Deans' stroke musings: A decision tree algorithm to identify predictors of post-stroke complex regional pain syndrome

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.

Tuesday, April 30, 2024

A decision tree algorithm to identify predictors of post-stroke complex regional pain syndrome

Change one word in the title and it won't be ABSOLUTELY FUCKING USELESS! Predictors to Preventors! But until we get survivors in charge directing research stroke will NEVER BE SOLVED!

A decision tree algorithm to identify predictors of post-stroke complex regional pain syndrome

Scientific Reports volume 14, Article number: 9893 (2024) Cite this article

Metrics details

Abstract

This prospective cohort study aimed to identify the risk factors for post-stroke complex regional pain syndrome (CRPS) using a decision tree algorithm while comprehensively assessing upper limb and lower limb disuse and physical inactivity. Upper limb disuse (Fugl-Meyer assessment of upper extremity [FMA-UE], Action Research Arm Test, Motor Activity Log), lower limb disuse (Fugl-Meyer Assessment of lower extremity [FMA-LE]), balance performance (Berg balance scale), and physical inactivity time (International Physical Activity Questionnaire-Short Form [IPAQ-SF]) of 195 stroke patients who visited the Kishiwada Rehabilitation Hospital were assessed at admission. The incidence of post-stroke CRPS was 15.4% in all stroke patients 3 months after admission. The IPAQ, FMA-UE, and FMA-LE were extracted as risk factors for post-stroke CRPS. According to the decision tree algorithm, the incidence of post-stroke CRPS was 1.5% in patients with a short physical inactivity time (IPAQ-SF < 635), while it increased to 84.6% in patients with a long inactivity time (IPAQ-SF ≥ 635) and severe disuse of upper and lower limbs (FMA-UE score < 19.5; FMA-LE score < 16.5). The incidence of post-stroke CRPS may increase with lower-limb disuse and physical inactivity, in addition to upper-limb disuse. Increasing physical activity and addressing lower- and upper-limb motor paralysis may reduce post-stroke CRPS.