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Strategy training is a rehabilitation intervention that aims to enhance problem-solving skills with respect to daily activity–related challenges and has achieved favorable results in Western countries. This study explored the perspectives of individuals with acquired brain injury (ABI) in Taiwan who received strategy training. Semi-structured interviews with community-dwelling adults with ABI were conducted, and reflective memos made by research team members were recorded. Interviews and memos were analyzed through thematic analysis This study included 55 participants. The analysis of the participants’ interview responses and memos yielded nine themes under three categories: 1) expectations regarding strategy training, 2) perceived benefits of strategy training, and 3) barriers affecting the process and outcomes of strategy training. All the participants endorsed strategy training through different gains. Most participants’ expectations before the intervention were uncertain. Including family members into the strategy training is of key importance for a successfulness of their goals. The participants’ experiences about strategy training were affected by various barriers (i.e., health and medical problems, the physical environment, and natural events). Clinicians and researchers should consider these expectations, benefits, and barriers when studying and implementing strategy training in non-Western contexts.IMPLICATIONS FOR REHABILITATIONStrategy training provides clients the opportunity to actively engage in their own goal setting and decision making.Strategy training increases the client’s confidence in their ability to participate in the community, communicate, and perform daily living and physical activities.Therapists should consider the health conditions and physical environment of clients when helping them set goals and before facilitating their engagement in the community.Taiwanese family members play a crucial role in supporting acquired brain injury survivors in strategy training. Strategy training provides clients the opportunity to actively engage in their own goal setting and decision making. Strategy training increases the client’s confidence in their ability to participate in the community, communicate, and perform daily living and physical activities. Therapists should consider the health conditions and physical environment of clients when helping them set goals and before facilitating their engagement in the community. Taiwanese family members play a crucial role in supporting acquired brain injury survivors in strategy training.

Objective: Aberrant driving behavior (ADB) decreases road safety and is particularly relevant for urban bus drivers, who are required to drive daily shifts of considerable duration. Although numerous frameworks based on human physiological features have been applied to predict ADB, the research remains at an early stage. This study used heart rate variability (HRV) parameters to establish ADB occurrence prediction models with various machine learning approaches. Methods: Twelve Taiwanese urban bus drivers were recruited for four consecutive days of naturalistic driving data collection (from their routine routes) between March and April 2020; driving behaviors and physiological signals were obtained from provided devices. Weather and traffic congestion information was determined from public data, while sleep quality and professional driving experience were self-reported. To develop the ADB prediction model, several machine learning models—logistic regression, random forest, naive Bayes, support vector machine, and gated recurrent unit (GRU)—were trained and 10-fold cross-validated by using the testing data. Results: Most drivers with ADB reported deficient sleep quality (≤80%), with significantly higher mean scores on the Karolinska Sleepiness Scale and driver behavior questionnaire subcategory of lapses and errors than drivers without ADB. Next, HRV indices significantly differed between the measurement of a pre-ADB event and a baseline. The accuracy of the GRU models ranged from 78.84% ± 1.49% to 89.57% ± 1.31%. Conclusion: Drivers with ADB tend to have inadequate sleep quality, which may increase their fatigue levels and impair driving performance. The established time-series models can be considered for ADB occurrence prediction among urban bus drivers.

Obstructive sleep apnea (OSA) with a low arousal threshold (low-ArTH) phenotype can cause minor respiratory events that exacerbate sleep fragmentation. Although anthropometric features may affect the risk of low-ArTH OSA, the associations and underlying mechanisms require further investigation. This study investigated the relationships of body fat and water distribution with polysomnography parameters by using data from a sleep center database. The derived data were classified as those for low-ArTH in accordance with criteria that considered oximetry and the frequency and type fraction of respiratory events and analyzed using mean comparison and regression approaches. The low-ArTH group members (n = 1850) were significantly older and had a higher visceral fat level, body fat percentage, trunk-to-limb fat ratio, and extracellular-to-intracellular (E–I) water ratio compared with the non-OSA group members (n = 368). Significant associations of body fat percentage (odds ratio [OR]: 1.58, 95% confident interval [CI]: 1.08 to 2.3, p < 0.05), trunk-to-limb fat ratio (OR: 1.22, 95% CI: 1.04 to 1.43, p < 0.05), and E–I water ratio (OR: 1.32, 95% CI: 1.08 to 1.62, p < 0.01) with the risk of low-ArTH OSA were noted after adjustments for sex, age, and body mass index. These observations suggest that increased truncal adiposity and extracellular water are associated with a higher risk of low-ArTH OSA.

Timely diagnosis of meniscus injuries is key for preventing knee joint dysfunction and improving patient outcomes because it decreases morbidity and facilitates treatment planning.To train and evaluate a deep learning model for automated detection of meniscus tears on knee magnetic resonance imaging (MRI).Bicentric retrospective study.In total, 584 knee MRI studies, divided among training (n = 234), testing (n = 200), and external validation (n = 150) data sets, were used in this study. The public data set MRNet was used as a second external validation data set to evaluate the performance of the model.A 3 T, coronal, and sagittal images from T1-weighted proton density (PD) fast spin-echo (FSE) with fat saturation and T2-weighted FSE with fat saturation sequences.The detection system for meniscus tear was based on the improved YOLOv4 model with Darknet-53 as the backbone. The performance of the model was also compared with that of three radiologists of varying levels of experience. The determination of the presence of a meniscus tear from surgery reports was used as the ground truth for the images.Sensitivity, specificity, prevalence, positive predictive value, negative predictive value, accuracy, and receiver operating characteristic curve were used to evaluate the performance of the detection model. Two-way analysis of variance, Wilcoxon signed-rank test, and Tukey's multiple tests were used to evaluate differences in performance between the model and radiologists.The overall accuracies for detecting meniscus tears using our model on the internal testing, internal validation, and external validation data sets were 95.4%, 95.8%, and 78.8%, respectively. One radiologist had significantly lower performance than our model in detecting meniscal tears (accuracy: 0.9025 ± 0.093 vs. 0.9580 ± 0.025).The proposed model had high sensitivity, specificity, and accuracy for detecting meniscus tears on knee MRIs.3 TECHNICAL EFFICACY: Stage 2.

Objectives. Microstate studies of electroencephalograms (EEGs) on schizophrenia (SCZ) and bipolar disorder (BD) demonstrated categorical differences. The relationship between microstate indices and clinical symptoms in each group, however, remained unclear. Our objective was to examine associations between EEG microstates and the core features of SCZ and BD. Methods. This study examined the resting EEG data of 40 patients with SCZ, 19 patients with BD (12 BD type I and 7 BD type II), and 16 healthy controls. EEG topographic maps were divided into four canonical microstate classes: A, B, C, and D. The Positive and Negative Syndrome Scale (PANSS), Young Mania Rating Scale, Hamilton Depression Rating Scale (HAMD), and Global Assessment of Functioning (GAF) were used to measure clinical symptoms and global functioning. Results. There was a significant inverse correlation between the proportion of time spent in microstate class A and GAF in patients with SCZ but not BD. Furthermore, the occurrence of microstate class A was positively correlated with the Positive Scale scores of the PANSS. Nevertheless, there were no group differences between the microstate classes. Conclusions. The results of this study indicate a negative correlation between microstate class A and global functioning in SCZ but not in BD. The association may be mediated by positive symptoms of SZ. Neural mechanisms underlying this relationship require further investigation.

