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, March 19, 2015

Measure of Functional Independence Dominates Discharge Outcome Prediction After Inpatient Rehabilitation for Stroke

Once again using totally subjective measurements to predict outcomes rather than objective measures like 3d MRI and PET scans showing the dead and damaged areas. What needs to change to convince them to drop the stupid subjective measures and join the scientific world with objective measures? This a a job for that great stroke association if they accept the job.
http://stroke.ahajournals.org/content/early/2015/02/24/STROKEAHA.114.007392.abstract
  1. Carl V. Granger, MD
+ Author Affiliations
  1. From the Department of Physical Medicine and Rehabilitation (A.W.B., B.A.S.) and Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN (T.M.T.); Uniform Data System for Medical Rehabilitation, Buffalo, NY (P.M.N., C.V.G.); Department of Health Care Studies, Daemen College, Amherst, NY (P.M.N.); and the Department of Neurology, University at Buffalo, Buffalo, NY (C.V.G.).
  1. Correspondence to Allen W. Brown, MD, Department of Physical Medicine and Rehabilitation, 200 First St SW, Mayo Clinic, Rochester, MN 55905. E-mail brown.allen@mayo.edu

Abstract

Background and Purpose—Identifying clinical data acquired at inpatient rehabilitation admission for stroke that accurately predict key outcomes at discharge could inform the development of customized plans of care(maybe call these stroke protocols?) to achieve favorable outcomes. The purpose of this analysis was to use a large comprehensive national data set to consider a wide range of clinical elements known at admission to identify those that predict key outcomes at rehabilitation discharge.
Methods—Sample data were obtained from the Uniform Data System for Medical Rehabilitation data set with the diagnosis of stroke for the years 2005 through 2007. This data set includes demographic, administrative, and medical variables collected at admission and discharge and uses the FIM (functional independence measure) instrument to assess functional independence. Primary outcomes of interest were functional independence measure gain, length of stay, and discharge to home.
Results—The sample included 148 367 people (75% white; mean age, 70.6±13.1 years; 97% with ischemic stroke) admitted to inpatient rehabilitation a mean of 8.2±12 days after symptom onset. The total functional independence measure score, the functional independence measure motor subscore, and the case-mix group were equally the strongest predictors for any of the primary outcomes. The most clinically relevant 3-variable model used the functional independence measure motor subscore, age, and walking distance at admission (r2=0.107). No important additional effect for any other variable was detected when added to this model.
Conclusions—This analysis shows that a measure of functional independence in motor performance and age at rehabilitation hospital admission for stroke are predominant predictors of outcome at discharge in a uniquely large US national data set.

1 comment:

  1. An r squared of 0.107 means that only 10.7% of the variance in the outcome was accounted for by the predictors. At my initial eval I had a 2 out of 7 on the FIM walking task because I needed the maximum assistance of two people. Since I have good community ambulation now I am glad initial test results are not necessarily destiny.

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