Risk Factors for Potential Drug-Drug Interactions in Patients on Chronic Peritoneal Dialysis.

INTRODUCTION: The prevalence of potential drug-drug interactions (pDDIs) is becoming a major safety concern, as it has been previously linked to a significant number of adverse drug events and could have serious consequences for patients, including death. This is especially relevant for patients with chronic renal failure, as they are particularly vulnerable to drug-drug interactions. The aim of this study was to evaluate the prevalence and associated factors of pDDIs in patients receiving chronic peritoneal dialysis. METHODS: An observational, cross-sectional study was conducted on consecutive peritoneal dialysis patients attending four tertiary care hospitals for regular monthly examination. The primary outcome was the number of pDDIs identified using Lexicomp. Potential predictors were determined using multiple linear regression. RESULTS: Total number of patients included in the study was 140. The results showed that pDDIs were highly prevalent, especially in patients who use antiarrhythmics (p = 0.001), have diabetes mellitus (p = 0.001), recently started peritoneal dialysis (p = 0.003), or have higher number of prescribed drugs (p < 0.001). Number of prescribed drugs (p < 0.001) remained a significant predictor of high-risk pDDIs in addition to the female gender (p = 0.043). CONCLUSION: Clinicians should be particularly cautious when prescribing multiple medications to high-risk patients, such as peritoneal dialysis patients, to mitigate the risk of drug-drug interactions and associated adverse health outcomes.

Electromyogram-Based Lip-Reading via Unobtrusive Dry Electrodes and Machine Learning Methods.

Lip-reading provides an effective speech communication interface for people with voice disorders and for intuitive human-machine interactions. Existing systems are generally challenged by bulkiness, obtrusiveness, and poor robustness against environmental interferences. The lack of a truly natural and unobtrusive system for converting lip movements to speech precludes the continuous use and wide-scale deployment of such devices. Here, the design of a hardware-software architecture to capture, analyze, and interpret lip movements associated with either normal or silent speech is presented. The system can recognize different and similar visemes. It is robust in a noisy or dark environment. Self-adhesive, skin-conformable, and semi-transparent dry electrodes are developed to track high-fidelity speech-relevant electromyogram signals without impeding daily activities. The resulting skin-like sensors can form seamless contact with the curvilinear and dynamic surfaces of the skin, which is crucial for a high signal-to-noise ratio and minimal interference. Machine learning algorithms are employed to decode electromyogram signals and convert them to spoken words. Finally, the applications of the developed lip-reading system in augmented reality and medical service are demonstrated, which illustrate the great potential in immersive interaction and healthcare applications.

Factors Associated with Potentially Inappropriate Prescribing in Patients on Peritoneal Dialysis.

INTRODUCTION: Inappropriate prescribing is common in patients with end-stage kidney disease, especially in those over 65 years of age. Our study aimed to reveal potentially inappropriate drug prescribing in patients on peritoneal dialysis (PD) and explore factors associated with this phenomenon. METHODS: The research was designed as an observational, cross-sectional study on a convenient sample of 145 consecutive patients with PD who attended the four tertiary-care hospitals in Serbia. The main outcome was the extent of inappropriate prescribing, as assessed by the medication appropriateness index, and potential predictors were tested by multiple linear regression. RESULTS: Inappropriate prescribing was a widespread phenomenon among patients on PD. The main factors that promote inappropriate prescribing in this subgroup of patients on kidney replacement therapy are comorbidities (p = 0.000), increased body weight (p = 0.022), a number of prescribed drugs (p = 0.000), and arterial hypertension on examination (p = 0.030). On the other hand, drinking alcohol and higher systolic blood pressure were associated with a lower inappropriate prescribing. CONCLUSION: In order to prevent the occurrence of inappropriate prescribing and its severe health or economic consequences, clinicians should pay special attention when prescribing new drugs to high-risk patients.

Missingness patterns in a comprehensive instrument identifying psychosocial and substance use risk in antenatal care.

