One-year longitudinal study of psychological distress and self-assessed health in survivors of out-of-hospital cardiac arrest.

OBJECTIVES: Few studies have investigated the psychological and health-related outcome after out-of-hospital cardiac arrest (OHCA) over time. This longitudinal study aims to evaluate psychological distress in terms of anxiety and depression, self-assessed health and predictors of these outcomes in survivors of OHCA, 3 and 12 months after resuscitation. METHODS: Recruitment took place from 2008 to 2011 and survivors of OHCA were identified through the national Swedish Cardiopulmonary Resuscitation Registry. Inclusion criteria were age ≥18 years, survival ≥12 months and a Cerebral Performance Category score ≤2. Questionnaires containing the Hospital Anxiety and Depression Scale and European Quality of Life 5 Dimensions 3 Level (EQ-5D-3L) were administered at 3 and 12 months after the OHCA. Participants were also asked to report treatment-requiring comorbidities. RESULTS: Of 298 survivors, 85 (29%) were eligible for this study and 74 (25%) responded. Clinically relevant anxiety was reported by 22 survivors at 3 months and by 17 at 12 months, while clinical depression was reported by 10 at 3 months and 4 at 12 months. The mean EQ-5D-3L index value increased from 0.82 (±0.26) to 0.88 (±0.15) over time. There were significantly less symptoms of psychological distress (p=0.01) and better self-assessed health (p=0.003) at 12 months. Treatment-requiring comorbidity predicted anxiety (OR 4.07, p=0.04), while being female and young age predicted poor health (OR 6.33, p=0.04; OR 0.91, p=0.002) at 3 months. At 12 months, being female was linked to anxiety (OR 9.23, p=0.01) and depression (OR 14.78, p=0.002), while young age predicted poor health (OR 0.93, p=0.003). CONCLUSION: The level of psychological distress and self-assessed health improves among survivors of OHCA between 3 and 12 months after resuscitation. Higher levels of psychological distress can be expected among female survivors and those with comorbidity, while survivors of young age and who are female are at greater risk of poor health.

Evaluation of a sensor algorithm for motor state rating in Parkinson's disease.

INTRODUCTION: A treatment response objective index (TRIS) was previously developed based on sensor data from pronation-supination tests. This study aimed to examine the performance of TRIS for medication effects in a new population sample with Parkinson's disease (PD) and its usefulness for constructing individual dose-response models. METHODS: Twenty-five patients with PD performed a series of tasks throughout a levodopa challenge while wearing sensors. TRIS was used to determine motor changes in pronation-supination tests following a single levodopa dose, and was compared to clinical ratings including the Treatment Response Scale (TRS) and six sub-items of the UPDRS part III. RESULTS: As expected, correlations between TRIS and clinical ratings were lower in the new population than in the initial study. TRIS was still significantly correlated to TRS (rs = 0.23, P < 0.001) with a root mean square error (RMSE) of 1.33. For the patients (n = 17) with a good levodopa response and clear motor fluctuations, a stronger correlation was found (rs = 0.38, RMSE = 1.29, P < 0.001). The mean TRIS increased significantly when patients went from the practically defined off to their best on state (P = 0.024). Individual dose-response models could be fitted for more participants when TRIS was used for modelling than when TRS ratings were used. CONCLUSION: The objective sensor index shows promise for constructing individual dose-response models, but further evaluations and retraining of the TRIS algorithm are desirable to improve its performance and to ensure its clinical effectiveness.

Tonic-clonic seizure detection using accelerometry-based wearable sensors: A prospective, video-EEG controlled study.

