Improving Pain Assessment Using Vital Signs and Pain Medication for Patients With Sickle Cell Disease: Retrospective Study

Background: Sickle cell disease (SCD) is the most common inherited blood disorder affecting millions of people worldwide. Most patients with SCD experience repeated, unpredictable episodes of severe pain. These pain episodes are the leading cause of emergency department visits among patients with SCD and may last for several weeks. Arguably, the most challenging aspect of treating pain episodes in SCD is assessing and interpreting a patient\u27s pain intensity level. Objective: This study aims to learn deep feature representations of subjective pain trajectories using objective physiological signals collected from electronic health records. Methods: This study used electronic health record data collected from 496 Duke University Medical Center participants over 5 consecutive years. Each record contained measures for 6 vital signs and the patient\u27s self-reported pain score, with an ordinal range from 0 (no pain) to 10 (severe and unbearable pain). We also extracted 3 features related to medication: medication type, medication status (given or applied, or missed or removed or due), and total medication dosage (mg/mL). We used variational autoencoders for representation learning and designed machine learning classification algorithms to build pain prediction models. We evaluated our results using an accuracy and confusion matrix and visualized the qualitative data representations. Results: We designed a classification model using raw data and deep representational learning to predict subjective pain scores with average accuracies of 82.8%, 70.6%, 49.3%, and 47.4% for 2-point, 4-point, 6-point, and 11-point pain ratings, respectively. We observed that random forest classification models trained on deep represented features outperformed models trained on unrepresented data for all pain rating scales. We observed that at varying Likert scales, our models performed better when provided with medication data along with vital signs data. We visualized the data representations to understand the underlying latent representations, indicating neighboring representations for similar pain scores with a higher resolution of pain ratings. Conclusions: Our results demonstrate that medication information (the type of medication, total medication dosage, and whether the medication was given or missed) can significantly improve subjective pain prediction modeling compared with modeling with only vital signs. This study shows promise in data-driven estimated pain scores that will help clinicians with additional information about the patient\u27s condition, in addition to the patient\u27s self-reported pain scores

Clustering of Pain Dynamics in Sickle Cell Disease from Sparse, Uneven Samples

Irregularly sampled time series data are common in a variety of fields. Many typical methods for drawing insight from data fail in this case. Here we attempt to generalize methods for clustering trajectories to irregularly and sparsely sampled data. We first construct synthetic data sets, then propose and assess four methods of data alignment to allow for application of spectral clustering. We also repeat the same process for real data drawn from medical records of patients with sickle cell disease -- patients whose subjective experiences of pain were tracked for several months via a mobile app. We find that different methods for aligning irregularly sampled sparse data sets can lead to different optimal numbers of clusters, even for synthetic data with known properties. For the case of sickle cell disease, we find that three clusters is a reasonable choice, and these appear to correspond to (1) a low pain group with occasionally acute pain, (2) a group which experiences moderate mean pain that fluctuates often from low to high, and (3) a group that experiences persistent high levels of pain. Our results may help physicians and patients better understand and manage patients\u27 pain levels over time, and we expect that the methods we develop will apply to a wide range of other data sources in medicine and beyond

Pain Intensity Assessment in Sickle Cell Disease patients using Vital Signs during Hospital Visits

Pain in sickle cell disease (SCD) is often associated with increased morbidity, mortality, and high healthcare costs. The standard method for predicting the absence, presence, and intensity of pain has long been self-report. However, medical providers struggle to manage patients based on subjective pain reports correctly and pain medications often lead to further difficulties in patient communication as they may cause sedation and sleepiness. Recent studies have shown that objective physiological measures can predict subjective self-reported pain scores for inpatient visits using machine learning (ML) techniques. In this study, we evaluate the generalizability of ML techniques to data collected from 50 patients over an extended period across three types of hospital visits (i.e., inpatient, outpatient and outpatient evaluation). We compare five classification algorithms for various pain intensity levels at both intra-individual (within each patient) and inter-individual (between patients) level. While all the tested classifiers perform much better than chance, a Decision Tree (DT) model performs best at predicting pain on an 11-point severity scale (from 0-10) with an accuracy of 0.728 at an inter-individual level and 0.653 at an intra-individual level. The accuracy of DT significantly improves to 0.941 on a 2-point rating scale (i.e., no/mild pain: 0-5, severe pain: 6-10) at an intra-individual level. Our experimental results demonstrate that ML techniques can provide an objective and quantitative evaluation of pain intensity levels for all three types of hospital visits.Comment: Accepted for presentation at the FIRST WORKSHOP ON COMPUTATIONAL & AFFECTIVE INTELLIGENCE IN HEALTHCARE APPLICATIONS (VULNERABLE POPULATIONS) In Conjunction with the International Conference on Pattern Recognition (ICPR) 202