Peer reviewed: True, Obstructive sleep apnea (OSA) is a risk factor for neurodegenerative diseases. This study determined whether continuous positive airway pressure (CPAP), which can alleviate OSA symptoms, can reduce neurochemical biomarker levels. Thirty patients with OSA and normal cognitive function were recruited and divided into the control (n = 10) and CPAP (n = 20) groups. Next, we examined their in-lab sleep data (polysomnography and CPAP titration), sleep-related questionnaire outcomes, and neurochemical biomarker levels at baseline and the 3-month follow-up. The paired t-test and Wilcoxon signed-rank test were used to examine changes. Analysis of covariance (ANCOVA) was performed to increase the robustness of outcomes. The Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index scores were significantly decreased in the CPAP group. The mean levels of total tau (T-Tau), amyloid-beta-42 (Aβ42), and the product of the two (Aβ42 × T-Tau) increased considerably in the control group (ΔT-Tau: 2.31 pg/mL; ΔAβ42: 0.58 pg/mL; ΔAβ42 × T-Tau: 48.73 pg2/mL2), whereas the mean levels of T-Tau and the product of T-Tau and Aβ42 decreased considerably in the CPAP group (ΔT-Tau: -2.22 pg/mL; ΔAβ42 × T-Tau: -44.35 pg2/mL2). The results of ANCOVA with adjustment for age, sex, body mass index, baseline measurements, and apnea-hypopnea index demonstrated significant differences in neurochemical biomarker levels between the CPAP and control groups. The findings indicate that CPAP may reduce neurochemical biomarker levels by alleviating OSA symptoms.

ObjectivesObstructive sleep apnea (OSA) may increase the risk of Alzheimer's disease (AD). However, potential associations among sleep-disordered breathing, hypoxia, and OSA-induced arousal responses should be investigated. This study determined differences in sleep parameters and investigated the relationship between such parameters and the risk of AD.MethodsPatients with suspected OSA were recruited and underwent in-lab polysomnography (PSG). Subsequently, blood samples were collected from participants. Patients' plasma levels of total tau (T-Tau) and amyloid beta-peptide 42 (Aβ42) were measured using an ultrasensitive immunomagnetic reduction assay. Next, the participants were categorized into low- and high-risk groups on the basis of the computed product (Aβ42 × T-Tau, the cutoff for AD risk). PSG parameters were analyzed and compared.ResultsWe included 36 patients in this study, of whom 18 and 18 were assigned to the low- and high-risk groups, respectively. The average apnea–hypopnea index (AHI), apnea, hypopnea index [during rapid eye movement (REM) and non-REM (NREM) sleep], and oxygen desaturation index (≥3%, ODI-3%) values of the high-risk group were significantly higher than those of the low-risk group. Similarly, the mean arousal index and respiratory arousal index (R-ArI) of the high-risk group were significantly higher than those of the low-risk group. Sleep-disordered breathing indices, oxygen desaturation, and arousal responses were significantly associated with an increased risk of AD. Positive associations were observed among the AHI, ODI-3%, R-ArI, and computed product.ConclusionsRecurrent sleep-disordered breathing, intermittent hypoxia, and arousal responses, including those occurring during the NREM stage, were associated with AD risk. However, a longitudinal study should be conducted to investigate the causal relationships among these factors.

ObjectiveAbnormal functional connectivity (FC) and structure in the brain are found in patients with fibromyalgia (FM). This study investigated FC and structural alterations of the visual cortical system, the emerging contributor to pain processing, in patients with FM.MethodsThirty pain-free participants and 26 patients with FM were enrolled. Clinical characteristics were evaluated using standardized scales. Structural and resting-state functional magnetic resonance imaging were conducted. Seed-based FC analyses, voxel-based morphometry, and surface-based morphometry were performed. The FC and cortical structure of the visual system were compared between the 2 groups. The correlation between functional and structural changes in the visual cortical system with clinical presentation in the FM group was analyzed.ResultsThe patients with FM showed increased FCs within visual networks, of which the FC between the visual medial network and the right lingual gyrus (LG) was positively correlated with the Fibromyalgia Impact Questionnaire (FIQ) score. However, the FM group showed decreased FCs from the visual occipital network (VON) to several regions, of which the FCs from the VON to the bilateral frontal orbital cortices were negatively correlated with the FIQ and Pittsburgh Sleep Quality Index scores. Cortical thickness of the lateral occipital cortex, LG, and pericalcarine in FM tended to increase.ConclusionAltered FCs and structure in the visual cortical system might be involved in the pathomechanisms and clinical presentation in FM. These findings could potentially support further studies that seek to find diagnostic methods and mechanism-based therapies in patients with FM.

Spasticity measured by manual tests, such as modified Ashworth scale (MAS), may not sufficiently reflect mobility function in stroke survivors. This study aims to identify additional ambulatory information provided by the pendulum test. Clinical assessments including Brünnstrom recovery stage, manual muscle test, MAS, Tinetti test (TT), Timed up and go test, 10-m walk test (10-MWT), and Barthel index were applied to 40 ambulant chronic stroke patients. The pendular parameters, first swing excursion (FSE) and relaxation index (RI), were extracted by an electrogoniometer. The correlations among these variables were analyzed by the Spearman and Pearson partial correlation tests. After controlling the factor of motor recovery (Brünnstrom recovery stage), the MAS of paretic knee extensor was negatively correlated with the gait score of TT (r = − 0.355, p = 0.027), while the FSE revealed positive correlations to the balance score of TT (r = 0.378, p = 0.018). RI were associated with the comfortable speed of 10-MWT (r = 0.367, p = 0.022). These results suggest a decrease of knee extensor spasticity links to a better gait and balance in chronic stroke patients. The pendular parameters can provide additional ambulatory information, as complementary to the MAS. The pendulum test can be a potential tool for patient selection and outcome assessment after spasticity treatments in chronic stroke population.

The aims of this study were (1) to compare the effect of robot-assisted gait orthosis (RAGO) plus conventional physiotherapy with the effect of conventional therapy alone on functional outcomes, including balance, walking ability, muscle strength, daily activity, and cognition, in chronic stroke patients, and (2) to determine the association of adjustable parameters of RAGO on functional outcomes. Adjustable parameters of RAGO included guidance force, treadmill speed, and body-weight support. This retrospective cohort study enrolled 32 patients with chronic stroke. Of these, 16 patients received RAGO plus conventional physiotherapy (RAGO group), and 16 patients received conventional physiotherapy alone (control group). Balance was assessed using the Berg Balance Scale, walking ability using the Functional Ambulation Category, muscle strength using the Motricity Index, daily activity using the Barthel Index, and cognition using the Mini-Mental State Examination. The scores were assessed before and after training. The Mini–Mental State Examination and the Berg Balance Scale increased significantly in both groups, whereas improvements in the Motricity Index and the Barthel Index were only observed in the RAGO group after intervention. During RAGO training, reducing guidance force and body-weight support assistance was associated with improvements in the Barthel Index, whereas higher treadmill walking speed was associated with improvements in the Berg Balance Scale. Our study found that RAGO combination therapy resulted in improvements in more functional outcomes than did conventional training alone. The adjustable parameters of the RAGO training were partly associated with training outcomes.

