A systematic review of studies reporting multivariable models to predict functional outcomes after post-stroke inpatient rehabilitation

Effects of a nurse-led motor function rehabilitation training program for patients with ischemic stroke and family caregivers: study protocol for a randomized controlled trial

BACKGROUND

Both individuals and society bear a considerable burden from ischemic stroke (IS), not only do patients continue suffering from motor dysfunction after discharge from hospital, but their caregivers also undertake the principal responsibility of assisting them in reintegrating into the family and society. To better improve the IS patients' limb function and daily life activities, their caregivers should also be involved in the training of the motor function rehabilitation during the period transitioning from hospital back home. This study mainly aims to investigate the effects of a nurse-led training for IS patients and their family caregivers on the improvement of the patients' physical function and the burden of caregivers.

METHODS/DESIGN

A randomized controlled trial with blind assessment will be conducted in hospitals and during the follow-ups at home. Fifty-eight pairs of adults diagnosed with ischemic stroke and their primary caregivers will be included. Participants will be randomly given with (1) a nurse-led, home-based motor rehabilitation training participated by caregivers (intervention group) or (2) routine self-care (control group). Both groups will receive assessment and health guidance on the day of discharge, and the intervention group will receive an additional home-based training program and supervision. These two groups will be followed up every week after discharge. The primary results are drawn from the evaluation of physical function and caregiver-related burden, and the secondary results derived from statistics of the modified Barthel index, stroke-specific quality of life, and National Institutes of Health Stroke Scale. Differences between the two groups will be measured by two-way repeated measures ANOVA, considering the data at baseline and at 1-week and 4-week follow-up after training.

DISCUSSION

Results may provide novel and valuable information on the effects of this culturally appropriate, caregiver-involved, and home-based rehabilitation training on the physical function of IS patients and caregiver-related burden.

TRIAL REGISTRATION

Chinese Clinical Trial Registry (chictr.org.cn) ChiCTR2300078798. Registered on December 19, 2023.

Machine learning is an effective method to predict the 3-month prognosis of patients with acute ischemic stroke

Background and objectives

Upwards of 50% of acute ischemic stroke (AIS) survivors endure varying degrees of disability, with a recurrence rate of 17.7%. Thus, the prediction of outcomes in AIS may be useful for treatment decisions. This study aimed to determine the applicability of a machine learning approach for forecasting early outcomes in AIS patients.

Methods

A total of 659 patients with new-onset AIS admitted to the Department of Neurology of both the First and Second Affiliated Hospitals of Bengbu Medical University from January 2020 to October 2022 included in the study. The patient' demographic information, medical history, Trial of Org 10,172 in Acute Stroke Treatment (TOAST), National Institute of Health Stroke Scale (NIHSS) and laboratory indicators at 24 h of admission data were collected. The Modified Rankine Scale (mRS) was used to assess the 3-mouth outcome of participants' prognosis. We constructed nine machine learning models based on 18 parameters and compared their accuracies for outcome variables.

Results

Feature selection through the Least Absolute Shrinkage and Selection Operator cross-validation (Lasso CV) method identified the most critical predictors for early prognosis in AIS patients as white blood cell (WBC), homocysteine (HCY), D-Dimer, baseline NIHSS, fibrinogen degradation product (FDP), and glucose (GLU). Among the nine machine learning models evaluated, the Random Forest model exhibited superior performance in the test set, achieving an Area Under the Curve (AUC) of 0.852, an accuracy rate of 0.818, a sensitivity of 0.654, a specificity of 0.945, and a recall rate of 0.900.

Conclusion

These findings indicate that RF models utilizing general clinical and laboratory data from the initial 24 h of admission can effectively predict the early prognosis of AIS patients.

Does cognitive learning potential measured with the dynamic Wisconsin Card Sorting Test predict rehabilitation outcome in elderly patients post-stroke?

OBJECTIVE

To determine whether cognitive learning potential measured with the dynamic Wisconsin Card Sorting Test has added value in predicting rehabilitation outcome in elderly patients post-stroke after controlling for age, ADL independence at admission, global cognitive functioning and depressive symptoms.

METHODS

Participants were patients with stroke admitted to a geriatric rehabilitation unit. ADL independence (Barthel Index) at discharge was used as measure for rehabilitation outcome. Predictor variables included age, ADL independence at admission, global cognitive functioning (Montreal Cognitive Assessment), depressive symptoms (Geriatric Depression Scale) and cognitive learning potential measured with the dWCST.

RESULTS

Thirty participants were included. Bivariate analyses showed that rehabilitation outcome was significantly correlated with ADL independence at admission (r = 0.443, p = 0.014) and global cognitive functioning (r = 0.491, p = 0.006). Regression analyses showed that the dWCST was not an independent predictor of rehabilitation outcome. ADL independence at admission was the only significant predictor of rehabilitation outcome (beta = 0.480, p = 0.007).

CONCLUSIONS

Cognitive learning potential, measured with the dWCST has no added value in predicting rehabilitation outcome in elderly patients post-stroke. ADL independence at admission was the only significant predictor of rehabilitation outcome.

REGISTRATION NUMBER NETHERLANDS TRIAL REGISTER

Trial NL7947.

Prognostic Value of Dysphagia for Activities of Daily Living Performance and Cognitive Level after Stroke

Objectives

The purpose of this study was to examine the association between baseline dysphagia and the improvement of activities of daily living performance and cognitive level among inpatients after stroke.

Methods

This was a retrospective cohort study of patients undergoing convalescent rehabilitation after stroke. Dysphagia was assessed using the Food Intake LEVEL Scale. Outcomes were the motor and cognitive scores of the Functional Independence Measure (FIM) at discharge. Multiple regression analysis was performed to examine the association between dysphagia at admission and these outcomes.

Results

There were 499 participants with a median age of 74 years. A multiple regression analysis was carried out after adjusting for potential confounders including age and sex. Dysphagia at admission was independently and negatively associated with motor (β=-0.157, P<0.001) and cognitive (β=-0.066, P=0.041) FIM scores at discharge.

Conclusions

Baseline dysphagia in patients after stroke was negatively associated with improvement in performance of activities of daily living and cognitive level.

[Factors Modulating Motor Function Changes in Stroke Patients During Inpatient Neurological Rehabilitation]

PURPOSE

To identify factors that have an impact on the degree of functional improvements in stroke patients during inpatient neurological rehabilitation.

METHODS

Retrospective analysis of 398 stroke patients who participated in an inpatient Phase C rehabilitation (Barthel index between 30 and 70 points). We correlated changes in 3 physiotherapeutic assessments (transfer from sitting to standing; transfer from bed to (wheel)chair; climbing stairs) and 3 occupational therapeutic assessments (eating/drinking; dressing of the upper part of the body; object manipulation) with the factors age, gender, Barthel-Index at admission, time since stroke, length of stay in inpatient rehab, number and extent of therapies and ischemic versus hemorrhagic stroke. In addition, a stepwise regression analysis was performed.

RESULTS

The patient group showed significant improvements in all assessments. Length of stay in inpatient rehab and number/extent of therapies correlated with improvements of transfer from sitting to standing, transfer from bed to (wheel)chair, climbing stairs, and dressing of the upper part of the body. Number/extent of therapies also correlated with eating/drinking. Barthel-Index at admission was negatively correlated with transfer from sitting to standing, transfer from bed to (wheel)chair, and dressing of the upper part of the body. No correlation between changes of motor functions and age or gender or type of stroke (ischemic versus hemorrhagic) was found. Patients<3 months after stroke showed stronger improvements of transfer from sitting to standing, transfer from bed to (wheel)chair, climbing stairs, dressing of the upper part of the body, and object manipulation than patients>6 months after stroke. However, patients<3 months after stroke also stayed 10 days longer in inpatient rehab. The stepwise regression analysis identified the number of physiotherapies and Barthel-Index at admission as the most important factors for changes in transfer from sitting to standing and transfer from bed to (wheel)chair, number of physiotherapies and time since stroke for climbing stairs, number of occupational therapies for eating/drinking, number of occupational therapies and time since stroke for dressing the upper part of the body and number of occupational therapies and length of inpatient rehab for object manipulation.

CONCLUSION

In stroke patients, a higher number of therapies is associated with greater improvements of motor functions. Age, gender and type of stroke have no relevant impact on changes of motor functions during inpatient rehabilitation.

Predicting the functional outcome of intensive inpatient rehabilitation after stroke: results from the RIPS Study

BACKGROUND

The complexity of stroke sequelae, the heterogeneity of outcome measures and rehabilitation pathways, and the lack of extensively validated prediction models represent a challenge in predicting stroke rehabilitation outcomes.