Zwanzig-Mori projection operators and EEG dynamics: deriving a simple equation of motion

We present a macroscopic theory of electroencephalogram (EEG) dynamics based on the laws of motion that govern atomic and molecular motion. The theory is an application of Zwanzig-Mori projection operators. The result is a simple equation of motion that has the form of a generalized Langevin equation (GLE), which requires knowledge only of macroscopic properties. The macroscopic properties can be extracted from experimental data by one of two possible variational principles. These variational principles are our principal contribution to the formalism. Potential applications are discussed, including applications to the theory of critical phenomena in the brain, Granger causality and Kalman filters

Age-Related Changes of Myelin Basic Protein in Mouse and Human Auditory Nerve

Age-related hearing loss (presbyacusis) is the most common type of hearing impairment. One of the most consistent pathological changes seen in presbyacusis is the loss of spiral ganglion neurons (SGNs). Defining the cellular and molecular basis of SGN degeneration in the human inner ear is critical to gaining a better understanding of the pathophysiology of presbyacusis. However, information on age-related cellular and molecular alterations in the human spiral ganglion remains scant, owing to the very limited availably of human specimens suitable for high resolution morphological and molecular analysis. This study aimed at defining age-related alterations in the auditory nerve in human temporal bones and determining if immunostaining for myelin basic protein (MBP) can be used as an alternative approach to electron microscopy for evaluating myelin degeneration. For comparative purposes, we evaluated ultrastructural alternations and changes in MBP immunostaining in aging CBA/CaJ mice. We then examined 13 temporal bones from 10 human donors, including 4 adults aged 38–46 years (middle-aged group) and 6 adults aged 63–91 years (older group). Similar to the mouse, intense immunostaining of MBP was present throughout the auditory nerve of the middle-aged human donors. Significant declines in MBP immunoreactivity and losses of MBP+ auditory nerve fibers were observed in the spiral ganglia of both the older human and aged mouse ears. This study demonstrates that immunostaining for MBP in combination with confocal microscopy provides a sensitive, reliable, and efficient method for assessing alterations of myelin sheaths in the auditory nerve. The results also suggest that myelin degeneration may play a critical role in the SGN loss and the subsequent decline of the auditory nerve function in presbyacusis

Detection of group A Streptococcus in tonsils from pediatric patients reveals high rate of asymptomatic streptococcal carriage

<p>Abstract</p> <p>Background</p> <p>Group A <it>Streptococcus </it>(GAS) causes acute tonsillopharyngitis in children, and approximately 20% of this population are chronic carriers of GAS. Antibacterial therapy has previously been shown to be insufficient at clearing GAS carriage. Bacterial biofilms are a surface-attached bacterial community that is encased in a matrix of extracellular polymeric substances. Biofilms have been shown to provide a protective niche against the immune response and antibiotic treatments, and are often associated with recurrent or chronic bacterial infections. The objective of this study was to test the hypothesis that GAS is present within tonsil tissue at the time of tonsillectomy.</p> <p>Methods</p> <p>Blinded immunofluorescent and histological methods were employed to evaluate palatine tonsils from children undergoing routine tonsillectomy for adenotonsillar hypertrophy or recurrent GAS tonsillopharyngitis.</p> <p>Results</p> <p>Immunofluorescence analysis using anti-GAS antibody was positive in 11/30 (37%) children who had tonsillectomy for adenotonsillar hypertrophy and in 10/30 (33%) children who had tonsillectomy for recurrent GAS pharyngitis. Fluorescent microscopy with anti-GAS and anti-cytokeratin 8 & 18 antibodies revealed GAS was localized to the tonsillar reticulated crypts. Scanning electron microscopy identified 3-dimensional communities of cocci similar in size and morphology to GAS. The characteristics of these communities are similar to GAS biofilms from <it>in vivo </it>animal models.</p> <p>Conclusion</p> <p>Our study revealed the presence of GAS within the tonsillar reticulated crypts of approximately one-third of children who underwent tonsillectomy for either adenotonsillar hypertrophy or recurrent GAS tonsillopharyngitis at the Wake Forest School of Medicine.</p> <p>Trial Registration</p> <p>The tissue collected was normally discarded tissue and no patient identifiers were collected. Thus, no subjects were formally enrolled.</p

