Association of Pre-stroke Frailty With Prognosis of Elderly Patients With Acute Cerebral Infarction: A Cohort Study

Machine learning decision support model for discharge planning in stroke patients

BACKGROUND/AIM

Efficient discharge for stroke patients is crucial but challenging. The study aimed to develop early predictive models to explore which patient characteristics and variables significantly influence the discharge planning of patients, based on the data available within 24 h of admission.

DESIGN

Prospective observational study.

METHODS

A prospective cohort was conducted at a university hospital with 523 patients hospitalised for stroke. We built and trained six different machine learning (ML) models, followed by testing and tuning those models to find the best-suited predictor for discharge disposition, dichotomized into home and non-home. To evaluate the accuracy, reliability and interpretability of the best-performing models, we identified and analysed the features that had the greatest impact on the predictions.

RESULTS

In total, 523 patients met the inclusion criteria, with a mean age of 61 years. Of the patients with stroke, 30.01% had non-home discharge. Our model predicting non-home discharge achieved an area under the receiver operating characteristic curve of 0.95 and a precision of 0.776. After threshold was moved, the model had a recall of 0.809. Top 10 variables by importance were National Institutes of Health Stroke Scale (NIHSS) score, family income, Barthel index (BI) score, FRAIL score, fall risk, pressure injury risk, feeding method, depression, age and dysphagia.

CONCLUSION

The ML model identified higher NIHSS, BI, and FRAIL, family income, higher fall risk, pressure injury risk, older age, tube feeding, depression and dysphagia as the top 10 strongest risk predictors in identifying patients who required non-home discharge to higher levels of care. Modern ML techniques can support timely and appropriate clinical decision-making.

RELEVANCE TO CLINICAL PRACTICE

This study illustrates the characteristics and risk factors of non-home discharge in patients with stroke, potentially contributing to the improvement of the discharge process.

REPORTING METHOD

STROBE guidelines.

Genetic liability to frailty in relation to functional outcome after ischemic stroke

BACKGROUND

Frailty appears to be associated with unfavorable prognosis after stroke in observational studies, but the causality remains largely unknown.

AIMS

The aim of this study is to investigate the potential causal effect of frailty on functional outcome at 3 months after ischemic stroke using the Mendelian randomization (MR) framework.

METHODS

Genetic instruments for frailty index were identified in a genome-wide association study meta-analysis including 175,226 individuals of European descent. Corresponding genetic association estimates for functional outcome after ischemic stroke at 90 days were taken from the Genetic of Ischemic Stroke Functional Outcome (GISCOME) network of 6021 patients. We performed inverse-variance weighted MR as the main analyses, followed by several alternate methods and sensitivity analyses.

RESULTS

In univariable MR, we found evidence that genetically predicted higher frailty index (odds ratio (OR) = 5.12; 95% confidence interval (CI) = 1.31-20.09; p = 0.019) was associated with worse functional outcome (modified Rankin Scale score ⩾3) after ischemic stroke. In further multivariable MR adjusting for potential confounding traits including body mass index, C-reactive protein, inflammatory bowel disease, and smoking initiation, the overall patterns between genetic liability to frailty and poor functional outcome status remained. Sensitivity analyses with complementary methods and with model unadjusted for baseline stroke severity (OR = 4.19; 95% CI = 1.26-13.90; p = 0.019) yielded broadly concordant results.

CONCLUSIONS

The present MR study suggested a possible causal effect of frailty on poor functional outcome after ischemic stroke. Frailty might represent a potential target for intervention to improve recovery after ischemic stroke.

Functioning and recovery during stroke rehabilitation: a comparison between pre-stroke frail and non-frail patients

PURPOSE

Pre-stroke frailty in older adults is associated with adverse outcomes after stroke in community-based and hospital-based populations. The aim of our study was to investigate the prevalence of pre-stroke frailty among older stroke survivors receiving medical specialistic rehabilitation and its association with outcomes and recovery.

METHODS

Pre-stroke frailty was measured by the Groningen Frailty Indicator (GFI, score ≥ 4 indicates frailty) in patients ≥ 65 years receiving stroke medical specialistic rehabilitation. Baseline, follow-up and change (i.e. recovery) scores of the Barthel index (BI), Stroke Impact Scale (SIS) 'mobility', 'communication', and 'memory and thinking', Hospital Anxiety and Depression Scale (HADS) and the EuroQoL-5 dimensions (EQ-5D) were compared between frail and non-frail patients with a multivariable regression model adjusting for confounders.

