Health Education for Chronic Kidney Disease Patients Not on Dialysis Through the Pictorial Patient Information Leaflet.

Background: Educating the patient with patient information leaflets is helpful to increase understanding and awareness about chronic kidney disease. Various educational materials are available online, but their quality is mixed. The content was found to be unreliable or incomprehensible. Objective: The study aimed to develop, validate, test the readability, translation, and design of the patient information leaflet and focused on assessing patients' knowledge levels using questionnaires after providing the validated patient information leaflet. Methods: A prospective study was conducted among chronic kidney disease patients who were not on dialysis. The patient information leaflet was prepared based on experts' opinions and a thorough review of various resources. Experts validated the content of the patient information leaflet through the content validity index. After being validated, the Baker Able leaflet design scale was used to evaluate the layout and design. Knowledge assessment questions were validated using item-content validity index scores to assess patient knowledge before and after providing the patient information leaflet. Results: A total of 60 randomly selected chronic kidney disease patients were enrolled. The content validity index of the patient information leaflet was found to be 0.9. The Baker Able leaflet design score was found to be 25. Knowledge was assessed and it showed that score had increased from 42 ± 6.95 to 73.5 ± 6.70, respectively, with a P-value <0.000. Conclusion: This study concluded that the patient information leaflet was developed based on standard procedures. Significant improvement was seen in patients' knowledge after utilizing a validated patient information leaflet.

Altered neural processing of the need to stop in young adults at risk for stimulant dependence.

Identification of neurocognitive predictors of substance dependence is an important step in developing approaches to prevent addiction. Given evidence of inhibitory control deficits in substance abusers (Monterosso et al., 2005; Fu et al., 2008; Lawrence et al., 2009; Tabibnia et al., 2011), we examined neural processing characteristics in human occasional stimulant users (OSU), a population at risk for dependence. A total of 158 nondependent OSU and 47 stimulant-naive control subjects (CS) were recruited and completed a stop signal task while undergoing functional magnetic resonance imaging (fMRI). A Bayesian ideal observer model was used to predict probabilistic expectations of inhibitory demand, P(stop), on a trial-to-trial basis, based on experienced trial history. Compared with CS, OSU showed attenuated neural activation related to P(stop) magnitude in several areas, including left prefrontal cortex and left caudate. OSU also showed reduced neural activation in the dorsal anterior cingulate cortex (dACC) and right insula in response to an unsigned Bayesian prediction error representing the discrepancy between stimulus outcome and the predicted probability of a stop trial. These results indicate that, despite minimal overt behavioral manifestations, OSU use fewer brain processing resources to predict and update the need for response inhibition, processes that are critical for adjusting and optimizing behavioral performance, which may provide a biomarker for the development of substance dependence.

Bayesian prediction and evaluation in the anterior cingulate cortex.

The dorsal anterior cingulate cortex (dACC) has been implicated in a variety of cognitive control functions, among them the monitoring of conflict, error, and volatility, error anticipation, reward learning, and reward prediction errors. In this work, we used a Bayesian ideal observer model, which predicts trial-by-trial probabilistic expectation of stop trials and response errors in the stop-signal task, to differentiate these proposed functions quantitatively. We found that dACC hemodynamic response, as measured by functional magnetic resonance imaging, encodes both the absolute prediction error between stimulus expectation and outcome, and the signed prediction error related to response outcome. After accounting for these factors, dACC has no residual correlation with conflict or error likelihood in the stop-signal task. Consistent with recent monkey neural recording studies, and in contrast with other neuroimaging studies, our work demonstrates that dACC reports at least two different types of prediction errors, and beyond contexts that are limited to reward processing.

Physical and psychosocial burden experienced by women on maintenance hemodialysis.

BACKGROUND: The global prevalence of chronic kidney disease is growing at an alarming rate, and the number of patients progressing to kidney failure is increasing. A substantial number of patients are undergoing hemodialysis (HD), which improves health and lengthens life. However, it imposes multiple physical and psychological demands on the patients. With the intensity of symptoms being greater among women, a greater focus is needed to obtain empirical evidence regarding the health problems of females receiving HD. MATERIALS AND METHODS: A descriptive qualitative design was used to explore the health problems of women undergoing maintenance HD. The sampling technique used was maximum variation purposive sampling. The data were collected through in-depth face-to-face interviews with 12 female patients attending the dialysis unit of a tertiary care hospital in northern Kerala, South India, using a semi-structured interview guide. The interview was audiotaped, and the participant content was later converted verbatim into English. The content was imported to NVivo and coded. Thematic analysis was performed using Braun and Clarke's six-step approach. RESULT: During data analysis, six major themes and 20 subthemes emerged. The themes include (1) physical suffering, (2) mental agony, (3) restricted life, (4) sexual inactivity, (5) breakdown of social life, and (6) financial hardship. CONCLUSION: Females undergoing maintenance hemodialysis experience significant health-related issues in all major dimensions of health. They are physically vulnerable, psychologically defeated, and socially detached. The study highlights the need for detailed evaluation and consistently supportive and educational care.

