Deans' stroke musings: Multistate Markov model for functional recovery in stroke: probability of state transition and prognosis prediction

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, September 27, 2025

Multistate Markov model for functional recovery in stroke: probability of state transition and prognosis prediction

You're that blitheringly stupid you don't know that predictions NEVER GET SURVIVORS RECOVERED?

And your mentors and senior researchers are no better?

Multistate Markov model for functional recovery in stroke: probability of state transition and prognosis prediction

Scientific Reports volume 15, Article number: 33003 (2025) Cite this article

Abstract

Stroke rehabilitation involves complex transitions between different functional states. This study developed and validated a five-state Markov model to quantify state transition probabilities and predict functional outcomes in stroke patients, providing quantitative support for clinical decision-making. We analyzed 2000 functional status observations from 1000 stroke patients (baseline and follow-up) at Tianjin Medical University General Hospital. Using modified Rankin Scale scores, patients were classified into five functional states (mild/moderate/severe disability, recovery, death). A continuous-time Markov model estimated transition intensities and probabilities, with validation through observed-versus-predicted comparisons and comprehensive sensitivity analyses. The Markov model revealed dynamic transitions among functional states: the monthly transition intensity from severe to moderate disability was the highest (3.13%), while the annual cumulative probability of full recovery was highest among patients with moderate disability (15.99%). At the 12-month follow-up, 65.4%, 59.6%, and 49.0% of patients with mild, moderate, and severe disability, respectively, remained in their original state, while 14.3%, 16.0%, and 14.5% achieved full recovery. One-way and probabilistic sensitivity analyses indicated that the model was robust to parameter variations, with narrow 95% confidence intervals. The multi-stata Markov model provided insights into the dynamic process of functional recovery after stroke in a specialized setting,offering a methodological framework that may support clinical prognosis assessment with appropriate validation. Patients with moderate disability exhibited the highest recovery potential, while those with severe disability demonstrated the fastest improvement rate, suggesting that individualized rehabilitation strategies may be considered tailored to different functional states.