74 research outputs found
Post-conflict private sector development : promoting durable peace : What are the characteristics and short comings of economic development in post-independent, sub-Saharan Africa : examples from Mozambique?
No full textIncludes abstract.In times of war the private sector adapts, often to function informally, and can serve to either perpetuate conflict or to incentivize peace. Accordingly, the private sector is a powerful tool that can be utilized during post-conflict reconstruction to enable sustain- able peace and economic development. After a conflict, in an effort to establish a means of survival outside of the war economy, there is a pressing need for the population to have a means by which to provide a livelihood and productively contribute to society. Establishing sustainable economic exchange and developing social capital between various members of society is one mechanism by which to achieve restorative justice and disincentivize conflict. ...this paper argues for a hybrid approach to private sector development that includes both the investment climate and interventionist methods to disincentivize a return to conflict
The Non-Motor Symptoms Scale in Parkinson’s disease : Validation and use
Get PDFThe Non-Motor Symptoms Scale (NMSS) was developed and validated in 2007 as the first instrument for the comprehensive assessment of a range of non-motor symptoms in Parkinson's disease (PD). Thirteen years have elapsed since its introduction and extensive international validation with good psychometric attributes has been carried out. Here, we review the validation data of the NMSS and its cross-validity with other scales, and describe the key evidence derived from use of the NMSS in clinical studies. To date, over 100 clinical studies and trials have made use of it as an outcome measure, showing consistent and strong correlations between NMSS burden and health-related quality of life measures. Moreover, the scale has shown to be capable of detecting longitudinal changes in non-motor symptoms, where studies have shown differential changes over time of several of the NMSS domains. The scale has become a key outcome in several randomized clinical trials. Highlighting the prevalence and importance of non-motor symptoms to quality of life in patients with PD, the development of NMSS has also been useful in signposting clinical and biomarker based research addressing non-motor symptoms in PD
Towards a multi-arm multi-stage platform trial of disease modifying approaches in Parkinson's disease
No full textAn increase in the efficiency of clinical trial conduct has been successfully demonstrated in the oncology field, by the use of multi-arm, multi-stage trials allowing the evaluation of multiple therapeutic candidates simultaneously, and seamless recruitment to phase 3 for those candidates passing an interim signal of efficacy. Replicating this complex innovative trial design in diseases such as Parkinson's disease is appealing, but in addition to the challenges associated with any trial assessing a single potentially disease modifying intervention in Parkinson's disease, a multi-arm platform trial must also specifically consider the heterogeneous nature of the disease, alongside the desire to potentially test multiple treatments with different mechanisms of action. In a multi-arm trial, there is a need to appropriately stratify treatment arms to ensure each are comparable with a shared placebo/standard of care arm; however, in Parkinson's disease there may be a preference to enrich an arm with a subgroup of patients that may be most likely to respond to a specific treatment approach. The solution to this conundrum lies in having clearly defined criteria for inclusion in each treatment arm as well as an analysis plan that takes account of predefined subgroups of interest, alongside evaluating the impact of each treatment on the broader population of Parkinson's disease patients. Beyond this, there must be robust processes of treatment selection, and consensus derived measures to confirm target engagement and interim assessments of efficacy, as well as consideration of the infrastructure needed to support recruitment, and the long-term funding and sustainability of the platform. This has to incorporate the diverse priorities of clinicians, triallists, regulatory authorities and above all the views of people with Parkinson's disease.</p
Hypothalamic pathology in Huntington disease
No full textItem does not contain fulltextHuntington's disease (HD), an autosomal dominant hereditary disorder associated with the accumulation of mutant huntingtin, is classically associated with cognitive decline and motor symptoms, notably chorea. However, growing evidence suggests that nonmotor symptoms are equally prevalent and debilitating. Some of these symptoms may be linked to hypothalamic pathology, demonstrated by findings in HD animal models and HD patients showing specific changes in hypothalamic neuropeptidergic populations and their associated functions. At least some of these alterations are likely due to local mutant huntingtin expression and toxicity, while others are likely caused by disturbed hypothalamic circuitry. Common problems include circadian rhythm disorders, including desynchronization of daily hormone excretion patterns, which could be targeted by novel therapeutic interventions, such as timed circadian interventions with light therapy or melatonin. However, translation of these findings from bench-to-bedside is hampered by differences in murine HD models and HD patients, including mutant huntingtin trinucleotide repeat length, which is highly heterogeneous across the various models. In this chapter, we summarize the current knowledge regarding hypothalamic alterations in HD patients and animal models, and the potential for these findings to be translated into clinical practice and management