ObjectiveIn patients with fibromyalgia (FM), the brain shows altered structure and functional connectivity, but the mechanisms underlying these changes remain unclear. This study investigated the associated changes in brain microstructures and neuroinflammation of patients with FM.MethodsWe recruited 14 patients with FM and 14 healthy controls (HCs). Visual analog scale (VAS), Beck Anxiety Inventory (BAI), and Beck Depression Inventory-II (BDI-II) were used for assessing their pain, anxiety, and depression levels, respectively. Diffusion kurtosis imaging (DKI) was used to visualize microstructural alterations associated with neuroinflammation in specific brain regions. The biomarkers for neuron damage, including serum tau and amyloid β protein fragment 1-42 (Aβ1-42) levels, were assessed. Spearman correlation of DKI parameters with VAS, BAI, and BDI-II scores as well as tau and Aβ1-42 levels were assessed.ResultsThe patients with FM had significantly higher levels of Aβ1-42 levels than HCs. Compared with HCs, the patients with FM showed significantly lower DKI parameters in the bilateral dorsolateral prefrontal cortex and orbitofrontal cortex. Patients with FM showed a significant correlation between the axial kurtosis values of the amygdala and VAS scores (left: ρ = −0.60, P = 0.02; right: ρ = −7.04, P = 0.005).ConclusionTo the best of our knowledge, this is the first study to use DKI to examine the brains of patients with FM. We noted significant DKI changes associated with neuroinflammation at specific areas in patients with FM. Our results provide valuable information on brain neuroinflammation and pathophysiological changes in patients with FM.

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Fibromyalgia syndrome (FM) is a multifactorial disorder whose pathogenesis and diagnosis are poorly understood. This study investigated differential serum proteome profiles in patients with FM and healthy pain-free controls and explored the association between serum proteome and clinical profiles in patients with FM. Twenty patients with FM (according to the American College of Rheumatology criteria, 2010) and 20 healthy pain-free controls were recruited for optimized quantitative serum proteomics analysis. The levels of pain, pressure pain threshold, sleep, anxiety, depression, and functional status were evaluated for patients with FM. We identified 22 proteins differentially expressed in FM when compared with healthy pain-free controls and propose a panel of methyltransferase-like 18 (METTL18), immunoglobulin lambda variable 3–25 (IGLV3–25), interleukin-1 receptor accessory protein (IL1RAP), and IGHV1OR21-1 for differentiating FM from controls by using a decision tree model (accuracy: 0.97). In addition, we noted several proteins involved in coagulation and inflammation pathways with distinct expression patterns in patients with FM. Novel proteins were also observed to be correlated with the levels of pain, depression, and dysautonomia in patients with FM. We suggest that upregulated inflammation can play a major role in the pathomechanism of FM. The differentially expressed proteins identified may serve as useful biomarkers for diagnosis and evaluation of FM in the future.

Abnormal resting-state functional connectivity (rs-FC) and brain structure have emerged as pathological hallmarks of fibromyalgia (FM). This study investigated and compared the accuracy of network rs-FC and brain structural features in identifying FM with a machine learning (ML) approach. Twenty-six FM patients and thirty healthy controls were recruited. Clinical presentation was measured by questionnaires. After MRI acquisitions, network rs-FC z-score and network-based gray matter volume matrices were exacted and preprocessed. The performance of feature selection and classification methods was measured. Correlation analyses between predictive features in final models and clinical data were performed. The combination of the recursive feature elimination (RFE) selection method and support vector machine (rs-FC data) or logistic regression (structural data), after permutation importance feature selection, showed high performance in distinguishing FM patients from pain-free controls, in which the rs-FC ML model outperformed the structural ML model (accuracy: 0.91 vs. 0.86, AUC: 0.93 vs. 0.88). The combined rs-FC and structural ML model showed the best performance (accuracy: 0.95, AUC: 0.95). Additionally, several rs-FC features in the final ML model correlated with FM’s clinical data. In conclusion, ML models based on rs-FC and brain structural MRI features could effectively differentiate FM patients from pain-free subjects.

Peer reviewed: True, Obstructive sleep apnea (OSA) is a global health concern and is typically diagnosed using in-laboratory polysomnography (PSG). However, PSG is highly time-consuming and labor-intensive. We, therefore, developed machine learning models based on easily accessed anthropometric features to screen for the risk of moderate to severe and severe OSA. We enrolled 3503 patients from Taiwan and determined their PSG parameters and anthropometric features. Subsequently, we compared the mean values among patients with different OSA severity and considered correlations among all participants. We developed models based on the following machine learning approaches: logistic regression, k-nearest neighbors, naïve Bayes, random forest (RF), support vector machine, and XGBoost. Collected data were first independently split into two data sets (training and validation: 80%; testing: 20%). Thereafter, we adopted the model with the highest accuracy in the training and validation stage to predict the testing set. We explored the importance of each feature in the OSA risk screening by calculating the Shapley values of each input variable. The RF model achieved the highest accuracy for moderate to severe (84.74%) and severe (72.61%) OSA. The level of visceral fat was found to be a predominant feature in the risk screening models of OSA with the aforementioned levels of severity. Our machine learning models can be employed to screen for OSA risk in the populations in Taiwan and in those with similar craniofacial structures.

The skeleton is one of the most important organs in the human body in assisting our motion and activities; however, bone density attenuates gradually as we age. Among common bone diseases are osteoporosis and Paget's, two of the most frequently found diseases in the elderly. Nowadays, a combination of multiple drugs is the optimal therapy to decelerate osteoporosis and Paget's pathologic process, which comes with various underlying adverse effects due to drug-drug interactions (DDIs). Artificial intelligence (AI) has the potential to evaluate the interaction, pharmacodynamics, and possible side effects between drugs. In this research, we created an AI-based machine-learning model to predict the outcomes of interactions between drugs used for osteoporosis and Paget's treatment, which helps mitigate the cost and time to implement the best combination of medications in clinical practice. In this study, a DDI dataset was collected from the DrugBank database within the osteoporosis and Paget diseases. We then extracted a variety of chemical features from the simplified molecular-input line-entry system (SMILES) of defined drug pairs that interact with each other. Finally, machine-learning algorithms were implemented to learn the extracted features. Our stack ensemble model from Random Forest and XGBoost reached an average accuracy of 74 % in predicting DDIs. It was superior to individual models as well as previous methods in terms of most measurement metrics. This study showed the potential of AI models in predicting DDIs of Osteoporosis-Paget's disease in particular, and other diseases in general.

Energy expenditure through metabolic equivalent (MET) prediction during resistance exercises in humans can be modeled by using cardiorespiratory parameters. In this study, we aimed to predict MET during six moderate-intensity resistance training sessions consisting of three different exercises. Eleven participants were recruited into two groups, an untrained (n = 5, with no resistance training experience) and a trained group (n = 6, with 2 months resistance training experience). Each participant completed six training sessions separated with a rest interval of 1–2 days. While wearing a mask for indirect calorimetric measurements using Cortex Metalyzer 3B, each participant performed training sessions consisting of three types of dumbbell exercises: shoulder press, deadlift, and squat. The metabolic equivalents (METs), respiratory exchange ratio (RER), heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), blood lactate (BL), and Borg rate of perceived exertion (RPE) were measured. The MET was predicted using generalized estimating equations (GEE) for repeated measure data collected during exercise and rest periods. It was observed that during exercise period, RER, HR, SBP, and BL for the training group (QIC = 187, 95% CI = −0.012~0.915, p = 0.000*~0.033*) while RER, HR, SBP, DBP, and RPE (QIC = 48, 95% CI = −0.024~0.422, p = 0.000*~0.002*) during resting period for untrained group significantly predicted MET for moderate-intensity interval resistance training. It is concluded that the cardiorespiratory variables are significantly related to MET. During exercise, RER and HR significantly predicted MET for both groups along with additional parameters of SBP and BL for the training group. While during the resting period, RER, HR, SBP, DBP, and RPE related significantly for untrained and BL for training group respectively.

