An Integrated Multi-Sensor Approach for the Remote Monitoring of Parkinson's Disease.

The increment of the prevalence of neurological diseases due to the trend in population aging demands for new strategies in disease management. In Parkinson's disease (PD), these strategies should aim at improving diagnosis accuracy and frequency of the clinical follow-up by means of decentralized cost-effective solutions. In this context, a system suitable for the remote monitoring of PD subjects is presented. It consists of the integration of two approaches investigated in our previous works, each one appropriate for the movement analysis of specific parts of the body: low-cost optical devices for the upper limbs and wearable sensors for the lower ones. The system performs the automated assessments of six motor tasks of the unified Parkinson's disease rating scale, and it is equipped with a gesture-based human machine interface designed to facilitate the user interaction and the system management. The usability of the system has been evaluated by means of standard questionnaires, and the accuracy of the automated assessment has been verified experimentally. The results demonstrate that the proposed solution represents a substantial improvement in PD assessment respect to the former two approaches treated separately, and a new example of an accurate, feasible and cost-effective mean for the decentralized management of PD.

Motor assessment of X-linked dystonia parkinsonism via machine-learning-based analysis of wearable sensor data.

X-linked dystonia parkinsonism (XDP) is a neurogenetic combined movement disorder involving both parkinsonism and dystonia. Complex, overlapping phenotypes result in difficulties in clinical rating scale assessment. We performed wearable sensor-based analyses in XDP participants to quantitatively characterize disease phenomenology as a potential clinical trial endpoint. Wearable sensor data was collected from 10 symptomatic XDP patients and 3 healthy controls during a standardized examination. Disease severity was assessed with the Unified Parkinson's Disease Rating Scale Part 3 (MDS-UPDRS) and Burke-Fahn-Marsden dystonia scale (BFM). We collected sensor data during the performance of specific MDS-UPDRS/BFM upper- and lower-limb motor tasks, and derived data features suitable to estimate clinical scores using machine learning (ML). XDP patients were at varying stages of disease and clinical severity. ML-based algorithms estimated MDS-UPDRS scores (parkinsonism) and dystonia-specific data features with a high degree of accuracy. Gait spatio-temporal parameters had high discriminatory power in differentiating XDP patients with different MDS-UPDRS scores from controls, XDP freezing of gait, and dystonic/non-dystonic gait. These analyses suggest the feasibility of using wearable sensor data for deriving reliable clinical score estimates associated with both parkinsonian and dystonic features in a complex, combined movement disorder and the utility of motion sensors in quantifying clinical examination.

Voice Biomarkers of Recovery From Acute Respiratory Illness.

Voice analysis is an emerging technology which has the potential to provide low-cost, at-home monitoring of symptoms associated with a variety of health conditions. While voice has received significant attention for monitoring neurological disease, few studies have focused on voice changes related to flu-like symptoms. Herein, we investigate the relationship between changes in acoustic features of voice and self-reported symptoms during recovery from a flu-like illness in a cohort of 29 subjects. Acoustic features were automatically extracted from "sick" and "well" visit data collected in the laboratory setting, and feature down-selection was used to identify those that change significantly between visits. The selected acoustic features were extracted from at-home data and used to construct a combined distance metric that correlated with self-reported symptoms (0.63 rank correlation). Changes in self-reported symptoms corresponding to 10% of the ordinal scale used in the study were detected with an area under the curve of 0.72. The results show that acoustic features derived from voice recordings may provide an objective measure for diagnosing and monitoring symptoms of respiratory illnesses.

Accelerometer data collected with a minimum set of wearable sensors from subjects with Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository.

Limb and trunk accelerometer data collected with wearable sensors from subjects with Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and non-motor symptoms. Dyskinesia and motor fluctuations are complications of PD medications. An objective measure of on/off time with/without dyskinesia has been sought for some time because it would facilitate the titration of medications. The objective of the dataset herein presented is to assess if wearable sensor data can be used to generate accurate estimates of limb-specific symptom severity. Nineteen subjects with PD experiencing motor fluctuations were asked to wear a total of five wearable sensors on both forearms and shanks, as well as on the lower back. Accelerometer data was collected for four days, including two laboratory visits lasting 3 to 4 hours each while the remainder of the time was spent at home and in the community. During the laboratory visits, subjects performed a battery of motor tasks while clinicians rated limb-specific symptom severity. At home, subjects were instructed to use a smartphone app that guided the periodic performance of a set of motor tasks.

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge.