Disturbed Clockwork Resetting in Sharp-1 and Sharp-2 Single and Double Mutant Mice

BACKGROUND: The circadian system provides the basis to anticipate and cope with daily recurrent challenges to maintain the organisms' homeostasis. De-synchronization of circadian feedback oscillators in humans causes 'jet lag', likely contributes to sleep-, psychiatric-, metabolic disorders and even cancer. However, the molecular mechanisms leading to the disintegration of tissue-specific clocks are complex and not well understood. METHODOLOGY/PRINCIPAL FINDINGS: Based on their circadian expression and cell culture experiments, the basic Helix-Loop-Helix (bHLH) transcription factors SHARP-1(Dec2) and SHARP-2(Stra13/Dec1) were proposed as novel negative regulators of the molecular clock. To address their function in vivo, we generated Sharp-1 and Sharp-2 single and double mutant mice. Our experiments reveal critical roles for both factors in regulating period length, tissue-specific control of clock gene expression and entrainment to external cues. Light-pulse experiments and rapid delays of the light-dark cycle (experimental jet lag) unravel complementary functions for SHARP-1 and SHARP-2 in controlling activity phase resetting kinetics. Moreover, we show that SHARP-1 and 2 can serve dual functions as repressors and co-activators of mammalian clock gene expression in a context-specific manner. This correlates with increased amplitudes of Per2 expression in the cortex and liver and a decrease in the suprachiasmatic nucleus (SCN) of double mutant mice. CONCLUSIONS/SIGNIFICANCE: The existence of separate mechanisms regulating phase of entrainment, rhythm amplitude and period length has been postulated before. The differential effects of Sharp-deficiency on rhythmicity and behavioral re-entrainment, coupled to tissue-dependent regulatory functions, provide a new mechanistic basis to further understand the complex process of clock synchronizations

Kif13b Regulates PNS and CNS Myelination Through the Dlg1 Scaffold

Microtubule-based kinesin motors have many cellular functions, including the transport of a variety of cargos. However, unconventional roles have recently emerged, and kinesins have also been reported to act as scaffolding proteins and signaling molecules. In this work, we further extend the notion of unconventional functions for kinesin motor proteins, and we propose that Kif13b kinesin acts as a signaling molecule regulating peripheral nervous system (PNS) and central nervous system (CNS) myelination. In this process, positive and negative signals must be tightly coordinated in time and space to orchestrate myelin biogenesis. Here, we report that in Schwann cells Kif13b positively regulates myelination by promoting p38γ mitogen-activated protein kinase (MAPK)-mediated phosphorylation and ubiquitination of Discs large 1 (Dlg1), a known brake on myelination, which downregulates the phosphatidylinositol 3-kinase (PI3K)/v-AKT murine thymoma viral oncogene homolog (AKT) pathway. Interestingly, Kif13b also negatively regulates Dlg1 stability in oligodendrocytes, in which Dlg1, in contrast to Schwann cells, enhances AKT activation and promotes myelination. Thus, our data indicate that Kif13b is a negative regulator of CNS myelination. In summary, we propose a novel function for the Kif13b kinesin in glial cells as a key component of the PI3K/AKT signaling pathway, which controls myelination in both PNS and CNS