Pharmacological, psychological and non-invasive brain stimulation interventions for preventing depression after stroke

Efficacy and Safety of Antidepressants in Patients With Comorbid Depression and Medical Diseases: An Umbrella Systematic Review and Meta-Analysis

Importance

Every third to sixth patient with medical diseases receives antidepressants, but regulatory trials typically exclude comorbid medical diseases. Meta-analyses of antidepressants have shown small to medium effect sizes, but generalizability to clinical settings is unclear, where medical comorbidity is highly prevalent.

Objective

To perform an umbrella systematic review of the meta-analytic evidence and meta-analysis of the efficacy and safety of antidepressant use in populations with medical diseases and comorbid depression.

Data Sources

PubMed and EMBASE were searched from inception until March 31, 2023, for systematic reviews with or without meta-analyses of randomized clinical trials (RCTs) examining the efficacy and safety of antidepressants for treatment or prevention of comorbid depression in any medical disease.

Study Selection

Meta-analyses of placebo- or active-controlled RCTs studying antidepressants for depression in individuals with medical diseases.

Data Extraction and Synthesis

Data extraction and quality assessment using A Measurement Tool for the Assessment of Multiple Systematic Reviews (AMSTAR-2 and AMSTAR-Content) were performed by pairs of independent reviewers following PRISMA guidelines. When several meta-analyses studied the same medical disease, the largest meta-analysis was included. Random-effects meta-analyses pooled data on the primary outcome (efficacy), key secondary outcomes (acceptability and tolerability), and additional secondary outcomes (response and remission).

Main Outcomes and Measures

Antidepressant efficacy presented as standardized mean differences (SMDs) and tolerability (discontinuation for adverse effects) and acceptability (all-cause discontinuation) presented as risk ratios (RRs).

Results

Of 6587 references, 176 systematic reviews were identified in 43 medical diseases. Altogether, 52 meta-analyses in 27 medical diseases were included in the evidence synthesis (mean [SD] AMSTAR-2 quality score, 9.3 [3.1], with a maximum possible of 16; mean [SD] AMSTAR-Content score, 2.4 [1.9], with a maximum possible of 9). Across medical diseases (23 meta-analyses), antidepressants improved depression vs placebo (SMD, 0.42 [95% CI, 0.30-0.54]; I2 = 76.5%), with the largest SMDs for myocardial infarction (SMD, 1.38 [95% CI, 0.82-1.93]), functional chest pain (SMD, 0.87 [95% CI, 0.08-1.67]), and coronary artery disease (SMD, 0.83 [95% CI, 0.32-1.33]) and the smallest for low back pain (SMD, 0.06 [95% CI, 0.17-0.39]) and traumatic brain injury (SMD, 0.08 [95% CI, -0.28 to 0.45]). Antidepressants showed worse acceptability (24 meta-analyses; RR, 1.17 [95% CI, 1.02-1.32]) and tolerability (18 meta-analyses; RR, 1.39 [95% CI, 1.13-1.64]) compared with placebo. Antidepressants led to higher rates of response (8 meta-analyses; RR, 1.54 [95% CI, 1.14-1.94]) and remission (6 meta-analyses; RR, 1.43 [95% CI, 1.25-1.61]) than placebo. Antidepressants more likely prevented depression than placebo (7 meta-analyses; RR, 0.43 [95% CI, 0.33-0.53]).

Conclusions and Relevance

The results of this umbrella systematic review of meta-analyses found that antidepressants are effective and safe in treating and preventing depression in patients with comorbid medical disease. However, few large, high-quality RCTs exist in most medical diseases.

Nomogram model for predicting the risk of post-stroke depression based on clinical characteristics and DNA methylation

Objective

To construct a comprehensive nomogram model for predicting the risk of post-stroke depression (PSD) by using clinical data that are easily collected in the early stages, and the level of DNA methylation, so as to help doctors and patients prevent the occurrence of PSD as soon as possible.

Methods

We continuously recruited 226 patients with a history of acute ischemic stroke and followed up for three months. Socio-demographic indicators, vascular-risk factors, and clinical data were collected at admission, and the outcome of depression was evaluated at the third month after stroke. At the same time, a DNA-methylation-related sequencing test was performed on the fasting peripheral blood of the hospitalized patients which was taken the morning after admission.

