Use the labels in the right column to find what you want. Or you can go thru them one by one, there are only 13987 posts. Searching is done in the search box in upper left corner. I blog on anything to do with stroke.DO NOT DO ANYTHING SUGGESTED HERE AS I AM NOT MEDICALLY TRAINED, YOUR DOCTOR IS, LISTEN TO THEM. BUT I BET THEY DON'T KNOW HOW TO GET YOU 100% RECOVERED. I DON'T EITHER, BUT HAVE PLENTY OF QUESTIONS FOR YOUR DOCTOR TO ANSWER.
Deans' stroke musings
Changing stroke rehab and research worldwide now.Time is Brain!Just think of all thetrillions and trillions of neuronsthateach daybecause there areeffective hyperacute therapies besides tPA(only 12% effective). I have 493 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:
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's quite disgusting that this information is not available from every stroke association and doctors group. My back ground story is here:http://oc1dean.blogspot.com/2010/11/my-background-story_8.html
Wednesday, June 14, 2017
Predicting Disability after Ischemic Stroke Based on Comorbidity Index and Stroke Severity—From the Virtual International Stroke Trials Archive-Acute Collaboration
Stroke Unit, Monash Health and Stroke and Aging Research Group, Monash University, Melbourne, VIC, Australia
Background and aim: The availability and access
of hospital administrative data [coding for Charlson comorbidity index
(CCI)] in large data form has resulted in a surge of interest in using
this information to predict mortality from stroke.(Not stopping mortality from stroke!) The aims of this
study were to determine the minimum clinical data set to be included in
models for predicting disability after ischemic stroke adjusting for CCI
and clinical variables and to evaluate the impact of CCI on prediction
Method: We leverage anonymized clinical trial
data in the Virtual International Stroke Trials Archive. This repository
contains prospective data on stroke severity and outcome. The inclusion
criteria were patients with available stroke severity score such as
National Institutes of Health Stroke Scale (NIHSS), imaging data, and
outcome disability score such as 90-day Rankin Scale. We calculate CCI
based on comorbidity data in this data set. For logistic regression, we
used these calibration statistics: Nagelkerke generalised R2
and Brier score; and for discrimination we used: area under the
receiver operating characteristics curve (AUC) and integrated
discrimination improvement (IDI). The IDI was used to evaluate
improvement in disability prediction above baseline model containing
age, sex, and CCI.
Results: The clinical data among 5,206 patients
(55% males) were as follows: mean age 69 ± 13 years, CCI 4.2 ± 0.8, and
median NIHSS of 12 (IQR 8, 17) on admission and 9 (IQR 5, 15) at 24 h.
In Model 2, adding admission NIHSS to the baseline model improved AUC
from 0.67 (95% CI 0.65–0.68) to 0.79 (95% CI 0.78–0.81). In Model 3,
adding 24-h NIHSS to the baseline model resulted in substantial
improvement in AUC to 0.90 (95% CI 0.89–0.91) and increased IDI by 0.23
(95% CI 0.22–0.24). Adding the variable recombinant tissue plasminogen
activator did not result in a further change in AUC or IDI to this
regression model. In Model 3, the variable NIHSS at 24 h explains 87.3%
of the variance of Model 3, follow by age (8.5%), comorbidity (3.7%),
and male sex (0.5%).
Conclusion: Our results suggest that prediction of
disability after ischemic stroke should at least include 24-h NIHSS and
age. The variable CCI is less important for prediction of disability in
this data set.