AIM

To prospectively investigate a multidimensional set of variables collected at admission to inpatient post-stroke rehabilitation as potential predictors of the functional level at discharge.

DESIGN

Multicentric prospective observational study.

SETTING

Patients were enrolled in four Intensive Rehabilitation Units (IRUs).

POPULATION

Patients were consecutively recruited in the period December 2019-December 2020 with the following inclusion criteria: aged 18+, with ischemic/haemorrhagic stroke, and undergoing inpatient rehabilitation within 30 days from stroke.

METHODS

This is a multicentric prospective observational study. The rehabilitation pathway was reproducible and evidence-based. The functional outcome was disability in activities of daily living, measured by the modified Barthel Index (mBI) at discharge. Potential multidimensional predictors, assessed at admission, included demographics, event description, clinical assessment, functional and cognitive profile, and psycho-social domains. The variables statistically associated with the outcome in the univariate analysis were fed into a multivariable model using multiple linear regression.

RESULTS

A total of 220 patients were included (median [IQR] age: 80 [15], 112 women, 175 ischemic). Median mBI was 26 (43) at admission and 62.5 (52) at discharge. In the multivariable analysis younger age, along with better functioning, fewer comorbidities, higher cognitive abilities, reduced stroke severity, and higher motor functions at admission, remained independently associated with higher discharge mBI. The final model allowed a reliable prediction of discharge functional outcome (adjusted R2=77.2%).

CONCLUSIONS

The model presented in this study, based on easily collectable, reliable admission variables, could help clinicians and researchers to predict the discharge scores of the global functional outcome for persons enrolled in an evidence-based inpatient stroke rehabilitation program.

CLINICAL REHABILITATION IMPACT

A reliable outcome prediction derived from standardized assessment measures and validated treatment protocols could guide clinicians in the management of patients in the subacute phase of stroke and help improve the planning of the rehabilitation individualized project.

Explaining predictors of discharge destination assessed along the patients' acute stroke journey

INTRODUCTION

Accurate prediction of outcome destination at an early stage would help manage patients presenting with stroke. This study assessed the predictive ability of three machine learning (ML) algorithms to predict outcomes at four different stages as well as compared the predictive power of stroke scores.

METHODS

Patients presenting with acute stroke to the Canberra Hospital between 2015 and 2019 were selected retrospectively. 16 potential predictors and one target variable (discharge destination) were obtained from the notes. k-Nearest Neighbour (kNN) and two ensemble-based classification algorithms (Adaptive Boosting and Bootstrap Aggregation) were employed to predict outcomes. Predictive accuracy was assessed at each of the four stages using both overall and per-class accuracy. The contribution of each variable to the prediction outcome was evaluated by the ensemble-based algorithm and using the Relief feature selection algorithm. Various combinations of stroke scores were tested using the aforementioned models.

RESULTS

Of the three ML models, Adaptive Boosting demonstrated the highest accuracy (90%) at Stage 4 in predicting death while the highest overall accuracy (81.7%) was achieved by kNN (k=2/City-block distance). Feature importance analysis has shown that the most important features are the 24-hour Scandinavian Stroke Scale (SSS) and 24-hour National Institutes of Health Stroke Scale (NIHSS) scores, dyslipidaemia, hypertension and premorbid mRS score. For the initial and 24-hour scores, there was a higher correlation (0.93) between SSS scores than for NIHSS scores (0.81). Reducing the overall four scores to InitSSS/24hrNIHSS increased accuracy to 95% in predicting death (Adaptive Boosting) and overall accuracy to 85.4% (kNN). Accuracies at Stage 2 (pre-treatment, 11 predictors) were not far behind those at Stage 4.

CONCLUSION

Our findings suggest that even in the early stages of management, a clinically useful prediction regarding discharge destination can be made. Adaptive Boosting might be the best ML model, especially when it comes to predicting death. The predictors' importance analysis also showed that dyslipidemia and hypertension contributed to the discharge outcome even more than expected. Further, surprisingly using mixed score systems might also lead to higher prediction accuracies.

Association Between Social Determinants of Health and Communication Difficulties in Poststroke U.S. Hispanic and Non-Hispanic White Populations

PURPOSE

The relationship among ethnicity, social determinants of health (SDOH), and disparities in poststroke outcomes is complex, and the impact on communication difficulties is unclear. This study investigated the presence and nature of communication difficulties in poststroke non-Hispanic White (PsnHw) and Hispanic U.S. populations using population-level data.

METHOD

We performed a cross-sectional analysis of 2,861 non-Hispanic White and 353 Hispanic poststroke respondents included in the 2014-2018 National Health Interview Survey. Respondents self-reported difficulties communicating in their usual language, in addition to providing information relating to demographics and lifestyle, health care access and utilization, health status, and SDOH. We used univariate statistics, generalized linear models, and an exploratory mediation analysis, to characterize the pattern of differences between these cohorts, examine associations between variables and communication difficulties, and determine the potential intermediate role of cumulative SDOH on the likelihood of reporting communication difficulties.

RESULTS

Findings indicated a more challenging life context for the poststroke Hispanic population due to SDOH disparities. Poverty and Internet use were associated with greater and lower odds of communication difficulties for PsnHw, respectively. The mediation analysis showed that ethnicity significantly affected communication difficulties, but only when mediated by SDOH. SDOH accounted for approximately two thirds of the total effect on reporting communication difficulties.

CONCLUSIONS

This study underscores the need for uniform measures of SDOH in prospective research and for interventions aimed at mitigating health disparities through addressing disparities in SDOH. Future research should focus on evaluating the effectiveness of such strategies in diverse ethnic and socioeconomic poststroke populations.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.24521419.

Effect of rehabilitation motivation on improving activities of daily living in subacute stroke patients

OBJECTIVES

To determine the effect of rehabilitation motivation on activities of daily living improvement in subacute stroke patients starting intensive rehabilitation.

MATERIALS AND METHODS

This was a single-center cohort study involving patients with a subacute stroke who were admitted to or discharged from a Recovery Rehabilitation Unit between February 2021 and August 2022. Improvement in Activity of Daily Living was evaluated using the Functional Independence Measure. We calculated the corrected motor Functional Independence Measure effectiveness using its motor-related items at admission and discharge. The Behavioral Regulation in Exercise Questionnaire 2 was used to evaluate admission rehabilitation motivation, and the Relative Autonomy index was calculated. Hierarchical multiple regression analysis was used to examine the relationship between the corrected motor Functional Independence Measure effectiveness and the Relative Autonomy Index.

RESULTS

Eighty-six of the 231 patients (37.2 %) were included in the analysis. Hierarchical multiple regression analysis adjusted for demographic and clinical variables demonstrated that age, comorbidities, and Relative Autonomy Index were significantly associated with corrected motor Functional Independence Measure effectiveness (R2 = 0.423, p ≺ .001).

CONCLUSION

Motivation at intensive rehabilitation initiation in patients with a subacute stroke influences Activities of Daily Living improvement. These results may help develop rehabilitation programs aimed at improving Activities of Daily Living in patients with subacute strokes.

Tele-rehabilitation on independence in activities of daily living after stroke: A Matched Case-Control Study

OBJECTIVES

To compare independence in activities of daily living (ADLs) in post-acute patients with stroke following tele-rehabilitation and matched in-person controls.

MATERIALS AND METHODS

Matched case-control study. A total of 35 consecutive patients with stroke who followed tele-rehabilitation were compared to 35 historical in-person patients (controls) matched for age, functional independence at admission and time since injury to rehabilitation admission (<60 days). The tele-rehabilitation group was also compared to the complete cohort of historical controls (n=990). Independence in ADLs was assessed using the Functional Independence Measure (FIM) and the Barthel Index (BI). We formally compared FIM and BI gains calculated as discharge score - admission scores, efficiency measured as gains / length of stay and effectiveness defined as (discharge score-admission score)/ (maximum score-admission score). We analyzed the minimal clinically important difference (MCID) for FIM and BI.

RESULTS

The groups showed no significant differences in type of stroke (ischemic or hemorrhagic), location, severity, age at injury, length of stay, body mass index, diabetes, dyslipidemia, hypertension, aphasia, neglect, affected side of the body, dominance or educational level. The groups showed no significant differences in gains, efficiency nor effectiveness either using FIM or Barthel Index. We identified significant differences in two specific BI items (feeding and transfer) in favor of the in-person group. No differences were observed in the proportion of patients who achieved MCID.