Results

A total of 206 samples were randomly divided into training dataset and validation set according to the ratio of 7:3. We screened 24 potentially-predictive factors by Univariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression analysis, and 10 of the factors were found to have predictive ability in the training set. The PSD nomogram model was established based on seven significant variables in multivariate logistic regression. The consistency statistic (C-index) was as high as 0.937, and the area under curve (AUC) in the ROC analysis was 0.933. Replication analysis results in the validation set suggest the C-index was 0.953 and AUC was 0.926. This shows that the model has excellent calibration and differentiating abilities.

Conclusion

Gender, Rankin score, history of hyperlipidemia, time from onset to hospitalization, location of stroke, National Institutes of Health Stroke scale (NIHSS) score, and the methylation level of the cg02550950 site are all related to the occurrence of PSD. Using this information, we developed a prediction model based on methylation characteristics.

Integrative-interpersonal dynamic therapy for poststroke depression (INID): study protocol of a randomised controlled pilot trial

INTRODUCTION

Depression is the most frequent psychiatric disorder following stroke, affecting about one-third of stroke survivors. Patients experience poorer recovery, lower quality of life and higher mortality compared with stroke survivors without depression. Despite these well-known malign consequences, poststroke depression (PSD) is regarded underdiagnosed and undertreated. Evidence of beneficial effects of psychotherapy to treat PSD remains scarce and inconclusive and is limited by heterogeneity in design, content and timing of the intervention. This pilot study aims to assess the feasibility of a newly developed integrative-interpersonal dynamic PSD intervention in an outpatient setting and provide a first estimation of the potential effect size as basis for the sample size estimation for a subsequent definite trial.

METHOD AND ANALYSIS

Patients will be recruited from two German stroke units. After discharge from inpatient rehabilitation, depressed stroke survivors will be randomised to short-term psychotherapy (12 weeks, ≤16 sessions) or enhanced treatment as usual. The manualised psychotherapy integrates key features of the Unified Psychodynamic and Cognitive-Behavioural Unified Protocol for emotional disorders and was adapted for PSD. Primary endpoints are recruitment feasibility and treatment acceptability, defined as a recruitment rate of ≥20% for eligible patients consenting to randomisation and ≥70% completion-rate of patients participating in the treatment condition. A preliminary estimation of the treatment effect based on the mean difference in Patient Health Questionnaire-9 (PHQ-9) scores between intervention and control group six months poststroke is calculated. Secondary endpoints include changes in depression (PHQ-9/Hamilton Depression Scale) and anxiety (Generalised Anxiety Disorder 7) of all participants across all follow-ups during the first year poststroke.

ETHICS AND DISSEMINATION

The INID pilot study received full ethical approval (S-321/2019; 2022-2286_1). Trial results will be published in a peer-reviewed journal in the first half of 2025. One-year follow-ups are planned to be carried out until summer 2025.

TRIAL REGISTRATION NUMBER

DRKS00030378.

Predictors of post-stroke depression: Validation of established risk factors and introduction of a dynamic perspective in two longitudinal studies

INTRODUCTION

Cerebral insults lead in many cases not only to cognitive impairment but also to disturbed emotionality. After stroke, one in three survivors develops a depression which impacts quality of life and rehabilitation. Meta-analyses have identified five main predictors of post-stroke depression (PSD): history of mental disorder, stroke severity, physical disability, cognitive impairment, and social support. However, these five established variables have never been conjointly investigated in a sample of stroke survivors. Therefore, their independent predictive values remain unclear. Moreover, predictors are most often used as time-invariant factors (status scores), neglecting the intraindividual dynamics after stroke.

METHODS

Our study analyses the data of two prospective longitudinal studies, investigating stroke survivors from two rehabilitation hospitals (N ₁ = 273) and one acute care hospital (N ₂ = 226). Baseline assessments included the five established predictors and depressive symptoms. After 6 months, depressive symptoms were reassessed in both studies (n ₁ = 176, n ₂ = 183), and physical disability and social support were reassessed in study 2. The predictivity of the five predictors and the additional predictivity of intraindividual dynamics for PSD were examined in multiple linear regression analyses.