Consumer wearables and sensors are a rich source of data about patients' daily disease and symptom burden, particularly in the case of movement disorders like Parkinson's disease (PD). However, interpreting these complex data into so-called digital biomarkers requires complicated analytical approaches, and validating these biomarkers requires sufficient data and unbiased evaluation methods. Here we describe the use of crowdsourcing to specifically evaluate and benchmark features derived from accelerometer and gyroscope data in two different datasets to predict the presence of PD and severity of three PD symptoms: tremor, dyskinesia, and bradykinesia. Forty teams from around the world submitted features, and achieved drastically improved predictive performance for PD status (best AUROC = 0.87), as well as tremor- (best AUPR = 0.75), dyskinesia- (best AUPR = 0.48) and bradykinesia-severity (best AUPR = 0.95).

mHealth and wearable technology should replace motor diaries to track motor fluctuations in Parkinson's disease.

Accurately monitoring motor and non-motor symptoms as well as complications in people with Parkinson's disease (PD) is a major challenge, both during clinical management and when conducting clinical trials investigating new treatments. A variety of strategies have been relied upon including questionnaires, motor diaries, and the serial administration of structured clinical exams like part III of the MDS-UPDRS. To evaluate the potential use of mobile and wearable technologies in clinical trials of new pharmacotherapies targeting PD symptoms, we carried out a project (project BlueSky) encompassing four clinical studies, in which 60 healthy volunteers (aged 23-69; 33 females) and 95 people with PD (aged 42-80; 37 females; years since diagnosis 1-24 years; Hoehn and Yahr 1-3) participated and were monitored in either a laboratory environment, a simulated apartment, or at home and in the community. In this paper, we investigated (i) the utility and reliability of self-reports for describing motor fluctuations; (ii) the agreement between participants and clinical raters on the presence of motor complications; (iii) the ability of video raters to accurately assess motor symptoms, and (iv) the dynamics of tremor, dyskinesia, and bradykinesia as they evolve over the medication cycle. Future papers will explore methods for estimating symptom severity based on sensor data. We found that 38% of participants who were asked to complete an electronic motor diary at home missed ~25% of total possible entries and otherwise made entries with an average delay of >4 h. During clinical evaluations by PD specialists, self-reports of dyskinesia were marked by ~35% false negatives and 15% false positives. Compared with live evaluation, the video evaluation of part III of the MDS-UPDRS significantly underestimated the subtle features of tremor and extremity bradykinesia, suggesting that these aspects of the disease may be underappreciated during remote assessments. On the other hand, live and video raters agreed on aspects of postural instability and gait. Our results highlight the significant opportunity for objective, high-resolution, continuous monitoring afforded by wearable technology to improve upon the monitoring of PD symptoms.

Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?

Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing.

Pregnancy in systemic sclerosis.

This comprehensive review summarizes retrospective and prospective studies on pregnancy in systemic sclerosis in order to educate physicians on critical management issues. Fertility is normal in women with established systemic sclerosis. Their rates of spontaneous losses are comparable to the general population, except for patients with late diffuse systemic sclerosis and severe internal organ involvement who may have higher risks of abortion. Prematurity is clearly higher among systemic sclerosis women, similarly to other rheumatic diseases such as systemic lupus erythematosus and anti-phospholipid antibody syndrome. A placental vasculopathy has been observed in some women with systemic sclerosis. Overall, the disease generally remains stable in most pregnancies. Women with pulmonary hypertension should avoid pregnancy on account of the high maternal mortality risk. Management of systemic sclerosis patients before and during pregnancy includes evaluation of organ involvement and autoantibody analysis, preconceptional folic acid, and discontinuation of drugs with teratogenic potential (bosentan, mycophenolate mofetil, methotrexate, etc.). Management by high-risk pregnancy teams including neonatologists is very important to ensure the best outcomes.

Free light chains of immunoglobulins in patients with systemic sclerosis: correlations with lung involvement and inflammatory milieu.