RESULTS

Of 322 included patients (34.2% females, median age 70 years), 43 (13.4%) patients reported pre-stroke frailty. There were no differences in BI or in destination of discharge between pre-stroke frail and non-frail stroke survivors receiving inpatient rehabilitation. However, pre-stroke frailty was associated with worse follow-up scores for all other measures. Recovery in pre-stroke frail patients was less favorable compared to non-frail patients for SIS mobility, HADS subscales and EQ-5D index and visual analogue scale.

CONCLUSION

Pre-stroke frailty was present in a minority of older stroke survivors receiving medical specialistic rehabilitation. BI and destination of discharge did not differ. Nevertheless, pre-stroke frailty was associated with worse functioning at follow-up for most measures of health status and with smaller improvements in mobility, mood and quality of life.

Effect of admission in the stroke care unit versus intensive care unit on in-hospital mortality in patients with acute ischemic stroke

BACKGROUND/OBJECTIVE

Few reports have directly compared the outcomes of patients with acute ischemic stroke (AIS) who are managed in a stroke care unit (SCU) with those who are managed in an intensive care units (ICU). This large database study in Japan aimed to compare in-hospital mortality between patients with AIS admitted into SCU and those admitted into ICU.

METHODS

Patients with AIS who were admitted between April 1, 2014, and March 31, 2019, were selected from the administrative database and divided into the SCU and ICU groups. We calculated the propensity score to match groups for which the admission unit assignment was independent of confounding factors, including the modified Rankin scale (mRS) score. The primary outcome was in-hospital mortality, and secondary outcomes were the mRS score at discharge, length of stay (LOS), and total hospitalization cost.

RESULTS

Overall, 8,683 patients were included, and 960 pairs were matched. After matching, the in-hospital mortality rates of the SCU and ICU groups were not significantly different (5.9% vs. 7.9%, P = 0.106). LOS was significantly shorter (SCU = 20.9 vs. ICU = 26.2 days, P < 0.001) and expenses were significantly lower in the SCU group than in the ICU group (SCU = 1,686,588 vs. ICU = 1,998,260 yen, P < 0.001). mRS scores (score of 1-3 or 4-6) at discharge were not significantly different after matching. Stratified analysis showed that the in-hospital mortality rate was lower in the ICU group than in the SCU group among patients who underwent thrombectomy.

CONCLUSIONS

In-hospital mortality was not significantly different between the ICU and SCU groups, with significantly lower costs and shorter LOS in the SCU group than in the ICU group.

Evaluating the FRAIL Questionnaire as a Trigger for Palliative Care Consultation After Acute Stroke

The American Heart Association and the American Stroke Association jointly released guidelines stating that all patients with a new diagnosis of stroke should receive palliative care consultation starting in the acute phase of care. The purpose of this project was to increase palliative care consultation rates for patients after an acute stroke by using a frailty score to trigger a palliative care consult. Provider education on palliative care and a 5-question fatigue, resistance, ambulation, illnesses, and loss of weight (FRAIL) questionnaire was delivered by a presentation, handouts, and a follow-up email using previously developed content. Patients included adults admitted to the neuroscience critical care unit of a Midwestern comprehensive stroke center with an admission diagnosis of acute stroke (n = 120). The charge nurse completed the FRAIL questionnaire as a screening tool to trigger a palliative care consult. A survey was also distributed to providers (n = 54) to understand their knowledge, thoughts, and feelings toward palliative care. There was an increase in patients who received palliative care consultation from 14.9% to 21.7% after implementation of the FRAIL questionnaire. Also, providers felt better able to provide symptom management to patients after acute stroke. Further research is necessary to determine if the FRAIL survey is an adequate trigger for palliative care consultation.

Neutrophil-to-leukocyte ratio and admission glycemia as predictors of short-term death in very old elderlies with lobar intracerebral hemorrhage

BACKGROUND

The incidence of spontaneous intracerebral hemorrhage (SICH) is highest in very old elderlies (≥75 years). The increasing use of antithrombotic drugs is shifting the epidemiology of SICH towards predominance of lobar subtype, suggesting an incremented propensity of bleeding associated with underlying cerebral amyloid angiopathy. With population aging and antithrombotic use, a parallel raise of proportion of lobar SICH is occurring. Improvement of prognostication in this specific age group and SICH type is needed. Routine blood biomarkers can contribute to prediction of short-term mortality after SICH.

