Potential Biomarkers for Post-Stroke Cognitive Impairment: A Systematic Review and Meta-Analysis.
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SUBMITTER: Kim KY
PROVIDER: S-EPMC8775398 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Post-stroke cognitive impairment (PSCI) affects more than one-third of stroke patients, and causes much greater harm to long-term function than the initial brain damage. No conventional Western medications have shown convincing clinical effectiveness for treating PSCI. Research shows that Traditional Chinese medicine (TCM) can improve cognitive function in patients. However, the clinical efficacy and safety remain controversial. The aim of this study was to examine the effectiveness and harmful effects of TCMs in the treatment of PSCI. Method: We searched seven databases and two clinical registration websites for randomized controlled trials (RCTs). The revised Cochrane risk of bias tool (RoB 2.0) was used to evaluate the methodological quality and RevMan 5.4 was used for data analysis. This study has been submitted to PROSPERO with registration number is CRD42020149299. Results: We included 34 studies in this review. The results of this study showed that TCM adjuvant therapy improved scores on the MoCA [MD = 2.55, 95% CI (1.56, 3.53), p < 0.00001; MD = 3.07, 95% CI (1.98, 4.17), p < 0.00001 at treatment duration of <3 and 3 months, respectively], MMSE [MD = 2.55, 95% CI (1.99, 3.10), p < 0.00001; MD = 2.53, 95% CI (1.59, 3.47), p < 0.00001; MD = 2.91, 95% CI (1.26, 4.56), p = 0.0006; MD = 3.11, 95% CI (-0.04, 6.27), p = 0.05 at treatment duration of <3, 3, 4, and 6 months, respectively], and BI [MD = 7.34, 95% CI (3.83, 10.85), p < 0.0001; MD = 8.98, 95% CI (4.76, 13.21), p < 0.0001 at treatment duration of <3 and 3 months, respectively] and reduced scores on the ADL (MD = -8.64, 95% CI (-9.83, -7.45), p < 0.00001; MD = -2.00, 95% CI (-2.94, -1.06), p < 0.0001 at treatment duration of 3 and 4 months, respectively], NIHSS [MD = -2.48, 95% CI (-4.97, 0.00), p = 0.05; MD = -3.81, 95% CI (-6.21, -1.40), p = 0.002 at treatment duration of <3 and 3 months, respectively], and CSS [MD = -2.47, 95% CI (-3.49, -1.45), p < 0.00001 at a treatment duration of 3 months]. No serious adverse reactions were observed. Conclusion: Despite the significant positive results, the present evidence supports, to a limited extent because of the methodological flaws and herbal heterogeneity, that TCM adjuvant therapy can be used for patients with PSCI. While, further rigorous RCTs are warranted to confirm the efficacy and safety of TCM. Systematic Review Registration: https://www.crd.york.ac.uk/prospero, identifier CRD42020149299.
| S-EPMC8883343 | biostudies-literature
Project description:BackgroundIdentifying whether acute stroke patients are at risk of cognitive decline could improve prognostic discussions and management. Structural computed tomography neuroimaging is routine in acute stroke, and may identify those at risk of post-stroke dementia or post-stroke cognitive impairment (PSCI).AimTo systematically review the literature to identify which stroke or pre-stroke features on brain computed tomography scans, performed at the time of stroke, are associated with post-stroke dementia or PSCI.Summary of reviewWe searched electronic databases to December 2020. We included studies reporting acute stroke brain computed tomography, and later diagnosis of a cognitive syndrome. We created summary estimates of size of unadjusted association between computed tomography features and cognition. Of 9536 citations, 28 studies (41 papers) were eligible (N = 7078, mean age 59.8-78.6 years). Cognitive outcomes were post-stroke dementia (10 studies), PSCI (17 studies), and one study analyzed both. Fifteen studies (N = 2952) reported data suitable for meta-analyses. White matter lesions (WML) (six studies, N = 1054, OR = 2.46, 95% CI = 1.25-4.84), cerebral atrophy (four studies, N = 558, OR = 2.80, 95% CI = 1.21-6.51), and pre-existing stroke lesions (three studies, N = 352, OR = 2.38, 95% CI = 1.06-5.32) were associated with post-stroke dementia. WML (four studies, N = 473, OR = 3.46, 95% CI = 2.17-5.52) were associated with PSCI. Other computed tomography features were either not associated with cognitive outcome, or there were insufficient data.ConclusionsCognitive impairment following stroke is of great concern to patients and carers. Features seen on visual assessment of acute stroke computed tomography brain scans are strongly associated with cognitive outcomes. Clinicians should consider when and how this information should be discussed with stroke survivors.