AIM: Humoral immunity and B cells are thought to play an important role in the pathophysiology of the systemic sclerosis (SSc). The production of free light chains (FLC) of immunoglobulins is abnormally high in several pathological autoimmune conditions and reflects B cell activation. Furthermore, FLCs demonstrated different biological activities including their capability to modulate the immune system, proteolytic activity and complement cascade activation. The aims of this study are to determine the FLC levels in patients with SSc compared with healthy controls (HC) and to study their possible association with organ involvement and disease characteristics. METHODS: Sixty-five patients with SSc and 20 HC were studied. Clinical and immunological inflammatory characteristics were assessed for all the patients with SSc. κ-FLC and λ-FLC, interleukin 6 (IL-6) and B cell activating factor levels were measured. RESULTS: The mean serum κ-FLC levels and FLC ratio were significantly higher in patients with SSc compared with HC, while the serum λ-FLC levels were comparable.The levels of FLC were comparable in patients with diffuse skin disease and limited skin involvement, while κ-FLC levels were increased in patients with restrictive lung (forced vital capacity (FVC) <80%) disease (26.4±7.4 mg/L) when compared with patients with FVC ≥80% (19.6±7.3 mg/L, P=0.009). In patients with SSc, the levels of serum κ-FLC level directly correlated with the IL-6 levels (R=0.3, P=0.001) and disease activity (R=0.4, P=0.003). CONCLUSIONS: FLC levels are elevated in SSc and high levels are associated with lung involvement and with a higher degree of inflammation, supporting a possible role of B cell activation in the pathophysiology of the disease.

Refractory adult-onset Still disease complicated by macrophage activation syndrome and acute myocarditis: A case report treated with high doses (8 mg/kg/d) of anakinra.

RATIONALE: Myocarditis is a rare but potentially fatal complication of Still's disease (about 7% of total cases). PATIENT CONCERNS: A 42-year-old woman was admitted to our ward with high-grade fever, rash and polyarthralgia, lasting since 4 weeks and rapidly complicated by MAS and acute heart failure. DIAGNOSES: Adult Onset Still's Disease rapidly developping macrophage activation syndrome and disseminated intravascular coagulopathy, further complicated by iperacute myocarditis with cardiac arrest. INTERVENTIONS: After failure of conventional therapies (steroids plus cyclosporine and then biological therapy with Anakinra 100 mg/day), the patient was treated with anakinra 100 mg sc 1 fl 4 times a day. OUTCOMES: Fast clinical and laboratoristic improvement and subsequent disease remission with complete recovery of cardiac function. LESSONS: This is the first case report in which high doses of Anakinra have been used to treat a refractory AOSD complicated by MAS and myocarditis. In AOSD complicated by life-threatening conditions, probably we need to consider aggressive therapeutic approaches with higher doses of Il-1 receptor blocker to switch off the hyper-inflammation.

The prognostic significance of the Birmingham Vasculitis Activity Score (BVAS) with systemic vasculitis patients transferred to the intensive care unit (ICU).

Systemic vasculitides represent a heterogeneous group of diseases that share clinical features including respiratory distress, renal dysfunction, and neurologic disorders. These diseases may often cause life-threatening complications requiring admission to an intensive care unit (ICU). The aim of the study was to evaluate the validity and responsiveness of Birmingham Vasculitis Activity Score (BVAS) score to predict survival in patients with systemic vasculitides admitted to ICU.A retrospective study was carried out from 2004 to 2014 in 18 patients with systemic vasculitis admitted to 2 different Rheumatology divisions and transferred to ICU due to clinical worsening, with a length of stay beyond 24 hours. We found that ICU mortality was significantly associated with higher BVAS scores performed in the ward (P = 0.01) and at the admission in ICU (P = 0.01), regardless of the value of Acute Physiology And Chronic Health Evaluation (APACHE II) scores (P = 0.50). We used receiver-operator characteristic (ROC) curve analysis to evaluate the possible cutoff value for the BVAS in the ward and in ICU and we found that a BVAS > 8 in the ward and that a BVAS > 10 in ICU might be a useful tool to predict in-ICU mortality.BVAS appears to be an excellent tool for assessing ICU mortality risk of systemic vasculitides patients admitted to specialty departments. Our experience has shown that performing the assessment at admission to the ward is more important than determining the evaluation before the clinical aggravation causing the transfer to ICU.

Prognostic Role of Ventricular Ectopic Beats in Systemic Sclerosis: A Prospective Cohort Study Shows ECG Indexes Predicting the Worse Outcome.