CONCLUSIONS

No significant differences were seen between total ADL scores for tele-rehabilitation and in-person rehabilitation. Future research studies should analyze a combined rehabilitation approach that utilizes both models.

Outcome of 1939 traumatic brain injury patients from road traffic accidents: Findings from specialist medical reports in a low to middle income country (LMIC)

OBJECTIVE

Road traffic accident (RTA) is the major cause of traumatic brain injury (TBI) in developing countries and affects mostly young adult population. This research aimed to describe the factors predicting functional outcome after TBI caused by RTA in a Malaysian setting.

METHODS

This was a retrospective cross-sectional study conducted on specialist medical reports written from 2009 to 2019, involving patients who survived after TBI from RTA. The functional outcome was assessed using the Glasgow Outcome Scale-Extended (GOSE). Factors associated with good outcome were analysed via logistic regression analysis. Multivariate logistic regression analysis was used to derive the best fitting Prediction Model and split-sample cross-validation was performed to develop a prediction model.

RESULTS

A total of 1939 reports were evaluated. The mean age of the study participants was 32.4 ± 13.7 years. Most patients were male, less than 40, and with average post RTA of two years. Good outcome (GOSE score 7 & 8) was reported in 30.3% of the patients. Factors significantly affecting functional outcome include age, gender, ethnicity, marital status, education level, severity of brain injury, neurosurgical intervention, ICU admission, presence of inpatient complications, cognitive impairment, post-traumatic headache, post traumatic seizures, presence of significant behavioural issue; and residence post discharge (p<0.05). After adjusting for confounding factors, prediction model identified age less than 40, mild TBI, absence of post traumatic seizure, absence of behaviour issue, absence of cognitive impairment and independent living post TBI as significant predictors of good functional outcome post trauma. Discrimination of the model was acceptable (C-statistic, 0.67; p<0.001, 95% CI: 0.62-0.73).

CONCLUSION

Good functional outcome following TBI due to RTA in this study population is comparable to other low to middle income countries but lower than high income countries. Factors influencing outcome such as seizure, cognitive and behavioural issues, and independent living post injury should be addressed early to achieve favourable long-term outcomes.

Comparing the contribution of each clinical indicator in predictive models trained on 980 subacute stroke patients: a retrospective study

Post-stroke disability affects patients' lifestyles after discharge, and it is essential to predict functional recovery early in hospitalization to allow time for appropriate decisions. Previous studies reported important clinical indicators, but only a few clinical indicators were analyzed due to insufficient numbers of cases. Although review articles can exhaustively identify many prognostic factors, it remains impossible to compare the contribution of each predictor. This study aimed to determine which clinical indicators contribute more to predicting the functional independence measure (FIM) at discharge by comparing standardized coefficients. In this study, 980 participants were enrolled to build predictive models with 32 clinical indicators, including the stroke impairment assessment set (SIAS). Trunk function had the most significant standardized coefficient of 0.221. The predictive models also identified easy FIM sub-items, SIAS, and grip strength on the unaffected side as having positive standardized coefficients. As for the predictive accuracy of this model, R² was 0.741. This is the first report that included FIM sub-items separately in post-stroke predictive models with other clinical indicators. Trunk function and easy FIM sub-items were included in the predictive model with larger positive standardized coefficients. This predictive model may predict prognosis with high accuracy, fewer clinical indicators, and less effort to predict.

Essential information for neurorecovery clinical trial design: trajectory of global disability in first 90 days post-stroke in patients discharged to acute rehabilitation facilities

BACKGROUND

Many stroke recovery interventions are most beneficial when started 2-14d post-stroke, a time when patients become eligible for inpatient rehabilitation facilities (IRF) and neuroplasticity is often at its peak. Clinical trials focused on recovery need to expand the time from this plasticity to later outcome timepoints.

METHODS

The disability course of patients with acute ischemic stroke (AIS) and intracranial hemorrhage (ICH) enrolled in Field Administration of Stroke Therapy Magnesium (FAST-MAG) Trial with moderate-severe disability (modified Rankin Scale [mRS] 3-5) on post-stroke day4 who were discharged to IRF 2-14d post-stroke were analyzed.

RESULTS

Among 1422 patients, 446 (31.4%) were discharged to IRFs, including 23.6% within 2-14d and 7.8% beyond 14d. Patients with mRS 3-5 on day4 discharged to IRFs between 2-14d accounted for 21.7% (226/1041) of AIS patients and 28.9% (110/381) of ICH patients, (p < 0.001). Among these AIS patients, age was 69.8 (± 12.7), initial NIHSS median 8 (IQR 4-12), and day4 mRS = 3 in 16.4%, mRS = 4 in 50.0%, and mRS = 5 in 33.6%. Among these ICH patients, age was 62.4 (± 11.7), initial NIHSS median 9 (IQR 5-13), day 4 mRS = 3 in 9.4%, mRS = 4 in 45.3%, and mRS = 5 in 45.3% (p < 0.01 for AIS vs ICH). Between day4 to day90, mRS improved ≥ 1 levels in 72.6% of AIS patients vs 77.3% of ICH patients, p = 0.3. For AIS, mRS improved from mean 4.17 (± 0.7) to 2.84 (± 1.5); for ICH, mRS improved from mean 4.35 (± 0.7) to 2.75 (± 1.3). Patients discharged to IRF beyond day14 had less improvement on day90 mRS compared with patients discharged between 2-14d.

CONCLUSIONS

In this acute stroke cohort, nearly 1 in 4 patients with moderate-severe disability on post-stroke day4 were transferred to IRF within 2-14d post-stroke. ICH patients had nominally greater mean improvement on mRS day90 than AIS patients. This course delineation provides a roadmap for future rehabilitation intervention studies.

Improvement of predictive accuracies of functional outcomes after subacute stroke inpatient rehabilitation by machine learning models

OBJECTIVES

Stepwise linear regression (SLR) is the most common approach to predicting activities of daily living at discharge with the Functional Independence Measure (FIM) in stroke patients, but noisy nonlinear clinical data decrease the predictive accuracies of SLR. Machine learning is gaining attention in the medical field for such nonlinear data. Previous studies reported that machine learning models, regression tree (RT), ensemble learning (EL), artificial neural networks (ANNs), support vector regression (SVR), and Gaussian process regression (GPR), are robust to such data and increase predictive accuracies. This study aimed to compare the predictive accuracies of SLR and these machine learning models for FIM scores in stroke patients.

METHODS

Subacute stroke patients (N = 1,046) who underwent inpatient rehabilitation participated in this study. Only patients' background characteristics and FIM scores at admission were used to build each predictive model of SLR, RT, EL, ANN, SVR, and GPR with 10-fold cross-validation. The coefficient of determination (R2) and root mean square error (RMSE) values were compared between the actual and predicted discharge FIM scores and FIM gain.

RESULTS

Machine learning models (R2 of RT = 0.75, EL = 0.78, ANN = 0.81, SVR = 0.80, GPR = 0.81) outperformed SLR (0.70) to predict discharge FIM motor scores. The predictive accuracies of machine learning methods for FIM total gain (R2 of RT = 0.48, EL = 0.51, ANN = 0.50, SVR = 0.51, GPR = 0.54) were also better than of SLR (0.22).

CONCLUSIONS

This study suggested that the machine learning models outperformed SLR for predicting FIM prognosis. The machine learning models used only patients' background characteristics and FIM scores at admission and more accurately predicted FIM gain than previous studies. ANN, SVR, and GPR outperformed RT and EL. GPR could have the best predictive accuracy for FIM prognosis.

Self-reported life-space mobility in the first year after ischemic stroke: longitudinal findings from the MOBITEC-Stroke project

BACKGROUND

Life-space mobility is defined as the size of the area in which a person moves about within a specified period of time. Our study aimed to characterize life-space mobility, identify factors associated with its course, and detect typical trajectories in the first year after ischemic stroke.

METHODS

MOBITEC-Stroke (ISRCTN85999967; 13/08/2020) was a cohort study with assessments performed 3, 6, 9 and 12 months after stroke onset. We applied linear mixed effects models (LMMs) with life-space mobility (Life-Space Assessment; LSA) as outcome and time point, sex, age, pre-stroke mobility limitation, stroke severity (National Institutes of Health Stroke Scale; NIHSS), modified Rankin Scale, comorbidities, neighborhood characteristics, availability of a car, Falls Efficacy Scale-International (FES-I), and lower extremity physical function (log-transformed timed up-and-go; TUG) as independent variables. We elucidated typical trajectories of LSA by latent class growth analysis (LCGA) and performed univariate tests for differences between classes.

