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17 - Preliminary algorithms for treatment-resistant bipolar depression

from Part IV - Special patient populations

Published online by Cambridge University Press:  25 March 2010

Jay D. Amsterdam
Affiliation:
University of Pennsylvania
Mady Hornig
Affiliation:
University of California, Irvine
Andrew A. Nierenberg
Affiliation:
Harvard Medical School
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Summary

Introduction

In this chapter a series of treatment algorithms are presented which may be used as a general guide in sequencing treatment so that patients who fail to respond to first-line conventional treatment may still very likely achieve a substantial amelioration, if not complete remission, of depressive syndromes or recurrences. Caution should be noted that most of the conclusions and recommendations presented are highly provisional, often based on databases from uncontrolled studies, and as such reflect the authors’ clinical experiences and biases. However, as there are relatively few randomized, controlled trials that address the necessary treatment decisions often required for the treatment-resistant bipolar patient, the clinician as well as the clinical research investigator is often faced with making the best possible judgment based on direct inferences from other illnesses and controlled case series. Despite these major caveats, depression in most treatment-resistant bipolar patients can usually be adequately treated. The optimal sequencing of these treatments in the general bipolar patient population, and how to most rapidly achieve this optimal sequencing in the individual patient with defined clinical or biochemical characteristics, is less clear.

A series of principles are emphasized in attempting to arrive at optimal pharmacotherapeutics.

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Publisher: Cambridge University Press
Print publication year: 2001

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