BACKGROUND: Psychosocial vulnerabilities (e.g. inadequate social support, financial insecurity, stress) and substance use elevate risks for adverse perinatal outcomes and maternal mental health morbidities. However, various barriers, including paucity of validated, simple and usable comprehensive instruments, impede execution of the recommendations to screen for such vulnerabilities in the first antenatal care visit. The current study presents findings from a newly implemented self-report tool created to overcome screening barriers in outpatient antenatal clinics. METHODS: This was a retrospective chart-review of 904 women who completed the Profile for Maternal & Obstetric Treatment Effectiveness (PROMOTE) during their first antenatal visit between June and December 2019. The PROMOTE includes the 4-item NIDA Quick Screen and 15 additional items that each assess a different psychosocial vulnerability. Statistical analysis included evaluation of missing data, and exploration of missing data patterns using univariate correlations and hierarchical clustering. RESULTS: Three quarters of women (70.0%) had no missing items. In the entire sample, all but four PROMOTE items (opioid use, planned pregnancy, educational level, and financial state) had < 5% missing values, suggesting good acceptability and feasibility. Several respondent-related characteristics such as lower education, less family support, and greater stress were associated with greater likelihood of missing items. Instrument-related characteristics associated with missing values were completing the PROMOTE in Spanish or question positioning at the end of the instrument. CONCLUSIONS AND IMPLICATIONS: Conducting a comprehensive screening of theoretically and clinically meaningful vulnerabilities in an outpatient setting is feasible. Study findings will inform modifications of the PROMOTE and subsequent digitisation.

An unusual cause of rapidly progressive glomerulonephritis associated with ANCA vasculitis and ovarian malignancy - a relapse 39 years after initial treatment.

A 69-year-old woman presented with severe anemia, proteinuria, microscopic hematuria and rapidly progressive renal failure. She was admitted to the nephrology department due to severe deterioration of renal function with complaints of malaise, fever, dry cough and occasional epistaxis that appeared 2 months prior to admission. Histopathologic examination of a specimen from kidney biopsy and immunologic findings revealed ANCA positive pauci-immune crescentic glomerulonephritis. The patient had a history of ovarian granulosa cell tumor and lung metastases that were treated surgically with postoperative radiotherapy and chemotherapy. Thoracic computed tomography showed tissue neoplasm in the right lung and ultrasound-guided percutaneous transthoracic biopsy confirmed granulosa cell tumor. That was a relapse, thirty-nine years after initial treatment of malignant disease and twenty-four years after surgical resection of metastases from both lungs. Although the association between malignancy and vasculitis has been well known for decades, this is the first described case of ANCA vasculitis associated with any type of gynecological malignancy and glomerulonephritis.

Applying machine learning methods to psychosocial screening data to improve identification of prenatal depression: Implications for clinical practice and research.

We utilized machine learning (ML) methods on data from the PROMOTE, a novel psychosocial screening tool, to quantify risk for prenatal depression for individual patients and identify contributing factors that impart greater risk for depression. Random forest algorithms were used to predict likelihood for being at high risk for prenatal depression (Edinburgh Postnatal Depression Scale; EPDS ≥ 13 and/or positive self-injury item) using data from 1715 patients who completed the PROMOTE. Performance matrices were calculated to assess the ability of the PROMOTE to accurately classify patients. Probability for depression was calculated for individual patients. Finally, recursive feature elimination was used to evaluate the importance of each PROMOTE item in the classification of depression risk. PROMOTE data were successfully used to predict depression with acceptable performance matrices (accuracy = 0.80; sensitivity = 0.75; specificity = 0.81; positive predictive value = 0.79; negative predictive value = 0.97). Perceived stress, emotional problems, family support, age, major life events, partner support, unplanned pregnancy, current employment, lifetime abuse, and financial state were the most important PROMOTE items in the classification of depression risk. Results affirm the value of the PROMOTE as a psychosocial screening tool for prenatal depression and the benefit of using it in conjunction with ML methods. Using such methods can help detect underreported outcomes and identify what in patients' lives makes them more vulnerable, thus paving the way for effective individually tailored precision medicine.

Performance Limits of Direct Wideband Coherent 3D Localization in Distributed Massive MIMO Systems.