RESULTS

In 59 participants (mean age 71.6, SD 10.0 years; 33.9% women), mean LSA at 3 months was 69.3 (SD 27.3). LMMs revealed evidence (p ≤ 0.05) that pre-stroke mobility limitation, NIHSS, comorbidities, and FES-I were independently associated with the course of LSA; there was no evidence for a significant effect of time point. LCGA revealed three classes: "low stable", "average stable", and "high increasing". Classes differed with regard to LSA starting value, pre-stroke mobility limitation, FES-I, and log-transformed TUG time.

CONCLUSION

Routinely assessing LSA starting value, pre-stroke mobility limitation, and FES-I may help clinicians identify patients at increased risk of failure to improve LSA.

Impacts of increases and decreases of drugs on rehabilitation outcomes of subacute stroke patients

OBJECTIVE

To examine changes in drugs for subacute stroke patients and elucidate the impact of medications on rehabilitation outcomes.

MATERIALS AND METHODS

A total of 295 subacute stroke patients who were admitted to the convalescent rehabilitation ward between June 2018 and May 2019 were included. Polypharmacy was defined as five or more drugs at admission. The primary outcome was the Functional Independence Measure Total score (FIM-T) at discharge. Multiple regression analysis was performed to examine the relationships between the FIM-T at discharge and drug changes or other factors. This study was conducted in two stages. The first analysis included all stroke patients, and the second analysis included only stroke patients with polypharmacy.

RESULTS

On multiple regression analysis, the number of drugs at admission (β=-0.628) was associated with FIM-T at discharge of all stroke patients. Furthermore, the number of additional drugs during hospitalization (β=-1.964) was associated with FIM-T at discharge in the 176 stroke patients with polypharmacy.

CONCLUSION

This study suggested that the number of drugs at admission and the addition of drugs during hospitalization might have a negative impact on the rehabilitation outcomes of subacute stroke patients.

Regression-based prognostic models for functional independence after postacute brain injury rehabilitation are not transportable: a systematic review

BACKGROUND AND OBJECTIVES

To identify and summarize validated multivariable prognostic models for the Functional Independence Measure® (FIM®) at discharge from post-acute inpatient rehabilitation in adults with acquired brain injury (ABI).

METHODS

This review was conducted based on the recommendations of the Cochrane Prognosis Methods Group and adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Three databases were systematically searched in May 2021 and updated in April 2022. Main inclusion criteria were: a) adult patients with ABI, b) validated multivariable prognostic model, c) time of prognostication within 1-week of admission to post-acute rehabilitation, and d) outcome was the FIM® at discharge from post-acute rehabilitation.

RESULTS

The search yielded 3,169 unique articles. Three articles fulfilled the inclusion criteria, accounting for n = 6 internally and n = 2 externally validated prognostic models. Discrimination was estimated as an area under the curve between 0.76 and 0.89. Calibration was deemed to be assessed insufficiently. The included models were judged to be of high risk of bias.

CONCLUSION

Current prognostic models for the FIM® in post-acute rehabilitation for patients with ABI lack the methodological rigor to support clinical use outside the development setting. Future studies addressing functional independence should ensure appropriate model validation and conform to uniform reporting standards for prognosis research.

The predictive role of fatigue and neuropsychological components on functional outcomes in COVID-19 after a multidisciplinary rehabilitation program

OBJECTIVE

To verify the impact of altered cognitive functioning and higher levels of mental fatigue, both reported after coronavirus disease 2019 (COVID-19), on rehabilitation treatment outcomes.

METHODS

In this real-practice retrospective pre-post intervention cohort study, cognitive functioning, measured through standardized neuropsychological measures, and individual levels of fatigue, depression and anxiety symptoms, were evaluated at admission to a rehabilitation program in individuals who had been hospitalized for COVID-19. The rehabilitation program effectiveness was measured through the Functional Independence Measure.

RESULTS

Among the patient sample (n = 66), 87.88% reported experiencing high levels of fatigue at admission, while 16.67% reported depressive symptoms, and 22.73% reported anxiety symptoms. After rehabilitation, the sample displayed a significant decrease in the level of disability, in both the motor and cognitive subscales. Neuropsychological and psychological functioning did not play a predictive role. The 45 patients who received mechanical ventilation during intensive care, representing 68.18% of the sample, benefited more from rehabilitation treatment.

CONCLUSIONS

The results support the importance of an early rehabilitation program after COVID-19 infection, independent of the initial neuropsychological and psychological functioning. Respiratory assistance may represent a crucial factor for short-term neuropsychological disease after-effects. Future studies on the long-term neuropsychological effect of COVID-19 infection on individual levels of disability are necessary.

Inpatient Rehabilitation After Acute Severe Stroke: Predictive Value of the National Institutes of Health Stroke Scale Among Other Potential Predictors for Discharge Destination

Background

Research focusing on predictors for discharge destination after rehabilitation of inpatients recovering from severe stroke is scarce. The predictive value of rehabilitation admission NIHSS score among other potential predictors available on admission to rehabilitation has not been studied.

Aim

The aim of this retrospective interventional study was to determine the predictive accuracy of 24 hours and rehabilitation admission NIHSS scores among other potential socio-demographic, clinical and functional predictors for discharge destination routinely collected on admission to rehabilitation.

Material and Methods

On a university hospital specialized inpatient rehabilitation ward 156 consecutive rehabilitants with 24 hours NIHSS score ⩾15 were recruited. On admission to rehabilitation, routinely collected variables potentially associated with discharge destination (community vs institution) were analyzed using logistic regression.

Results

70 (44.9%) of rehabilitants were discharged to community, and 86 (55.1%) were discharged to institutional care. Those discharged home were younger and more often still working, had less often dysphagia/tube feeding or DNR decision in the acute phase, shorter time from stroke onset to rehabilitation admission, less severe impairment (NIHSS score, paresis, neglect) and disability (FIM score, ambulatory ability) on admission, and faster and more significant functional improvement during the in-stay than those institutionalized.

Conclusion

The most influential independent predictors for community discharge on admission to rehabilitation were lower admission NIHSS score, ambulatory ability and younger age, NIHSS being the most powerful. The odds of being discharged to community decreased with 16.1% for every 1 point increase in NIHSS. The 3-factor model explained 65.7% of community discharge and 81.9% of institutional discharge, the overall predictive accuracy being 74.7%. The corresponding figures for admission NIHSS alone were 58.6%, 70.9% and 65.4%.

Evaluation of the predictive factors of the short-term effects of a multidisciplinary rehabilitation in COVID-19 survivors

OBJECTIVE

Functional impairments after coronavirus disease 2019 (COVID-19) constitute a major concern in rehabilitative settings; however, evidence assessing the efficacy of rehabilitation programs is lacking. The aim of this study was to verify the clinical characteristics that may represent useful predictors of the short-term effectiveness of multidisciplinary rehabilitation.

METHODS

In this real-practice retrospective pre-post intervention cohort study, the short-term effectiveness of a multidisciplinary patient-tailored rehabilitation program was assessed through normalized variations in the Functional Independence Measure in post-acute care patients who had overcome severe COVID-19. Biochemical markers, motor and nutritional characteristics, and the level of comorbidity were evaluated as predictors of functional outcome. Length of stay in the rehabilitation ward was also considered.

RESULTS

Following rehabilitation, all participants (n = 53) reported a significant decrease in the level of disability in both motor and cognitive functioning. However, neither motor and nutritional characteristics nor comorbidities played a significant role in predicting the overall positive change registered after rehabilitation.

CONCLUSIONS

The results support the existing sparse evidence addressing the importance of an early rehabilitation program for patients who received intensive care and post-acute care due to severe COVID-19.

Clinical Items for Geriatric Patients with Post-Stroke at Discharge or Transfer after Rehabilitation Therapy in a Chronic-Phase Hospital: A Retrospective Pilot Study

Clinical factors related to destination after rehabilitation therapy for geriatric patients with post-stroke in chronic-phase hospitals have not been elucidated. This study analyzed the clinical characteristics of geriatric patients with post-stroke at discharge/transfer after rehabilitation therapy in a chronic-phase hospital. Fifty-three patients (20 men, 33 women; mean age 81.36 ± 8.14 years) were recruited (the period analyzed: October 2013−March 2020). Clinical data were statistically analyzed among patients discharged to homes or facilities for older adults or transferred to another hospital. In addition, we analyzed the clinical items at discharge and transfer after rehabilitation therapy using a decision tree analysis. Twelve patients were discharged, eighteen were discharged to facilities for older adults, and twenty-three were transferred to another hospital. There were significant differences in the modified Rankin Scale, admission dates, functional independence measure (FIM) score, and Barthel Index score in the three groups (p < 0.05). Patients with motor subtotal functional independence scores of ≥14 (chronologically improved ≥5) after rehabilitation therapy for <291 days were more likely to be discharged home. Patients in a chronic-phase hospital who improved within a limited period were discharged to their homes, whereas those who were bedridden tended to be transferred to another hospital.

