Outcomes in Patients With Poststroke Seizures: A Systematic Review and Meta-Analysis.

Importance: Published data about the impact of poststroke seizures (PSSs) on the outcomes of patients with stroke are inconsistent and have not been systematically evaluated, to the authors' knowledge. Objective: To investigate outcomes in people with PSS compared with people without PSS. Data Sources: MEDLINE, Embase, PsycInfo, Cochrane, LILACS, LIPECS, and Web of Science, with years searched from 1951 to January 30, 2023. Study Selection: Observational studies that reported PSS outcomes. Data Extraction and Synthesis: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was used for abstracting data, and the Joanna Briggs Institute tool was used for risk-of-bias assessment. Data were reported as odds ratio (OR) and standardized mean difference (SMD) with a 95% CI using a random-effects meta-analysis. Publication bias was assessed using funnel plots and the Egger test. Outlier and meta-regression analyses were performed to explore the source of heterogeneity. Data were analyzed from November 2022 to January 2023. Main Outcomes and Measures: Measured outcomes were mortality, poor functional outcome (modified Rankin scale [mRS] score 3-6), disability (mean mRS score), recurrent stroke, and dementia at patient follow-up. Results: The search yielded 71 eligible articles, including 20 110 patients with PSS and 1 166 085 patients without PSS. Of the participants with PSS, 1967 (9.8%) had early seizures, and 10 605 (52.7%) had late seizures. The risk of bias was high in 5 studies (7.0%), moderate in 35 (49.3%), and low in 31 (43.7%). PSSs were associated with mortality risk (OR, 2.1; 95% CI, 1.8-2.4), poor functional outcome (OR, 2.2; 95% CI, 1.8-2.8), greater disability (SMD, 0.6; 95% CI, 0.4-0.7), and increased dementia risk (OR, 3.1; 95% CI, 1.3-7.7) compared with patients without PSS. In subgroup analyses, early seizures but not late seizures were associated with mortality (OR, 2.4; 95% CI, 1.9-2.9 vs OR, 1.2; 95% CI, 0.8-2.0) and both ischemic and hemorrhagic stroke subtypes were associated with mortality (OR, 2.2; 95% CI, 1.8-2.7 vs OR, 1.4; 95% CI, 1.0-1.8). In addition, early and late seizures (OR, 2.4; 95% CI, 1.6-3.4 vs OR, 2.7; 95% CI, 1.8-4.1) and stroke subtypes were associated with poor outcomes (OR, 2.6; 95% CI, 1.9-3.7 vs OR, 1.9; 95% CI, 1.0-3.6). Conclusions and Relevance: Results of this systematic review and meta-analysis suggest that PSSs were associated with significantly increased mortality and severe disability in patients with history of stroke. Unraveling these associations is a high clinical and research priority. Trials of interventions to prevent seizures may be warranted.

Common Pathways of Epileptogenesis in Patients With Epilepsy Post-Brain Injury: Findings From a Systematic Review and Meta-analysis.

BACKGROUND AND OBJECTIVES: Epilepsy may result from various brain injuries, including stroke (ischemic and hemorrhagic), traumatic brain injury, and infections. Identifying shared common biological pathways and biomarkers of the epileptogenic process initiated by the different injuries may lead to novel targets for preventing the development of epilepsy. We systematically reviewed biofluid biomarkers to test their association with the risk of post-brain injury epilepsy. METHODS: We searched articles until January 25, 2022, in MEDLINE, Embase, PsycInfo, Web of Science, and Cochrane. The primary outcome was the difference in mean biomarker levels in patients with and without post-brain injury epilepsy. We used the modified quality score on prognostic studies for risk of bias assessment. We calculated each biomarker's pooled standardized mean difference (SMD) and 95% CI. Molecular interaction network and enrichment analyses were conducted in Cytoscape (PROSPERO CRD42021297110). RESULTS: We included 22 studies with 1,499 cases with post-brain injury epilepsy and 7,929 controls without post-brain injury epilepsy. Forty-five biomarkers in the blood or CSF were investigated with samples collected at disparate time points. Of 22 studies, 21 had a moderate-to-high risk of bias. Most of the biomarkers (28/45) were investigated in single studies; only 9 provided validation data, and studies used variable definitions for early-onset and late-onset seizures. A meta-analysis was possible for 19 biomarkers. Blood glucose levels in 4 studies were significantly higher in patients with poststroke epilepsy (PSE) than those without PSE (SMD 0.44; CI 0.19-0.69). From individual studies, 15 biomarkers in the blood and 7 in the CSF were significantly associated with post-brain injury epilepsy. Enrichment analysis identified that the significant biomarkers (interleukin [IL]-6, IL-1ß]) were predominantly inflammation related. DISCUSSION: We cannot yet recommend using the reported biomarkers for designing antiepileptogenesis trials or use in the clinical setting because of methodological heterogeneity, bias in the included studies, and insufficient validation studies. Although our analyses indicate the plausible role of inflammation in epileptogenesis, this is likely not the only mechanism. For example, an individual's genetic susceptibilities might contribute to his/her risk of epileptogenesis after brain injury. Rigorously designed biomarker studies with methods acceptable to the regulatory bodies should be conducted.

