Deans' stroke musings: Wearable movement-tracking data identify Parkinson’s disease years before clinical diagnosis

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.

Saturday, July 15, 2023

Wearable movement-tracking data identify Parkinson’s disease years before clinical diagnosis

With your risk of Parkinsons post stroke it is your doctor's responsibility to detect this early so interventions can be applied. Your doctor has had 6+ years to come up with Parkinson's prevention protocols. Were the competent or incompetent in that requirement?

Parkinson’s Disease May Have Link to Stroke March 2017

The latest here:

Wearable movement-tracking data identify Parkinson’s disease years before clinical diagnosis

Nature Medicine (2023)Cite this article

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Abstract

Parkinson’s disease is a progressive neurodegenerative movement disorder with a long latent phase and currently no disease-modifying treatments. Reliable predictive biomarkers that could transform efforts to develop neuroprotective treatments remain to be identified. Using UK Biobank, we investigated the predictive value of accelerometry in identifying prodromal Parkinson’s disease in the general population and compared this digital biomarker with models based on genetics, lifestyle, blood biochemistry or prodromal symptoms data. Machine learning models trained using accelerometry data achieved better test performance in distinguishing both clinically diagnosed Parkinson’s disease (n = 153) (area under precision recall curve (AUPRC) 0.14 ± 0.04) and prodromal Parkinson’s disease (n = 113) up to 7 years pre-diagnosis (AUPRC 0.07 ± 0.03) from the general population (n = 33,009) compared with all other modalities tested (genetics: AUPRC = 0.01 ± 0.00, P = 2.2 × 10⁻³; lifestyle: AUPRC = 0.03 ± 0.04, P = 2.5 × 10⁻³; blood biochemistry: AUPRC = 0.01 ± 0.00, P = 4.1 × 10⁻³; prodromal signs: AUPRC = 0.01 ± 0.00, P = 3.6 × 10⁻³). Accelerometry is a potentially important, low-cost screening tool for determining people at risk of developing Parkinson’s disease and identifying participants for clinical trials of neuroprotective treatments.