found between the proprioceptive assessment outcomes (assessed before the beginning of the motor rehabilitation) of stroke participants with impaired proprioception and their ARAT clinical scores assessed at the first follow-up (week 12) (rho =- 0.74 and p=0.047 for the absolute error; rho =-0.78 and p= 0.03 for the variability of the signed error). The results from this preliminary study indicated a significant relationship between proprioceptive impairments and motor function performances in proprioceptively impaired chronic stroke participants.

Frailty proportional mean residual life regression for clustered survival data: A hierarchical quasi-likelihood method.

Frailty models are widely used to model clustered survival data arising in multicenter clinical studies. In the literature, most existing frailty models are proportional hazards, additive hazards, or accelerated failure time model based. In this paper, we propose a frailty model framework based on mean residual life regression to accommodate intracluster correlation and in the meantime provide easily understand and straightforward interpretation for the effects of prognostic factors on the expectation of the remaining lifetime. To overcome estimation challenges, a novel hierarchical quasi-likelihood approach is developed by making use of the idea of hierarchical likelihood in the construction of the quasi-likelihood function, leading to hierarchical estimating equations. Simulation results show favorable performance of the method regardless of frailty distributions. The utility of the proposed methodology is illustrated by its application to the data from a multi-institutional study of breast cancer.

Joint regression analysis for survival data in the presence of two sets of semi-competing risks.

In many clinical trials, multiple time-to-event endpoints including the primary endpoint (e.g., time to death) and secondary endpoints (e.g., progression-related endpoints) are commonly used to determine treatment efficacy. These endpoints are often biologically related. This work is motivated by a study of bone marrow transplant (BMT) for leukemia patients, who may experience the acute graft-versus-host disease (GVHD), relapse of leukemia, and death after an allogeneic BMT. The acute GVHD is associated with the relapse free survival, and both the acute GVHD and relapse of leukemia are intermediate nonterminal events subject to dependent censoring by the informative terminal event death, but not vice versa, giving rise to survival data that are subject to two sets of semi-competing risks. It is important to assess the impacts of prognostic factors on these three time-to-event endpoints. We propose a novel statistical approach that jointly models such data via a pair of copulas to account for multiple dependence structures, while the marginal distribution of each endpoint is formulated by a Cox proportional hazards model. We develop an estimation procedure based on pseudo-likelihood and carry out simulation studies to examine the performance of the proposed method in finite samples. The practical utility of the proposed method is further illustrated with data from the motivating example.

Work with me, not for me: Relationship between robotic assistance and performance in subacute and chronic stroke patients.

INTRODUCTION: Studies in robotic therapy which applied the performance enhancement approach report improvements in motor performance during training, though these improvements do not always transfer to motor learning. OBJECTIVES: We postulate that there exists an assistance threshold for which performance saturates. Above this threshold, the robot's input outweighs the patient's input and likely learning is not fostered. This study investigated the relationship between assistance and performance changes in stroke patients to find the assistance threshold for performance saturation. METHODS: Twelve subacute and chronic stroke patients engaged in five sessions (over two weeks, each 60 min) in which they performed a reaching task with the rehabilitation robot H-Man in presence of varying levels of haptic assistance (50 N/m to 290 N/m, randomized order). In two additional sessions, a therapist manually tuned the assistance to promote maximal motor learning. RESULTS: Higher levels of assistance resulted in smoother and faster performance that saturated at assistance levels with K ≥ 110 N/m. Also, the therapist selected assistance levels of K = 175 N/m or below. CONCLUSION: The findings of the study indicate that low levels of assistance (K ≤ 175 N/m) can sufficiently induce a significant change in performance.

Proprioceptive assessment in clinical settings: Evaluation of joint position sense in upper limb post-stroke using a robotic manipulator.

Proprioception is a critical component for motor functions and directly affects motor learning after neurological injuries. Conventional methods for its assessment are generally ordinal in nature and hence lack sensitivity. Robotic devices designed to promote sensorimotor learning can potentially provide quantitative precise, accurate, and reliable assessments of sensory impairments. In this paper, we investigate the clinical applicability and validity of using a planar 2 degrees of freedom robot to quantitatively assess proprioceptive deficits in post-stroke participants. Nine stroke survivors and nine healthy subjects participated in the study. Participants' hand was passively moved to the target position guided by the H-Man robot (Criterion movement) and were asked to indicate during a second passive movement towards the same target (Matching movement) when they felt that they matched the target position. The assessment was carried out on a planar surface for movements in the forward and oblique directions in the contralateral and ipsilateral sides of the tested arm. The matching performance was evaluated in terms of error magnitude (absolute and signed) and its variability. Stroke patients showed higher variability in the estimation of the target position compared to the healthy participants. Further, an effect of target was found, with lower absolute errors in the contralateral side. Pairwise comparison between individual stroke participant and control participants showed significant proprioceptive deficits in two patients. The proposed assessment of passive joint position sense was inherently simple and all participants, regardless of motor impairment level, could complete it in less than 10 minutes. Therefore, the method can potentially be carried out to detect changes in proprioceptive deficits in clinical settings.

