RESUMEN
The rising prevalence of Parkinson's disease (PD) globally presents a significant public health challenge for national healthcare systems, particularly in low-to-middle income countries, such as Thailand, which may have insufficient resources to meet these escalating healthcare needs. There are also many undiagnosed cases of early-stage PD, a period when therapeutic interventions would have the most value and least cost. The traditional "passive" approach, whereby clinicians wait for patients with symptomatic PD to seek treatment, is inadequate. Proactive, early identification of PD will allow timely therapeutic interventions, and digital health technologies can be scaled up in the identification and early diagnosis of cases. The Parkinson's disease risk survey (TCTR20231025005) aims to evaluate a digital population screening platform to identify undiagnosed PD cases in the Thai population. Recognizing the long prodromal phase of PD, the target demographic for screening is people aged ≥ 40 years, approximately 20 years before the usual emergence of motor symptoms. Thailand has a highly rated healthcare system with an established universal healthcare program for citizens, making it ideal for deploying a national screening program using digital technology. Designed by a multidisciplinary group of PD experts, the digital platform comprises a 20-item questionnaire about PD symptoms along with objective tests of eight digital markers: voice vowel, voice sentences, resting and postural tremor, alternate finger tapping, a "pinch-to-size" test, gait and balance, with performance recorded using a mobile application and smartphone's sensors. Machine learning tools use the collected data to identify subjects at risk of developing, or with early signs of, PD. This article describes the selection and validation of questionnaire items and digital markers, with results showing the chosen parameters and data analysis methods to be robust, reliable, and reproducible. This digital platform could serve as a model for similar screening strategies for other non-communicable diseases in Thailand.
RESUMEN
BACKGROUND: Cognitive impairment is common in Parkinson's disease (PD) and has a substantial impact on quality of life. Despite numerous trials targeting various PD features, we still lack effective treatments for cognition beyond cholinesterase inhibitors. OBJECTIVE: To identify the gaps in recent clinical trials with cognitive outcomes in PD and consider areas for improvement. METHODS: We examined recent clinical trials with cognitive outcomes in PD registered on ClinicalTrials.gov, excluding trials without cognitive outcomes, non-interventional studies, and in atypical Parkinsonian disorders. Included trials were categorized by treatment approach (investigational medicinal product, behavioral, physical activity, device-based). Details of trial design and outcomes were collected. RESULTS: 178 trials at different stages of trial completion were considered. 46 trials were completed, 25 had available results. Mean follow-up duration was 29.9 weeks. Most common cognitive measure was Montreal Cognitive Assessment. Most were performed in North America or Europe. Majority of the participants identified as non-Hispanic and White. Only eight trials showed improvement in cognition, none showed improvement beyond four months. These included trials of international medicinal products, cognitive and physical interventions and devices. GRADE certainty levels ranged from Moderate to Very Low. Only mevidalen had a Moderate certainty for potential clinical effectiveness. CONCLUSIONS: Amongst a large number of trials for cognition in PD, only a small proportion were completed. Few showed significant improvement, with no proven long-lasting effects. Trial design, lack of enrichment for at-risk groups, short follow-up duration, insensitive outcome measures likely contribute to lack of detectable benefit and should be considered in future trials.
