Post-Stroke Mortality, Stroke Severity, and Preadmission Antipsychotic Medicine Use – A Population-Based Cohort Study

<div><p>Background and Purpose</p><p>It has been suggested that antipsychotic medication may be neuroprotective and may reduce post-stroke mortality, but studies are few and ambiguous. We aimed to investigate the post-stroke effects of preadmission antipsychotic use.</p><p>Methods</p><p>We conducted a nationwide, population-based cohort study of 81,143 persons admitted with stroke in Denmark from 2003–2010. Using Danish health care databases, we extracted data on preadmission use of antipsychotics and confounding factors. We examined the association between current, former, and never use of antipsychotics and stroke severity, length of hospital stay, and 30-day post-stroke mortality using logistic regression analysis, survival analysis, and propensity score matching.</p><p>Results</p><p>Current users of antipsychotics had a higher risk of severe or very severe stroke on The Scandinavian Stroke Scale than never users of antipsychotics (adjusted odds ratios, 1.43; 95% CI, 1.29–1.58). Current users were less likely to be discharged from hospital within 30 days of admission than never users (probability of non-discharge, 27.0% vs. 21.9%). Antipsychotics was associated with an increased 30-day post-stroke mortality among current users (adjusted mortality rate ratios, 1.42; 95% CI, 1.29–1.55), but not among former users (adjusted mortality rate ratios, 1.05; 95% CI, 0.98–1.14).</p><p>Conclusions</p><p>Preadmission use of antipsychotics was associated with a higher risk of severe stroke, a longer duration of hospital stay, and a higher post-stroke mortality, even after adjustment for known confounders. Antipsychotics play an important role in the treatment of many psychiatric conditions, but our findings do not support the hypothesis that they reduce stroke severity or post-stroke mortality.</p></div

Association between preadmission antipsychotic medication use and 30-day mortality in acute stroke patients in various adjusted models.

<p>Model 1: adjusted for age group and calendar period. Overall estimates adjusted for gender in all models.</p><p>†Model 2: further adjusted for type of stroke, former stroke, pre-stroke drug use (lipid-lowering drugs, antihypertensive drugs, antidiabetic drugs, platelet inhibitors) and education level.</p><p>‡Model 3: further adjusted for year of admission, severity of stroke, and modified Charlson’s index (cerebrovascular disorders excluded). No interaction between genders in model 3 (<i>p</i> = 0.79).</p

Association between preadmission antipsychotic medication use and risk of severe and very severe stroke on the Scandinavian Stroke Scale on admission for acute stroke.

<p>Stroke severity on the Scandinavian Stroke Scale dichotomized into two groups (mild and moderate versus severe and very severe). Adjusted for former stroke, pre-stroke drug use (lipid-lowering drugs, antihypertensive drugs, antidiabetic drugs, platelet inhibitors), education level, age group, year of admission, and modified Charlson’s index (cerebrovascular disorders excluded). Overall estimates adjusted for gender. Interaction between genders (<i>p</i><0.01).</p

Pregnancy Outcome According to Diagnosis of Depression and Use of Antidepressants (AD).

<p>Pregnancy Outcome According to Diagnosis of Depression and Use of Antidepressants (AD).</p

Baseline Characteristics According to Diagnosis of Depression and Use of Antidepressants (AD).

<p>Baseline Characteristics According to Diagnosis of Depression and Use of Antidepressants (AD).</p

Stratified Analyses according to Diagnosis of Depression.

a<p>Probabilites of event.</p>b<p>Adjusted for maternal age, cohabitation, income, education, history of severe mental disorder and drug abuse in case of the marginal analysis and the stratified analysis for no diagnosis of depression.</p><p>Adjusted for maternal age, cohabitation, education, and history of severe mental disorder in case of the stratified analysis for a diagnosis of depression.</p