Objectives: This study aimed to investigate the safety and efficacy of high-definition transcranial alternating current stimulation (HD-tACS) to the left primary motor cortex (M1) in the treatment of fibromyalgia (FM) patients. Methods: In this randomized, double-blind, sham-controlled clinical trial, patients with FM were recruited in a teaching hospital. Thirty-eight patients were randomized to active HD-tACS (n = 19) or sham stimulation (n = 19). Active stimulation included a daily session of 20-min stimulation of 1 mA HD-tACS over the left M1 for ten sessions in two weeks. The primary outcome was the change in pain intensity and quality of life, assessed using the numeric rating scale (NRS) and the fibromyalgia impact questionnaire (FIQ) at baseline and after two weeks of treatment. Secondary outcomes included other core symptoms of FM (psychological distress, sleep quality, hyperalgesia measured by pressure pain threshold) and changes in biomarkers’ total Tau and Aβ1-42. All analyses were based on intention-to-treat for a significance level of p < 0.05. Results: Of the 38 randomized patients, 35 completed the study. After two weeks, HD-tACS induced a significant reduction in FIQ score post-treatment. However, there were no significant differences in NRS and FIQ scores compared to sham stimulation. Most adverse events were mild in severity. Nevertheless, one patient receiving HD-tACS attempted suicide during the trial. Conclusions: These results suggest that HD-tACS may effectively reduce pain, psychological distress, and symptom impacts in FM patients. However, we found no significant differences between the two groups. Future studies investigating HD-tACS in FM are warranted.

Mechanical properties are crucial parameters for scaffold design for bone tissue engineering; therefore, it is important to understand the definitions of the mechanical properties of bones and relevant analysis methods, such that tissue engineers can use this information to properly design the mechanical properties of scaffolds for bone tissue engineering. The main purpose of this article is to provide a review and practical guide to understand and analyze the mechanical properties of compact bone that can be defined and extracted from the stress–strain curve measured using uniaxial tensile test until failure. The typical stress–strain curve of compact bone measured using uniaxial tensile test until failure is a bilinear, monotonically increasing curve. The associated mechanical properties can be obtained by analyzing this bilinear stress–strain curve. In this article, a computer programming code for analyzing the bilinear stress–strain curve of compact bone for quantifying the associated mechanical properties is provided, such that the readers can use this computer code to perform the analysis directly. In addition to being applied to compact bone, the information provided by this article can also be applied to quantify the mechanical properties of any material having a bilinear stress–strain curve, such as a whole bone, some metals and biomaterials. The information provided by this article can be applied by tissue engineers, such that they can have a reference to properly design the mechanical properties of scaffolds for bone tissue engineering. The information can also be applied by researchers in biomechanics and orthopedics to compare the mechanical properties of bones in different physiological or pathological conditions.

We propose the deep hierarchical network (DHN) for the quantitative analysis of facial palsy. Facial palsy, also known as Bell’s palsy, is the most common type of facial nerve palsy that results in the loss of muscle control in the affected facial regions. Typical symptoms include facial deformity and facial expression dysfunction. To the best of our best knowledge, all approaches for the automatic detection of facial palsy consider hand-crafted features. This paper reports the first deep-learning-based approach developed for the real-time quantitative analysis of facial palsy. The proposed DHN consists of three component networks: the first detects the subject’s face, the second detects the facial landmarks and line segments on the detected face, and the third detects the local palsy regions. The first component network is built on the YOLO2 detector. The second component network is developed on a fused network architecture that incorporates a line segment learning network for locating the facial landmarks and line segments. The third component network is developed on an object detection network with the line-segment-embedded input that combines the landmarked region and the line segments detected by the second component network. The novelties of this research include: 1) the modification of a state-of-the-art edge detector for extracting the facial line segments; 2) the embedding of the line segment learning for the detection of facial landmarks and local palsy regions; 3) the quantitative description of the facial palsy syndrome intensity; and 4) the release of the first clinically labeled database, the YouTube Facial Palsy (YFP) database. The making of the YFP database solves the issue that previous methods were all evaluated on proprietary databases, making the comparison of different methods extremely difficult. The YFP database includes 32 videos of 21 patients collected from YouTube and labeled by clinic specialists. To enhance the robustness against facial expression variations, we include the CK+ facial expression database in the training. We show that the proposed DHN not only just detects the local palsy regions but also captures the intensity of the facial palsy syndrome over time, enabling the quantitative description of the syndrome. The experiments show that the proposed approach offers an accurate and efficient real-time solution for facial palsy analysis.

Fibromyalgia syndrome (FM) is a multifactorial disorder whose pathogenesis and diagnosis are poorly understood. This study investigated differential serum proteome profiles in patients with FM and healthy pain-free controls and explored the association between serum proteome and clinical profiles in patients with FM. Twenty patients with FM (according to the American College of Rheumatology criteria, 2010) and 20 healthy pain-free controls were recruited for optimized quantitative serum proteomics analysis. The levels of pain, pressure pain threshold, sleep, anxiety, depression, and functional status were evaluated for patients with FM. We identified 22 proteins differentially expressed in FM when compared with healthy pain-free controls and propose a panel of methyltransferase-like 18 (METTL18), immunoglobulin lambda variable 3-25 (IGLV3-25), interleukin-1 receptor accessory protein (IL1RAP), and IGHV1OR21-1 for differentiating FM from controls by using a decision tree model (accuracy: 0.97). In addition, we noted several proteins involved in coagulation and inflammation pathways with distinct expression patterns in patients with FM. Novel proteins were also observed to be correlated with the levels of pain, depression, and dysautonomia in patients with FM. We suggest that upregulated inflammation can play a major role in the pathomechanism of FM. The differentially expressed proteins identified may serve as useful biomarkers for diagnosis and evaluation of FM in the future.

Objective To evaluate the efficacy of shared decision-making (SDM) intervention among patients with lumbar degenerative diseases (LDDs) in terms of decision self-efficacy, control preferences, SDM process, decision satisfaction, and conflict. Methods A total of 130 outpatients with LDDs recruited from orthopedic or rehabilitation clinics were randomly assigned to the SDM intervention (n = 67) or comparison (n = 63) groups. Patients in the intervention group received decision aids (DAs) with decision coaching and those in controlled group received standard educational materials from a health educator. The primary outcome was decision self-efficacy, and secondary outcomes were control preference, SDM process, conflict, and satisfaction. Results The SDM intervention significantly improved decision self-efficacy (mean difference [MD] = 7.1, 95% confidence interval [CI]: 1.7–12.5, partial η2 = 0.05) and reduced conflict (MD = −7.0, 95% CI: −12.2 to −1.9, partial η2 = 0.06), especially in patients without family involvement, compared with the health education group. However, no significant between-group differences were observed in other outcomes. Conclusion SDM intervention improved SDM self-efficacy and reduced conflict in patients with LDDs. Practice Implications Clinicians can integrate DAs and decision coaching in SDM conversations. SDM intervention seems to engage patients in decision-making, especially those without family involvement.

