Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Wednesday, December 10, 2025

Turning slowly could signal Parkinson’s long before diagnosis

 Does your doctor have enough competence to distinguish turning slowly because of stroke vs. your risk of Parkinsons post stroke? Your doctor better figure it out fast because YOU NEED PARKINSONS PREVENTION PROTOCOLS! And you don't want a wrong diagnosis.

Turning slowly could signal Parkinson’s long before diagnosis

A 10-year study of older adults found that slower turning speed, measured by wearable sensors, could predict Parkinson’s disease 8.8 years before clinical diagnosis, with deviations in peak angular velocity detectable well before symptoms appear.

The findings, published in Annals of Neurology, suggest that wearable technology could serve as an early, noninvasive tool to identify and monitor individuals at risk for Parkinson’s, potentially enabling earlier interventions.

“This research opens a vital window for early intervention,” said Brook Galna, PhD, Murdoch University’s School of Allied Health, Perth, Australia. “By detecting changes in turning speed through wearable sensors, in combination with other early signs of Parkinson’s, we can identify individuals at risk long before symptoms become clinically apparent. Earlier detection of people at risk of developing Parkinson’s will speed the discovery and testing of neuroprotective treatments designed to slow disease progression and keep people living independently for longer.”

In the TREND study, 1,051 older adults were followed for over 10 years. Participants used wearable sensors placed on the lower back to measure turning performance during 1-minute walks down a 20-metre hallway. Peak angular velocity while turning was tracked across 5 visits, and the development of clinically diagnosed Parkinson’s disease was recorded. Longitudinal models assessed changes in turning over time, and Cox regression analysed whether baseline turning measures predicted time to Parkinson’s onset, controlling for age and sex.

During follow-up, 23 participants were diagnosed with Parkinson’s disease, on average 5.3 years after baseline. Slower turning speed at baseline was associated with a higher risk of developing Parkinson’s, with detectable deviations from controls emerging approximately 8.8 years before diagnosis. A machine learning model combining age, sex, and turning speed identified 60% of prediagnostic Parkinson’s cases and 80.5% of non-cases.

“This is, to our knowledge, the first study to longitudinally assess turning in older adults at risk of Parkinson’s disease, with multiple follow-ups,” the authors wrote. “Our results suggest that turning measures may aid in predicting the clinical Parkinson’s disease diagnosis and enhance a panel of prediagnostic markers for identifying high-risk individuals. Using a single wearable inertial measurement unit and validated algorithms, the approach used in this study is practical for large-scale screening for Parkinson’s disease.”

Reference: https://onlinelibrary.wiley.com/doi/10.1002/ana.78034

SOURCE: Murdoch University

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