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, August 29, 2013

In-Hospital Risk Prediction for Post-stroke Depression

But why do we care about predicting post-stroke depression? Do we not have consensus that all survivors should get anti-depression drugs because they lead to a better recovery?
Antidepressants may help people recover from stroke even if they are not depressed
"Taken together, the available data make a strong case for the prophylactic use and effectiveness of antidepressants post stroke," the researchers said.

Does no one think at all? Is everyone in the stroke world stupid?
http://stroke.ahajournals.org/content/44/9/2441.abstract.html?etoc


Development and Validation of the Post-stroke Depression Prediction Scale

  1. Marieke J. Schuurmans, RN, PhD
+ Author Affiliations
  1. From the Department of Rehabilitation, Nursing Science and Sports, Rudolf Magnus Institute of Neuroscience, University Medical Centre Utrecht, Utrecht, The Netherlands (J.M.d.M.-v.G., T.B.H., E.L., M.J.S.); Faculty of Healthcare, University of Applied Sciences Utrecht, Utrecht, The Netherlands (R.G.A.E.); and Julius Center for Health Sciences and Primary Care, Utrecht University, Utrecht, The Netherlands (D.E.G.).
  1. Correspondence to Janneke M. de Man-van Ginkel, RN, PhD, Division Neurosciences, UMC Utrecht, W01.121, Heidelberglaan 100, 3584 XC Utrecht, The Netherlands. E-mail J.M.deMan@umcutrecht.nl

Abstract

Background and Purpose—The timely detection of post-stroke depression is complicated by a decreasing length of hospital stay. Therefore, the Post-stroke Depression Prediction Scale was developed and validated. The Post-stroke Depression Prediction Scale is a clinical prediction model for the early identification of stroke patients at increased risk for post-stroke depression.
Methods—The study included 410 consecutive stroke patients who were able to communicate adequately. Predictors were collected within the first week after stroke. Between 6 to 8 weeks after stroke, major depressive disorder was diagnosed using the Composite International Diagnostic Interview. Multivariable logistic regression models were fitted. A bootstrap-backward selection process resulted in a reduced model. Performance of the model was expressed by discrimination, calibration, and accuracy.
Results—The model included a medical history of depression or other psychiatric disorders, hypertension, angina pectoris, and the Barthel Index item dressing. The model had acceptable discrimination, based on an area under the receiver operating characteristic curve of 0.78 (0.72–0.85), and calibration (P value of the U-statistic, 0.96). Transforming the model to an easy-to-use risk-assessment table, the lowest risk category (sum score, <−10) showed a 2% risk of depression, which increased to 82% in the highest category (sum score, >21).
Conclusions—The clinical prediction model enables clinicians to estimate the degree of the depression risk for an individual patient within the first week after stroke.
Key Words:

1 comment:

  1. Yes, the answer is yes. Everyone in the stroke world is stupid.

    ReplyDelete