IntroductionStroke can lead to life-long disability and constitutes a huge financial burden on the family and society. Stroke survivors with cognitive impairment often experience considerable challenges in the process of recovery and returning to society. Interventions that effectively help individuals resume essential daily activities and return to active participation in their communities are lacking. This study examines the efficacy of a newly-developed intervention programme, the Optimising Participation after Stroke through Strategy-training (OPASS) programme, for improving community participation among stroke survivors with cognitive impairment.Methods and analysisA single-blind, parallel-group randomised controlled trial with allocation concealment and assessor blinding will be implemented to assess the efficacy of the OPASS programme. An expected 210 adults with cognitive impairment following stroke will be randomly assigned to either the experimental intervention (OPASS) group or the attention control group. In addition to their usual rehabilitation, both groups will receive 45 min sessions, twice weekly for a total of 12–15 sessions. The primary outcome is change in participation performance, which will be measured using the participation measure—three domains, four dimensions scale. Additional measures include the Activity Measure for Post-Acute Care generic outpatient short forms, Montreal Cognitive Assessment, Stroop Test, Trail Making Test and General Self-Efficacy Scale. These scales will be administered at baseline, post-intervention, 3-month follow-up, 6-month follow-up and 12-month follow-up. Their results will be analysed using multiple linear regression models and mixed-effects regression models. Further assessment of feasibility and acceptability of the intervention will be conducted through structured interviews with participants, caregivers and therapists. These interviews will be transcribed and thematically analysed.Ethics and disseminationEthics approval was obtained from the Ethics Committee of Taipei Medical University (approval number: N201804055). The findings will be disseminated through presentations at scientific conferences and through publication in peer-reviewed journals.Trial registration numberNCT03792061; pre-results.

ObjectiveFibromyalgia (FM) is a chronic widespread pain syndrome. Although its mechanism remains relatively unknown, accelerated neurodegeneration in the brain has been reported in patients with FM. Sleep disturbance can increase the risk of neurocognitive disorders, which are associated with tau and beta-amyloid (Aβ) protein accumulation. We hypothesize neurodegeneration in patients with FM may be associated with sleep disturbance.MethodsIn this case-control study, we analyzed serum tau and Aβ levels and their association with symptom profiles for patients with FM, by recruiting 22 patients with FM and 22 age-matched healthy participants. The visual analog scale, Fibromyalgia Impact Questionnaire, pressure pain threshold test, Pittsburgh Sleep Quality Index (PSQI), Beck Depression Inventory-II, Beck Anxiety Inventory, and serum tau and beta-amyloid-42 (Aβ-42) levels were recorded. The Mann–Whitney test was conducted to compare questionnaire and protein level results between the groups. Pearson correlation test was conducted to investigate the correlation of questionnaire scores with tau and Aβ-42 levels in patients with FM. The significance level was set at P ResultsSerum tau and Aβ-42 levels were significantly higher in patients with FM than in controls. A positive correlation between serum tau levels and PSQI scores was observed in patients with FM (r = 0.476, P = .025). We found that only sleep disturbance in patients with FM was significantly associated with higher serum tau levels among all symptom scores.ConclusionsWe suggest sleep disturbance may play a vital role in the pathomechanism of accelerated neurodegeneration in FM.

Oxygen consumption (VO2) during strength training can be predicted through surface electromyography (sEMG) of local muscles. This research aimed to determine relations between VO2 and sEMG of upper and lower body muscles to predict VO2 from sEMG during moderate-intensity strength training exercises. Of the 12 participants recruited, 11 were divided into two groups: untrained (n = 5; with no training experience) and trained (n = 6; with 2 months of training experience). On different days, each individual completed six training sessions. Each participant performed training sessions consisting of three types of dumbbell exercises: shoulder press, deadlift, and squat, while wearing a mask for indirect calorimetric measurements of VO2 using the Cortex Metalyzer 3B. sEMG measurements of the bilateral middle deltoid, lumbar erector spinae, quadriceps (rectus femoris), and hamstring (biceps femoris) muscles were recorded. The VO2 was predicted from sEMG root mean square (RMS) values of the investigated muscles during the exercise period using generalized estimating equation (GEE) modeling. The predicted models for the three types of exercises for the untrained vs. trained groups were shoulder press [QIC = 102, * p = 0.000 vs. QIC = 82, * p = 0.000], deadlift [QIC = 172, * p = 0.000 vs. QIC = 320, * p = 0.026], and squat [QIC = 76, * p = 0.000 vs. QIC = 348, * p = 0.001], respectively. It was observed that untrained vs. trained groups predicted GEE models [quasi-likelihood under an independence model criterion (QIC) = 368, p = 0.330 vs. QIC = 837, p = 0.058], respectively. The study obtained significant VO2 prediction models during shoulder press, deadlift, and squat exercises using the right and left middle deltoid, right and left lumbar erector spinae, left rectus femoris, and right and left biceps femoris sEMG RMS for the untrained and trained groups during moderate-intensity strength training exercises.

Introduction Conflicting results persist regarding the effectiveness of robotic-assisted gait training (RAGT) for functional gait recovery in post-stroke survivors. We used several machine learning algorithms to construct prediction models for the functional outcomes of robotic neurorehabilitation in adult patients. Methods and materials Data of 139 patients who underwent Lokomat training at Taipei Medical University Hospital were retrospectively collected. After screening for data completeness, records of 91 adult patients with acute or chronic neurological disorders were included in this study. Patient characteristics and quantitative data from Lokomat were incorporated as features to construct prediction models to explore early responses and factors associated with patient recovery. Results Experimental results using the random forest algorithm achieved the best area under the receiver operating characteristic curve of 0.9813 with data extracted from all sessions. Body weight (BW) support played a key role in influencing the progress of functional ambulation categories. The analysis identified negative correlations of BW support, guidance force, and days required to complete 12 Lokomat sessions with the occurrence of progress, while a positive correlation was observed with regard to speed. Conclusions We developed a predictive model for ambulatory outcomes based on patient characteristics and quantitative data on impairment reduction with early-stage robotic neurorehabilitation. RAGT is a customized approach for patients with different conditions to regain walking ability. To obtain a more-precise and clearer predictive model, collecting more RAGT training parameters and analyzing them for each individual disorder is a possible approach to help clinicians achieve a better understanding of the most efficient RAGT parameters for different patients. Trial registration: Retrospectively registered.

Background We designed a novel ankle foot orthosis (AFO), namely, ideal training AFO (IT-AFO), with motion feedback on the hemiparetic lower limb to improve ambulation in individuals with stroke-related hemiplegia. We, therefore sought to compare the kinematic parameters of gait between IT-AFO with and without dynamic control and conventional anterior-type AFO or no AFO. Methods Gait parameters were measured using the RehaWatch® system in seven individuals with hemiplegia (mean 51.14 years). The parameters were compared across four conditions: no AFO, conventional anterior AFO, IT-AFO without dynamic control, and IT-AFO with dynamic control, with three trials of a 10-m walk test for each. Results The dorsiflexion angle increased during the swing phase when the IT-AFO was worn, and it was larger with dynamic control. These data can confirm drop foot improvement; however, the difference between the parameters with- and without-AFO control conditions was not significant in the swing phase. The IT-AFO with or without dynamic control enhanced the loading response to a greater extent between the hemiparetic and unaffected lower limbs than conventional AFO or no AFO. The duration of the stance phase on the hemiparetic lower limb was also longer when using IT-AFO with and without dynamic control than that when using conventional AFO, which improved asymmetry. User comfort and satisfaction was greater with IT-AFO than with the other conditions. Conclusions The IT-AFO with dynamic control improved gait pattern and weight shifting to the hemiparetic lower limb, reducing gait asymmetry. The difference with and without dynamic control of IT-AFO is not statistically significant, and it is limited by sample size. However, this study shows the potential of IT-AFO in applying positive motion feedback with gait training. Trial registration Taipei Medical University-Joint Institutional Review Board. N201510010. Registered 12 February 2015. http://ohr.tmu.edu.tw/main.php.

