Learning from the lived experience of functionally healthy older adults: What does it mean to be “healthy”?

BackgroundReports of older adults’ perceptions of ageing and health generally do not consider individual health status, instead presenting large cohort data or focussing on specific population groups. Moreover, qualitative studies have largely included participants with suboptimal health.AimThis study aimed to examine functionally healthy older adults’ perceptions of health and healthy ageing.MethodTwenty-two functionally healthy older adults living independently in the community (aged 61–83 years; 68% female) participated in six focus groups to explore their perceptions about “health” and “healthy ageing”. Quantitative measures were used to describe participants’ health status.FindingsSeven themes describing participants’ experiences of healthy ageing were identified: “know thyself”, “knowledge and information management”, “choices, agency, and control”, “autonomy and flexibility”, “being strategic”, “community connections”, and “getting more out of life”. Key competencies for healthy ageing were subsequently derived, drawing connections between beliefs, behaviours, and knowledge about healthy ageing.DiscussionThe identified health behaviours perceived to be important for healthy ageing align with previous reports. The subsequent overarching healthy-ageing competencies (“recognise opportunity”, “strategise”, “maximise benefits”, and “active participation”) present important pillars underpinning the process of healthy ageing that have not been previously considered in this context.ConclusionThe behaviours perceived to influence older adults’ health are varied, and the competencies identified in this study present a broad framework underpinning these behaviours. The identified competencies have the potential to inform public health initiatives, practice, and policy, empowering individuals to optimise their health.     

Influence of calcium channel antagonists on nonsomatic signs of nicotine and d-amphetamine withdrawal in mice

BackgroundNonsomatic signs of psychostimulant withdrawal, difficult to demonstrate in animal paradigms, may appear to promote drug seeking and drug relapse in humans; thus, it is important to understand the mechanisms that mediate this kind of behaviors. The present study was undertaken to examine the calcium-dependent mechanism of negative nonsomatic and anhedonia-related symptoms of acute and protracted withdrawal of nicotine and d-amphetamine.MethodsMice were chronically treated with nicotine (seven days, three times daily, 3.35 mg/kg, sc) or d-amphetamine (14 days, once daily, 2.5 mg/kg, ip). Then, at the first, seventh or 14th day of withdrawal, anxiety- or depression-related effects, as well as cognition or nociception were studied.ResultsOur results demonstrated that, at the seventh or 14th day of d-amphetamine or nicotine withdrawal, respectively, mice exhibited increased anxiety and depression-like effects, memory impairment and hyperalgesia. Further, major findings showed that calcium channel antagonists, i.e., nimodipine, verapamil and flunarizine (10 and 20 mg/kg, ip), injected before the test, attenuated above-mentioned signs of drug withdrawal.ConclusionsAs an outcome, these findings support the hypothesis that similar calcium-dependent mechanisms are involved in an aversive nonsomatic component, associated with nicotine or d-amphetamine withdrawal. We can suggest that calcium channel blockers have potential to alleviate drug withdrawal and may thus be beneficial as pharmacotherapy of drug cessation and relapse.     

Automatic modeling of pectus excavatum corrective prosthesis using artificial neural networks

Pectus excavatum is the most common deformity of the thorax. Pre-operative diagnosis usually includes Computed Tomography (CT) to successfully employ a thoracic prosthesis for anterior chest wall remodeling. Aiming at the elimination of radiation exposure, this paper presents a novel methodology for the replacement of CT by a 3D laser scanner (radiation-free) for prosthesis modeling.The complete elimination of CT is based on an accurate determination of ribs position and prosthesis placement region through skin surface points. The developed solution resorts to a normalized and combined outcome of an artificial neural network (ANN) set. Each ANN model was trained with data vectors from 165 male patients and using soft tissue thicknesses (STT) comprising information from the skin and rib cage (automatically determined by image processing algorithms). Tests revealed that ribs position for prosthesis placement and modeling can be estimated with an average error of 5.0 ± 3.6 mm. One also showed that the ANN performance can be improved by introducing a manually determined initial STT value in the ANN normalization procedure (average error of 2.82 ± 0.76 mm). Such error range is well below current prosthesis manual modeling (approximately 11 mm), which can provide a valuable and radiation-free procedure for prosthesis personalization.     

Performance analysis of four nonlinearity analysis methods using a model with variable complexity and application to uterine EMG signals

Several measures have been proposed to detect nonlinear characteristics in time series. Results on time series, multiple surrogates and their z-score are used to statistically test for the presence or absence of non-linearity. The z-score itself has sometimes been used as a measure of nonlinearity. The sensitivity of nonlinear methods to the nonlinearity level and their robustness to noise have rarely been evaluated in the past. While surrogates are important tools to rigorously detect nonlinearity, their usefulness for evaluating the level of nonlinearity is not clear. In this paper we investigate the performance of four methods arising from three families that are widely used in non-linearity detection: statistics (time reversibility), predictability (sample entropy, delay vector variance) and chaos theory (Lyapunov exponents). We used sensitivity to increasing complexity and the mean square error (MSE) of Monte Carlo instances for quantitative comparison of their performances. These methods were applied to a Henon nonlinear synthetic model in which we can vary the complexity degree (CD). This was done first by applying the methods directly to the signal and then using the z-score (surrogates) with and without added noise. The methods were then applied to real uterine EMG signals and used to distinguish between pregnancy and labor contraction bursts. The discrimination performances were compared to linear frequency based methods classically used for the same purpose such as mean power frequency (MPF), peak frequency (PF) and median frequency (MF). The results show noticeable difference between different methods, with a clear superiority of some of the nonlinear methods (time reversibility, Lyapunov exponents) over the linear methods. Applying the methods directly to the signals gave better results than using the z-score, except for sample entropy.     