Discharge Rehabilitation Measures Predict Activity Limitations in Patients With Stroke 6 Months After Inpatient Rehabilitation

OBJECTIVE

The aim of this study was to identify rehabilitation measures at discharge from acute inpatient stroke rehabilitation that predict activity limitations at 6 mos postdischarge.

DESIGN

This is a retrospective analysis of a prospective, longitudinal, observational cohort study. It was conducted in an acute inpatient rehabilitation unit at an urban, academic medical center. Activity limitations in patients ( N = 141) with stroke of mild-moderate severity were assessed with the activity measure for post-acute care at inpatient stroke rehabilitation discharge and 6-mo follow-up. Rehabilitation measures at discharge were investigated as predictors for activity limitations at 6 mos.

RESULTS

Measures of balance (Berg Balance Scale), functional limitations in motor-based activities (functional independence measure-motor subscore), and motor impairment (motricity index), in addition to discharge activities measure for post-acute care scores, strongly predicted activity limitations in basic mobility and daily activities at 6 mos (51% and 41% variance explained, respectively). Functional limitations in cognition (functional independence measure-cognitive subscore) and executive function impairment (Trail Making Test-part B), in addition to the discharge activities measure for post-acute care score, modestly predicted limitations in cognitively based daily activities at 6 mos (12% of variance).

CONCLUSIONS

Standardized rehabilitation measures at inpatient stroke rehabilitation discharge can predict future activity limitations, which may improve prediction of outcome post-stroke and aid in postdischarge treatment planning.

Machine learning is an effective method to predict the 90-day prognosis of patients with transient ischemic attack and minor stroke

Objective

We aimed to investigate factors related to the 90-day poor prognosis (mRS≥3) in patients with transient ischemic attack (TIA) or minor stroke, construct 90-day poor prognosis prediction models for patients with TIA or minor stroke, and compare the predictive performance of machine learning models and Logistic model.

Method

We selected TIA and minor stroke patients from a prospective registry study (CNSR-III). Demographic characteristics,smoking history, drinking history(≥20g/day), physiological data, medical history,secondary prevention treatment, in-hospital evaluation and education,laboratory data, neurological severity, mRS score and TOAST classification of patients were assessed. Univariate and multivariate logistic regression analyses were performed in the training set to identify predictors associated with poor outcome (mRS≥3). The predictors were used to establish machine learning models and the traditional Logistic model, which were randomly divided into the training set and test set according to the ratio of 70:30. The training set was used to construct the prediction model, and the test set was used to evaluate the effect of the model. The evaluation indicators of the model included the area under the curve (AUC) of the discrimination index and the Brier score (or calibration plot) of the calibration index.

Result

A total of 10967 patients with TIA and minor stroke were enrolled in this study, with an average age of 61.77 ± 11.18 years, and women accounted for 30.68%. Factors associated with the poor prognosis in TIA and minor stroke patients included sex, age, stroke history, heart rate, D-dimer, creatinine, TOAST classification, admission mRS, discharge mRS, and discharge NIHSS score. All models, both those constructed by Logistic regression and those by machine learning, performed well in predicting the 90-day poor prognosis (AUC >0.800). The best performing AUC in the test set was the Catboost model (AUC=0.839), followed by the XGBoost, GBDT, random forest and Adaboost model (AUCs equal to 0.838, 0, 835, 0.832, 0.823, respectively). The performance of Catboost and XGBoost in predicting poor prognosis at 90-day was better than the Logistic model, and the difference was statistically significant(P<0.05). All models, both those constructed by Logistic regression and those by machine learning had good calibration.

Conclusion

Machine learning algorithms were not inferior to the Logistic regression model in predicting the poor prognosis of patients with TIA and minor stroke at 90-day. Among them, the Catboost model had the best predictive performance. All models provided good discrimination.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01672-z.

Sarcopenia affects Functional Independence Measure motor scores in elderly patients with stroke

OBJECTIVES

There is no unified view of the relationship between sarcopenia and the activities of daily living (ADL) in stroke patients. This study aimed to determine whether sarcopenia affects the ADL in elderly patients with stroke.

MATERIALS AND METHODS

This case-control study included 472 stroke patients aged ≥ 65 years who were admitted to the convalescent rehabilitation ward. Sarcopenia was defined as a decrease in both the skeletal muscle mass index and handgrip strength, based on the Asian Working Group for Sarcopenia 2019 criteria cut-off, which was assessed on admission. ADL was assessed using the Functional Independence Measure-motor (FIM-m) score at discharge. The Charlson comorbidity index, Mini Nutritional Assessment-Short Form, Brunnstrom recovery stage of the upper limb, Brunnstrom recovery stage of the lower limb and total amount of rehabilitation during hospitalization were evaluated as confounding factors. To clarify whether sarcopenia affects the ADL in patients with stroke, we conducted a multiple regression analysis with the presence of sarcopenia as the independent variable and FIM-m at discharge as the objective variable.

RESULTS

The final analysis included 283 patients; among them, 163 (57.6%) patients had sarcopenia at the time of admission to the convalescent rehabilitation ward. In the multiple regression analysis, sarcopenia was independently associated with FIM-m at hospital discharge, even after adjusting for confounders (β = -0.100, p = 0.034).

CONCLUSIONS

Sarcopenia at admission in elderly patients with stroke affected the FIM-m at discharge, even after adjusting for multiple confounders.

Validity of the Controlling Nutritional Status score as a Nutritional Assessment Tool early after stroke

Malnutrition is relatively common in stroke survivors and it also affects weight loss and muscle strength. Various nutritional assessment tools have been used to monitor changes in nutritional status. Among such tools, the Controlling Nutritional Status (CONUT) score is a convenient and cost-effective index calculated from serum albumin level, total peripheral lymphocyte count, and total cholesterol level. This study investigated the prognostic role of malnutrition, as assessed by the CONUT scoring system. We hypothesized that malnutrition negatively affects outcomes as expressed by Functional Independence Measure (FIM) motor or Berg Balance Scale (BBS) change in stroke patients. This was a retrospective cohort study involving 117 individuals including first-time subacute stroke inpatients from March 2017 to February 2020. All participants were evaluated with BBS and FIM. We used multiple linear regression analysis with backward stepwise selection to examine the association between CONUT and changes during rehabilitation. After adjusting for independent predictors, we found the CONUT score to be associated with FIM motor (B = -1.848 ± 5.811, P < 0.001) and BBS change (B = -2.035 ± 0.424, P < 0.001). The present study showed that the malnutritional status calculated by the CONUT score at admission might help to predict the functional outcomes of stroke patients. The CONUT score is a comprehensive and feasible marker that could provide information for the nutritional management of stroke patients to significantly improve their clinical outcomes.

Functional Independence predicts patients with stroke more likely to be discharged to the community after inpatient rehabilitation

BACKGROUND

Functional domain predictors of discharge destination following inpatient rehabilitation for stroke have not been thoroughly identified.

OBJECTIVES

1) Determine the relationships between intrinsic variables (demographic; comorbidities; functional independence at admission to and at discharge from an inpatient rehabilitation facility (IRF)) and discharge to home. 2) Determine cut scores for Functional Independence Measure® (FIM) subscales and domains that predict discharge to the community.

METHODS

This study was a secondary analysis of a large, multi-IRF dataset from the Uniform Data System for Medical Rehabilitation. Participants were adults with stroke who were discharged from an IRF in 2019 (n = 92,153).

RESULTS

Correlations with discharge to the community were strongest for discharge FIM scores (r = 0.330 to 0.580), followed by admission FIM scores (r = 0.245 to 0.411), which were stronger than the demographic and comorbidity variables (r = 0.005 to 0.110). Logistic regression analysis indicated 5 of 6 FIM domains (Social Cognition, Self-care, Sphincter, Transfer, and Locomotion) scored at admission and at discharge were predictive of discharge home. Receiver operating characteristic curve analyses determined the best cut point for each domain. For each FIM measure, the area under the curve was greater when the measure was obtained at discharge than it was at admission.