We address the accuracy of wideband direct position estimation of a radio transmitter via a distributed antenna array in 5G cellular systems. Our derivations are based only on the presence of spatially coherent line-of-sight (LoS) signal components, which is a realistic assumption in small cells, especially in the mmWave range. The system model considers collocated time and phase synchronized receiving front-ends with antennas distributed in 3D space at known locations and connected to the front-ends via calibrated coaxial cables or analog radio-frequency-over-fiber links. Furthermore, the signal model assumes spherical wavefronts. We derive the Cramér-Rao bounds (CRBs) for two implementations of the system: with (a) known signals and (b) random Gaussian signals. The results show how the bounds depend on the carrier frequency, number of samples used for estimation, and signal-to-noise ratios. They also show that increasing the number of antennas (such as in massive MIMO systems) considerably improves the accuracy and lowers the signal-to-noise threshold for localization even for non-cooperative transmitters. Finally, our derivations show that the square roots of the bounds are two to three orders of magnitude below the carrier wavelength for realistic system parameters.

Encapsulated Omental Necrosis as an Unexpected Postoperative Finding: A Case Report.

Postsurgical fat necrosis is a frequent finding in abdominal cross-sectional imaging. Epiploic appendagitis and omental infarction are a result of torsion or vascular occlusion. Surgery or pancreatitis are conditions that can have a traumatic and ischemic effect on fatty tissue. The imaging appearances may raise concerns for recurrent malignancy, but percutaneous biopsy and diagnostic follow-up assist in the accurate diagnosis of omental infarction. Herein we describe a case of encapsulated omental necrosis temporally related to gastric surgery. Preoperative CT and MRI findings showed the characteristics of encapsulated, postcontrast nonviable tumefaction in the epigastrium without clear imaging features of malignancy. Due to the size of the lesion and the patient's primary disease, tumor recurrence could not be completely ruled out, and the patient underwent surgery. Histopathological analysis confirmed the diagnosis of steatonecrosis of the omentum.

Sodium thiosulphate and progression of vascular calcification in end-stage renal disease patients: a double-blind, randomized, placebo-controlled study.

BACKGROUND: Sodium thiosulphate (NaTS) is mostly used in haemodialysis (HD) patients with calcific uraemic arteriolopathy. This double-blind, randomized, placebo-controlled study assessed the effect of NaTS on progression of cardiovascular calcifications in HD patients. METHODS: From 65 screened patients, we recruited 60 patients with an abdominal aorta Agatston calcification score ≥100. Thirty patients were randomized to receive NaTS 25 g/1.73 m2 and 30 patients to receive 100 mL of 0.9% sodium chloride intravenously during the last 15 min of HD over a period of 6 months. The primary endpoint was the absolute change of the abdominal aortic calcification score. RESULTS: The abdominal aortic calcification score and calcification volume of the abdominal aorta increased similarly in both treatment groups during the trial. As compared with the saline group, patients receiving NaTS exhibited a reduction of their iliac artery calcification score (-137 ± 641 versus 245 ± 755; P = 0.049), reduced pulse wave velocity (9.6 ± 2.7 versus 11.4 ± 3.6; P = 0.000) and a lower carotid intima-media thickness (0.77 ± 0.1 versus 0.83 ± 00.17; P = 0.033) and had better preservation of echocardiographic parameters of left ventricular hypertrophy. No patient of the NaTS group developed new cardiac valve calcifications during the trial as compared with 8 of 29 patients in the saline group. By univariate analysis, NaTS therapy was the only predictor of not developing new valvular calcifications. No adverse events possibly related to NaTS infusion were noted. CONCLUSIONS: While NaTS failed to retard abdominal aortic calcification progress, it positively affected calcification progress in iliac arteries and heart valves as well as several other cardiovascular functional parameters.

Genomic dissection of enhancers uncovers principles of combinatorial regulation and cell type-specific wiring of enhancer-promoter contacts.

Genomic binding of transcription factors, like the glucocorticoid receptor (GR), is linked to the regulation of genes. However, as we show here, GR binding is a poor predictor of GR-dependent gene regulation even when taking the 3D organization of the genome into account. To connect GR binding sites to the regulation of genes in the endogenous genomic context, we turned to genome editing. By deleting GR binding sites, individually or in combination, we uncovered how cooperative interactions between binding sites contribute to the regulation of genes. Specifically, for the GR target gene GILZ, we show that the simultaneous presence of a cluster of GR binding sites is required for the activity of an individual enhancer and that the GR-dependent regulation of GILZ depends on multiple GR-bound enhancers. Further, by deleting GR binding sites that are shared between different cell types, we show how cell type-specific genome organization and enhancer-blocking can result in cell type-specific wiring of promoter-enhancer contacts. This rewiring allows an individual GR binding site shared between different cell types to direct the expression of distinct transcripts and thereby contributes to the cell type-specific consequences of glucocorticoid signaling.