| S-EPMC9260488 | biostudies-literature
Project description:BackgroundA considerable number of stroke survivors suffered from cognitive impairment, and more than one third of stroke survivors are affected at 3 and 12 months after the stroke. Although the published systematic reviews suggest that acupuncture can help improve post-stroke cognitive dysfunction, the power of the results is low due to study limitations. Therefore, this review is necessary to analyze the effect of acupuncture on cognitive impairment after stroke and to provide evidence for cognitive impairment in stroke.MethodsThis study will be carried out in strict accordance with the Cochrane Handbook for Systematic Reviews of Interventions. According to the pre-established search strategy (PICOS framework), all the literature will be obtained from online databases including Cochrane Central Register of Controlled Trials in the Cochrane Library, Medline (via PubMed), EMBASE (via embase.com), CINAHL (via EBSCOhost), China National Knowledge Infrastructure database, WanFang Database, Chinese Science and Technology Periodical Database, and Sino-Med Database from inception until December 31, 2021 with no language limitations. Two reviewers will screen the records and include quality studies according to inclusion criteria independently. The data needed will be extracted independently by 2 authors according to a table of data extraction. Any inconsistencies in literature screening and data collection will be resolved to reach a consensus via discussion with a third author. Risk of bias for each study will be assessed using risk of bias tool. RevMan5.3 will be used to analyze the data. Heterogeneity will be identified and measured by Chi2. Subgroup analyses and sensitivity analysis will be carried out. Grading of Recommendations Assessment, Development and Evaluation will be used to evaluate the evidence for each outcome.ConclusionThe results of this study will provide a theoretical basis for the clinical use of electro-acupuncture to treat cognitive dysfunction after stroke.Unique inplasy numberINPLASY202210038.
| S-EPMC8878786 | biostudies-literature
Project description:ObjectiveCognitive impairment is a detrimental complication of stroke that compromises the quality of life of the patients and poses a huge burden on society. Due to the lack of effective early prediction tools in clinical practice, many researchers have introduced machine learning (ML) into the prediction of post-stroke cognitive impairment (PSCI). However, the mathematical models for ML are diverse, and their accuracy remains highly contentious. Therefore, this study aimed to examine the efficiency of ML in the prediction of PSCI.MethodsRelevant articles were retrieved from Cochrane, Embase, PubMed, and Web of Science from the inception of each database to 5 December 2022. Study quality was evaluated by PROBAST, and c-index, sensitivity, specificity, and overall accuracy of the prediction models were meta-analyzed.ResultsA total of 21 articles involving 7,822 stroke patients (2,876 with PSCI) were included. The main modeling variables comprised age, gender, education level, stroke history, stroke severity, lesion volume, lesion site, stroke subtype, white matter hyperintensity (WMH), and vascular risk factors. The prediction models used were prediction nomograms constructed based on logistic regression. The pooled c-index, sensitivity, and specificity were 0.82 (95% CI 0.77-0.87), 0.77 (95% CI 0.72-0.80), and 0.80 (95% CI 0.71-0.86) in the training set, and 0.82 (95% CI 0.77-0.87), 0.82 (95% CI 0.70-0.90), and 0.80 (95% CI 0.68-0.82) in the validation set, respectively.ConclusionML is a potential tool for predicting PSCI and may be used to develop simple clinical scoring scales for subsequent clinical use.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?RecordID=383476.