CONCLUSIONS

Clinicians may consider the cut points presented for each domain at admission and at discharge when setting goals or making recommendations for patients with stroke who aspire to a discharge from an IRF to a community setting.

Predicting Ischemic Stroke Outcome Using Deep Learning Approaches

Predicting functional outcomes after an Ischemic Stroke (IS) is highly valuable for patients and desirable for physicians. This facilitates physicians to set reasonable goals for patients and cooperate with patients and relatives effectively, and furthermore to reach common after-stroke care decisions for recovery and make exercise plans to facilitate rehabilitation. The objective of this research is to apply three current Deep Learning (DL) approaches for 6-month IS outcome predictions, using the openly accessible International Stroke Trial (IST) dataset. Furthermore, another objective of this research is to compare these DL approaches with machine learning (ML) for performing in clinical prediction. After comparing various ML methods (Deep Forest, Random Forest, Support Vector Machine, etc.) with current DL frameworks (CNN, LSTM, Resnet), the results show that DL doesn’t outperform ML significantly. DL methods and reporting used for analyzing structured medical data should be developed and improved.

Effects of Neuromuscular Electrical Stimulation Combined with Repetitive Transcranial Magnetic Stimulation on Upper Limb Motor Function Rehabilitation in Stroke Patients with Hemiplegia

OBJECTIVE

To investigate the effect of neuromuscular electrical stimulation (NMES) combined with repetitive transcranial magnetic stimulation (rTMS) on upper limb motor dysfunction in stroke patients with hemiplegia.

METHODS

A total of 240 stroke patients with hemiplegia who met the inclusion criteria were selected and randomly divided into 4 groups (60 cases in each group): control group, NMES group, rTMS group, and NMES + rTMS group. Before treatment and 4 weeks after treatment, we evaluated and compared the results including Fugl-Meyer assessment of upper extremity (FMA-UE) motor function, modified Barthel index (MBI), modified Ashworth scale (MAS), and motor nerve electrophysiological results among the 4 groups.

RESULTS

Before treatment, there was no significant difference in the scores of FMA-UE, MBI, MAS, and motor nerve electrophysiological indexes among the four groups, with comparability. Compared with those before treatment, the scores of the four groups were significantly increased and improved after treatment. And the score of the NMES + rTMS group was notably higher than those in the other three groups.

CONCLUSION

NMES combined with rTMS can conspicuously improve the upper extremity motor function and activities of daily life of stroke patients with hemiplegia, which is worthy of clinical application and promotion.

Functional Independence Measure Subtypes among Inpatients with Subacute Stroke: Classification via Latent Class Analysis

Objectives:

Using Functional Independence Measure (FIM) records, this study used latent class analysis (LCA) to clarify the structure of activities of daily living (ADL) status in patients following stroke.

Methods:

In this retrospective, single-center study, we extracted the medical records of patients with stroke who were admitted to a rehabilitation hospital in Japan between April 2018 and March 2020. LCA was used to determine classes of ADL status based on response patterns in FIM items converted from the original seven levels to three levels: Complete Dependence, FIM1–2; Modified Dependence, FIM3–5; Independence, FIM6–7. We compared the length of stay and discharge destinations among subgroups of patients with different ADL status at admission.

Results:

From 373 patients, 1592 FIM records were analyzed. These were classified into six ADL status classes based on “Complete Dependence,” “Modified Dependence,” and “Independence” in the motor and cognitive domains. Significant differences were observed among the six admission ADL subgroups for the length of stay (median values in patient subgroups based on admission ADL status: 126, 146, 90, 65, 44, and 29 days in the Motor Complete/Cognitive Complete, Motor Complete/Cognitive Modified, Motor Modified/Cognitive Modified, Motor Modified/Cognitive Independent, Motor Independent/Cognitive Modified, and Motor Independent/Cognitive Independent groups, respectively) and discharge destinations (patients discharged home: 27%, 62%, 81%, 92%, 95%, and 98%, respectively, and to acute care hospitals: 18%, 14%, 8%, 8%, 2%, and 2%, respectively).

Conclusions:

LCA successfully stratified ADL status in patients with stroke undergoing rehabilitation and may aid in determining an appropriate treatment regimen.

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.

Assessment, goal setting, and botulinum neurotoxin a therapy in the management of post-stroke spastic movement disorder: updated perspectives on best practice

INTRODUCTION

Post-stroke spastic movement disorder (PS-SMD) appears up to 20% in the first week following stroke and 40% in the chronic phase. It may create major hurdles to overcome in early stroke rehabilitation and as one relevant factor that reduces quality of life to a major degree in the chronic phase.

AREAS COVERED

In this review, we discuss predictors,early identification, clinical assessments, goal setting, and management in multiprofessional team, including Botulinum neurotoxin A (BoNT-A) injection for early and chronic management of PS-SMD.

EXPERT OPINION

The earlier PS-SMD is recognized and managed, the better the outcome will be. The comprehensive management in the subacute or chronic phase of PS-SMD with BoNT-A injections requires detailed assessment, patient-centered goal setting, technical-guided injection, effective dosing of BoNT-A per site, muscle, and session and timed adjunctive treatment, delivered in a multi-professional team approach in conjunction with physical treatment. Evidence-based data showed BoNT-A injections are safe and effective in managing focal, multifocal, segmental PS-SMD and its complications. If indicated, BoNT-A therapy should be accompanied with adjunctive treatment in adequate time slots. BoNT-A could be added to oral, intrathecal, and surgical treatment in severe multisegmental or generalized PS-SMD to reach patient/caregiver's goals, especially in chronic PS-SMD.

Young individuals with stroke in rehabilitation: a cohort study

Stroke in younger populations is a public health crisis and the prevalence is rising. Little is known about the progress of younger individuals with stroke in rehabilitation. Characterization of the course and speed of recovery is needed so that rehabilitation professionals can set goals and make decisions. This was a cohort study with data extracted from electronic medical records. Participants were 408 individuals diagnosed with stroke who participated in inpatient rehabilitation in an urban, academic medical center in the USA. The main predictor was age which was categorized as (18-44, 45-64, 65-74 and 75+). Outcomes included baseline-adjusted discharge functional independence measure (FIM) scores and FIM efficiency. In linear regression models for FIM scores, the reference category was the youngest age group. The oldest group was discharged with significantly lower FIM total (B = -8.84), mobility (B = -4.13), self-care (B = -4.07) and cognitive (B = -1.57) scores than the youngest group after controlling for covariates. The 45-64 group also finished with significantly lower FIM total (B = -6.17), mobility (B = -2.61) and self-care (B = -3.01) scores than youngest group. FIM efficiencies were similar for all ages in each of the FIM scales. Younger individuals with stroke make slightly greater functional gains compared to older individuals with stroke, but other factors, such as admission scores, are more important and the rates of recovery may be similar.

European evidence-based recommendations for clinical assessment of upper limb in neurorehabilitation (CAULIN): data synthesis from systematic reviews, clinical practice guidelines and expert consensus

BACKGROUND

Technology-supported rehabilitation can help alleviate the increasing need for cost-effective rehabilitation of neurological conditions, but use in clinical practice remains limited. Agreement on a core set of reliable, valid and accessible outcome measures to assess rehabilitation outcomes is needed to generate strong evidence about effectiveness of rehabilitation approaches, including technologies. This paper collates and synthesizes a core set from multiple sources; combining existing evidence, clinical practice guidelines and expert consensus into European recommendations for Clinical Assessment of Upper Limb In Neurorehabilitation (CAULIN).

METHODS

Data from systematic reviews, clinical practice guidelines and expert consensus (Delphi methodology) were systematically extracted and synthesized using strength of evidence rating criteria, in addition to recommendations on assessment procedures. Three sets were defined: a core set: strong evidence for validity, reliability, responsiveness and clinical utility AND recommended by at least two sources; an extended set: strong evidence OR recommended by at least two sources and a supplementary set: some evidence OR recommended by at least one of the sources.