Impact of genetic polymorphisms on the risk of epilepsy amongst patients with acute brain injury: A systematic review.

BACKGROUND AND PURPOSE: The genetics of late seizure or epilepsy secondary to traumatic brain injury (TBI) or stroke are poorly understood. We undertook a systematic review to test the association of single-nucleotide polymorphisms (SNPs) with the risk of post-traumatic epilepsy (PTE) and post-stroke epilepsy (PSE). METHODS: We followed methods from our prespecified protocol on PROSPERO to identify indexed articles for this systematic review. We collated the association statistics from the included articles to assess the association of SNPs with the risk of epilepsy amongst TBI or stroke patients. We assessed study quality using the Q-Genie tool. We report odds ratios (OR) and hazard ratios with 95% confidence intervals (CIs). RESULTS: The literature search yielded 420 articles. We included 16 studies in our systematic review, of which seven were of poor quality. We examined published data on 127 SNPs from 32 genes identified in PTE and PSE patients. Eleven SNPs were associated with a significantly increased risk of PTE. Three SNPs, TRMP6 rs2274924, ALDH2 rs671, and CD40 -1C/T, were significantly associated with an increased risk of PSE, while two, AT1R rs12721273 and rs55707609, were significantly associated with reduced risk. The meta-analysis for the association of the APOE ɛ4 with PTE was nonsignificant (OR 1.8, CI 0.6-5.6). CONCLUSIONS: The current evidence on the association of genetic polymorphisms in epilepsy secondary to TBI or stroke is of low quality and lacks validation. A collaborative effort to pool genetic data linked to epileptogenesis in stroke and TBI patients is warranted.

Salivary Proteomics Identifies Transthyretin as a Biomarker of Early Dementia Conversion.

Background: Alzheimer's disease (AD) remains to date an incurable disease with a long asymptomatic phase. Early diagnosis in peripheral biofluids has emerged as key for identifying subjects at risk and developing therapeutics and preventative approaches. Objective: We apply proteomics discovery to identify salivary diagnostic biomarkers for AD, which are suitable for self-sampling and longitudinal biomonitoring during aging. Methods: 57 participants were recruited for the study and were categorized into Cognitively normal (CNh) (n = 19), mild cognitive impaired (MCI) (n = 21), and Alzheimer's disease (AD) (n = 17). On a subset of subjects, 3 CNh and 3 mild AD, shot-gun filter aided sample preparation (FASP) proteomics and liquid chromatography mass spectroscopy (LC-MS/MS) was employed in saliva and cerebrospinal fluid (CSF) to identify neural-derived proteins. The protein level of salivary Transthyretin (TTR) was validated using western blot analysis across groups. Results: We found that 19.8% of the proteins in saliva are shared with CSF. When we compared the saliva and CSF proteome, 24 hits were decreased with only one protein expressed more. Among the differentially expressed proteins, TTR with reported function in amyloid misfolding, shows a significant drop in AD samples, confirmed by western blot showing a 0.5-fold reduction in MCI and AD compared to CNh. Conclusion: A reduction in salivary TTR appears with the onset of cognitive symptoms. More in general, the proteomic profiling of saliva shows a plethora of biomarkers worth pursuing as non-invasive hallmarks of dementia in the preclinical stage.