Hypokalaemic quadriparesis in a patient with urinary diversion through Indiana pouch.

A man in his 20s, a patient with chronic kidney disease with a baseline estimated glomerular filtration rate of 33 mL/min/1.73 m2, who had an Indiana pouch continent urinary diversion procedure done at 6 years of age for bladder exstrophy, presented to the emergency room with sudden-onset progressive quadriparesis over 6 hours with power 1/5 in all the limbs with preserved reflexes. He was fully conscious and oriented, with stable vital signs. On evaluation, he had severe hypokalaemia and severe metabolic acidosis (both high anion gap and non-anion gap acidosis). Imaging studies showed bilateral gross hydroureteronephrosis, and renal and pouch calculi. Hypokalaemia was promptly treated with intravenous potassium chloride and acidosis with emergency haemodialysis. The patient had a complete motor recovery following intravenous potassium correction and was discharged with oral potassium and bicarbonate supplements. Here, the Indiana pouch, its metabolic and electrolyte complications, and its treatment are discussed.

A Rare Cause of Nephrotic Syndrome in Adults - Collagenofibrotic Glomerulopathy.

Adult-onset nephrotic syndrome (NS) is commonly caused by minimal change disease, focal segmental glomerulosclerosis, andmembranous nephropathy. Rare causes of NS include amyloidosis, immunoglobulin deposition disease, fibronectin glomerulopathy, and Collagenofibrotic glomerulopathy (CG). CG is caused by deposition of Type 3 collagen in the mesangium and subendothelial area. It usually presents as asymptomatic proteinuria, NS, hypertension, and renal failure. Histologically, it can present as Congo red-negative nodular glomerulosclerosis and requires electron microscopy for confirmation of diagnosis. Electron microscopy shows characteristic fibers which are curved, frayed and have a transverse band with periodicity of 43-65 nm. There is no specific treatment, and it can recur after kidney transplantation.

An unusual case of Henoch-Schönlein purpura.

Vasculitis has protean manifestations with etiological non-specificity of histological lesions. The natural history of Henoch-Schönlein purpura in adults is less well established. We report an adult female patient who presented with palpable skin purpura and was evaluated to have IgA nephritis who remains stable on treatment with cyclophosphamide and steroids.

Control of a humanoid robot by a noninvasive brain-computer interface in humans.

We describe a brain-computer interface for controlling a humanoid robot directly using brain signals obtained non-invasively from the scalp through electroencephalography (EEG). EEG has previously been used for tasks such as controlling a cursor and spelling a word, but it has been regarded as an unlikely candidate for more complex forms of control owing to its low signal-to-noise ratio. Here we show that by leveraging advances in robotics, an interface based on EEG can be used to command a partially autonomous humanoid robot to perform complex tasks such as walking to specific locations and picking up desired objects. Visual feedback from the robot's cameras allows the user to select arbitrary objects in the environment for pick-up and transport to chosen locations. Results from a study involving nine users indicate that a command for the robot can be selected from four possible choices in 5 s with 95% accuracy. Our results demonstrate that an EEG-based brain-computer interface can be used for sophisticated robotic interaction with the environment, involving not only navigation as in previous applications but also manipulation and transport of objects.

Generalized features for electrocorticographic BCIs.

This paper studies classifiability of electrocorticographic signals (ECoG) for use in a human brain-computer interface (BCI). The results show that certain spectral features can be reliably used across several subjects to accurately classify different types of movements. Sparse and nonsparse versions of the support vector machine and regularized linear discriminant analysis linear classifiers are assessed and contrasted for the classification problem. In conjunction with a careful choice of features, the classification process automatically and consistently identifies neurophysiological areas known to be involved in the movements. An average two-class classification accuracy of 95% for real movement and around 80% for imagined movement is shown. The high accuracy and generalizability of these results, obtained with as few as 30 data samples per class, support the use of classification methods for ECoG-based BCIs.

Online electromyographic control of a robotic prosthesis.

