Hospital admissions prior to primary intracerebral haemorrhage and relevant factors associated with survival

Role of frailty in predicting outcomes after stroke: a systematic review and meta-analysis

Background

Stroke is considered the second most common cause of death and the third leading cause of disability worldwide. Frailty, characterized by increased vulnerability to stressors, is emerging as a key factor affecting outcomes in older adults and stroke patients. This study aimed to estimate the prevalence of frailty in acute stroke patients and assess its association with mortality and poor functional outcome.

Methods

Medline, Google Scholar, and Science Direct databases were systematically searched for English-language studies that included adult stroke patients (>16 years), have defined frailty, and reported mortality and functional outcomes. Meta-analysis was done using STATA 14.2, and the results were expressed as pooled odds ratios (OR) with 95% confidence intervals (CI). Heterogeneity was assessed using the I2 statistic and the Chi-square test. Study quality was evaluated using the Newcastle Ottawa Scale (NOS).

Results

Twenty-five studies were included in the analysis. Frailty prevalence in stroke patients was 23% (95% CI 22% - 23%). Unadjusted analysis showed an OR of 2.66 (95% CI: 1.93 - 3.67) for mortality and 2.04 (95% CI: 1.49 - 2.80) for poor functional outcome. Adjusted estimates indicated an OR of 1.22 (95% CI: 1.1 - 1.35) for mortality and 1.21 (95% CI: 1.04 - 1.41) for poor functional outcome, with substantial heterogeneity for both adjusted and unadjusted analyses. No publication bias was detected for the prevalence of frailty. However, there was a publication bias for the association between frailty and mortality.

Conclusions

Frailty was significantly associated with increased mortality and poorer functional outcomes in stroke patients. Our study highlights the need to focus on frailty in stroke patients to improve outcomes and quality of life. Further research should aim to standardize assessment of frailty and reduce heterogeneity in study outcomes.

Systematic review registration

https://www.crd.york.ac.uk/prospero/#searchadvanced, CRD42023470325.

Systematic Review of the Association of the Hospital Frailty Risk Score with Mortality in Patients with Cerebrovascular and Cardiovascular Disease

BACKGROUND

There is limited systematic data on the association between the Hospital Frailty Risk Score (HFRS) and characteristics and mortality in patients with cerebrovascular and cardiovascular disease (CVD). This systematic review aimed to summarise the use of the HFRS in describing the prevalence of frailty in patients with CVD, the clinical characteristics of patients with CVD, and the association between frailty on the likelihood of mortality in patients with CVD.

METHODS

A systematic literature search for observational studies using terms related to CVD, cerebrovascular disease, and the HFRS was conducted using 6 databases in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies were appraised using the Newcastle-Ottawa Scale (NOS).

RESULTS

Seventeen observational studies were included, all rated 'good' quality according to the NOS. One study investigated 5 different CVD cohorts (atrial fibrillation (AF), heart failure (HF), hypotension, hypertension, and chronic ischemic heart disease), 1 study investigated 2 different CVD cohorts (AF and acute myocardial infarction (AMI)), 6 studies investigated HF, 3 studies investigated AMI, 4 studies investigated stroke, 1 study investigated AF, and 1 study investigated cardiac arrest. Increasing frailty risk category was associated with increased age, female sex, and non-white racial group across all CVD. Increasing frailty risk category is also associated with increased length of hospital stay, total costs, and increased odds of 30-day all-cause mortality across all CVD.

CONCLUSIONS

The HFRS is an efficient and effective tool for stratifying frailty in patients with CVD and predicting adverse health outcomes.

Prevalence and Risk Factors of Frailty in Stroke Patients: A Meta-Analysis and Systematic Review

OBJECTIVES

Summarize the existing evidence regarding the prevalence and risk factors of frailty in stroke patients.

DESIGN

A meta-analysis and systematic review.

PARTICIPANTS

Stroke patients in hospitals or communities.

