Antidepressant use and stroke or mortality risk in the elderly

Association between tricyclic antidepressants and health outcomes among older people: A systematic review and meta-analysis

Tricyclic antidepressants are effective for managing depression and other disorders. However, they can cause adverse reactions due to their anticholinergic properties, with the risk of such events increasing with age. This study identifies and describes clinical studies that evaluate associations between the use of tricyclic antidepressants and adverse health outcomes (falls, fractures, and mortality) among older people. A systematic search of the literature in English, Spanish, and French was conducted using the electronic databases PubMed, ISI Web of Science, PsycINFO, and Cochrane. The systematic review included a total of 18 studies. The meta-analysis examined the 14 studies that investigated the association between the use of tricyclic antidepressants and the risk of falls and fractures (4 of the 18 studies focused on mortality and so were excluded from the meta-analysis). The odds ratio (OR) was 1.40 (95 % CI = 1.27-1.53, p < 0.001). The Cochran Q test was significant (X2 = 79.72, p < 0.001), indicating high heterogeneity (I2 = 84.9 %). An additional meta-analysis was conducted on studies reporting hazard ratios (HRs), yielding an HR of 1.21 (95 % CI = 0.93-1.58, p = 0.16). Meta-regression analysis indicated that the years of follow-up could have a significant effect on the association studied (p = 0.008). In conclusion, enhancing our understanding of the use of antidepressants and the associated risk of adverse events in older adults will enable the identification of the most appropriate type of antidepressant for each clinical situation.

A comprehensive overview of post-stroke depression treatment options

Nearly one-third of all stroke patients develop depression at any time after a stroke, and its presence is associated with unfavorable outcomes. This narrative review aims to provide a synopsis of possible pharmacological and non-pharmacological treatment modalities for post-stroke depression (PSD). Several studies have demonstrated the efficacy and safety of selective serotonin reuptake inhibitors in treating the symptoms of this clinical condition. The treatment of PSD has been recently enhanced by innovative approaches, such as cognitive-behavioral therapy, virtual reality, telehealth, repetitive transcranial magnetic stimulation, and non-conventional therapies, which might improve depression treatment in stroke survivors. Future high-quality randomized controlled trials are necessary to confirm this hypothesis.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Identifying the regulatory network of microRNAs and mRNAs to clarify molecular mechanisms in stroke by bioinformatics analysis

BACKGROUND

Stroke is one of the leading causes of disability and mortality worldwide.

OBJECTIVE

To identify the regulatory network of microRNAs (miRNAs) and mRNAs to clarify molecular mechanisms in stroke.

METHODS

Four miRNA datasets and two mRNA datasets of stroke were downloaded from the GEO database. R-Studio was utilized to analyze differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) in the blood of stroke and control patients. FunRich software was utilized to conduct GO and biological pathway analysis on DEmiRNAs, and to search for transcription factors (TFs) of DEmiRNAs. Subsequently, we used miRDB, miRTarBase, and TargetScan to identify DEmiRNAs target genes and intersected with DEmRNAs to find common target genes. The miRNA-mRNA regulatory network of common target genes was constructed by using the Cytoscape. The biological and functional roles of target genes in the regulatory network were predicted using GO and KEGG pathway analyses.

RESULTS

464 DEmiRNAs and 329 DEmRNAs were screened. The top ten TFs (SP1, SP4, EGR1, TCF3, NKX6-1, ZFP161, RREB1, MEF2A, NFIC, POU2F1) were visualized. 16747 target genes of DEmiRNAs were predicted. Target genes were intersected with DEmRNAs, 107 common target genes and 162 DEmiRNAs regulating these common genes were obtained, and then a regulatory network was constructed. Target genes of the regulatory network were primarily enriched in VEGF signaling pathway, lipid and atherosclerosis, T cell receptor signaling pathway.

CONCLUSION

This study found that VEGF signaling pathway, lipid and atherosclerosis, T cell receptor signaling pathway are implicated in the biological process of stroke by constructing the regulatory network of miRNAs-mRNAs, which may have guide significance for the pathogenesis and treatment of stroke.

