Dementia Prediction in Older Adults Using Sex-Specific Health Trajectory Clustering.

With increasing number of people living with dementia, the problem of late diagnosis significantly impacts a person's quality of life while early signs of dementia may provide useful insights to facilitate better treatment plans. With time, this progressive neurodegenerative syndrome could progress from mild cognitive impairment to dementia. A pattern of health conditions can be characterized in unsupervised manner to help predict this progress. As a significant extension to our previous work with streaming clustering model, we consider additional information for predicting dementia onset. With empirical observations, we discover the importance of examining sex and age to predict dementia onset. To this end, we propose a sex-specific model with age-constraint for predicting dementia onset and validate the effectiveness of our models using data from Mayo Clinic Study of Aging (MCSA). The proposed sex-specific models for older adult populations (>=65 years of age) outperformed the previous models with F-score of 77% and 78% for male-specific and female-specific models, respectively. Our experiments of sex-specific temporal clustering of features in older adults demonstrate the potential of more personalized models for early alerts of dementia.

Solvent Regeneration Methods for Combined Dearomatization, Desulfurization, and Denitrogenation of Fuels Using Deep Eutectic Solvents.

Deep eutectic solvents (DESs) can be used as potential solvents for various applications. However, their recovery depends on both economic and environmental considerations. In this study, the possibilities for the recovery of methyl triphenyl phosphonium bromide/triethylene glycol (MTPPB/TEG 1:4) after the application of combined dearomatization, desulfurization, and denitrogenation of fuels are investigated. The DES was first prepared and characterized for its density, viscosity, and water content. Then, the single-stage liquid-liquid extraction was conducted in addition to testing the repetitive use of the DES. After that, two regeneration methods were studied: the stripping method (with n-heptane) and the washing method (with distilled water or diethyl ether). In addition, a parametric study was conducted to optimize the regeneration methods. The results showed that washing the used DES with distilled water was significantly more effective than stripping the DES with n-heptane. In terms of quinoline reduction, distilled water reduced the quinoline content in the DES from 3.2 to 2.1 wt %, while n-heptane showed a minor reduction in the quinoline content (3.2 to 3 wt %). It was also found that a much more effective recovery could be achieved by (i) increasing the DES-to-regeneration solvent mass ratio and (ii) increasing the number of wash cycles. Furthermore, the regeneration temperature did not have a significant effect on the recyclability of the DES. The results demonstrated that the regenerated DES was as effective in extraction as a fresh batch of DES.

Detection of Dementia Signals from Longitudinal Clinical Visits Using One-Class Classification.

Dementia is one of the major health challenges in aging populations, with 50 million people diagnosed worldwide. However, dementia is often underdiagnosed or delayed resulting in missed opportunities for appropriate care plans. Identifying early signs of dementia is essential for better life quality of aging populations. Monitoring early signs of individual health changes could help clinicians diagnose dementia in its early stages with more effective treatment plans. However, rare data for dementia cases compared to the normal (i.e., imbalance class distribution) make it challenging to develop robust supervised learning models. In order to alleviate this issue, we investigated one-class classification (OCC) techniques, which use only majority class (i.e., normal cases) in model development to detect dementia signals from older adult clinical visits. The OCC models identify abnormality of older adults' longitudinal health conditions to predict incident dementia. The predictive performance of the OCC was compared with a recent streaming clustering-based technique and demonstrated higher predictive power. Our analysis showed that OCC has a promising potential to increase power in predicting dementia.

Quality assessment of functional status documentation in EHRs across different healthcare institutions.

The secondary use of electronic health records (EHRs) faces challenges in the form of varying data quality-related issues. To address that, we retrospectively assessed the quality of functional status documentation in EHRs of persons participating in Mayo Clinic Study of Aging (MCSA). We used a convergent parallel design to collect quantitative and qualitative data and independently analyzed the findings. We discovered a heterogeneous documentation process, where the care practice teams, institutions, and EHR systems all play an important role in how text data is documented and organized. Four prevalent instrument-assisted documentation (iDoc) expressions were identified based on three distinct instruments: Epic smart form, questionnaire, and occupational therapy and physical therapy templates. We found strong differences in the usage, information quality (intrinsic and contextual), and naturality of language among different type of iDoc expressions. These variations can be caused by different source instruments, information providers, practice settings, care events and institutions. In addition, iDoc expressions are context specific and thus shall not be viewed and processed uniformly. We recommend conducting data quality assessment of unstructured EHR text prior to using the information.

Prediction of Incident Dementia Using Patient Temporal Health Status.