This paper presents a two-part study investigating the use of forearm surface electromyographic (EMG) signals for real-time control of a robotic arm. In the first part of the study, we explore and extend current classification-based paradigms for myoelectric control to obtain high accuracy (92-98%) on an eight-class offline classification problem, with up to 16 classifications/s. This offline study suggested that a high degree of control could be achieved with very little training time (under 10 min). The second part of this paper describes the design of an online control system for a robotic arm with 4 degrees of freedom. We evaluated the performance of the EMG-based real-time control system by comparing it with a keyboard-control baseline in a three-subject study for a variety of complex tasks.

Beyond the gamma band: the role of high-frequency features in movement classification.

Electrocorticographic spectral changes during movement show a behavioral inflection in the classic gamma band (30-70 Hz). We quantify this inflection and demonstrate that it limits classification accuracy. We call for the designation of a functionally defined band above it, which we denote the chi-band.

Towards adaptive classification for BCI.

Non-stationarities are ubiquitous in EEG signals. They are especially apparent in the use of EEG-based brain-computer interfaces (BCIs): (a) in the differences between the initial calibration measurement and the online operation of a BCI, or (b) caused by changes in the subject's brain processes during an experiment (e.g. due to fatigue, change of task involvement, etc). In this paper, we quantify for the first time such systematic evidence of statistical differences in data recorded during offline and online sessions. Furthermore, we propose novel techniques of investigating and visualizing data distributions, which are particularly useful for the analysis of (non-)stationarities. Our study shows that the brain signals used for control can change substantially from the offline calibration sessions to online control, and also within a single session. In addition to this general characterization of the signals, we propose several adaptive classification schemes and study their performance on data recorded during online experiments. An encouraging result of our study is that surprisingly simple adaptive methods in combination with an offline feature selection scheme can significantly increase BCI performance.

The influence of emotions on cognitive control: feelings and beliefs-where do they meet?

The influence of emotion on higher-order cognitive functions, such as attention allocation, planning, and decision-making, is a growing area of research with important clinical applications. In this review, we provide a computational framework to conceptualize emotional influences on inhibitory control, an important building block of executive functioning. We first summarize current neuro-cognitive models of inhibitory control and show how Bayesian ideal observer models can help reframe inhibitory control as a dynamic decision-making process. Finally, we propose a Bayesian framework to study emotional influences on inhibitory control, providing several hypotheses that may be useful to conceptualize inhibitory control biases in mental illness such as depression and anxiety. To do so, we consider the neurocognitive literature pertaining to how affective states can bias inhibitory control, with particular attention to how valence and arousal may independently impact inhibitory control by biasing probabilistic representations of information (i.e., beliefs) and valuation processes (e.g., speed-error tradeoffs).

Rational decision-making in inhibitory control.

An important aspect of cognitive flexibility is inhibitory control, the ability to dynamically modify or cancel planned actions in response to changes in the sensory environment or task demands. We formulate a probabilistic, rational decision-making framework for inhibitory control in the stop signal paradigm. Our model posits that subjects maintain a Bayes-optimal, continually updated representation of sensory inputs, and repeatedly assess the relative value of stopping and going on a fine temporal scale, in order to make an optimal decision on when and whether to go on each trial. We further posit that they implement this continual evaluation with respect to a global objective function capturing the various reward and penalties associated with different behavioral outcomes, such as speed and accuracy, or the relative costs of stop errors and go errors. We demonstrate that our rational decision-making model naturally gives rise to basic behavioral characteristics consistently observed for this paradigm, as well as more subtle effects due to contextual factors such as reward contingencies or motivational factors. Furthermore, we show that the classical race model can be seen as a computationally simpler, perhaps neurally plausible, approximation to optimal decision-making. This conceptual link allows us to predict how the parameters of the race model, such as the stopping latency, should change with task parameters and individual experiences/ability.

Accessory thymus in posterior mediastinum.

Presence of thymus in the normal position as well as in the posterior mediastinum is an unusual phenomenon. We report here a case of posterior mediastinal mass in a 20-month old male child who presented with dysphagia and dry cough. Investigations revealed it to be a solid posterior mediastinal mass, suspected to be either lymphoma or a neuroblastoma. Excision of the mass followed by histopathologic examination revealed the mass to be a normal thymus. This case indicates that a benign mass, an accessory thymus, though rare, can be located in the posterior mediastinum and cause symptoms similar to solid mediastinal tumors.

Real-time functional brain mapping using electrocorticography.

We demonstrate the feasibility of real-time cortical mapping from arrays of subdural electrodes using the electrocorticographic signal power in the higher spectral frequencies (76-200 Hz, or "chi-index"). Hand area was mapped offline in eight individuals using brief baseline and hand-movement measurements. In one patient, hand sensorimotor cortex was identified online during a handshake. We propose that this high-frequency component of the electrocorticogram provides a generic, reliable, clinically useful correlate of local cortical function.