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.

Thursday, September 19, 2024

A Predictive Model for Functionality Improvement after Stroke Rehabilitation

 Predicting failure to recover is ABSOLUTELY USELESS! Survivors would like you to deliver 100% recovery protocols! When the fuck will you do what survivors want?

A Predictive Model for Functionality Improvement after Stroke Rehabilitation

, , , ,
https://doi.org/10.1016/j.jnrt.2024.100157
Get rights and content
Under a Creative Commons license
open access

Abstract

Objective

This study develops a simple predictive model for identifying stroke patients who have a better chance of showing improved activities of daily living (ADL) outcomes following a stroke.

Methods

The cohort of 489 stroke patients was divided into testing and training groups. Multivariate logistic regression analysis was conducted for each model. Four models were compared using the C statistic (AUC), Akaike’s information criterion (AIC), and other metrics. The best model was assessed using a nomogram.

Results

Univariate analysis revealed that several variables measured significantly higher at discharge than at admission, including manual muscle testing, standing, and so on. Multivariate logistic regression analysis revealed that activities-specific balance confidence, Brunnstrom recovery stage for lower extremities, standing, the mini-balance evaluation systems test, and the Hamilton anxiety scale were independent predictors of ADL. Model 1 was found to be more accurate for the prediction of ADL (AUC: training, 0.916 [0.889−0.943] and test, 0.887 [0.806−0.968]; AIC: training, 257.42 and test, 76.79) than model 2 (AUC: training, 0.850 [0.894−0.806] and test, 0.819 [0.715−0.923]; AIC: training, 314.44 and test, 83.78), model 3 (AUC: training, 0.862 [0.901−0.823] and test, 0.830 [0.731−0.929]; AIC: training, 307.76 and test, 86.55), and model 4 (AUC: training, 0.862 [0.901−0.823] and test, 0.833 [0.733−0.932]; AIC: training, 305.8 and test, 86.28).

Conclusion

A multivariate model can be used to predict functionality improvement, as measured by ADL, following hospitalization with a stroke.

Posted by at
Labels: , , , ,

No comments:

Post a Comment

Subscribe to: Post Comments (Atom)