PURPOSE: The aim of this prospective, video-electroencephalography (video-EEG) controlled study was to evaluate the performance of an accelerometry-based wearable system to detect tonic-clonic seizures (TCSs) and to investigate the accuracy of different seizure detection algorithms using separate training and test data sets. METHODS: Seventy-five epilepsy surgery candidates undergoing video-EEG monitoring were included. The patients wore one three-axis accelerometer on each wrist during video-EEG. The accelerometer data was band-pass filtered and reduced using a movement threshold and mapped to a time-frequency feature space representation. Algorithms based on standard binary classifiers combined with a TCS specific event detection layer were developed and trained using the training set. Their performance was evaluated in terms of sensitivity and false positive (FP) rate using the test set. RESULTS: Thirty-seven available TCSs in 11 patients were recorded and the data was divided into disjoint training (27 TCSs, three patients) and test (10 TCSs, eight patients) data sets. The classification algorithms evaluated were K-nearest-neighbors (KNN), random forest (RF) and a linear kernel support vector machine (SVM). For the TCSs detection performance of the three algorithms in the test set, the highest sensitivity was obtained for KNN (100% sensitivity, 0.05 FP/h) and the lowest FP rate was obtained for RF (90% sensitivity, 0.01 FP/h). CONCLUSIONS: The low FP rate enhances the clinical utility of the detection system for long-term reliable seizure monitoring. It also allows a possible implementation of an automated TCS detection in free-living environment, which could contribute to ascertain seizure frequency and thereby better seizure management.

Sensor-based algorithmic dosing suggestions for oral administration of levodopa/carbidopa microtablets for Parkinson's disease: a first experience.

OBJECTIVE: Dosing schedules for oral levodopa in advanced stages of Parkinson's disease (PD) require careful tailoring to fit the needs of each patient. This study proposes a dosing algorithm for oral administration of levodopa and evaluates its integration into a sensor-based dosing system (SBDS). MATERIALS AND METHODS: In collaboration with two movement disorder experts a knowledge-driven, simulation based algorithm was designed and integrated into a SBDS. The SBDS uses data from wearable sensors to fit individual patient models, which are then used as input to the dosing algorithm. To access the feasibility of using the SBDS in clinical practice its performance was evaluated during a clinical experiment where dosing optimization of oral levodopa was explored. The supervising neurologist made dosing adjustments based on data from the Parkinson's KinetiGraph™ (PKG) that the patients wore for a week in a free living setting. The dosing suggestions of the SBDS were compared with the PKG-guided adjustments. RESULTS: The SBDS maintenance and morning dosing suggestions had a Pearson's correlation of 0.80 and 0.95 (with mean relative errors of 21% and 12.5%), to the PKG-guided dosing adjustments. Paired t test indicated no statistical differences between the algorithmic suggestions and the clinician's adjustments. CONCLUSION: This study shows that it is possible to use algorithmic sensor-based dosing adjustments to optimize treatment with oral medication for PD patients.

An upper body garment with integrated sensors for people with neurological disorders - early development and evaluation.

BACKGROUND: In neurology and rehabilitation the primary interest for using wearables is to supplement traditional patient assessment and monitoring in hospital settings with continuous data collection at home and in community settings. The aim of this project was to develop a novel wearable garment with integrated sensors designed for continuous monitoring of physiological and movement related variables to evaluate progression, tailor treatments and improve diagnosis in epilepsy, Parkinson's disease and stroke. In this paper the early development and evaluation of a prototype designed to monitor movements and heart rate is described. An iterative development process and evaluation of an upper body garment with integrated sensors included: identification of user needs, specification of technical and garment requirements, garment development and production as well as evaluation of garment design, functionality and usability. The project is a multidisciplinary collaboration with experts from medical, engineering, textile, and material science within the wearITmed consortium. The work was organized in regular meetings, task groups and hands-on workshops. User needs were identified using results from a mixed-methods systematic review, a focus group study and expert groups. Usability was evaluated in 19 individuals (13 controls, 6 patients with Parkinson's disease) using semi-structured interviews and qualitative content analysis. RESULTS: The garment was well accepted by the users regarding design and comfort, although the users were cautious about the technology and suggested improvements. All electronic components passed a washability test. The most robust data was obtained from accelerometer and gyroscope sensors while the electrodes for heart rate registration were sensitive to motion artefacts. The algorithm development within the wearITmed consortium has shown promising results. CONCLUSIONS: The prototype was accepted by the users. Technical improvements are needed, but preliminary data indicate that the garment has potential to be used as a tool for diagnosis and treatment selection and could provide added value for monitoring seizures in epilepsy, fluctuations in PD and activity levels in stroke. Future work aims to improve the prototype further, develop algorithms, and evaluate the functionality and usability in targeted patient groups. The potential of incorporating blood pressure and heart-rate variability monitoring will also be explored.