Energy expenditure during weight training exercises produces great fitness and health benefits for humans, but few studies have investigated energy expenditure directly during weight training. Therefore, in this study, we aimed to determine energy costs during three training sessions consisting of three different exercises. Ten participants were randomly allocated into two groups: an untrained (n = 5, with no weight training experience) and a trained group (n = 5, with some weight training experience). Each participant completed three training sessions on separate days. While wearing a mask for indirect calorimetric measurements, each participant participated in training sessions conducted with three dumbbell exercises: the bent-over row, deadlift, and lunge. Metabolic equivalents (METs), energy expenditure (EE), respiratory exchange ratio (RER), heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), and rate of perceived exertion (RPE) were measured. The total energy cost was calculated from the oxygen consumption (VO2) during each exercise. Our results showed that the METs of a single training session were 3.3 for the untrained group and 3.4 for the trained group, while the sum of the EE was 683–688 and 779–840 kcal, respectively. The physiological parameters, such as heart rate (p = 0.001 *) for the lunge and rate of perceived exertion (p = 0.005 *) for the bent-over row, changed significantly in both groups. It was concluded that the exercise protocol of this study involved a moderate intensity of 2.4–3.9 METs. The energy cost of each training exercise was between 179 and 291 kcal.

Failure to deliver the standard stroke care is suspected to be a potential reason for disproportionately high mortality among patients with co-morbid bipolar disorder (BD). Few studies have explored adverse outcomes and medical care costs concurrently (as a proxy for care intensity) among patients with BD admitted for stroke. Data for this nationwide population-based study were extracted from the Taiwan National Health Insurance Research Database, on 580 patients with BD hospitalized for stroke (the study group) and a comparison group consisting of randomly selected 1740 stroke patients without BD matched by propensity scores. Conditional logistic regression was used to estimate odds ratios (OR) for adverse in-hospital outcomes between study group and comparison group. We found that stroke patients with BD had significantly lower in-hospital mortality (3.28% vs. 5.63%), acute respiratory failure (2.59% vs. 5.57%), and use of mechanical ventilation (6.55% vs. 10.23%) than the comparison group. After adjusting for geographical location, urbanization level, monthly income, hypertension, diabetes, hyperlipidemia, and coronary heart disease, the odds of in-hospital mortality, acute respiratory failure, and use of mechanical ventilation in the BD group were 0.56 (95% CI: 0.34-0.92), 0.46 (95% CI: 0.26-0.80), and 0.63 (95% CI: 0.44-0.91), respectively. No differences were found in hospitalization costs and the length of hospital stay. With comparable hospitalization costs and length of hospital stay, we concluded that stroke patients with BD had lower in-hospital mortality and serious adverse events compared to stroke patients without BD.

Parameters derived from the goniometer measures in the Pendulum test are insufficient in describing the function of abnormal muscle activity in the spasticity. To explore a quantitative evaluation of muscle activation-movement interaction, we propose a novel index based on phase amplitude coupling (PAC) analysis with the consideration of the relations between movement and surface electromyography (SEMG) activity among 22 hemiplegic stroke patients. To take off trend and noise, we use the empirical mode decomposition (EMD) to obtain intrinsic mode functions (IMFs) of the angular velocity due to its superior decomposing ability in nonlinear oscillations. Shannon entropy based on angular velocity (phase)-envelope of EMG (amplitude) distribution was calculated to demonstrate characteristics of the coupling between SEMG activity and joint movement. We also compare our results with those from traditional methods such as the normalized relaxation index derived from the Pendulum test and the mean root mean square (RMS) of the SEMG signals in the study. Our results show effective discrimination ability between spastic and nonaffected limbs using our method $({\rm p} . This study indicates the feasibility of using the novel indices based on the PAC in evaluation the spasticity among the hemiplegic stroke patients with less than three swinging cycles.

© 2016 Chung et al. This work is published by Dove Medical Press Limited, and licensed under a Creative Commons Attribution License. The full terms of the License are available at http://creativecommons.org/licenses/by/4.0/. The license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. © 2016 Chung et al. This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms. php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). Neuroscience and Neuroeconomics 2016:5 45–53 Neuroscience and Neuroeconomics Dovepress

OBJECTIVES The effects of non-invasive brain stimulation (NBS), including repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (TDCS), in treating FM remain inconclusive. The aim of this study was to investigate present evidence of using NBS as an add-on treatment in treating FM. METHODS We conducted a database search of the Medline, Embase, PsycINFO and Cochrane Library electronic databases, from inception to July 2015, to analyse randomized controlled trials of NBS in treating FM. A total of 16 studies were included in the current meta-analysis. RESULTS The pooled mean effect sizes of the 16 included studies revealed significant favourable effects of NBS. The weighted mean effect size in reducing pain, depression, fatigue, sleep disturbance and tender points and improving general health/function were 0.667 (95% CI 0.446, 0.889), 0.322 (95% CI 0.140, 0.504), 0.511 (95% CI 0.247, 0.774), 0.682 (95% CI 0.350, 1.014), 0.867 (95% CI 0.310, 1.425) and 0.473 (95% CI 0.285, 0.661), respectively. rTMS stimulation yielded a greater effect size compared with that of TDCS (effect size 0.698 and 0.568, respectively; P < 0.0001). The primary motor cortex (M1) stimulation yielded a subtle greater effect size in pain reduction compared with that of the dorsolateral prefrontal cortex (effect size 0.709 and 0.693, respectively; P < 0.0001). No linear relationships were found between the effect sizes and treatment regimens and dose. Most of reported adverse effects were minor. CONCLUSIONS Both rTMS and TDCS may be feasible and safe modalities for treating FM. The general effects of rTMS and TDCS are compatible in FM patients. M1 stimulation may be better in pain reduction and the dorsolateral prefrontal cortex may be better in depression improvement.

We propose the Hierarchical Detection Network (HDN) for the detection of facial palsy syndrome. This can be the first deep-learning based approach for the facial palsy detection. The proposed HDN consists of three component networks, the first detects faces, the second detects the landmarks on the detected faces, and the third detects the local palsy regions. The first and the third component networks are built on the Darknet framework, but with fewer layers of convolutions for shorter processing speed. The second component network employs the latest 3D face alignment network for locating the landmarks. The first component network employs a Na × Na grid over the overall input image, while the third component network employs a Nb × Nb grid over each detected face, making the HDN capable of efficiently locating the affected palsy regions. As previous approaches were evaluated on proprietary databases, we have collected 32 videos from YouTube and made the first public database for facial palsy study. To enhance the robustness against expression variations, we include the CK+ facial expression database in the training and testing phases. We show that the HDN does not just detect the local palsy regions, but also captures the frequency of the intensity, enabling the video-to-description diagnosis of the syndrome. Experiments show that the proposed approach offers an accurate and efficient solution for facial palsy detection/diagnosis.