RESULTS

History of mental disorder was a risk factor for depressive symptoms after stroke at all measurement times (B = 3.32 to 3.97; p < 0.01). Physical disability was a risk factor at all measurement times (B = -0.09 to -0.03; p < 0.05) except 6 months after rehabilitation. Social support was a protective factor (B = -2.69 to -1.91; p < 0.01) outside the acute phase (R ² = 0.15-0.39). Intraindividual changes in physical disability and perceived social support were independent predictors of PSD 6 months after the acute phase (B = -0.08/-0.14; p < 0.01), in addition to status scores on established variables (ΔR ² = 0.08, p < 0.001).

DISCUSSION

History of mental disorder, physical disability, and social support are independent predictors of depressive symptoms in the first year post-stroke, also when considered conjointly. Future studies should control for these variables when investigating new predictors of PSD. In addition, intraindividual changes in known predictors after stroke play a relevant role in the pathogenesis of PSD and should be considered in clinical practice and future research.

In-hospital predictors of post-stroke depression for targeted initiation of Selective Serotonin Reuptake Inhibitors (SSRIs)

BACKGROUND

Although SSRIs are no longer widely prescribed for post-stroke motor recovery, fluoxetine demonstrated beneficial effects on post-stroke depression (PSD). Given the potential side effects of SSRIs, targeted initiation among individuals at highest risk for PSD warrants consideration. While previous studies have identified stroke severity and psychiatric history as factors associated with PSD, its predictability remains unknown. In this study, we investigate inpatient predictive factors to better identify individuals who might derive the most benefit from targeted initiation of SSRIs.

METHODS

We performed a retrospective analysis of a prospectively-collected registry of adult patients presenting with acute ischemic stroke to a tertiary referral urban academic comprehensive stroke center between 2016-2020. Patients were seen 4-6 weeks post-discharge and administered the PHQ-9 (Patient Health Questionnaire-9) to screen for PSD (PHQ-9 ≥ 5). Demographics, history of depression, stroke severity, and inpatient PHQ-9 scores were abstracted. Logistic regression was used to determine factors associated with PSD and an ROC analysis determined the predictability of PSD in the inpatient setting.

RESULTS

Three hundred seven individuals were administered the PHQ-9 at follow-up (mean age 65.5 years, 52% female). History of depression (OR = 4.11, 95% CI: 1.65-10.26) and inpatient PHQ-9 score (OR = 1.17, 95% CI: 1.06-1.30) were significantly associated with PSD. Stroke severity, marital status, living alone, employment, and outpatient therapy were not associated with PSD. The ROC curve using a positive inpatient PHQ-9 achieved an area under the curve (AUC) of 0.65 (95% CI: 0.60-0.70), while the AUC was 0.72 (95% CI: 0.66-0.77) after adding history of depression.

CONCLUSIONS

History of depression and a positive inpatient PHQ-9 appear to be most strongly predictive of long-term PSD. Initiating SSRIs only in those individuals at highest risk for PSD may help reduce the burden of stroke recovery in this targeted population while minimizing adverse side effects.

A Narrative Review on the Non-Pharmacologic Interventions in Post-Stroke Depression

Stroke is a major cause of death and disability globally. Post-stroke depression (PSD) is a major driver for poor recovery and poor quality of life with extra burden for the patient and the caregiver. We have previously shown the inflammatory basis of PSD with associated bioenergetic failure, disruption of the blood-brain barrier, cell death, and persistent maladapted inflammation, making the PSD a norm rather than the exception, highlighting the unmet need for therapeutic intervention in PSD across the recovery trajectory. In this era, various interventions are focused on pharmacotherapy; however, non-pill-based medication should also be explored as post-stroke patients are likely to suffer from the adverse effects of polypharmacy. This narrated review explores the status of non-pharmacological interventions in managing PSD. We performed a PubMed search using pre-specified keywords looking at various non-pharmacologic approaches for the management of PSD. Worldwide, approaches such as non-invasive brain stimulation, behavioral and psychosocial therapy, as well as exercise, acupuncture, music, literature, and art therapies are available as monotherapy or adjunctive treatment for PSD. While current literature shows convincing results on the benefits of non-pharmacologic interventions, more robust studies are necessary to determine its utility in PSD.

