Mathematical model for predicting treatment outcome in patients with destructive pulmonary multiresistant tuberculosis

2020 ◽  
Vol 0 (4) ◽  
pp. 24-32
Author(s):  
O.S. Shevchenko ◽  
L.D. Todoriko ◽  
I.A. Ovcharenko ◽  
Y.B. Radzishevskа ◽  
S.S. Ovcharenko
2009 ◽  
Vol 17 (5) ◽  
pp. 671-677 ◽  
Author(s):  
Benjamin A. Lipsky ◽  
Adam B. Polis ◽  
Keith C. Lantz ◽  
Josephine M. Norquist ◽  
Murray A. Abramson

2012 ◽  
Vol 13 (2) ◽  
pp. 233-240 ◽  
Author(s):  
Rudolf Uher ◽  
Katherine E Tansey ◽  
Karim Malki ◽  
Roy H Perlis

2007 ◽  
Vol 13 (1) ◽  
pp. 5 ◽  
Author(s):  
R Emsley ◽  
P Oosthuizen ◽  
D Niehaus ◽  
L Koen ◽  
B Chiliza

<p>Multiple factors play a role in determining the outcome of schizophrenia. However, the role of these factors is poorly understood, and research findings so far have been inconclusive and sometimes contradictory. Various demographic and baseline clinical factors have been reported to be associated with treatment outcome. Also, early symptom reduction after initiation of antipsychotic therapy is closely related to later treatment response. However, associations as such do not necessarily imply predictive value, and none of these factors can be regarded as clinically useful in predicting treatment outcome. This article discusses selected aspects of treatment outcome and its prediction in schizophrenia, focusing particularly on early treatment response, ethnicity, neurological soft signs, and the predictive value of a discriminant functional analysis model utilising a combination of putative predictors. Such a model holds promise, and it is to be hoped that future refinements will lead to a clinically useful model for predicting outcome.</p>


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