Computer-based intrapartum fetal monitoring and beyond: A review of the 2nd Workshop on Signal Processing and Monitoring in Labor (October 2017, Oxford, UK).

The second Signal Processing and Monitoring in Labor workshop gathered researchers who utilize promising new research strategies and initiatives to tackle the challenges of intrapartum fetal monitoring. The workshop included a series of lectures and discussions focusing on: new algorithms and techniques for cardiotocogoraphy (CTG) and electrocardiogram acquisition and analyses; the results of a CTG evaluation challenge comparing state-of-the-art computerized methods and visual interpretation for the detection of arterial cord pH <7.05 at birth; the lack of consensus about the role of intrapartum acidemia in the etiology of fetal brain injury; the differences between methods for CTG analysis "mimicking" expert clinicians and those derived from "data-driven" analyses; a critical review of the results from two randomized controlled trials testing the former in clinical practice; and relevant insights from modern physiology-based studies. We concluded that the automated algorithms performed comparably to each other and to clinical assessment of the CTG. However, the sensitivity and specificity urgently need to be improved (both computerized and visual assessment). Data-driven CTG evaluation requires further work with large multicenter datasets based on well-defined labor outcomes. And before first tests in the clinic, there are important lessons to be learnt from clinical trials that tested automated algorithms mimicking expert CTG interpretation. In addition, transabdominal fetal electrocardiogram monitoring provides reliable CTG traces and variability estimates; and fetal electrocardiogram waveform analysis is subject to promising new research. There is a clear need for close collaboration between computing and clinical experts. We believe that progress will be possible with multidisciplinary collaborative research.

Direct Wideband Coherent Localization by Distributed Antenna Arrays.

We address wideband direct coherent localization of a radio transmitter by a distributed antenna array in a multipath scenario with spatially-coherent line-of-sight (LoS) signal components. Such a signal scenario is realistic in small cells, especially indoors in the mmWave range. The system model considers collocated time and phase synchronized receiving front-ends with antennas distributed in 3D space at known locations connected to the front-ends via calibrated coaxial cables or analog radio frequency over fiber links. The signal model assumes spherical wavefronts. We propose two ML-type algorithms (for known and unknown transmitter waveforms) and a subspace-based SCM-MUSIC algorithm for wideband direct coherent position estimation. We demonstrate the performance of the methods by Monte Carlo simulations. The results show that even in multipath environments, it is possible to achieve localization accuracy that is much better (by two to three orders of magnitude) than the carrier wavelength. They also suggest that the methods that do not exploit knowledge of the waveform have mean-squared errors approaching the Cramér-Rao bound.

The 5A Allele of the MMP3-Gene Promoter Polymorphism Is a Risk Factor for Poor Outcome of Hemodialysis Patients.

Cardiovascular morbidity is the leading cause of death in dialysis patients and many risk factors have been involved in its pathogenesis. Genetic susceptibility may be of importance including polymorphism for matrix metalloproteinase 3 (MMP3), which is an enzyme that catalyzes the degradation of collagen, proteoglycans, fibronectin, laminine and elastin. The MMP3 gene promoter contains an insertion/deletion polymorphism characterised by an array of 5 or 6 adenosine residues (5A/6A) at -1612 position. Literature data show that the 5A or 6A allele of the MMP3 gene shows different risk for cardiovascular and overall outcome in general population. The aim was to analyze the -1612 5A/6A promoter polymorphism in a group of hemodialysis patients and to correlate the findings with cardiovascular morbidity and 7-year all-cause and cardiovascular mortality. This study included 196 patients on hemodialysis for longer than six months at University Medical Center Zvezdara. The leading causes of end stage renal disease were hypertension and diabetes mellitus. Venous blood was collected on midweek dialysis session and genotype analysis was performed by using polymerase chain reaction-restriction fragment length polymorphism method. Among the 198 hemodialysis patients, there were 142 (72%) 5A/6A heterozygotes, 12 (6%) 5A/5A homozygotes, and 44 (22%) 6A/6A homozygotes. These data are consistent with Hardy-Weinberg equilibrium. After 7-year follow-up, the 5A homozygotes showed the lowest all-cause and cardiovascular survival, while the 6A homozygotes showed the highest cardiovascular survival. The 5A allele of the MMP3-gene promoter polymorphism is a potential risk factor in the poor outcome of hemodialysis patients.