Parkinson's disease and Covid-19: The effect and use of telemedicine
No full textAs a result of the Coronavirus Disease 2019 (Covid-19) pandemic the use of telemedicine and remote assessments for patients has increased exponentially, enabling healthcare professionals to reduce the need for in-person clinical visits and, consequently, reduce the exposure to the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). This development has been aided by increased guidance on digital health technologies and cybersecurity measures, as well as reimbursement options within healthcare systems. Having been able to continue to connect with people with Parkinson's Disease (PwP, PD) has been crucial, since many saw their symptoms worsen over the pandemic. Inspite of the success of telemedicine, sometimes even enabling delivery of treatment and research, further validation and a unified framework are necessary to measure the true benefit to both clinical outcomes and health economics. Moreover, the use of telemedicine seems to have been biased towards people from a white background, those with higher education, and reliable internet connections. As such, efforts should be pursued by being inclusive of all PwP, regardless of geographical area and ethnic background. In this chapter, we describe the effect he Covid-19 pandemic has had on the use of telemedicine for care and research in people with PD, the limiting factors for further rollout, and how telemedicine might develop further
Personalised Advanced Therapies in Parkinson’s Disease : The Role of Non-Motor Symptoms Profile
Get PDFDevice-aided therapies, including levodopa-carbidopa intestinal gel infusion, apomorphine subcutaneous infusion, and deep brain stimulation, are available in many countries for the management of the advanced stage of Parkinson’s disease (PD). Currently, selection of device-aided therapies is mainly focused on patients’ motor profile while non-motor symptoms play a role limited to being regarded as possible exclusion criteria in the decision-making process for the delivery and sustenance of a successful treatment. Differential beneficial effects on specific non-motor symptoms of the currently available device-aided therapies for PD are emerging and these could hold relevant clinical implications. In this viewpoint, we suggest that specific non-motor symptoms could be used as an additional anchor to motor symptoms and not merely as exclusion criteria to deliver bespoke and patient-specific personalised therapy for advanced PD
Cross-sectional analysis of the Parkinson's disease Non-motor International Longitudinal Study baseline non-motor characteristics, geographical distribution and impact on quality of life
Get PDFGrowing evidence suggests that non-motor symptoms (NMS) in Parkinson’s disease (PD) have differential progression patterns that have a different natural history from motor progression and may be geographically influenced. We conducted a cross-sectional analysis of 1607 PD patients of whom 1327 were from Europe, 208 from the Americas, and 72 from Asia. The primary objective was to assess baseline non-motor burden, defined by Non-Motor Symptoms Scale (NMSS) total scores. Other aims included identifying the factors predicting quality of life, differences in non-motor burden between drug-naïve and non-drug-naïve treated patients, and non-motor phenotypes across different geographical locations. Mean age was 65.9 ± 10.8 years, mean disease duration 6.3 ± 5.6 years, median Hoehn and Yahr stage was 2 (2–3), and 64.2% were male. In this cohort, mean NMSS scores were 46.7 ± 37.2. Differences in non-motor burden and patterns differed significantly between drug-naïve participants, those with a disease duration of less than five years, and those with a duration of five years or over (p ≤ 0.018). Significant differences were observed in geographical distribution (NMSS Europe: 46.4 ± 36.3; Americas: 55.3 ± 42.8; Asia: 26.6 ± 25.1; p < 0.001), with differences in sleep/fatigue, urinary, sexual, and miscellaneous domains (p ≤ 0.020). The best predictor of quality of life was the mood/apathy domain (β = 0.308, p < 0.001). This global study reveals that while non-motor symptoms are globally present with severe NMS burden impacting quality of life in PD, there appear to be differences depending on disease duration and geographical distribution.Fil: Van Wamelen, Daniel J.. King's College Hospital; Reino Unido. King's College London; Reino Unido. Radboud Universiteit Nijmegen. Donders Instituto Brain Cognition and Behavior. SNN Machine Learning Group; Países BajosFil: Sauerbier, Anna. King's College London; Reino Unido. University of Cologne; AlemaniaFil: Leta, Valentina. King's College London; Reino