Automated telephone communication systems for preventive healthcare and management of long-term conditions.

BACKGROUND: Automated telephone communication systems (ATCS) can deliver voice messages and collect health-related information from patients using either their telephone's touch-tone keypad or voice recognition software. ATCS can supplement or replace telephone contact between health professionals and patients. There are four different types of ATCS: unidirectional (one-way, non-interactive voice communication), interactive voice response (IVR) systems, ATCS with additional functions such as access to an expert to request advice (ATCS Plus) and multimodal ATCS, where the calls are delivered as part of a multicomponent intervention. OBJECTIVES: To assess the effects of ATCS for preventing disease and managing long-term conditions on behavioural change, clinical, process, cognitive, patient-centred and adverse outcomes. SEARCH METHODS: We searched 10 electronic databases (the Cochrane Central Register of Controlled Trials; MEDLINE; Embase; PsycINFO; CINAHL; Global Health; WHOLIS; LILACS; Web of Science; and ASSIA); three grey literature sources (Dissertation Abstracts, Index to Theses, Australasian Digital Theses); and two trial registries (www.controlled-trials.com; www.clinicaltrials.gov) for papers published between 1980 and June 2015. SELECTION CRITERIA: Randomised, cluster- and quasi-randomised trials, interrupted time series and controlled before-and-after studies comparing ATCS interventions, with any control or another ATCS type were eligible for inclusion. Studies in all settings, for all consumers/carers, in any preventive healthcare or long term condition management role were eligible. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods to select and extract data and to appraise eligible studies. MAIN RESULTS: We included 132 trials (N = 4,669,689). Studies spanned across several clinical areas, assessing many comparisons based on evaluation of different ATCS types and variable comparison groups. Forty-one studies evaluated ATCS for delivering preventive healthcare, 84 for managing long-term conditions, and seven studies for appointment reminders. We downgraded our certainty in the evidence primarily because of the risk of bias for many outcomes. We judged the risk of bias arising from allocation processes to be low for just over half the studies and unclear for the remainder. We considered most studies to be at unclear risk of performance or detection bias due to blinding, while only 16% of studies were at low risk. We generally judged the risk of bias due to missing data and selective outcome reporting to be unclear.For preventive healthcare, ATCS (ATCS Plus, IVR, unidirectional) probably increase immunisation uptake in children (risk ratio (RR) 1.25, 95% confidence interval (CI) 1.18 to 1.32; 5 studies, N = 10,454; moderate certainty) and to a lesser extent in adolescents (RR 1.06, 95% CI 1.02 to 1.11; 2 studies, N = 5725; moderate certainty). The effects of ATCS in adults are unclear (RR 2.18, 95% CI 0.53 to 9.02; 2 studies, N = 1743; very low certainty).For screening, multimodal ATCS increase uptake of screening for breast cancer (RR 2.17, 95% CI 1.55 to 3.04; 2 studies, N = 462; high certainty) and colorectal cancer (CRC) (RR 2.19, 95% CI 1.88 to 2.55; 3 studies, N = 1013; high certainty) versus usual care. It may also increase osteoporosis screening. ATCS Plus interventions probably slightly increase cervical cancer screening (moderate certainty), but effects on osteoporosis screening are uncertain. IVR systems probably increase CRC screening at 6 months (RR 1.36, 95% CI 1.25 to 1.48; 2 studies, N = 16,915; moderate certainty) but not at 9 to 12 months, with probably little or no effect of IVR (RR 1.05, 95% CI 0.99, 1.11; 2 studies, 2599 participants; moderate certainty) or unidirectional ATCS on breast cancer screening.Appointment reminders delivered through IVR or unidirectional ATCS may improve attendance rates compared with no calls (low certainty). For long-term management, medication or laboratory test adherence provided the most general evidence across conditions (25 studies, data not combined). Multimodal ATCS versus usual care showed conflicting effects (positive and uncertain) on medication adherence. ATCS Plus probably slightly (versus control; moderate certainty) or probably (versus usual care; moderate certainty) improves medication adherence but may have little effect on adherence to tests (versus control). IVR probably slightly improves medication adherence versus control (moderate certainty). Compared with usual care, IVR probably improves test adherence and slightly increases medication adherence up to six months but has little or no effect at longer time points (moderate certainty). Unidirectional ATCS, compared with control, may have little effect or slightly improve medication adherence (low certainty). The evidence suggested little or no consistent effect of any ATCS type on clinical outcomes (blood pressure control, blood lipids, asthma control, therapeutic coverage) related to adherence, but only a small number of studies contributed clinical outcome data.The above results focus on areas with the most general findings across conditions. In condition-specific areas, the effects of ATCS varied, including by the type of ATCS intervention in use.Multimodal ATCS probably decrease both cancer pain and chronic pain as well as depression (moderate certainty), but other ATCS types were less effective. Depending on the type of intervention, ATCS may have small effects on outcomes for physical activity, weight management, alcohol consumption, and diabetes mellitus. ATCS have little or no effect on outcomes related to heart failure, hypertension, mental health or smoking cessation, and there is insufficient evidence to determine their effects for preventing alcohol/substance misuse or managing illicit drug addiction, asthma, chronic obstructive pulmonary disease, HIV/AIDS, hypercholesterolaemia, obstructive sleep apnoea, spinal cord dysfunction or psychological stress in carers.Only four trials (3%) reported adverse events, and it was unclear whether these were related to the interventions. AUTHORS' CONCLUSIONS: ATCS interventions can change patients' health behaviours, improve clinical outcomes and increase healthcare uptake with positive effects in several important areas including immunisation, screening, appointment attendance, and adherence to medications or tests. The decision to integrate ATCS interventions in routine healthcare delivery should reflect variations in the certainty of the evidence available and the size of effects across different conditions, together with the varied nature of ATCS interventions assessed. Future research should investigate both the content of ATCS interventions and the mode of delivery; users' experiences, particularly with regard to acceptability; and clarify which ATCS types are most effective and cost-effective.