Antidepressants and the Risk of Ischemic Stroke in Older Adults According to the Degree of Serotonin Reuptake Inhibition: A Retrospective Cohort Study

OBJECTIVE

The effects of serotonin reuptake inhibition induced by antidepressants on ischemic stroke and its pathophysiology remain unclear despite the frequent use of antidepressants and high fatality of ischemic stroke. We estimated the risk of ischemic stroke associated with antidepressant use in older adults according to the degree of serotonin reuptake inhibition.

DESIGN

Retrospective cohort study.

PARTICIPANTS

The cohort consisted of older adult patients who were treated with antidepressants.

MEASUREMENTS

We estimated the risk of ischemic stroke associated with antidepressant use in older adults according to the degree of serotonin reuptake inhibition using Korea's National Health Insurance System-Senior Cohort. Exposure to antidepressants was categorized by type (strong, intermediate, or weak serotonin reuptake inhibitors [SRIs]) and by the mean prescribed dose per day and treatment duration. The risk for the strong and intermediate SRIs group was compared with that of the weak SRIs group using a Cox proportional hazards regression model.

RESULTS

Of 97,411 were weak SRIs users, and 107,152 and 18,783 were users of strong and intermediate SRIs. The risk of ischemic stroke was 1.192- and 1.057-fold higher in strong and intermediate SRI users, respectively than in weak SRI users. Hazard ratios were increased in higher dose and shorter duration user groups. The risk increased 1.753-fold in strong SRI users with anticonvulsants and 1.387-fold in intermediate SRI users with PPIs.

CONCLUSION

The use of strong and intermediate SRIs should be considered carefully in older adult patients, especially when high-dose antidepressants are prescribed even for a short duration.

Twenty-three medication-taking traits and stroke: A comprehensive Mendelian randomization study

Background

Certain medication categories may increase the risk of stroke. Nonetheless, the evidence regarding the causal relationship of medication-taking in promoting stroke and subtypes is deficient.

Methods

We evaluated the causal effect of a genetic predisposition for certain medication categories on stroke and subtypes (ischemic and hemorrhagic categories) by a two-sample Mendelian randomization (MR) analysis. Data for 23 medication categories were gathered from a genome-wide association study (GWAS) involving 318,177 patients. The Medical Research Council Integrative Epidemiology Unit Open GWAS database and the FinnGen consortium were used to gather GWAS data for stroke and subtypes. Inverse variance weighted, MR-Egger, and weighted median were used for the estimation of causal effects. Cochran's Q test, MR-Egger intercept test, and leave-one-out analysis were used for sensitivity analyses.

Results

Ten medication categories were linked to a high stroke risk. Nine categories were linked to a high-risk ischemic stroke. Five categories were associated with small vessel ischemic stroke. Nine categories were positively associated with large artery atherosclerotic ischemic stroke. Three categories causally increased the possibility of cardioembolic ischemic stroke. Four categories were associated with intracerebral hemorrhage. Four categories were associated with nontraumatic intracranial hemorrhage. Three categories were causally associated with subarachnoid hemorrhage (SAH). Four categories were associated with the combination of SAH, unruptured cerebral aneurysm, and aneurysm operations SAH.

Conclusions

This study confirms that some medication categories lead to a greater risk of strokes. Meanwhile, it has an implication for stroke screening as well as direct clinical significance in the design of conduction of future randomized controlled trials.

The White Matter Functional Abnormalities in Patients with Transient Ischemic Attack: A Reinforcement Learning Approach

Background

Transient ischemic attack (TIA) is a known risk factor for stroke. Abnormal alterations in the low-frequency range of the gray matter (GM) of the brain have been studied in patients with TIA. However, whether there are abnormal neural activities in the low-frequency range of the white matter (WM) in patients with TIA remains unknown. The current study applied two resting-state metrics to explore functional abnormalities in the low-frequency range of WM in patients with TIA. Furthermore, a reinforcement learning method was used to investigate whether altered WM function could be a diagnostic indicator of TIA.

Methods

We enrolled 48 patients with TIA and 41 age- and sex-matched healthy controls (HCs). Resting-state functional magnetic resonance imaging (rs-fMRI) and clinical/physiological/biochemical data were collected from each participant. We compared the group differences between patients with TIA and HCs in the low-frequency range of WM using two resting-state metrics: amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). The altered ALFF and fALFF values were defined as features of the reinforcement learning method involving a Q-learning algorithm.