Specific data regarding the full range of stroke outcomes among patients with rheumatoid arthritis (RA) are lacking. This study aimed to investigate outcomes in RA patients hospitalized for a stroke. The study retrieved data from the Taiwan Longitudinal Health Insurance Database 2005. We identified 26,336 patients who were hospitalized for stroke treatment. Of these patients, 736 patients with a prior diagnosis of RA before the index hospitalization were selected as the study group. We selected 2208 age–sex-matched patients without RA as the comparison group. We performed conditional logistic regressions to calculate odds ratios (ORs) for in-hospital mortality and secondary diagnoses of pneumonia, urinary tract infections (UTIs), peptic ulcers, acute respiratory failure, and the use of mechanical ventilation to compare RA patients and comparison patients. We also compared the length of stay (LOS) and hospitalization costs between patients with RA and comparison patients. We found that RA patients had a significantly increased risk of peptic ulcer during the stroke hospitalization (OR = 1.52, 95% CI = 1.05–2.20). However, there were no significant differences between patients with RA and comparison patients in terms of in-hospital mortality, pneumonia, UTIs, acute respiratory failure, or the use of mechanical ventilation. Furthermore, the LOS of stroke hospitalization did not differ between the two groups. We concluded that RA patients hospitalized for a stroke do not have a significantly different risk of in-hospital mortality, pneumonia, UTIs, and mechanical ventilator use, but they have a higher risk of peptic ulcers. Additionally, among patients with a subarachnoid/intracerebral hemorrhagic stroke, RA patients were more likely to have received mechanical ventilation than comparison patients (adjusted OR = 1.89, 95% CI = 1.14–3.15).

Table S1. Meteorological and gaseous data measured by the traffic-related EPA Yonghe air quality monitoring stations during the study period. Table S2. Instruments used to characterize the exposure conditions for rats. Figure S2. Characterization of particle size and penetration distribution (between outdoor and whole-body exposure system) determined using a scanning mobility particle sizer (SMPS, TSI 3936; upper size limit: 710 nm). (a) The exposure cages (yellow marked: 1–1, 1–3, 1–5, 2–3, 3–1, 3–3 and 3–5) were measured for size-penetration distribution. (b) The individual cage for animal exposure showed a consistent size-penetration distribution. The geometric mean diameter (GMD) was 50 nm. (DOCX 152 kb)

Background Cardiovascular diseases are reported to be associated with both chronic rhinosinusitis (CRS) and dementia. Nevertheless, whether dementia is associated with CRS is still unknown. In the present study, we explored the association between dementia with prior CRS using a population-based data set. Methods This study used the Taiwan Longitudinal Health Insurance Database 2000 as the source of data for a case-control study. We included 8768 subjects with dementia as cases and 8768 age- and sex-matched subjects as controls. We identified cases who had received a diagnosis of CRS before having received a diagnosis of dementia. Conditional logistic regression analyses were performed to examine the association of dementia with previously diagnosed CRS. Results Results showed that of all sampled subjects, 875 (5.0%) had been previously diagnosed with CRS. A chi-squared test showed that there was a significant difference in the prevalences of prior CRS between cases and controls (6.0% versus 4.0%; p < 0.001). The adjusted odds ratio (OR) of prior CRS for subjects with dementia was 1.44 (95% CI, 1.25—1.66) compared with controls. Furthermore, compared with controls, the OR of prior CRS was similar for subjects with dementia for both sexes (the OR for male subjects was 1.48 and OR for female subjects was 1.41). Conclusion We concluded that subjects with dementia had a higher odds of having had prior CRS than controls. This study implies a potential association between CRS and dementia.

This study aimed to explore the risk for depressive disorder (DD) among stroke patients with statin use. Totally, 11,218 patients who had a first-time acute hospitalization for stroke were identified from Taiwan's Longitudinal Health Insurance Database 2000. We individually followed each study subject for a 1-year period to identify those patients who were subsequently diagnosed with DD during the follow-up period. We found that the incidence rate of DD during the 1-year follow-up period was 5.52 (95% CI: 4.70-6.43) and 3.46 (95% CI: 3.08-3.88) per 100 person-years for stroke patients who were statin users and nonusers, respectively. Cox proportional hazards regressions revealed that the adjusted hazard ratio (HR) for DD during the 1-year follow-up period was 1.59 for stroke patients who were statin users compared to those who were non-statin users. We further found that the adjusted HR for DD for stroke patients who were regular statin users was 1.65 compared to stroke patients who had never been prescribed statin. However, there was no increased hazard of DD for stroke patients who were irregular statin users compared to stroke patients who had never been prescribed statin (HR: 1.22, 95% CI: 0.70-2.11).

Cognitive derangement and neurological symptoms are observed in patients with anemia. Although it is still controversial, a few studies suggested that anemia may increase the risk of dementia. This study aimed to explore the association between iron-deficiency anemia (IDA) and dementia in a population-based case-control study. We retrieved our study sample from the Taiwan Longitudinal Health Insurance Database 2000. We extracted 8300 subjects with a diagnosis of dementia and 8300 age- and gender-matched controls. The results showed that there was a significant difference in the prevalence of prior IDA between cases and controls (6.0% vs. 3.8%, p

Whether statins and an angiotensin-converting enzyme inhibitors (ACEIs) / angiotensin receptor blockors (ARBs) are associated with reduced risks of infection events is still inconclusive. This study aimed to explore the risk of hospitalization for pneumonia among patients who had received treatment with ACEIs/ARBs and/or statins using a population-based dataset. This study included 19,281 patients as cases who were hospitalized for pneumonia and 19,281 controls. We used a logistic regression to compute the odds ratio (OR) and 95% confidence interval (CI) for having previously used statins or an ACEI/ ARB between patients who were hospitalized for pneumonia treatment and controls. We found there were significant associations between hospitalization for pneumonia and statin-only users (p

OBJECTIVES Fourteen-day rehospitalization with new traumatic spinal cord injury (tSCI) diagnosis is used as an indicator for the diagnostic quality of the first hospitalization. In this nationwide population-based cohort study, we identified risk factors for this indicator. METHODS We conducted a nested case-control study by using the data of patients who received a first hospitalization for trauma between 2001 and 2011. The data were retrieved from Taiwan's National Health Insurance Research Database. Variables including demographic and trauma characteristics were compared between patients diagnosed with tSCI at the first hospitalization and those receiving a 14-day rehospitalization with new tSCI diagnosis. RESULTS Of the 23 617 tSCI patients, 997 had 14-day rehospitalization with new tSCI diagnosis (incidence rate, 4.22%). The risk of 14-day rehospitalization with new tSCI diagnosis was significantly lower in patients with severe (injury severity score [ISS] = 16-24; odds ratio [OR], 0.17; 95% confidence interval [CI], 0.13-0.21) and profound (ISS > 24; OR, 0.11; 95% CI, 0.07-0.18) injuries. Interhospital transfer (OR, 8.20; 95% CI, 6.48-10.38) was a significant risk factor, along with injuries at the thoracic (OR, 1.62; 95% CI, 1.21-2.18), lumbar (OR, 1.30; 95% CI, 1.02-1.65), and multiple (OR, 3.23; 95% CI, 1.86-5.61) levels. Brain (OR, 2.82), chest (OR, 2.99), and abdominal (OR, 2.74) injuries were also identified as risk factors. In addition, the risk was higher in patients treated at the orthopedic department (OR, 2.26; 95% CI, 1.78-2.87) and those of other surgical disciplines (OR, 1.89; 95% CI, 1.57-2.28) than in those treated at the neurosurgery department. CONCLUSIONS Delayed tSCI diagnoses are not uncommon, particularly among trauma patients with ISSs < 16 or those who are transferred from lower-level hospitals. Further validation and implementation of evidence-based decision rules is essential for improving the diagnostic quality of traumatic thoracolumbar SCI.

