Skip to main content

Early detection of relapse in panic disorder

Buy Article:

$51.00 plus tax (Refund Policy)

Mavissakalian MR, Guo S. Early detection of relapse in panic disorder.

Acta Psychiatr Scand 2004: 1–7. © Blackwell Munksgaard 2004. Objective: 

To explore predictive models of relapsing based on change in symptoms at a time when panic disorder patients are still in remission following discontinuation of antidepressants. Method: 

Forty-seven subjects, who were randomized to double-blind placebo and who had valid data at four time points: pretreatment, randomization to placebo substitution, an assessment on placebo prior to the last assessment or relapse and their last assessment (relapsers n = 15, non-relapsers n = 32) were studied using descriptive, growth curve analysis and logistic regression methodologies. Results: 

Measures of generalized anxiety, fearfulness and disability at work and at home were better predictors of relapse than measures of panic and anxiety sensitivity. Logistic regression models using any one of these four general variables and its linear change correctly predicted relapse for 78.7–84.4% of the study subjects. Conclusion: 

It is possible to gauge, with a fair degree of accuracy, the probability of relapsing in panic disorder patients who have discontinued serotonergic antidepressants 2 months prior to the return of panic.
No References
No Citations
No Supplementary Data
No Data/Media
No Metrics

Keywords: antidepressants; early detection/prediction; panic disorder; relapse prevention

Document Type: Research Article

Affiliations: 1: Department of Psychiatry, Case Western Reserve University and The Louis Stokes Cleveland VAMC, Cleveland, OH 2: School of Social Work, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Publication date: 2004-11-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more