Dementia is one of the most prevalent health problems in the aging population. Despite the significant number of people affected, dementia diagnoses are often significantly delayed, missing opportunities to maximize life quality. Early identification of older adults at high risk for dementia may help to maximize current quality of life and to improve planning for future health needs in dementia patients. However, most existing risk prediction models predominantly use static variables, not considering temporal patterns of health status. This study used an attention-based time-aware model to predict incident dementia that incorporated longitudinal temporal health conditions. The predictive performance of the time-aware model was compared with three traditional models using static variables and demonstrated higher predictive power.

Microfluidics for Electrochemical Energy Conversion.

Electrochemical energy conversion is an important supplement for storage and on-demand use of renewable energy. In this regard, microfluidics offers prospects to raise the efficiency and rate of electrochemical energy conversion through enhanced mass transport, flexible cell design, and ability to eliminate the physical ion-exchange membrane, an essential yet costly element in conventional electrochemical cells. Since the 2002 invention of the microfluidic fuel cell, the research field of microfluidics for electrochemical energy conversion has expanded into a great variety of cell designs, fabrication techniques, and device functions with a wide range of utility and applications. The present review aims to comprehensively synthesize the best practices in this field over the past 20 years. The underlying fundamentals and research methods are first summarized, followed by a complete assessment of all research contributions wherein microfluidics was proactively utilized to facilitate energy conversion in conjunction with electrochemical cells, such as fuel cells, flow batteries, electrolysis cells, hybrid cells, and photoelectrochemical cells. Moreover, emerging technologies and analytical tools enabled by microfluidics are also discussed. Lastly, opportunities for future research directions and technology advances are proposed.

Single-dose oral anti-arrhythmic drugs for cardioversion of recent-onset atrial fibrillation: a systematic review and network meta-analysis of randomized controlled trials.

AIMS: Single oral dose anti-arrhythmic drugs (AADs) are used to cardiovert recent-onset atrial fibrillation (AF); however, the optimal agent is uncertain. METHODS: We performed a systematic review and network meta-analysis of randomized trials testing single oral dose AADs vs. any comparator to cardiovert AF <7 days duration. We searched MEDLINE, Embase, and CENTRAL to April 2020. The primary outcome was successful cardioversion at timepoint nearest 8 h after administration. RESULTS: From 12 712 citations, 22 trials (2320 patients) were included. Thirteen trials included patients with some degree of heart failure; 19 included patients with some degree of ischaemic heart disease vs. placebo or rate-control (32% success) at 8 h, flecainide [73%, network odds ratio (OR) 7.6, 95% credible interval (CrI) 4.4-14.0], propafenone (70%, OR 4.6, CrI 2.9-7.3), and pilsicainide (59%, OR 10.0, CrI 1.8-69.0), but not amiodarone (28%, OR 1.0, CrI 0.4-2.8) were superior. Flecainide (OR 7.5, CrI 2.6-24.0) and propafenone (OR 4.5, CrI 1.6-13.0) were superior to amiodarone; propafenone vs. flecainide did not statistically differ (OR 0.6, CrI 0.3-1.1). At longest follow-up, amiodarone was superior to placebo (OR 11.0, CrI 3.2-41.0), flecainide vs. amiodarone (OR 0.79, CrI 0.19-3.1), and propafenone vs. amiodarone (OR 0.36, CrI 0.092-1.4) were not statistically different, and flecainide was superior to propafenone (OR 2.2, CrI 1.1-4.8). Atrial and ventricular tachyarrhythmias, bradyarrhythmias, and hypotension were rare with PO AADs. CONCLUSION: Single oral dose Class 1C AADs are effective and safe for cardioversion of recent-onset AF. Flecainide may be superior to propafenone. Amiodarone is a slower acting alternative.

Early Alert of Elderly Cognitive Impairment using Temporal Streaming Clustering.

more than 44 million people have been diagnosed with dementia worldwide, and this number is estimated to triple by next three decades. Given this increasing trend of older adults with cognitive impairment (CI; dementia and mild cognitive impairment) and its significant underdiagnosis, early identification of CI and understanding its progression is a critical step towards a better quality of life for the aging population. Early alert of individual health changes could facilitate better ways for clinicians to diagnose CI in its early stages and come up with more effective treatment plans. However, there is a lack of approaches to characterize patient health conditions accounting for temporal information in an unsupervised manner. Limited CI cases and its costly ascertainment in clinical settings also make unsupervised learning more promising in CI research. In this paper, a streaming clustering model was used to determine distinct patterns of older adults' health changes from their clinical visits in Mayo Clinic Study of Aging. The streaming clustering was also examined to study its ability to generate early alerts for potential incidents of CI. Our analysis demonstrated that temporal characteristics incorporated in a streaming clustering model has a promising potential to increase power in predicting CI.

An Organic Redox Flow Cell-Inspired Paper-Based Primary Battery.