Breathing Exercises for Improving Cognitive Function in Patients with Stroke

Patients with stroke may experience a certain degree of cognitive decline during the period of recovery, and a considerable number of such patients have been reported to show permanent cognitive damage. Therefore, the period of recovery and rehabilitation following stroke is critical for rapid cognitive functional improvements. As dysfunctional breathing has been reported as one of the factors affecting the quality of life post stroke, a number of studies have focused on the need for improving the breathing function in these patients. Numerous breathing exercises have been reported to enhance the respiratory, pulmonary, cognitive, and psychological functions. However, scientific evidence on the underlying mechanisms by which these exercises improve cognitive function is scattered at best. Therefore, it has been difficult to establish a protocol of breathing exercises for patients with stroke. In this review, we summarize the psychological, vascular, sleep-related, and biochemical factors influencing cognition in patients and highlight the need for breathing exercises based on existing studies. Breathing exercises are expected to contribute to improvements in cognitive function in stroke based on a diverse array of supporting evidence. With relevant follow-up studies, a protocol of breathing exercises can be developed for improving the cognitive function in patients with stroke.

Depression symptoms 6 years after stroke are associated with higher perceived impact of stroke, limitations in ADL and restricted participation

Late post-stroke depression symptoms are understudied. This study aimed to investigate depression symptoms 6 years after stroke, and associations with perceived impact of stroke, activities of daily living (ADL), and participation in social and everyday activities. Data was collected in a 6-year follow-up in a longitudinal study of stroke. Assessments included Hospital Anxiety and Depression Scale (HADS) for depression symptoms, Stroke Impact Scale 3.0. for perceived impact of stroke, Barthel Index for ADL, Frenchay Activities Index for participation in social and everyday activities. The research questions were addressed by bivariate analyses (with HADS-D ≥ 4 as cut-off), and hierarchical multiple regression analyses using continuous HADS-D scores. Forty percent of the 105 participants (57% men, age 30-91) showed depression symptoms (HADS-D ≥ 4). Depression symptoms were associated with higher perceived impact of stroke, more dependence in ADL, and more restrictions in participation in social and everyday activities. Most of those with depression symptoms had low scores on HADS, indicating that even mild depression symptoms might be relevant to identify and target in treatment and rehabilitation of long-term consequences of stroke.

Prediction of Poststroke Depression Based on the Outcomes of Machine Learning Algorithms

Poststroke depression (PSD) is a major psychiatric disorder that develops after stroke; however, whether PSD treatment improves cognitive and functional impairments is not clearly understood. We reviewed data from 31 subjects with PSD and 34 age-matched controls without PSD; all subjects underwent neurological, cognitive, and functional assessments, including the National Institutes of Health Stroke Scale (NIHSS), the Korean version of the Mini-Mental Status Examination (K-MMSE), computerized neurocognitive test (CNT), the Korean version of the Modified Barthel Index (K-MBI), and functional independence measure (FIM) at admission to the rehabilitation unit in the subacute stage following stroke and 4 weeks after initial assessments. Machine learning methods, such as support vector machine, k-nearest neighbors, random forest, voting ensemble models, and statistical analysis using logistic regression were performed. PSD was successfully predicted using a support vector machine with a radial basis function kernel function (area under curve (AUC) = 0.711, accuracy = 0.700). PSD prognoses could be predicted using a support vector machine linear algorithm (AUC = 0.830, accuracy = 0.771). The statistical method did not have a better AUC than that of machine learning algorithms. We concluded that the occurrence and prognosis of PSD in stroke patients can be predicted effectively based on patients’ cognitive and functional statuses using machine learning algorithms.

Can pharmacological, psychological and non-invasive brain stimulation interventions prevent depression after stroke? A cochrane review summary with commentary

BACKGROUND

Depression is very common in patients after a stroke and it can impact recovery.

OBJECTIVE

The Cochrane Review aimed to determine whether psychological therapy, pharmacological interventions, non-invasive brain stimulation, or their combination can prevent depression after stroke.

METHODS

The population addressed were patients who suffered from a stroke and had no previous diagnosis of depressive disorders. Studies comparing pharmacological intervention to placebo, psychological therapy to usual care, and non-invasive brain stimulation to sham stimulation or usual care were included.

RESULTS

Outcome information was available for nine pharmacological and two psychological trials, showing favorable treatment effects.