| S-EPMC10434510 | biostudies-literature
Project description:BackgroundCognitive impairment is one of the common sequelae after stroke, which not only hinders the recovery of patients but also increases the financial burden on families. In the absence of effective therapeutic measures, acupuncture treatment has been widely used in China to treat post-stroke cognitive impairment (PSCI), but the specific efficacy is unclear. Therefore, this review aimed to evaluate the true efficacy of acupuncture treatment in patients with PSCI.MethodsWe searched eight databases [PubMed, Embase, Web of Science, Cochrane Central Register of Controlled Trials, China Biomedical Literature Database (CBM), China Science and Technology Journal (VIP) database, the China National Knowledge Infrastructure (CNKI) database, and Wan fang database] from the inception to May 2022 for randomized controlled trials (RCTs) related to acupuncture treatment combined with cognitive rehabilitation (CR) for PSCI. Two investigators independently used a pre-designed form to extract valid data from eligible RCTs. The risk of bias was assessed through tools provided by the Cochrane Collaboration. The meta-analysis was implemented through Rev Man software (version 5.4). The strength of the evidence obtained was evaluated using GRADE profiler software. Adverse events (AEs) were collected by reading the full text and used to evaluate the safety of acupuncture treatment.ResultsThirty-eight studies involving a total of 2,971 participants were included in this meta-analysis. Overall, the RCTs included in this meta-analysis were poor in methodological quality. The combined results showed that acupuncture treatment combined with CR showed significant superiority compared to CR alone in terms of improving cognitive function [Mean Difference (MD) = 3.94, 95% confidence intervals (CI): 3.16-4.72, P < 0.00001 (MMSE); MD = 3.30, 95%CI: 2.53-4.07, P < 0.00001 (MoCA); MD = 9.53, 95%CI: 5.61-13.45, P < 0.00001 (LOTCA)]. Furthermore, the combination of acupuncture treatment and CR significantly improved patients' self-care ability compared to CR alone [MD = 8.66, 95%CI: 5.85-11.47, P < 0.00001 (MBI); MD = 5.24, 95%CI: 3.90-6.57, P < 0.00001 (FIM)]. Meanwhile, subgroup analysis showed that MMSE scores were not sufficiently improved in the comparison of electro-acupuncture combined with CR versus CR alone (MD = 4.07, 95%CI: -0.45-8.60, P = 0.08). However, we also observed that electro-acupuncture combined with CR was superior to the use of CR alone in improving MoCA and MBI scores in patients with PSCI [MD = 2.17, 95%CI: 0.65-3.70, P = 0.005 (MoCA); MD = 1.74, 95%CI: 0.13-3.35, P = 0.03 (MBI)]. There was no significant difference in the occurrence of adverse events (AE) between acupuncture treatment combined with CR and CR alone (P > 0.05). The certainty of the evidence was rated low level because of flaws in the study design and considerable heterogeneity among the included studies.ConclusionThis review found that acupuncture treatment combined with CR may have a positive effect on improving cognitive function and self-care ability in PSCI patients. However, our findings should be treated with caution owing to the existence of methodological quality issues. High-quality studies are urgently required to validate our results in the future.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022338905, identifier: CRD42022338905.