METHODS

We undertook a systematic review and meta-analysis using articles available in 8 databases, including PubMed, The Cochrane Library, Web of Science, Embase, Chinese Biomedical Database (CBM), China National Knowledge Infrastructure Database (CNKI), Wanfang Database, and Weipu Database (VIP) from January 1990 to April 2022. Studies were quality rated using the Newcastle-Ottawa Scale and Agency for Healthcare Research and Quality tool.

RESULTS

A total of 24 studies involving 30,423 participants were identified. The prevalence of frailty and pre-frailty in stroke patients was 27% (95%CI: 0.23-0.31) and 47.9% (95%CI: 0.43-0.53). Female gender (OR = 1.76, 95%CI: 1.63-1.91), advanced age (MD = 6.73, 95%CI: 3.55-9.91), diabetes (OR = 1.34, 95%CI: 1.06-1.69), hyperlipidemia (OR = 1.46, 95%CI: 1.04-2.04), atrial fibrillation (OR = 1.36, 95%CI: 1.01-1.82), National Institutes of Stroke Scale (NIHSS) admission scores (MD = 2.27, 95%CI: 1.72-2.81) were risk factors of frailty in stroke patients.

CONCLUSIONS

Frailty was more prevalent in stroke patients. Female gender, advanced age, diabetes, hyperlipidemia, atrial fibrillation, and National Institutes of Stroke Scale (NIHSS) admission scores were identified as risk factors for frailty in stroke patients. In the future, medical staff should pay attention to the early screening of frailty in high-risk groups and provide information on its prevention.

The Allure of Big Data to Improve Stroke Outcomes: Review of Current Literature

PURPOSE OF REVIEW

To critically appraise literature on recent advances and methods using "big data" to evaluate stroke outcomes and associated factors.

RECENT FINDINGS

Recent big data studies provided new evidence on the incidence of stroke outcomes, and important emerging predictors of these outcomes. Main highlights included the identification of COVID-19 infection and exposure to a low-dose particulate matter as emerging predictors of mortality post-stroke. Demographic (age, sex) and geographical (rural vs. urban) disparities in outcomes were also identified. There was a surge in methodological (e.g., machine learning and validation) studies aimed at maximizing the efficiency of big data for improving the prediction of stroke outcomes. However, considerable delays remain between data generation and publication. Big data are driving rapid innovations in research of stroke outcomes, generating novel evidence for bridging practice gaps. Opportunity exists to harness big data to drive real-time improvements in stroke outcomes.

Prevalence and implications of frailty in acute stroke: systematic review & meta-analysis

BACKGROUND

frailty is common in older adults and associated with poor outcomes following illness. Although stroke is predominantly a disease of older people, our knowledge of frailty in stroke is limited. We aimed to collate the literature on acute stroke and frailty to estimate the prevalence of pre-stroke frailty and its associations with outcomes.

METHODS

paired researchers searched multidisciplinary electronic databases for papers describing frailty and acute stroke. We assessed risk of bias using Newcastle-Ottawa tools appropriate to study design. We created summary estimates of pre-stroke frailty using random effects models. We collated whether studies reported significant positive associations between frailty and clinical outcomes in adjusted models.

RESULTS

we included 14 studies (n = 27,210 participants). Seven studies (n = 8,840) used a frailty index approach, four studies (n = 14,924) used Hospital Frailty Risk Scores. Pooled prevalence of pre-stroke frailty was 24.6% (95% confidence interval, CI: 16.2-33.1%; low quality evidence, downgraded due to heterogeneity, bias). Combining frailty and pre-frailty (nine studies, n = 23,827), prevalence of any frailty syndrome was 66.8% (95%CI: 49.9-83.7%). Seven studies were at risk of bias, from participant selection or method of frailty assessment. Pre-stroke frailty was associated with all adverse outcomes assessed, including longer-term mortality (positive association in 6 of 6 studies reporting this outcome; odds ratio: 3.75 [95%CI: 2.41-5.70]), length of admission (3 of 4 studies) and disability (4 of 6 studies).

CONCLUSIONS

despite substantial heterogeneity, whichever way it is measured, frailty is common in patients presenting with acute stroke and associated with poor outcomes. This has implications for the design of stroke services and pathways.