Gaussian Process-Gated Hierarchical Mixtures of Experts.

In this article, we propose novel Gaussian process-gated hierarchical mixtures of experts (GPHMEs). Unlike other mixtures of experts with gating models linear in the input, our model employs gating functions built with Gaussian processes (GPs). These processes are based on random features that are non-linear functions of the inputs. Furthermore, the experts in our model are also constructed with GPs. The optimization of the GPHMEs is performed by variational inference. The proposed GPHMEs have several advantages. They outperform tree-based HME benchmarks that partition the data in the input space, and they achieve good performance with reduced complexity. Another advantage is the interpretability they provide for deep GPs, and more generally, for deep Bayesian neural networks. Our GPHMEs demonstrate excellent performance for large-scale data sets, even with quite modest sizes.

Learning the hierarchical organization of the frontal lobe with differential causal effects.

In this video article, accompanying the paper "An approach to learning the hierarchical organization of the frontal lobe", we discuss a data driven approach to learning brain connectivity. Hierarchical models of brain connectivity are useful to understand how the brain can process sensory information, make decisions, and perform other high-level tasks. Despite extensive research, understanding the structure of the prefrontal cortex (PFC) remains a crucial challenge. In this work, we propose an approach to studying brain signals and uncovering characteristics of the underlying neural circuity, based on the mathematics of Gaussian processes and causal strengths. For discovering causations, we propose a metric referred to as double-averaged differential causal effect, which is a variant of the recently proposed differential causal effect, and it can be used as a principled measure of the causal strength between time series. We applied this methodology to study local field potential data from the frontal lobe, where the interest was in finding the causal relationship between the medial and lateral PFC areas of the brain. Our results suggest that the medial PFC causally influences the lateral PFC.

High-gamma and beta bursts in the Left Supramarginal Gyrus can accurately differentiate verbal memory states and performance.

The left supramarginal gyrus (LSMG) may mediate attention to memory, and gauge memory state and performance. We performed a secondary analysis of 142 verbal delayed free recall experiments, in patients with medically-refractory epilepsy with electrode contacts implanted in the LSMG. In 14 of 142 experiments (in 14 of 113 patients), the cross-validated convolutional neural networks (CNNs) that used 1-dimensional(1-D) pairs of convolved high-gamma and beta tensors, derived from the LSMG recordings, could label recalled words with an area under the receiver operating curve (AUROC) of greater than 60% [range: 60-90%]. These 14 patients were distinguished by: 1) higher amplitudes of high-gamma bursts; 2) distinct electrode placement within the LSMG; and 3) superior performance compared with a CNN that used a 1-D tensor of the broadband recordings in the LSMG. In a pilot study of 7 of these patients, we also cross-validated CNNs using paired 1-D convolved high-gamma and beta tensors, from the LSMG, to: a) distinguish word encoding epochs from free recall epochs [AUC 0.6-1]; and distinguish better performance from poor performance during delayed free recall [AUC 0.5-0.86]. These experiments show that bursts of high-gamma and beta generated in the LSMG are biomarkers of verbal memory state and performance.

Microscale multicircuit brain stimulation: Achieving real-time brain state control for novel applications.