Self-Paced Reaching after Stroke: A Quantitative Assessment of Longitudinal and Directional Sensitivity Using the H-Man Planar Robot for Upper Limb Neurorehabilitation.

Technology aided measures offer a sensitive, accurate and time-efficient approach for the assessment of sensorimotor function after neurological insult compared to standard clinical assessments. This study investigated the sensitivity of robotic measures to capture differences in planar reaching movements as a function of neurological status (stroke, healthy), direction (front, ipsilateral, contralateral), movement segment (outbound, inbound), and time (baseline, post-training, 2-week follow-up) using a planar, two-degrees of freedom, robotic-manipulator (H-Man). Twelve chronic stroke (age: 55 ± 10.0 years, 5 female, 7 male, time since stroke: 11.2 ± 6.0 months) and nine aged-matched healthy participants (age: 53 ± 4.3 years, 5 female, 4 male) participated in this study. Both healthy and stroke participants performed planar reaching movements in contralateral, ipsilateral and front directions with the H-Man, and the robotic measures, spectral arc length (SAL), normalized time to peak velocities (TpeakN ), and root-mean square error (RMSE) were evaluated. Healthy participants went through a one-off session of assessment to investigate the baseline. Stroke participants completed a 2-week intensive robotic training plus standard arm therapy (8 × 90 min sessions). Motor function for stroke participants was evaluated prior to training (baseline, week-0), immediately following training (post-training, week-2), and 2-weeks after training (follow-up, week-4) using robotic assessment and the clinical measures Fugl-Meyer Assessment (FMA), Activity-Research-Arm Test (ARAT), and grip-strength. Robotic assessments were able to capture differences due to neurological status, movement direction, and movement segment. Movements performed by stroke participants were less-smooth, featured longer TpeakN , and larger RMSE values, compared to healthy controls. Significant movement direction differences were observed, with improved reaching performance for the front, compared to ipsilateral and contralateral movement directions. There were group differences depending on movement segment. Outbound reaching movements were smoother and featured longer TpeakN values than inbound movements for control participants, whereas SAL, TpeakN , and RMSE values were similar regardless of movement segment for stroke patients. Significant change in performance was observed between initial and post-assessments using H-Man in stroke participants, compared to conventional scales which showed no significant difference. Results of the study indicate the potential of H-Man as a sensitive tool for tracking changes in performance compared to ordinal scales (i.e., FM, ARAT).

Characterization of single amino acid substitutions in the ß2 integrin subunit of patients with leukocyte adhesion deficiency (LAD)-1.

Leukocyte adhesion deficiency 1 (LAD-1) is caused by defects in the ß2 integrin subunit. We studied 18 missense mutations, 14 of which fail to support the surface expression of the ß2 integrins. Integrins with the ß2-G150D mutation fail to bind ligands, possibly due to the failure of the α1 segment of the ßI domain to assume an α-helical structure. Integrins with the ß2-G716A mutation are not maintained in their resting states, and the patient has the severe phenotype of LAD-1. The ß2-S453N and ß2-P648L mutants support the expression of integrins and adhesion functions. They should be re-classified as polymorphic variants.