OBJECTIVE

Our aim was to investigate the contribution of routine blood biomarkers for short-term mortality (30-days) in elderly patients with lobar SICH.

METHODS

Retrospective analysis of consecutive 130 patients with ≥ 75 years and lobar SICH. The outcome was 30-day mortality. Logistic regression analysis was used to investigate whether admission routine biomarkers can be used as predictors.

RESULTS

The case fatality was 40.8%. Admission glycaemia level, neutrophil to lymphocyte ratio and mean platelet volume were significantly different between groups (p = 0.001, p = 0.024, p = 0.038, respectively). There was no significant difference in all other routine biomarkers. On multivariate analysis, admission higher mean BG level (odds ratio [OR]: 1.010, 95% confidence interval [CI]: 1.001-1.019, p = 0.026) and neutrophil to lymphocyte ratio (OR: 1.070, 95% CI: 1.008-1.136, p = 0.027) emerged as predictors.

CONCLUSION

In very old patients with lobar SICH, higher BG level and neutrophil to lymphocyte ratio are associated with increased risk of short-term death.

Morphology of paraspinal muscles in frail and non-frail older adults evaluated through FRAIL scale

BACKGROUND

Frailty is a condition characterized by the progressive deterioration of physiological functioning, which is closely related to adverse events. Multiple previous investigations applied frailty scales for spine research, and the purpose of this study is to investigate the differences in the morphology of the paraspinal muscles in frail and non-frail older adults evaluated through FRAIL scale.

METHODS

The sample of this retrospectively cross-sectional study consisted of individuals who were ≥ 60 years of age and with lumbar degenerative disease. We divided patients into two groups (0-2 = non-Frail, 3-5 = Frail) according to the FRAIL scale. The cross-sectional area (CSA) and percentage of the fatty infiltration (FI%) of the paraspinal muscles were compared between the two groups.

RESULTS

The fCSA (functional cross-sectional area) of the non-Frail group (32.78 [28.52, 38.28]) (cm²) was significantly greater than that of the Frail group (28.50 [24.11, 34.77]) (p < 0.001). The ES FI% (erector spinae fatty infiltration rate) (24.83 ± 6.61 vs. 29.60 ± 7.92, p < 0.001) and MF FI% (multifidus fatty infiltration rate) (31.68 ± 5.63 vs. 41.12 ± 7.04, p < 0.001) of the non-Frail group were significantly lower than that of Frail group.

CONCLUSIONS

The paraspinal muscles of elderly Frail patients screened by the FRAIL scale are worse than those of the non-Frail patients, and the ability of the FRAIL scale to distinguish paraspinal muscle morphology has important clinical significance.

Association between pre-stroke sarcopenia risk and stroke-associated infection in older people with acute ischemic stroke

Background

Stroke-associated infection (SAI) is a common complication after a stroke. The incidence of infection was higher in people with sarcopenia than in the general population. However, the relationship between pre-stroke sarcopenia risk and SAI in older patients has not been confirmed. This study aimed to investigate the association between pre-stroke sarcopenia risk and SAI in older patients with acute ischemic stroke (AIS).

Methods

This retrospective study was conducted by the Peking University People's Hospital. We evaluated the pre-stroke sarcopenia risk by applying the SARC-F questionnaire. Multivariate logistic regression was applied to explore the association between pre-stroke sarcopenia risk and SAI.

Results

A total of 1,002 elder patients with AIS (592 men; 72.9 ± 8.6 years) were enrolled in our study. Pre-stroke sarcopenia risk was found in 29.1% of the cohort. The proportion of patients with pre-stroke sarcopenia risk was larger in the SAI group than in the non-SAI group (43.2 vs. 25.3%, p   < 0.001). In multivariate logistic analysis, pre-stroke sarcopenia risk was shown to be independently associated with SAI (OR = 1.454, 95% CI: 1.008-2.097, p = 0.045) after adjusting for potential factors. This association remained consistent across the subgroups based on age, sex, body mass index, smoking status, drinking status, diabetes, hypertension, and dyslipidemia.

Conclusion

Pre-stroke sarcopenia risk was independently associated with SAI in older patients with AIS. Our findings highlight the significance of pre-stroke sarcopenia identification in the prevention and management of SAI in this population.