CONCLUSIONS

The available evidence suggests that pharmacological interventions and psychological therapy may prevent depression and improve mood after stroke. Although, the current evidence is of very low quality resulting in serious uncertainties about the estimates of effect observed.

Depression Outcomes Among Patients Treated With Fluoxetine for Stroke Recovery: The AFFINITY Randomized Clinical Trial

Importance

One in 3 adults experiences clinically significant symptoms of depression during the first year after a stroke, but evidence to support the use of antidepressants in this population remains scant.

Objective

To investigate whether daily treatment with 20 mg of fluoxetine hydrochloride reduces the proportion of people affected by clinically significant symptoms of depression after stroke.

Design, Setting, and Participants

In this secondary analysis of the Assessment of Fluoxetine in Stroke Recovery parallel-group, randomized (1:1 assignment), double-blind, placebo-controlled clinical trial, 1221 participants in Australia, New Zealand, and Vietnam were recruited between January 11, 2013, and June 30, 2019, and were followed up for 6 months. Adults aged 18 years or older were recruited 2 to 15 days after experiencing a stroke associated with modified Rankin Scale score of 1 or higher.

Interventions

Fluoxetine hydrochloride, 20 mg, or matched placebo daily for 26 weeks.

Main Outcomes and Measures

A 9-item Patient Health Questionnaire (PHQ-9) score of 9 or lower was a prespecified secondary outcome of the trial. Assessments were completed at baseline and at 4, 12, and 26 weeks. Other outcomes of interest included participant-reported clinician diagnosis of depression, prescription of a nontrial antidepressant, or nonpharmacologic treatment of depression. Analysis was on an intention-to-treat basis.

Results

A total of 607 participants (378 men [62.3%]; mean [SD] age, 64.3 [12.2] years) were randomly assigned treatment with placebo, and 614 participants (397 men [64.7%]; mean [SD] age, 63.4 [12.4] years) were randomly assigned treatment with 20 mg of fluoxetine hydrochloride daily. The groups were balanced for demographic and clinical measures. At baseline, 112 patients (18.5%) in the placebo group and 116 patients (18.9%) in the fluoxetine group had PHQ-9 scores of 9 or higher. During follow-up, 126 of 596 participants (21.1%) treated with placebo and 121 of 598 participants (20.2%) treated with fluoxetine had PHQ-9 scores of 9 or higher (P = .70). A similar proportion of participants with PHQ-9 scores less than 9 at baseline who were treated with fluoxetine hydrochloride and placebo developed PHQ-9 scores of 9 or higher during the trial (placebo, 72 of 488 [14.8%]; and fluoxetine, 63 of 485 [13.0%]; P = .43). A slightly higher number of participants in the placebo group than in the fluoxetine group had a participant-reported clinician diagnosis of depression (42 of 602 [7.0%] vs 26 of 601 [4.3%]; P = .05). By week 26, 14 participants (2.3%) in the placebo group and 12 participants (1.9%) in the fluoxetine group had died (P = .67).

Conclusions and Relevance

Routine daily treatment with 20 mg of fluoxetine did not decrease the proportion of people affected by clinically significant symptoms of depression after a stroke, nor did it affect the proportion of people prescribed an antidepressant or receiving nonpharmacologic treatments compared with placebo.

Trial Registration

http://anzctr.org.au Identifier: ACTRN12611000774921.

Palliative care after stroke: A review

BACKGROUND

Palliative care is an integral aspect of stroke unit care. In 2016, the American Stroke Association published a policy statement on palliative care and stroke. Since then there has been an expansion in the literature on palliative care and stroke.

AIM

Our aim was to narratively review research on palliative care and stroke, published since 2015.

RESULTS

The literature fell into three broad categories: (a) scope and scale of palliative care needs, (b) organization of palliative care for stroke, and (c) shared decision making. Most literature was observational. There was a lack of evidence about interventions that address specific palliative symptoms or improve shared decision making. Racial disparities exist in access to palliative care after stroke. There was a dearth of literature from low- and middle-income countries.

CONCLUSION

We recommend further research, especially in low- and middle-income countries, including research to explore why racial disparities in access to palliative care exist. Randomized trials are needed to address specific palliative care needs after stroke and to understand how best to facilitate shared decision making.