BACKGROUND: Arrhythmias are frequent in Systemic Sclerosis (SSc) and portend a bad prognosis, accounting alone for 6% of total deaths. Many of these patients die suddenly, thus prevention and intensified risk-stratification represent unmet medical needs. The major goal of this study was the definition of ECG indexes of poor prognosis. METHODS: We performed a prospective cohort study to define the role of 24h-ECG-Holter as an additional risk-stratification technique in the identification of SSc-patients at high risk of life-threatening arrhythmias and sudden cardiac death (SCD). One-hundred SSc-patients with symptoms and/or signs suggestive of cardiac involvement underwent 24h-ECG-Holter. The primary end-point was a composite of SCD or need for implantable cardioverter defibrillator (ICD). RESULTS: Fifty-six patients (56%) had 24h-ECG-Holter abnormalities and 24(24%) presented frequent ventricular ectopic beats (VEBs). The number of VEBs correlated with high-sensitive cardiac troponin T (hs-cTnT) levels and inversely correlated with left-ventricular ejection fraction (LV-EF) on echocardiography. During a mean follow-up of 23.1±16.0 months, 5 patients died suddenly and two required ICD-implantation. The 7 patients who met the composite end-point had a higher number of VEBs, higher levels of hs-cTnT and NT-proBNP and lower LV-EF (p = 0.001 for all correlations). All these 7 patients had frequent VEBs, while LV-EF was not reduced in all and its range was wide. At ROC curve, VEBs>1190/24h showed 100% of sensitivity and 83% of specificity to predict the primary end-point (AUROC = 0.92,p<0.0001). Patients with VEBS>1190/24h had lower LV-EF and higher hs-cTnT levels and, at multivariate analysis, the presence of increased hs-cTnT and of right bundle branch block on ECG emerged as independent predictors of VEBs>1190/24h. None of demographic or disease-related characteristics emerged as predictors of poor outcome. CONCLUSIONS: VEBS>1190/24h identify patients at high risk of life-threatening arrhythmic complications. Thus, 24h-ECG-Holter should be considered a useful additional risk-stratification test to select SSc-patients at high-risk of SCD, in whom an ICD-implantation could represent a potential life-saving intervention.

Body-Sensor-Network-Based Kinematic Characterization and Comparative Outlook of UPDRS Scoring in Leg Agility, Sit-to-Stand, and Gait Tasks in Parkinson's Disease.

Recently, we have proposed a body-sensor-network-based approach, composed of a few body-worn wireless inertial nodes, for automatic assignment of Unified Parkinson's Disease Rating Scale (UPDRS) scores in the following tasks: Leg agility (LA), Sit-to-Stand (S2S), and Gait (G). Unlike our previous works and the majority of the published studies, where UPDRS tasks were the sole focus, in this paper, we carry out a comparative investigation of the LA, S2S, and G tasks. In particular, after providing an accurate description of the features identified for the kinematic characterization of the three tasks, we comment on the correlation between the most relevant kinematic parameters and the UPDRS scoring. We analyzed the performance achieved by the automatic UPDRS scoring system and compared the estimated UPDRS evaluation with the one performed by neurologists, showing that the proposed system compares favorably with typical interrater variability. We then investigated the correlations between the UPDRS scores assigned to the various tasks by both the neurologists and the automatic system. The results, based on a limited number of subjects with Parkinson's disease (PD) (34 patients, 47 clinical trials), show poor-to-moderate correlations between the UPDRS scores of different tasks, highlighting that the patients' motor performance may vary significantly from one task to another, since different tasks relate to different aspects of the disease. An aggregate UPDRS score is also considered as a concise parameter, which can provide additional information on the overall level of the motor impairments of a Parkinson's patient. Finally, we discuss a possible implementation of a practical e-health application for the remote monitoring of PD patients.

Temozolomide and radiotherapy versus radiotherapy alone in high grade gliomas: a very long term comparative study and literature review.

UNLABELLED: Temozolomide (TMZ) is the first line drug in the care of high grade gliomas. The combined treatment of TMZ plus radiotherapy is more effective in the care of brain gliomas then radiotherapy alone. Aim of this report is a survival comparison, on a long time (>10 years) span, of glioma patients treated with radiotherapy alone and with radiotherapy + TMZ. MATERIALS AND METHODS: In this report we retrospectively reviewed the outcome of 128 consecutive pts with diagnosis of high grade gliomas referred to our institutions from April 1994 to November 2001. The first 64 pts were treated with RT alone and the other 64 with a combination of RT and adjuvant or concomitant TMZ. RESULTS: Grade 3 (G3) haematological toxicity was recorded in 6 (9%) of 64 pts treated with RT and TMZ. No G4 haematological toxicity was observed. Age, histology, and administration of TMZ were statistically significant prognostic factors associated with 2 years overall survival (OS). PFS was for GBM 9 months, for AA 11. CONCLUSIONS: The combination of RT and TMZ improves long term survival in glioma patients. Our results confirm the superiority of the combination on a long time basis.