Results

Compared with HCs, patients with TIA showed decreased ALFF in the right cingulate gyrus/right superior longitudinal fasciculus/left superior corona radiata and decreased fALFF in the right cerebral peduncle/right cingulate gyrus/middle cerebellar peduncle. Based on these two rs-fMRI metrics, an optimal Q-learning model was obtained with an accuracy of 82.02%, sensitivity of 85.42%, specificity of 78.05%, precision of 82.00%, and area under the curve (AUC) of 0.87.

Conclusion

The present study revealed abnormal WM functional alterations in the low-frequency range in patients with TIA. These results support the role of WM functional neural activity as a potential neuromarker in classifying patients with TIA and offer novel insights into the underlying mechanisms in patients with TIA from the perspective of WM function.

The Predictive Value of Dynamic Intrinsic Local Metrics in Transient Ischemic Attack

BACKGROUND

Transient ischemic attack (TIA) is known as "small stroke." However, the diagnosis of TIA is currently difficult due to the transient symptoms. Therefore, objective and reliable biomarkers are urgently needed in clinical practice.

OBJECTIVE

The purpose of this study was to investigate whether dynamic alterations in resting-state local metrics could differentiate patients with TIA from healthy controls (HCs) using the support-vector machine (SVM) classification method.

METHODS

By analyzing resting-state functional MRI (rs-fMRI) data from 48 patients with and 41 demographically matched HCs, we compared the group differences in three dynamic local metrics: dynamic amplitude of low-frequency fluctuation (d-ALFF), dynamic fractional amplitude of low-frequency fluctuation (d-fALFF), and dynamic regional homogeneity (d-ReHo). Furthermore, we selected the observed alterations in three dynamic local metrics as classification features to distinguish patients with TIA from HCs through SVM classifier.

RESULTS

We found that TIA was associated with disruptions in dynamic local intrinsic brain activities. Compared with HCs, the patients with TIA exhibited increased d-fALFF, d-fALFF, and d-ReHo in vermis, right calcarine, right middle temporal gyrus, opercular part of right inferior frontal gyrus, left calcarine, left occipital, and left temporal and cerebellum. These alternations in the dynamic local metrics exhibited an accuracy of 80.90%, sensitivity of 77.08%, specificity of 85.37%, precision of 86.05%, and area under curve of 0.8501 for distinguishing the patients from HCs.

CONCLUSION

Our findings may provide important evidence for understanding the neuropathology underlying TIA and strong support for the hypothesis that these local metrics have potential value in clinical diagnosis.

Recognition of the Possible miRNA-mRNA Controlling Network in Stroke by Bioinformatics Examination

BACKGROUND

Based on the latest research of WHO, it has been revealed that more than 15 million people suffer from stroke every year worldwide. Of these 15 million people, 6 million succumb to death, and 5 million get permanently disabled. This is the prime reason for the substantial economic burden on all parts of the world.

METHODS

These data have been obtained from the GEO database, and the GEO2R tool was used to find out the differentially expressed miRNAs (DEMs) between the stroke and normal patients' blood. FunRich and miRNet were considered to find potential upstream transcription factors and downstream target genes of candidate EMRs. Next, we use GO annotation and KEGG pathway enrichment. Target genes were analyzed with the help of the R software. Then, the STRING database and Cytoscape software were used to conduct PPI and DEM-hub gene networks. Finally, GSE58294 was used to estimate the hub gene expressions.

RESULTS

Six DEMs in total were selected out from GSE95204 and GSE117064 datasets. 663 DEMs' target genes were predicted, and NRF1, EGR1, MYC, YY1, E2F1, SP4, and SP1 were predicted as an upstream transcription factor for DEMs' target genes. Target genes of DEMs were primarily augmented in the PI3K-Akt signaling pathway and p53 signaling pathway. The network construction of DEM hygiene is potentially modulated by hsa-miR-3591-5p, hsa-miR-548as-3p, hsa-miR-206, and hsa-miR-4503 hub genes which were found among the top 10 of the hub genes. Among the top 10 hub genes, justification of CTNNB1, PTEN, ESR1, CCND1, KRAS, AKT1, CCND2, CDKN1B, and MYCN was constant with that in the GSE58294 dataset.

CONCLUSION

In summary, our research first constructs the miRNA-mRNA network in stroke, which probably renders an awakening purview into the pathogenesis and cure of stroke.