Unido. King's College Hospital; Reino UnidoFil: Rodriguez Blazquez, Carmen. Instituto de Salud Carlos III; EspañaFil: Falup Pecurariu, Cristian. Transilvania University; RumaniaFil: Rodriguez Violante, Mayela. Instituto Nacional de Neurología y Neurocirugía; MéxicoFil: Rizos, Alexandra. King's College London; Reino Unido. King's College Hospital; Reino UnidoFil: Tsuboi, Y.. Fukuoka University; JapónFil: Metta, Vinod. King's College Hospital; Reino UnidoFil: Bhidayasiri, Roongroj. Chulalongkorn University Hospital; TailandiaFil: Bhattacharya, Kalyan. Formerly RG Kar Medical College and Institute of Neuroscience; IndiaFil: Borgohain, Rupam. Nizam’s Institute of Medical Sciences; IndiaFil: Prashanth, L.K.. Vikram Hospitals; India. Parkinson's Disease And Movement Disorders Clinic; IndiaFil: Rosales, Raymond. University Of Santo Tomas Hospital; FilipinasFil: Lewis, Simon. The University Of Sydney; AustraliaFil: Fung, Victor. Westmead Hospital; Australia. The University Of Sydney; AustraliaFil: Behari, Madhuri. All India Institute Of Medical Sciences; IndiaFil: Goyal, Vinay. All India Institute Of Medical Sciences; IndiaFil: Kishore, Asha. Sree Chitra Tirunal Institute For Medical Sciences And Technology; IndiaFil: Perez Lloret, Santiago. Universidad Abierta Interamericana. Secretaría de Investigación. Centro de Altos Estudios En Ciencias Humanas y de la Salud - Sede Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Martinez Martin, Pablo. Instituto de Salud Carlos III; EspañaFil: Chaudhuri, K. Ray. King's College Hospital; Reino Unido. King's College London; Reino Unid
Using prodromal non-motor symptoms to predict Parkinson's disease onset and motor phenotype
No full textBACKGROUND: Non-motor symptoms are highly prevalent in prodromal Parkinson's disease (PD); however, their impact on PD trajectory remains largely unexplored. We aimed to assess whether prevalent prodromal non-motor symptoms could predict future motor phenotype and time-to-PD diagnosis.METHODS: We studied the prodromal cohort of the ongoing Parkinson's Progression Markers Initiative (n=958), which prospectively assesses individuals with prodromal PD features (genetic: n=361, hyposmia: n=298, rapid eye movement behaviour disorder: n=136, combination: n=163) with up to 10 years of follow-up. The presence of prevalent prodromal symptoms was defined by evidence-based cut-off scores. In unmedicated or OFF-state PD converters (total n=52), binary logistic regression models established whether these predicted non-tremor-dominant (n=35) and tremor-dominant (n=17) motor phenotypes at diagnosis. Cox proportional hazards models determined whether identified prodromal symptoms predicted a shorter time-to-phenoconversion across all PD converters (n=59) and non-converters (n=343). Both models adjusted for age and sex.RESULTS: Prodromal anxiety and hyposmia were each associated with an increased risk of subsequent non-tremor-dominant PD, compared with other motor phenotypes (adjusted OR=4.45, 95% CI 1.34 to 15.27 and adjusted OR=3.90, 95% CI 1.01 to 15.16, respectively). Concurrent prodromal anxiety and hyposmia predicted an increased risk of PD phenoconversion over time (HR=4.93, 95% CI 2.71 to 8.98).CONCLUSION: In this exploratory analysis, individuals with prodromal hyposmia and anxiety phenoconverted to PD sooner and more often had a non-tremor-dominant phenotype, potentially reflecting more widespread pathology or specific pathophysiology underlying these symptoms. This may improve phenotyping prodromal PD and stratifying poorer prognostic trajectories for earlier and more personalised management.</p
Technologies for identification of prodromal movement disorder phases and at-risk individuals
No full textTimely identification of individuals at risk for developing neurodegenerative conditions is an unmet need which would enable us to initiate treatment at an earlier stage and potentially slowing down disease progression or reducing the risk of phenoconversion. Currently, the identification of prodromal stages remains challenging due to the lack of uniform criteria for the prodromal stage of neurodegenerative conditions and suboptimal symptom identification due to limitations in diary and scale-based assessments. Here, remote and wearable technology might offer a new way forward. In this chapter we summarize the currently available evidence for technology based identification of both motor and nonmotor features in neurodegenerative conditions, in particular Parkinson’s (PD) and Huntington’s disease (HD) and spinocerebellar ataxias (SCA). Although limited in absolute number, most studies have focused on prodromal and premanifest motor features, showing e.g., reduced arm swing and changes in gait parameters in prodromal individuals at risk for PD, as well as gait and balance abnormalities in premanifest HD and SCA gene mutation carriers. Nonmotor features, on the other hand, remain understudied with only limited evidence for the identification of cognitive changes in premanifest HD gene mutation carriers. Further efforts, especially in the field of nonmotor features, are needed before such technology could be used in clinical practice to identify individuals at risk for or in a premanifest stage of neurodegenerative conditions.</p
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