Engaging hospitalized patients in clinical care: Study protocol for a pragmatic randomized controlled trial

BackgroundPatients who are better informed and more engaged in their health care have higher satisfaction with health care and better health outcomes. While patient engagement has been a focus in the outpatient setting, strategies to engage inpatients in their care have not been well studied. We are undertaking a study to assess how patients' information needs during hospitalization can be addressed with health information technologies. To achieve this aim, we developed a personalized inpatient portal that allows patients to see who is on their care team, monitor their vital signs, review medications being administered, review current and historical lab and test results, confirm allergies, document pain scores and send questions and comments to inpatient care providers. The purpose of this paper is to describe the protocol for the study.Methods/designThis pragmatic randomized controlled trial will enroll 426 inpatient cardiology patients at an urban academic medical center into one of three arms receiving: 1) usual care, 2) iPad with general internet access, or 3) iPad with access to the personalized inpatient portal. The primary outcome of this trial is patient engagement, which is measured through the Patient Activation Measure. To assess scalability and potential reach of the intervention, we are partnering with a West Coast community hospital to deploy the patient engagement technology in their environment with an additional 160 participants.ConclusionThis study employs a pragmatic randomized control trial design to test whether a personalized inpatient portal will improve patient engagement. If the study is successful, continuing advances in mobile computing technology should make these types of interventions available in a variety of clinical care delivery settings.     

Muscle motion and EMG activity in vibration treatment

The aim of this study is to highlight the relationship between muscle motion, generated by whole body vibration, and the correspondent electromyographic (EMG) activity and to suggest a new method to customize the stimulation frequency. Simultaneous recordings of EMG and tri-axial accelerations of quadriceps rectus femoris from fifteen subjects undergoing vibration treatments were collected. Vibrations were delivered via a sinusoidal oscillating platform at different frequencies (10–45 Hz). Muscle motion was estimated by processing the accelerometer data. Large EMG motion artifacts were removed using sharp notch filters centred at the vibration frequency and its superior harmonics. EMG–RMS values were computed and analyzed before and after artifact suppression to assess muscular activity. Muscles acceleration amplitude increased with frequency. Muscle displacements revealed a mechanical resonant-like behaviour of the muscle. Resonance frequencies and dumping factors depended on subject. Moreover, RMS of artifact-free EMG was found well correlated (R² = 0.82) to the actual muscle displacement, while the maximum of the EMG response was found related to the mechanical resonance frequency of muscle.Results showed that maximum muscular activity was found in correspondence to the mechanical resonance of the muscle itself. Assuming the hypothesis that muscle activation is proportional to muscle displacement, treatment optimization (i.e. to choose the best stimulation frequency) could be obtained by simply monitoring local acceleration (resonance), leading to a more effective muscle stimulation. Motion artifact produced an overestimation of muscle activity, therefore its removal was essential.     

An ontology-based approach to patient follow-up assessment for continuous and personalized chronic disease management

ObjectiveChronic diseases are complex and persistent clinical conditions that require close collaboration among patients and health care providers in the implementation of long-term and integrated care programs. However, current solutions focus partially on intensive interventions at hospitals rather than on continuous and personalized chronic disease management. This study aims to fill this gap by providing computerized clinical decision support during follow-up assessments of chronically ill patients at home.MethodsWe proposed an ontology-based framework to integrate patient data, medical domain knowledge, and patient assessment criteria for chronic disease patient follow-up assessments. A clinical decision support system was developed to implement this framework for automatic selection and adaptation of standard assessment protocols to suit patient personal conditions. We evaluated our method in the case study of type 2 diabetic patient follow-up assessments.ResultsThe proposed framework was instantiated using real data from 115,477 follow-up assessment records of 36,162 type 2 diabetic patients. Standard evaluation criteria were automatically selected and adapted to the particularities of each patient. Assessment results were generated as a general typing of patient overall condition and detailed scoring for each criterion, providing important indicators to the case manager about possible inappropriate judgments, in addition to raising patient awareness of their disease control outcomes. Using historical data as the gold standard, our system achieved a rate of accuracy of 99.93% and completeness of 95.00%.ConclusionsThis study contributes to improving the accessibility, efficiency and quality of current patient follow-up services. It also provides a generic approach to knowledge sharing and reuse for patient-centered chronic disease management.     

A double-chamber rotating bioreactor for the development of tissue-engineered hollow organs: From concept to clinical trial

Cell and tissue engineering are now being translated into clinical organ replacement, offering alternatives to fight morbidity, organ shortages and ethico-social problems associated with allotransplantation. Central to the recent first successful use of stem cells to create an organ replacement in man was our development of a bioreactor environment. Critical design features were the abilities to drive the growth of two different cell types, to support 3D maturation, to maintain biomechanical and biological properties and to provide appropriate hydrodynamic stimuli and adequate mass transport. An analytical model was developed and applied to predict oxygen profiles in the bioreactor-cultured organ construct and in the culture media, comparing representative culture configurations and operating conditions. Autologous respiratory epithelial cells and mesenchymal stem cells (BMSCs, then differentiated into chondrocytes) were isolated, characterized and expanded. Both cell types were seeded and cultured onto a decellularized human donor tracheal matrix within the bioreactor. One year post-operatively, graft and patient are healthy, and biopsies confirm angiogenesis, viable epithelial cells and chondrocytes. Our rotating double-chamber bioreactor permits the efficient repopulation of a decellularized human matrix, a concept that can be applied clinically, as demonstrated by the successful tracheal transplantation.