Pharmacotherapy effectiveness in treating depression after traumatic brain injury: A meta-analysis
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Objective:
Depression is a highly prevalent neuropsychiatric sequela among individuals who have experienced traumatic brain injury (TBI). Despite its high prevalence, there continues to be conflicting evidence surrounding the efficacy of medication for treating depression post-TBI and whether different treatments have distinct effects. The aim of this study was to systematically review and synthesize the available evidence for the effectiveness of pharmacotherapy for depression following a TBI.
Methods:
A meta-analysis was completed using several online databases (PubMed, National Institute of Health and Care Excellence, and Healthcare Databases Advanced Search) to search for clinical trials involving various pharmacological treatments for depression in patients with TBIs. Twelve studies met the inclusion criteria and were assessed using their sample size, treatment duration, treatment used, TBI severity, method of assessment, and medication response. Standardized mean difference effect sizes (Cohen’s d) were calculated for each study using pre- and postintervention scores and pooled using a random effects model to produce a summary effect size.
Results:
Fourteen effect sizes were calculated, and a mild to moderate pooled effect size (Cohen’s d=–0.49, 95% CI: –0.96, –0.02, p=0.02) was found. Ten studies demonstrated effect sizes that were statistically significant, and four were nonsignificant. The weighted pooled effect size was higher for single-group design studies (Cohen’s d=–1.35, 95% CI: –2.14, –0.56, N=5) compared with independent-group designs (Cohen’s d=0.001, CI: –0.59, 0.58; N=9).
Conclusions:
This meta-analysis tentatively supports the view that pharmacological treatment may be effective in reducing depressive symptoms in those with depression following TBI. However, evidence from randomized controlled trials alone demonstrated no beneficial effect. The limitations are also discussed.
Depression is a highly prevalent neuropsychiatric sequela among individuals who have experienced traumatic brain injury (TBI). Despite its high prevalence, there continues to be conflicting evidence surrounding the efficacy of medication for treating depression post-TBI and whether different treatments have distinct effects. The aim of this study was to systematically review and synthesize the available evidence for the effectiveness of pharmacotherapy for depression following a TBI.
Methods:
A meta-analysis was completed using several online databases (PubMed, National Institute of Health and Care Excellence, and Healthcare Databases Advanced Search) to search for clinical trials involving various pharmacological treatments for depression in patients with TBIs. Twelve studies met the inclusion criteria and were assessed using their sample size, treatment duration, treatment used, TBI severity, method of assessment, and medication response. Standardized mean difference effect sizes (Cohen’s d) were calculated for each study using pre- and postintervention scores and pooled using a random effects model to produce a summary effect size.
Results:
Fourteen effect sizes were calculated, and a mild to moderate pooled effect size (Cohen’s d=–0.49, 95% CI: –0.96, –0.02, p=0.02) was found. Ten studies demonstrated effect sizes that were statistically significant, and four were nonsignificant. The weighted pooled effect size was higher for single-group design studies (Cohen’s d=–1.35, 95% CI: –2.14, –0.56, N=5) compared with independent-group designs (Cohen’s d=0.001, CI: –0.59, 0.58; N=9).
Conclusions:
This meta-analysis tentatively supports the view that pharmacological treatment may be effective in reducing depressive symptoms in those with depression following TBI. However, evidence from randomized controlled trials alone demonstrated no beneficial effect. The limitations are also discussed.
Original language | English |
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Pages (from-to) | 220-227 |
Journal | Journal of Neuropsychiatry and Clinical Neurosciences |
Volume | 31 |
Issue number | 3 |
Early online date | 14 Jan 2019 |
DOIs | |
Publication status | Published - Jul 2019 |
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