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Validating screening tools for depression in epilepsy.

Kirsten M Fiest1, Scott B Patten, Samuel Wiebe

  • 1Department of Community Health Sciences, Institute for Public Health, University of Calgary, Calgary, Alberta, Canada; Department of Psychiatry, Mathison Centre for Mental Health Research & Education, University of Calgary, Calgary, Alberta, Canada; Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.

Epilepsia
|August 30, 2014
PubMed
Summary
This summary is machine-generated.

This study validated depression screening tools for epilepsy patients. The PHQ-9 and HADS showed balanced sensitivity and specificity, with specific cut points recommended for screening versus case finding.

Keywords:
DepressionEpidemiologyEpilepsySensitivity and specificity

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Area of Science:

  • Neurology
  • Psychiatry
  • Clinical Diagnostics

Background:

  • Depression frequently co-occurs with epilepsy, necessitating accurate screening.
  • Existing depression screening tools lack validation in epilepsy populations.
  • Timely identification of depression in epilepsy is crucial for patient management.

Purpose of the Study:

  • To validate three common depression screening scales in individuals with epilepsy.
  • To determine optimal scoring cut points for these scales in this specific population.
  • To compare the diagnostic accuracy of selected scales against a gold standard.

Main Methods:

  • 300 individuals with epilepsy completed sociodemographic questionnaires and depression screening tools (HADS, PHQ-9, PHQ-2).
  • 185 participants underwent a structured clinical interview as the gold standard for depression diagnosis.
  • Diagnostic accuracy of screening scales was evaluated using various cut points against the gold standard.

Main Results:

  • The prevalence of depression in the study population was 14.6% based on the gold standard.
  • The Hospital Anxiety and Depression Scale (HADS) achieved 84.6% sensitivity at a cut point of 6.
  • The Patient Health Questionnaire (PHQ)-9 algorithm demonstrated 96.2% specificity.
  • The PHQ-9 (cut point 9) and HADS (cut point 7) offered the best overall balance of sensitivity and specificity (AUC 88% and 90%).

Conclusions:

  • The PHQ-9 (cut point 9) and HADS (cut point 7) provide the best overall diagnostic performance.
  • For broad screening, the PHQ-9 algorithm maximizes specificity.
  • For identifying potential cases, HADS at a cut point of 6 optimizes sensitivity.
  • Selecting appropriate scale cut points should align with study objectives and resources; disease-specific cut points are recommended.