RESULTS

In total, 12 measures (with primary focus on stroke) were included, encompassing body function and activity level of the International Classification of Functioning and Health. The core set recommended for clinical practice and research: Fugl-Meyer Assessment of Upper Extremity (FMA-UE) and Action Research Arm Test (ARAT); the extended set recommended for clinical practice and/or clinical research: kinematic measures, Box and Block Test (BBT), Chedoke Arm Hand Activity Inventory (CAHAI), Wolf Motor Function Test (WMFT), Nine Hole Peg Test (NHPT) and ABILHAND; the supplementary set recommended for research or specific occasions: Motricity Index (MI); Chedoke-McMaster Stroke Assessment (CMSA), Stroke Rehabilitation Assessment Movement (STREAM), Frenchay Arm Test (FAT), Motor Assessment Scale (MAS) and body-worn movement sensors. Assessments should be conducted at pre-defined regular intervals by trained personnel. Global measures should be applied within 24 h of hospital admission and upper limb specific measures within 1 week.

CONCLUSIONS

The CAULIN recommendations for outcome measures and assessment procedures provide a clear, simple, evidence-based three-level structure for upper limb assessment in neurological rehabilitation. Widespread adoption and sustained use will improve quality of clinical practice and facilitate meta-analysis, critical for the advancement of technology-supported neurorehabilitation.

Women and Stroke: Different, yet Similar

BACKGROUND

The impact of gender on acute ischemic stroke, in terms of presentation, severity, etiology, and outcome, is increasingly getting recognized. Here, we analyzed the gender-related differences in etiology and outcome of ischemic stroke in South India.

METHODS

Patients with first ever ischemic stroke within 1 week of onset presenting to the Comprehensive Stroke Care Centre, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, India, were included in our study. Clinical and risk factor profile was documented. The stroke severity was assessed using the National Institutes of Health Stroke Scale (NIHSS) at onset, and stroke subtype classification was done using Trial of Org 10172 in Acute Ischemic Stroke criteria. The 3-month functional outcome was assessed using the modified Rankin Scale (mRS) with excellent outcome defined as an mRS ≤2.

RESULTS

Of the 742 patients, 250 (33.7%) were females. The age, clinical profile, and rate of reperfusion therapies did not differ between the genders. Women suffered more severe strokes (mean NIHSS 9.5 vs. 8.4, p = 0.03). While large artery atherosclerosis was more common in men (21.3% vs. 14.8%, p = 0.03), cardioembolic strokes secondary to rheumatic heart disease were more common in women (27.2% vs. 19.7%, p = 0.02). Men had a better 3-month functional outcome compared to women (68.6% vs. 61.2%, p = 0.04), but was not statistically significant after adjusting for confounders.

CONCLUSION

Our data, from a single comprehensive stroke unit from South India, suggest that stroke in women are different, yet similar in many ways to men. Guideline-based treatment can result in comparable short-term outcomes, irrespective of admission stroke severity.

ADL Outcome of Stroke by Stroke Type and Time from Onset to Admission to a Comprehensive Inpatient Rehabilitation Ward

OBJECTIVE

To examine the effect of onset to admission interval (OAI) and stroke type on activities of daily living (ADL) outcome.

MATERIALS AND METHODS

Stroke patients (n=3112) admitted to and discharged from comprehensive inpatient rehabilitation wards at Nanakuri Memorial Hospital were classified into 8 OAI segments and by stroke type [intracerebral hemorrhage (ICH) and cerebral infarction (CI)]. Motor subscore of the Functional Independence Measure (FIM-M) on admission, FIM-M at discharge, FIM-M gain, length of stay (LOS), and FIM-M efficiency in the ICH and CI group matched by OAI segment were compared using the Wilcoxon test. Multiple comparisons using the Steel-Dwass test of FIM-M on admission, FIM-M at discharge, FIM-M gain, LOS, and FIM-M efficiency by OAI segments were performed.

RESULTS

FIM-M on admission was lower in the ICH group than the CI group in matched OAI segments. However, FIM-M improvement was greater in the ICH group than the CI group, resulting in no difference in FIM-M between groups at discharge. In both groups, the longer the OAI, the lower the FIM-M on admission and at discharge. The distribution pattern of significant differences among OAI segments differed between the groups. LOS tended to be longer and FIM-M efficiency tended to be higher in the ICH group than in the CI group.

CONCLUSIONS

The brain mass effect at the time of admission was larger and took longer to decrease in the ICH group than in the CI group. These results may improve prediction of outcomes in comprehensive inpatient rehabilitation wards.

Predictive models for independence after stroke rehabilitation: Maugeri external validation and development of a new model

BACKGROUND

Many efforts have been devoted to identify predictors of functional outcomes after stroke rehabilitation. Though extensively recommended, there are very few external validation studies.

OBJECTIVE

To externally validate two predictive models (Maugeri model 1 and model 2) and to develop a new model (model 3) that estimate the probability of achieving improvement in physical functioning (primary outcome) and a level of independence requiring no more than supervision (secondary outcome) after stroke rehabilitation.

METHODS

We used multivariable logistic regression analysis for validation and development. Main outcome measures were: Functional Independence Measure (FIM) (primary outcome), Functional Independence Staging (FIS) (secondary outcome) and Minimal Clinically Important Difference (MCID).

RESULTS

Patients with stroke admitted to a rehabilitation center from 2006 to 2019 were retrospectively studied (N = 710). Validation of Maugeri models confirmed very good discrimination: for model 1 AUC = 0.873 (0.833-0.915) and model 2 AUC = 0.803 (0.749-0.857). The Hosmer-Lemeshow χ2 was 6.07(p = 0.63) and 8.91(p = 0.34) respectively. Model 3 yielded an AUC = 0.894 (0.857-0.929) (primary outcome) and an AUC = 0.769 (0.714-0.825) (MCID).

CONCLUSIONS

Discriminative power of both Maugeri models was externally confirmed (in a 20 years younger population) and a new model (incorporating aphasia) was developed outperforming Maugeri models in primary outcome and MCID.

Functional recovery of patients with intracerebral haemorrhage and cerebral infarction after rehabilitation

To investigate potential differences in functional recovery after rehabilitation between intracerebral haemorrhage and cerebral infarction, we retrospectively compared the outcomes of patients with intracerebral haemorrhage (N = 208) and cerebral infarction (N = 480) who were consecutively discharged from our convalescent rehabilitation hospital between January 2013 and December 2018. Functional improvement was estimated by functional independence effectiveness measurements (proportion of potential for improvement achieved) upon discharge. Univariate analysis showed no significant differences in functional improvement between the two groups possibly because of the demographic variations upon admission. Multiple regression analysis demonstrated that the impact and type of factors related to functional improvement (functional independence measure upon admission, age, length of hospital stay, and time to admission after onset) were similar in both groups. Nevertheless, stratified analysis revealed, compared with patients with cerebral infarction, better improvement in patients with intracerebral haemorrhage that were admitted early after onset (<20 days), which exhibited high or moderate severity upon admission (functional independence measure: 36-89), or had a long hospital stay (>129 days). The present study showed differences as well as similarities in functional recovery between two stroke subtypes and suggests that better functional improvement might be expected in patients with intracerebral haemorrhage compared with those with cerebral infarction through an earlier start of intensive rehabilitation or longer rehabilitation in the hospital even if they exhibited relatively severe impairment upon admission. The type of stroke should be taken into consideration when predicting functional recovery and planning rehabilitation management in stroke patients.

Predicting Independence 6 and 18 Months after Ischemic Stroke Considering Differences in 12 Countries: A Secondary Analysis of the IST-3 Trial

Objectives

This study is aimed at identifying the best clinical model to predict poststroke independence at 6 and 18 months, considering sociodemographic and clinical characteristics, and then identifying differences between countries.

Methods

Data was retrieved from the International Stroke Trial 3 study. Nine clinical variables (age, gender, severity, rt-PA, living alone, atrial fibrillation, history of transient ischemic attack/stroke, and abilities to lift arms and walk) were measured immediately after the stroke and considered to predict independence at 6 and 18 months poststroke. Independence was measured using the Oxford Handicap Scale. The adequacy, predictive capacity, and discriminative capacity of the models were checked. Countries were added to the final models.

Results

At 6 months poststroke, 35.8% (n = 1088) of participants were independent, and at 18 months, this proportion decreased to 29.9% (n = 747). Both 6 and 18 months poststroke predictive models obtained fair discriminatory capacities. Gender, living alone, and rt-PA only reached predictive significance at 18 months. Poststroke patients from Poland and Sweden showed greater chances to achieve independence at 6 months compared to the UK. Poland also achieved greater chances at 18 months. Italy had worse chances than the UK at both follow-ups. Discussion. Six and eight variables predicted poststroke independence at 6 and 18 months, respectively. Some variables only reached significance at 18 months, suggesting a late influence in stroke patients' rehabilitation. Differences found between countries in achieving independence may be related to healthcare system organization or cultural characteristics, a hypothesis that must be addressed in future studies. These results can allow the development of tailored interventions to improve the outcomes.