Individualization of levodopa treatment using a microtablet dispenser and ambulatory accelerometry.

AIM: This 4-week open-label observational study describes the effect of introducing a microtablet dose dispenser and adjusting doses based on objective free-living motor symptom monitoring in individuals with Parkinson's disease (PD). METHODS: Twenty-eight outpatients with PD on stable levodopa treatment with dose intervals of ≤4 hour had their daytime doses of levodopa replaced with levodopa/carbidopa microtablets, 5/1.25 mg (LC-5) delivered from a dose dispenser device with programmable reminders. After 2 weeks, doses were adjusted based on ambulatory accelerometry and clinical monitoring. RESULTS: Twenty-four participants completed the study per protocol. The daily levodopa dose was increased by 15% (112 mg, P < 0.001) from period 1 to 2, and the dose interval was reduced by 12% (22 minutes, P = 0.003). The treatment adherence to LC-5 was high in both periods. The MDS-UPDRS parts II and III, disease-specific quality of life (PDQ-8), wearing-off symptoms (WOQ-19), and nonmotor symptoms (NMS Quest) improved after dose titration, but the generic quality-of-life measure EQ-5D-5L did not. Blinded expert evaluation of accelerometry results demonstrated improvement in 60% of subjects and worsening in 25%. CONCLUSIONS: The introduction of a levodopa microtablet dispenser and accelerometry aided dose adjustments improve PD symptoms and quality of life in the short term.

Wearable sensors for clinical applications in epilepsy, Parkinson's disease, and stroke: a mixed-methods systematic review.

OBJECTIVES: Wearable technology is increasingly used to monitor neurological disorders. The purpose of this systematic review was to synthesize knowledge from quantitative and qualitative clinical researches using wearable sensors in epilepsy, Parkinson's disease (PD), and stroke. METHODS: A systematic literature search was conducted in PubMed and Scopus spanning from 1995 to January 2017. A synthesis of the main findings, reported adherence to wearables and missing data from quantitative studies, is provided. Clinimetric properties of measures derived from wearables in laboratory, free activities in hospital, and free-living environment were also evaluated. Qualitative thematic synthesis was conducted to explore user experiences and acceptance of wearables. RESULTS: In total, 56 studies (50 reporting quantitative and 6 reporting qualitative data) were included for data extraction and synthesis. Among studies reporting quantitative data, 5 were in epilepsy, 21 PD, and 24 studies in stroke. In epilepsy, wearables are used to detect and differentiate seizures in hospital settings. In PD, the focus is on quantification of cardinal motor symptoms and medication-evoked adverse symptoms in both laboratory and free-living environment. In stroke upper extremity activity, walking and physical activity have been studied in laboratory and during free activities. Three analytic themes emerged from thematic synthesis of studies reporting qualitative data: acceptable integration in daily life, lack of confidence in technology, and the need to consider individualization. CONCLUSIONS: Wearables may provide information of clinical features of interest in epilepsy, PD and stroke, but knowledge regarding the clinical utility for supporting clinical decision making remains to be established.

Comparison of Minimally Invasive Percutaneous Plate Osteosynthesis and Open Reduction Internal Fixation on Proximal Humeral Fracture in Elder Patients: A Systematic Review and Meta-Analysis.

OBJECTIVE: The study aims to compare minimally invasive percutaneous plate osteosynthesis (MIPO) and open reduction internal fixation (ORIF) in the treatment of proximal humeral fracture in elder patients. METHOD: PubMed, Medline, EMbase, Ovid, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wangfang, and VIP Database for Chinese Technical Periodicals were searched to identify all relevant studies from inception to October 2016. Data were analyzed with Cochrane Collaboration's Review Manage 5.2. RESULTS: A total of 630 patients from 8 publications were included in the systematic review and meta-analysis. The pooled results showed that MIPO was superior to ORIF in the treatment of proximal humeral fracture in elder patients. It was reflected in reducing blood loss, operation time, postoperative pain, or fracture healing time of the surgery and in improving recovery of muscle strength. Concerning complications, no significant difference was seen between MIPO and ORIF. CONCLUSION: The MIPO was more suitable than ORIF for treating proximal humeral fracture in elder patients.