Predictors of cerebrovascular event reoccurrence in patients with depression: a retrospective cohort study

Wa Cai1, Christoph Mueller2,3, Hitesh Shetty2

  • 1Institute of Acupuncture and Anesthesia, Shanghai Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China 408346323@qq.com.

BMJ Open
|January 10, 2020
PubMed

Insights

Recurrent cerebrovascular events (CBVD) impact 20% of patients with depression and prior CBVD. Older age and physical health issues, not depression severity, predict recurrence risk.

Area of Science:

  • Neurology
  • Psychiatry
  • Epidemiology

Background:

  • Patients with depression and cerebrovascular disease (CBVD) have an increased risk of recurrent morbidity.
  • Identifying predictors of CBVD recurrence is crucial for effective patient management and secondary prevention strategies.

Purpose of the Study:

  • To identify predictors of recurrent cerebrovascular morbidity in a cohort of patients diagnosed with depression and a history of cerebrovascular disease (CBVD).

Main Methods:

  • A cohort of patients aged 50+ with depression and prior hospitalised CBVD was identified from a case register (2008-2017).
  • Patients were followed for CBVD recurrence or death due to CBVD.
  • Sociodemographic data, symptom/functioning scores, medications, and comorbidities were analyzed using multivariate survival analyses.

Main Results:

  • Of 1292 patients, 20.4% experienced CBVD recurrence over a median follow-up of 1.66 years.
  • Older age (HR 1.02), physical health problems (HR 2.47), and anticoagulant use (HR 1.40) predicted higher recurrence risk.
  • Antipsychotic medication use was associated with a reduced risk (HR 0.66).

Conclusions:

  • Approximately one in five patients with depression and CBVD experienced recurrence within 20 months.
  • Recurrence risk was primarily associated with older age and physical health status.
  • Depression severity, mental health symptoms, functional status, and antidepressant use did not significantly predict recurrence.
Abstract

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