Objective Interstitial cystitis/bladder pain syndrome (IC/BPS) is a chronic disabling condition of the urological system. Many gynecological conditions are reported to be associated with IC/BPS. This study presents epidemiological evidence of a possible association between dysmenorrhea and IC/BPS, using population-based data. Design A case–control study. Setting Taiwan. Sample The study sample was retrieved from Taiwan's Longitudinal Health Insurance Database 2000, i.e. 291 women aged 18–45 years with a diagnosis of IC/BPS between January 2000 and December 2010 (cases) and 873 randomly selected controls matched on age and index date of ambulatory care visit. We used logistic regression conditioned on age to calculate the odds ratio of cases having a prior diagnosis of dysmenorrhea relative to controls. Results Prior dysmenorrhea was found in 87 (29.9%) cases and in 163 (18.7%) of the controls. Conditional logistic regression showed a crude odds ratio of 1.86 (95% confidence interval 1.37–2.52, p

BACKGROUND Whether post-stroke spasticity is associated with autonomic status is unclear. The purpose of our study was to determine whether spasticity in post-stroke patients is associated with heart rate variability (HRV), an indicator of sympathetic and parasympathetic regulation. OBJECTIVE To determine whether HRV is associated with spasticity in post-stroke patients. METHODS Our cross-sectional observational study included 21 post-stroke patients with varying degrees of knee spasticity. We measured patients' heart rate variability (HRV) during the morning and afternoon of the same day using the modified Ashworth assessment and the pendulum test. The relationship between HRV and the spasticity parameters was evaluated based on the Pearson correlation coefficient (r). RESULTS The data for the morning measurements showed that the relaxation index negatively correlated with the high frequency (HF) power of HRV (r = -0.47, P < 0.05), and positively correlated with the low frequency (LF) power of HRV (r = 0.47, P < 0.05) and the LF/HF power ratio (r = 0.55, P < 0.05). Similar correlations were observed between the diurnal differences of HRV and the relaxation index. No correlation was observed among the data for the afternoon measurements. CONCLUSIONS Higher parasympathetic tone and lower sympathetic tone are associated with a higher degree of knee spasticity in post-stroke patients. Further studies are warranted to confirm our findings and investigate the pathological mechanisms involved.

The authors of the published version of this article incorrectly presented the affiliation of Li-Chin Sung. The revised affiliation is now presented correctly in this article.

Background The link between chronic inflammatory disease and cardiovascular disease (CVD) is recognized. Chronic rhinosinusitis (CRS) is one of the most common chronic inflammatory diseases. However, whether CRS increases the risk for CVD is still unknown. This epidemiology study investigated the risk for acute myocardial infarction (AMI) in patients with CRS using a large-scale population-based cohort study. Methods Data on all study cohorts were retrieved from the Longitudinal Health Insurance Database in Taiwan. In total, data on 7975 CRS subjects from 2001 to 2003 were extracted for the study cohort. We selected 39,875 comparison subjects whose demographic variables matched those of the study cohort. We individually tracked each subject for a 6-year period (from 2001 to 2009) to identify which subjects subsequently received a diagnosis of AMI. A stratified Cox proportional hazards regression was used to compare the 6-year risk of a subsequent AMI after a diagnosis of CRS. Results Among the 47,850 sampled subjects, the incidence rate of AMI during the 6-year follow-up period was 5.66/1000 person-years; rates were 8.49 and 5.09/1000 person-years for the study and comparison cohort, respectively. The hazard ratio (HR) for AMI during the 6-year follow-up period for subjects with CRS was 1.70 (95% confidence interval [CI], 1.52~1.91). In addition, after adjusting for cardiovascular risk factors, the HR of AMI for subjects with CRS was 1.48 (95% CI, 1.32~1.67) compared with subjects without CRS. Conclusion Patients with CRS were at higher risk for AMI occurrence in the 6-year follow-up.

Background The multi-mode modulation is a key feature of sleep EEG. And the short-term fractal property reflects the sympathovagal modulation of heart rate variability (HRV). The properties of EEG and HRV strongly correlated with sleep status and are interesting in clinic diagnosis. New method 19 healthy female subjects were included for over-night standard polysomnographic study. Hilbert Huang transform (HHT) was used to characterize the temporal features of slow- and fast-wave oscillations decomposed from sleep EEG at different stages. Masking signals were used for solving the mode-mixing problem in HHT. On the other hand, detrended fluctuation analysis (DFA) was used to assess short-term property of HRV denoted as DFA α1, which reflects the temporal activity of autonomic nerve system (ANS). Thus, the dynamic interaction between sleep EEG and HRV can be examined through the relationship between the features of sleep EEG and DFA α1 of HRV. Results The frequency feature of sleep EEG serves as a good indicator for the depth of sleep during non-rapid eye movement (NREM) sleep, and amplitude feature of fast-wave oscillation is a good index for distinguishing rapid eye movement (REM) from NREM sleep. Comparison with existing method The relationship between DFA α1 of HRV and the mean amplitude of fast-wave oscillation of sleep EEG affirmed with Pearson correlation coefficient is more significant than the correlation verified by the traditional spectral analysis. Conclusion The dynamic properties of sleep EEG and HRV derived by EMD and DFA represent important features for cortex and ANS activities during sleep.

Objectives/Hypothesis: It has been recognized that chronic rhinosinusitis (CRS) involves intracranial vessels and may be associated with stroke occurrence. However, the detailed epidemiological profile of stroke risk among patients with CRS is still not well understood. Therefore, this study aimed to explore the frequency and risk for stroke among patients with CRS by conducting a large scale population-based cohort study in Taiwan. Methods: All study cohorts were retrieved from the Taiwan Longitudinal Health Insurance Database. This study included 15,846 CRS subjects in the study cohort and 47,538 randomly selected subjects in the comparison cohort. We individually tracked each subject in this study for a 5 year period following their index dates to identify each subject that received a subsequent diagnosis of stroke. Stratified Cox proportional hazards regressions were analyzed to compare the 5 year risk of subsequent stroke following a diagnosis of CRS. Results: The incidence rate of stroke during the 5-year follow-up period was 10.65 (95% CI: 9.93–11.41) per 100 person years and 7.53 (95% CI: 7.18–7.89) per 100 person years for the study and comparison cohort, respectively. The covariate-adjusted hazard ratio (HR) for stroke revealed that that subjects with CRS were more likely than comparison subjects to have a diagnosis of ischemic stroke during the 5-year follow-up period (HR = 1.34, 95% CI = 1.18–1.53). However, there was no significant difference in the risk of subarachnoid hemorrhage (HR = 1.52, 95% CI = 0.94–2.47) or intracerebral hemorrhage (HR = 0.96, 95% CI = 0.71–1.31). Conclusions: Patients with CRS were at higher risk for stroke occurrence during the 5 year follow-up.