A portable paper-based organic redox flow primary battery using sustainable quinone chemistry is presented. The compact prototype relies on the capillary forces of the paper matrix to develop a quasi-steady flow of the reactants through a pair of porous carbon electrodes without the need of external pumps. Co-laminar capillary flow allows operation Under mixed-media conditions, in which an alkaline anolyte and an acidic catholyte are employed. This feature enables higher electrochemical cell voltages during discharge operation and the utilization of a wider range of available species and electrolytes and provides the advantage to form a neutral or near-neutral pH as the electrolytes neutralize at the absorbent pad, which allows a safe disposal after use. The effects of the device design parameters have been studied to enhance battery features such as power output, operational time, and fuel utilization. The device achieves a faradaic efficiency of up to 98 %, which is the highest reported in a capillary-based electrochemical power source, as well as a cell capacity of up to 11.4 Ah L-1 cm-2 , comparable to state-of-the-art large-scale redox flow cells.

Atrial fibrillation in elderly patients with implantable loop recorders for unexplained syncope.

BACKGROUND: An implantable loop recorder (ILR) assists in the diagnosis of unexplained syncope and atrial fibrillation (AF). Both become prevalent with age. Limited data exist describing the incidence of AF as the diagnostic rhythm underlying syncope in the elderly. This study aims to report the incidence of AF in older adults with ILRs for unexplained syncope and identify clinical characteristics associated with AF in this population. METHODS: Retrospective observational study on patients with unexplained syncope seen in syncope clinics from two Canadian centers. Participants were ≥65 years old, without a history of AF, and received an ILR for unexplained syncope. Data were collected from patient's clinic charts. Arrhythmia diagnosis was based on ILR electrocardiogram reading during syncope (symptom-rhythm correlation). Fisher's exact test and the Student's t test were used to compare participants with and without AF. RESULTS: In our cohort of 222 patients, 124 were females and 98 were males. Mean age at implant was 80 ± 8 years. Arrhythmia was diagnosed in 98 patients (44.1%). Median time to diagnosis was 18 months. AF was diagnosed in 17 (7.7%) participants. There were fewer males in the AF group than the no AF group (11.8%, 46.8%, p = 0.01). Age, baseline EKG, and prevalence of hypertension, diabetes, stroke, or ischemic heart disease were not statistically different between patients with AF and without AF. CONCLUSIONS: Atrial fibrillation was a common diagnostic rhythm in this cohort of adults, aged 65 and older, with ILRs for unexplained syncope. It was observed more frequently in females.

"Bleaching" glycerol in a microfluidic fuel cell to produce high power density at minimal cost.

Glycerol/bleach flow-through microfluidic fuel cells are presented. Carbon paper-modified Pt/C nanoparticles were used as the anode and cathode. Glycerol oxidation in alkaline medium was tested against hypochlorite reduction in alkaline and acidic media. The mixed media system displayed a power density of 315 mW cm-2 and an open circuit voltage of 1.9-2.0 V.

Implantable loop recorders in the real world: a study of two Canadian centers.

PURPOSE: Implantable loop recorders (ILRs) are increasingly being used for ambulatory electrocardiography. We sought to evaluate ILR indications, diagnostic yield, ILR-guided interventions, and complications in two Canadian centers. METHODS: This was a retrospective study using electronic medical records to identify ILR implants at Queen's University and the University of Manitoba. Information was collected on patient characteristics, medications, indication for implant, results of prior investigations, diagnostic outcome, and subsequent management. RESULTS: A total of 540 patients were identified; 386 had completed monitoring at time of analysis. Forty patients were lost to follow-up. Indications were unexplained syncope 84.8%, palpitations 12.8%, and suspected atrial fibrillation 11.7%. For syncope, ILRs documented arrhythmia or conduction disorder in 46%. Most common conditions were asystole/sinus pause (22%), complete heart block (10.4%), and atrial fibrillation (AF) (6.9%). After ILR diagnosis, 39.9% of implanted patients received pacemaker/ICD and 2.7% underwent catheter ablation. For palpitations, ILRs documented arrhythmia or conduction disorder in 60.4%. Most common conditions were AVNRT, AF, complete heart block, and ventricular tachycardia. After diagnosis, 25% underwent catheter ablation and 22.9% received pacemaker/ICD. For suspected AF, AF was diagnosed in 40%. Complications were observed in 3.3% of implanted patients: implant site infection 1.5%, non-infectious implant site pain requiring device removal or pocket revision 1.5%, 0.2% hypertrophic scar, and 0.2% device malfunction. CONCLUSIONS: An ILR has excellent diagnostic yield for syncope, palpitations, and suspected AF, and a considerable proportion of patients undergo ILR-directed interventions following monitoring. ILR implantation is a low-risk procedure.