Semiparametric estimation in generalized linear mixed models with auxiliary covariates: a pairwise likelihood approach.

Auxiliary covariates are often encountered in biomedical research settings where the primary exposure variable is measured only for a subgroup of study subjects. This article is concerned with generalized linear mixed models in the presence of auxiliary covariate information for clustered data. We propose a novel semiparametric estimation method based on a pairwise likelihood function and develop an estimating equation-based inference procedure by treating both the error structure and random effects as nuisance parameters. This method is robust against misspecification of either error structure or random-effects distribution and allows for dependence between random effects and covariates. We show that the resulting estimators are consistent and asymptotically normal. Extensive simulation studies evaluate the finite sample performance of the proposed estimators and demonstrate their advantage over the validation set based method and the existing method. We illustrate the method with two real data examples.

Physical activity and nutrition behavioural outcomes of a home-based intervention program for seniors: a randomized controlled trial.

BACKGROUND: This intervention aimed to ascertain whether a low-cost, accessible, physical activity and nutrition program could improve physical activity and nutrition behaviours of insufficiently active 60-70 year olds residing in Perth, Australia. METHODS: A 6-month home-based randomised controlled trial was conducted on 478 older adults (intervention, n = 248; control, n = 230) of low to medium socioeconomic status. Both intervention and control groups completed postal questionnaires at baseline and post-program, but only the intervention participants received project materials. A modified fat and fibre questionnaire measured nutritional behaviours, whereas physical activity was measured using the International Physical Activity Questionnaire. Generalised estimating equation models were used to assess the repeated outcomes over both time points. RESULTS: The final sample consisted of 176 intervention participants and 199 controls (response rate 78.5%) with complete data. After controlling for demographic and other confounding factors, the intervention group demonstrated increased participation in strength exercise (p < 0.001), walking (p = 0.029) and vigorous activity (p = 0.015), together with significant reduction in mean sitting time (p < 0.001) relative to controls. Improvements in nutritional behaviours for the intervention group were also evident in terms of fat avoidance (p < 0.001), fat intake (p = 0.021) and prevalence of frequent fruit intake (p = 0.008). CONCLUSIONS: A minimal contact, low-cost and home-based physical activity program can positively influence seniors' physical activity and nutrition behaviours. TRIAL REGISTRATION: anzctr.org.au Identifier: ACTRN12609000735257.

Mixture analysis of heterogeneous physical activity outcomes.

PURPOSE: The health benefits of physical activity (PA) are well established. PA outcomes, being semicontinuous in nature, often exhibit a large portion of zero values together with continuous positive values that are right-skewed. We propose a novel two-part mixture regression model with random effects to characterize heterogeneity of the clustered PA data. METHODS: In the binary part, the odds of PA participation are modeled with the use of a logistic mixed regression model. In the continuous part, the PA intensity conditional on those individuals engaging in PA is assessed by a gamma mixture regression model. Random effects are incorporated within the two parts to account for correlation of the observations. RESULTS: Model fitting and inference are performed through the Gaussian quadrature technique, which is implemented conveniently in the SAS PROC NLMIXED. The development of mixture methodology for analyzing PA is motivated by a study of PA in the daily life of patients with chronic obstructive pulmonary disease. CONCLUSIONS: The findings demonstrate the usefulness of the mixture analysis, which enables the separate identification of pertinent factors affecting PA participation and PA intensity for different patient subgroups.

Mixture cure model with random effects for clustered interval-censored survival data.

The mixture cure model is an effective tool for analysis of survival data with a cure fraction. This approach integrates the logistic regression model for the proportion of cured subjects and the survival model (either the Cox proportional hazards or accelerated failure time model) for uncured subjects. Methods based on the mixture cure model have been extensively investigated in the literature for data with exact failure/censoring times. In this paper, we propose a mixture cure modeling procedure for analyzing clustered and interval-censored survival time data by incorporating random effects in both the logistic regression and PH regression components. Under the generalized linear mixed model framework, we develop the REML estimation for the parameters, as well as an iterative algorithm for estimation of the survival function for interval-censored data. The estimation procedure is implemented via an EM algorithm. A simulation study is conducted to evaluate the performance of the proposed method in various practical situations. To demonstrate its usefulness, we apply the proposed method to analyze the interval-censored relapse time data from a smoking cessation study whose subjects were recruited from 51 zip code regions in the southeastern corner of Minnesota.