| S-EPMC9946978 | biostudies-literature
Project description:IntroductionIncreasing attention is being paid to interventions for cognitive impairment (CI) post-stroke, including for CI that does not meet dementia criteria. The aim of this paper was to conduct a systematic review and meta-analysis of the prevalence of cognitive impairment no dementia (CIND) within one year post-stroke.Patients and methodsPubmed, EMBASE and PsychInfo were searched for papers published in English in 1995-2017. Included studies were population or hospital-based cohort studies for first-ever/recurrent stroke, assessing CIND using standardised criteria at 1-12 months post-stroke. Abstracts were screened, followed by full text review of potentially relevant articles. Data were extracted using a standard form, and study quality was appraised using the Crowe Critical Appraisal Tool. A pooled prevalence of CIND with 95% confidence intervals (CI) was estimated using random-effects meta-analysis. Heterogeneity was measured using the I2 statistic.ResultsA total of 7000 abstracts were screened, followed by 1028 full text articles. Twenty-three articles were included in the systematic review, and 21 in the meta-analysis. The pooled CIND prevalence was 38% [95% CI = 32-43%] (I2=92.5%, p < 0.01). Study quality emerged as one source of heterogeneity. The five studies with the highest quality scores had no heterogeneity (I2=0%, p = 0.99), with a similar pooled prevalence (39%, 95%CI = 35-42%). Other sources of heterogeneity were stroke type, inclusion of pre-stroke CI, and age at assessment time.Discussion and conclusion: Meta-analysis of available studies indicates that in the first year post-stroke, 4 in 10 patients display a level of cognitive impairment that does not meet the criteria for dementia.
| S-EPMC6591758 | biostudies-literature
Project description:BackgroundSeveral studies have assessed the link between cognitive impairment and risk of future stroke, but results have been inconsistent. We conducted a systematic review and meta-analysis of cohort studies to determine the association between cognitive impairment and risk of future stroke.MethodsWe searched MEDLINE and Embase (1966 to November 2013) and conducted a manual search of bibliographies of relevant retrieved articles and reviews. We included cohort studies that reported multivariable adjusted relative risks and 95% confidence intervals or standard errors for stroke with respect to baseline cognitive impairment.ResultsWe identified 18 cohort studies (total 121 879 participants) and 7799 stroke events. Pooled analysis of results from all studies showed that stroke risk increased among patients with cognitive impairment at baseline (relative risk [RR] 1.39, 95% confidence interval [CI] 1.24-1.56). The results were similar when we restricted the analysis to studies that used a widely adopted definition of cognitive impairment (i.e., Mini-Mental State Examination score < 25 or nearest equivalent) (RR 1.64, 95% CI 1.46-1.84). Cognitive impairment at baseline was also associated with an increased risk of fatal stroke (RR 1.68, 95% CI 1.21-2.33) and ischemic stroke (RR 1.65, 95% CI 1.41-1.93).InterpretationBaseline cognitive impairment was associated with a significantly higher risk of future stroke, especially ischemic and fatal stroke.
| S-EPMC4188684 | biostudies-literature
Project description:ImportanceCOVID-19 is associated with clinically significant symptoms despite resolution of the acute infection (i.e., post-COVID-19 syndrome). Fatigue and cognitive impairment are amongst the most common and debilitating symptoms of post-COVID-19 syndrome.ObjectiveTo quantify the proportion of individuals experiencing fatigue and cognitive impairment 12 or more weeks following COVID-19 diagnosis, and to characterize the inflammatory correlates and functional consequences of post-COVID-19 syndrome.Data sourcesSystematic searches were conducted without language restrictions from database inception to June 8, 2021 on PubMed/MEDLINE, The Cochrane Library, PsycInfo, Embase, Web of Science, Google/Google Scholar, and select reference lists.Study selectionPrimary research articles which evaluated individuals at least 12 weeks after confirmed COVID-19 diagnosis and specifically reported on fatigue, cognitive impairment, inflammatory parameters, and/or functional outcomes were selected.Data extraction & synthesisTwo reviewers independently extracted published summary data and assessed methodological quality and risk of bias. A meta-analysis of proportions was conducted to pool Freeman-Tukey double arcsine transformed proportions using the random-effects restricted maximum-likelihood model.Main outcomes & measuresThe co-primary outcomes were the proportions of individuals reporting fatigue and cognitive impairment, respectively, 12 or more weeks following COVID-19 infection. The secondary outcomes were inflammatory correlates and functional consequences associated with post-COVID-19 syndrome.ResultsThe literature search yielded 10,979 studies, and 81 studies were selected for inclusion. The fatigue meta-analysis comprised 68 studies, the cognitive impairment meta-analysis comprised 43 studies, and 48 studies were included in the narrative synthesis. Meta-analysis revealed that the proportion of individuals experiencing fatigue 12 or more weeks following COVID-19 diagnosis was 0.32 (95% CI, 0.27, 0.37; p < 0.001; n = 25,268; I2 = 99.1%). The proportion of individuals exhibiting cognitive impairment was 0.22 (95% CI, 0.17, 0.28; p < 0.001; n = 13,232; I2 = 98.0). Moreover, narrative synthesis revealed elevations in proinflammatory markers and considerable functional impairment in a subset of individuals.Conclusions & relevanceA significant proportion of individuals experience persistent fatigue and/or cognitive impairment following resolution of acute COVID-19. The frequency and debilitating nature of the foregoing symptoms provides the impetus to characterize the underlying neurobiological substrates and how to best treat these phenomena.Study registrationPROSPERO (CRD42021256965).
