Objective. Stroke is the commonest cause of epileptic seizures in older adults. Risk factors for post-stroke seizure (PSS) are well known, however, predicting PSS risk is clinically challenging. This study aimed to evaluate the predictive accuracy of PSS risk prediction models developed to date. Methods. We performed a systematic review and meta-analysis of studies using MEDLINE and EMBASE from database inception to 28 th December 2020. The search criteria included all peer-reviewed research articles, in which PSS risk prediction models were developed or validated for ischaemic and/or haemorrhagic stroke. Random-effects meta-analysis was used to generate summary statistics of model performance and receiver operating characteristic curves. Quality appraisal of studies was conducted using PROBAST. Results. Thirteen original studies involving 182,673 stroke patients (mean age: 38-74.9 years; 29.4-60.9% males), reporting 15 PSS risk prediction models were included. The incidence of early PSS (occurring one week from stroke onset) and late PSS (occurring >one week from stroke onset) was 4.5% and 2.1%, respectively. Cortical involvement, functional deficits, increasing lesion size, early seizures, younger age, and haemorrhage were the commonest predictors across the models. SeLECT demonstrated greatest predictive accuracy (AUC 0.77 [95% CI: 0.71-0.82]) for late PSS following ischaemic stroke, and CAVE for predicting late PSS following haemorrhagic stroke (AUC 0.81 [0.76-0.86]). Fourteen of 15 studies demonstrated a high risk of bias, with lack of model validation and reporting of performance measures on calibration and discrimination being the commonest reasons. Significance. Although risk factors for PSS are widely documented, this review identified few multivariate models with low risk of bias, synthetising single variables into an individual prediction of seizure risk. Such models may help personalise clinical management and serve as useful research tools by identifying stroke patients at high risk of developing PSS for recruitment into studies of anti-epileptic drug prophylaxis.

ObjectiveTo determine the interrater variability for TIA diagnostic agreement among expert clinicians (neurologists/stroke physicians), administrative data, and nonspecialists.MethodsWe performed a meta-analysis of studies from January 1984 to January 2019 using MEDLINE, EMBASE, and PubMed. Two reviewers independently screened for eligible studies and extracted interrater variability measurements using Cohen's kappa scores to assess diagnostic agreement.ResultsNineteen original studies consisting of 19,421 patients were included. Expert clinicians demonstrate good agreement for TIA diagnosis (κ = 0.71, 95% confidence interval [CI] = 0.62–0.81). Interrater variability between clinicians' TIA diagnosis and administrative data also demonstrated good agreement (κ = 0.68, 95% CI = 0.62–0.74). There was moderate agreement (κ = 0.41, 95% CI = 0.22–0.61) between referring clinicians and clinicians at TIA clinics receiving the referrals. Sixty percent of 748 patient referrals to TIA clinics were TIA mimics.ConclusionsOverall agreement between expert clinicians was good for TIA diagnosis, although variation still existed for a sizeable proportion of cases. Diagnostic agreement for TIA decreased among nonspecialists. The substantial number of patients being referred to TIA clinics with other (often neurologic) diagnoses was large, suggesting that clinicians, who are proficient in managing TIAs and their mimics, should run TIA clinics.

BackgroundPercutaneous coronary intervention (PCI), the preferred coronary reperfusion strategy, induces endothelial trauma which may mount an inflammatory response. This has been shown to increase the likelihood of further major adverse cardiovascular events (MACE). Colchicine, a cheap and widely used anti-inflammatory has shown promise in improving cardiovascular outcomes. We aimed to perform a systematic review and meta-analysis to study the effects of colchicine in patients with symptomatic coronary artery disease (CAD) who have undergone PCI.MethodWe systematically reviewed and meta-analysed 7 randomised controlled trials including a total of 6660 patients (colchicine group: 3347, control group: 3313; mean age=60.9±10). Six studies included participants who had a ≤13.5-day history of acute coronary syndrome (ACS). One study included patients with both ACS and chronic coronary syndrome. The follow-up of studies ranged from 3 days to 22.6 months.ResultsThe use of colchicine in patients who underwent PCI significantly reduced MACE outcomes (risk ratio 0.73 (95% CI 0.61 to 0.87); p=0.0003) with minimal heterogeneity across the analysis (I2=6%; P for Cochran Q=0.38). These results were driven mainly by the reduction in repeat vessel revascularisation, stroke and stent thrombosis. The number needed to treat to prevent one occurrence of MACE was 41.ConclusionColchicine significantly reduced the risk of MACE in patients with CAD who underwent PCI, mostly in the reduction of repeat vessel revascularisation, stroke and stent thrombosis. The efficacy of colchicine should be further studied by distinguishing its use alongside different stent types and dosing regimens.PROSPERO registration numberCRD42021245699.