Neurological and psychiatric disorders typically result from dysfunction across multiple neural circuits. Most of these disorders lack a satisfactory neuromodulation treatment. However, deep brain stimulation (DBS) has been successful in a limited number of disorders; DBS typically targets one or two brain areas with single contacts on relatively large electrodes, allowing for only coarse modulation of circuit function. Because of the dysfunction in distributed neural circuits - each requiring fine, tailored modulation - that characterizes most neuropsychiatric disorders, this approach holds limited promise. To develop the next generation of neuromodulation therapies, we will have to achieve fine-grained, closed-loop control over multiple neural circuits. Recent work has demonstrated spatial and frequency selectivity using microstimulation with many small, closely-spaced contacts, mimicking endogenous neural dynamics. Using custom electrode design and stimulation parameters, it should be possible to achieve bidirectional control over behavioral outcomes, such as increasing or decreasing arousal during central thalamic stimulation. Here, we discuss one possible approach, which we term microscale multicircuit brain stimulation (MMBS). We discuss how machine learning leverages behavioral and neural data to find optimal stimulation parameters across multiple contacts, to drive the brain towards desired states associated with behavioral goals. We expound a mathematical framework for MMBS, where behavioral and neural responses adjust the model in real-time, allowing us to adjust stimulation in real-time. These technologies will be critical to the development of the next generation of neurostimulation therapies, which will allow us to treat problems like disorders of consciousness and cognition.

A quantitative model of the cerebral windkessel and its relevance to disorders of intracranial dynamics.

OBJECTIVE: Traditional models of intracranial dynamics fail to capture several important features of the intracranial pressure (ICP) pulse. Experiments show that, at a local amplitude minimum, the ICP pulse normally precedes the arterial blood pressure (ABP) pulse, and the cranium is a band-stop filter centered at the heart rate for the ICP pulse with respect to the ABP pulse, which is the cerebral windkessel mechanism. These observations are inconsistent with existing pressure-volume models. METHODS: To explore these issues, the authors modeled the ABP and ICP pulses by using a simple electrical tank circuit, and they compared the dynamics of the circuit to physiological data from dogs by using autoregressive with exogenous inputs (ARX) modeling. RESULTS: The authors' ARX analysis showed close agreement between the circuit and pulse suppression in the canine cranium, and they used the analogy between the circuit and the cranium to examine the dynamics that underlie this pulse suppression. CONCLUSIONS: This correspondence between physiological data and circuit dynamics suggests that the cerebral windkessel consists of the rhythmic motion of the brain parenchyma and CSF that continuously opposes systolic and diastolic blood flow. Such motion has been documented with flow-sensitive MRI. In thermodynamic terms, the direct current (DC) power of cerebral arterial perfusion drives smooth capillary flow and alternating current (AC) power shunts pulsatile energy through the CSF to the veins. This suggests that hydrocephalus and related disorders are disorders of CSF path impedance. Obstructive hydrocephalus is the consequence of high CSF path impedance due to high resistance. Normal pressure hydrocephalus (NPH) is the consequence of high CSF path impedance due to low inertance and high compliance. Low-pressure hydrocephalus is the consequence of high CSF path impedance due to high resistance and high compliance. Ventriculomegaly is an adaptive physiological response that increases CSF path volume and thereby reduces CSF path resistance and impedance. Pseudotumor cerebri is the consequence of high DC power with normal CSF path impedance. CSF diversion by shunting is an accessory windkessel-it drains energy (and thereby lowers ICP) and lowers CSF path resistance and impedance. Cushing's reflex is an accessory windkessel in extremis-it maintains DC power (arterial hypertension) and reduces AC power (bradycardia). The windkessel theory is a thermodynamic approach to the study of energy flow through the cranium, and it points to a new understanding of hydrocephalus and related disorders.

UNSUPERVISED CLUSTERING AND ANALYSIS OF CONTRACTION-DEPENDENT FETAL HEART RATE SEGMENTS.

The computer-aided interpretation of fetal heart rate (FHR) and uterine contraction (UC) has not been developed well enough for wide use in delivery rooms. The main challenges still lie in the lack of unclear and nonstandard labels for cardiotocography (CTG) recordings, and the timely prediction of fetal state during monitoring. Rather than traditional supervised approaches to FHR classification, this paper demonstrates a way to understand the UC-dependent FHR responses in an unsupervised manner. In this work, we provide a complete method for FHR-UC segment clustering and analysis via the Gaussian process latent variable model, and density-based spatial clustering. We map the UC-dependent FHR segments into a space with a visual dimension and propose a trajectory-based FHR interpretation method. Three metrics of FHR trajectory are defined and an open-access CTG database is used for testing the proposed method.