| S-EPMC8715665 | biostudies-literature
Project description:BackgroundCognitive impairment and dementia are common after stroke. It is unclear if risk differs between ischaemic stroke subtypes. Lacunar strokes might be less likely to affect cognition than more severe, larger cortical strokes, except that lacunar strokes are associated with cerebral small vessel disease (SVD), which is the commonest vascular cause of dementia.MethodsWe searched MEDLINE and PsychINFO for studies of mild cognitive impairment (MCI) or dementia after lacunar or cortical ischaemic stroke. We calculated the OR for cognitive impairment/dementia in lacunar versus non-lacunar stroke, and their incidence and prevalence in lacunar stroke as a pooled proportion.FindingsWe identified 24 relevant studies of 7575 patients, including 2860 with lacunar stroke; 24% had MCI or dementia post stroke. Similar proportions of patients with lacunar and non-lacunar stroke (16 studies, n=6478) had MCI or dementia up to 4 years after stroke (OR 0.72 (95% CI 0.43 to 1.20)). The prevalence of dementia after lacunar stroke (six studies, n=1421) was 20% (95% CI 9 to 33) and the incidence of MCI or dementia (four studies, n=275) was 37% (95% CI 23 to 53). Data were limited by short follow-up, subtype classification methods and confounding.InterpretationCognitive impairment appears to be common after lacunar strokes despite their small size, suggesting that associated SVD may increase their impact. New prospective studies are required with accurate stroke subtyping to assess long term outcomes while accounting for confounders.
| S-EPMC3717603 | biostudies-literature
Project description:Backgroundstroke is the main cause of disability in high-income countries, and ranks second as a cause of death worldwide. Patients with acute stroke are at risk for infections, but reported post-stroke infection rates vary considerably. We performed a systematic review and meta-analysis to estimate the pooled post-stroke infection rate and its effect on outcome.MethodsMEDLINE and EMBASE were searched for studies on post-stroke infection. Cohort studies and randomized clinical trials were included when post-stroke infection rate was reported. Rates of infection were pooled after assessment of heterogeneity. Associations between population- and study characteristics and infection rates were quantified. Finally, we reviewed the association between infection and outcome.Results87 studies were included involving 137817 patients. 8 studies were restricted to patients admitted on the intensive care unit (ICU). There was significant heterogeneity between studies (P < 0.001, I(2) = 97%). The overall pooled infection rate was 30% (24-36%); rates of pneumonia and urinary tract infection were 10% (95% confidence interval [CI] 9-10%) and 10% (95%CI 9-12%). For ICU studies, these rates were substantially higher with 45% (95% CI 38-52%), 28% (95%CI 18-38%) and 20% (95%CI 0-40%). Rates of pneumonia were higher in studies that specifically evaluated infections and in consecutive studies. Studies including older patients or more females reported higher rates of urinary tract infection. Pneumonia was significantly associated with death (odds ratio 3.62 (95%CI 2.80-4.68).ConclusionsInfection complicated acute stroke in 30% of patients. Rates of pneumonia and urinary tract infection after stroke were 10%. Pneumonia was associated with death. Our study stresses the need to prevent infections in patients with stroke.
| S-EPMC3185266 | biostudies-literature