Functional recoveries of patients with branch atheromatous disease after rehabilitation: Comparison with other types of cerebral infarction and importance of stratification by clinical categories

BACKGROUND

Functional recoveries after rehabilitation of patients with branch atheromatous disease (BAD) have not been well investigated, however, clinical category of cerebral infarction including BAD itself could be a potential predictive factor for functional outcome.

OBJECTIVE

To describe characteristics of functional recoveries of patients with BAD through comparison with other types of cerebral infarction.

METHODS

We retrospectively compared outcomes of patients with BAD (N = 222), cardioembolic cerebral infarction (CE: N = 177) and atherothrombotic cerebral infarction (AT: N = 219) by using functional independence measure (FIM) and FIM effectiveness (the proportion of potential for improvement achieved).

RESULTS

Univariate analysis showed that FIM on discharge was comparable among three types of cerebral infarction, but that FIM effectiveness in patients with BAD was significantly higher than those with CE or AT. Stratified analysis revealed higher FIM effectiveness in patients with BAD compared to patients with CE or AT, if they were male, younger (≤72 years) or had supratentorial brain lesions. Multiple regression analysis demonstrated that location of the brain lesion (supratentorial vs infratentorial) and gender (male vs female) were significantly associated with FIM on discharge, and that cognitive function on admission as well as gender were significantly associated with FIM effectiveness in patients with BAD, but not in patients with CE or AT.

CONCLUSIONS

Outcomes after rehabilitation of patients with BAD may be characterized by better functional improvement, especially if patients are male, relatively younger or with supratentorial lesions. The impact and the type of factors related to functional recoveries of patients with BAD may be different from other types of stroke. The present study suggested that clinical category of stroke should be taken into consideration in prediction of outcomes and planning of rehabilitation management.

Hip abduction with ankle dorsiflexion (HAAD) score and trunk seating control within 72 h after stroke predicts long-term disability: A cohort study

BACKGROUND

The aim of this study was to determine whether muscle strength of the lower limb and trunk during the acute phase after stroke are predictors of motor function and disability 90 days after hospital discharge.

METHODS

This prospective study used a nonconcurrent design to evaluate stroke patients at two time points: a) first 72 h: hip abduction and ankle dorsiflexion (HAAD) score, trunk sitting control, clinical evaluation, demographic profile, and stroke severity using the National Institutes of Health Stroke Scale (NIHSS); b) 90 days after hospital discharge: modified Rankin scale (mRS). The participants were divided into two groups: good outcome (mRS 0-2) and worse outcome (mRS>2), and the differences between them were assessed statistically. Clinical and demographic variables were included in the multiple logistic regression analysis. The ROC curve was used to illustrate the clinical sensitivity and specificity of the HAAD score cutoff for the outcomes.

RESULTS

Thirty-seven patients were included: 16 with mRS≤2 and 21 with mRS>2. Patients in the worse outcome group were older (p = 0.02) and presented with higher NIHSS scores (p = 0.002), lower HAAD scores (p < 0.001), higher pain sensation (p = 0.04), greater altered perception (p = 0.008), and no trunk control in the sitting position (p = 0.004). A lower HAAD score (OR = 0.09; 95%CI: 0.14-0.53; p < 0.001) and the absence of trunk control in the sitting position (OR = 0.55; 95%CI:0.54-0.95; p < 0.001) were associated with unsatisfactory outcomes.

CONCLUSION

A HAAD score <6 and the absence of trunk control while sitting during the first 72 h are predictors of worse long-term disability in stroke patients.

Factors predicting clinically significant functional gain and discharge to home in stroke in-patients after rehabilitation - A retrospective cohort study

Objective

This study explored factors which predict stroke survivors who could achieve “clinically significant functional gain” and return home when being discharged from a local hospital after in-patient stroke rehabilitation programme.

Methods

This study included 562 inpatients with stroke who were residing at community dwellings before onset of stroke, and transferred to a convalescent hospital for rehabilitation from four acute hospitals over one year. The main outcome variables of prediction were (a) achieving “clinically significant functional gain” as measured by (a1) achievement of “minimal clinically important difference” (MCID) of improvement in Functional Independence Measure Motor Measure (FIM-MM)”, (a2) one or more level(s) of improvement in function group according to the patients’ FIM-MM, and (b) discharge to home. Sixteen predictor variables were identified and studied firstly with univariate binary logistic regression and those significant variables were then put into multivariate binary logistic regression.

Results

Based on multivariate regression, the significant predictors for “clinically significant functional gain” were: younger age <75 years old, higher Glasgow Coma Scale score at admission, with haemorrhagic stroke, intermediate FIM-MM function group. Those significant predictors for “discharge to home” were: living with family/caregivers before stroke, higher FIM score at admission, and one or more level(s) of improvement in FIM-MM function group.

Conclusions

This study identified findings consistent with overseas studies in additional to some new interesting findings. Early prediction of stroke discharge outcomes helps rehabilitation professionals and occupational therapists to focus on the use of appropriate intervention strategies and pre-discharge preparation.

Changes in the Activity Measure for Post-Acute Care Domains in Persons With Stroke During the First Year After Discharge From Inpatient Rehabilitation

OBJECTIVE

To describe functional changes after inpatient stroke rehabilitation using the Activity Measure for Post-Acute Care (AM-PAC), an assessment measure sensitive to change and with a low risk of ceiling effect.

DESIGN

Retrospective, longitudinal cohort study.

SETTING

Inpatient rehabilitation unit of an urban academic medical center.

PARTICIPANTS

Among 433 patients with stroke admitted from 2012-2016, a total of 269 (62%) were included in our database and 89 of 269 patients (33.1%) discharged from inpatient stroke rehabilitation had complete data. Patients with and without complete data were very similar. The group had a mean age of 68.0±14.2 years, National Institutes of Health Stroke Score of 8.0±8.0, and rehabilitation length of stay of 14.7±7.4 days, with 84% having an ischemic stroke and 22.5% having a recurrent stroke.

INTERVENTION

None.

MAIN OUTCOME MEASURES

Changes in function across the first year after discharge (DC) were measured in a variety of ways. Continuous mean scores for the basic mobility (BM), daily activity (DA), and applied cognitive domains of the AM-PAC were calculated at and compared between inpatient DC and 6 (6M) and 12 months (12M) post DC. Categorical changes among individuals were classified as "improved," "unchanged," or "declined" between the 3 time points based on the minimal detectable change, (estimated) minimal clinically important difference, and a change ≥1 AM-PAC functional stage (FS).

RESULTS

For the continuous analyses, the Friedman test was significant for all domains (P≤.002), with Wilcoxon signed-rank test significant for all domains from DC to 6M (all P<.001) but with no change in BM and DA between 6M and 12M (P>.60) and a decline in applied cognition (P=.002). Despite group improvements from DC to 6M, for categorical changes at an individual level 10%-20% declined and 50%-70% were unchanged. Despite insignificant group differences from 6M-12M, 15%-25% improved and 20%-30% declined in the BM and DA domains.

CONCLUSIONS

Despite group gains from DC to 6M and an apparent "plateau" after 6M post stroke, there was substantial heterogeneity at an individual level. Our results underscore the need to consider individual-level outcomes when evaluating progress or outcomes in stroke rehabilitation.

Machine learning to predict mortality after rehabilitation among patients with severe stroke

Stroke is among the leading causes of death and disability worldwide. Approximately 20–25% of stroke survivors present severe disability, which is associated with increased mortality risk. Prognostication is inherent in the process of clinical decision-making. Machine learning (ML) methods have gained increasing popularity in the setting of biomedical research. The aim of this study was twofold: assessing the performance of ML tree-based algorithms for predicting three-year mortality model in 1207 stroke patients with severe disability who completed rehabilitation and comparing the performance of ML algorithms to that of a standard logistic regression. The logistic regression model achieved an area under the Receiver Operating Characteristics curve (AUC) of 0.745 and was well calibrated. At the optimal risk threshold, the model had an accuracy of 75.7%, a positive predictive value (PPV) of 33.9%, and a negative predictive value (NPV) of 91.0%. The ML algorithm outperformed the logistic regression model through the implementation of synthetic minority oversampling technique and the Random Forests, achieving an AUC of 0.928 and an accuracy of 86.3%. The PPV was 84.6% and the NPV 87.5%. This study introduced a step forward in the creation of standardisable tools for predicting health outcomes in individuals affected by stroke.

Vitality index is a predictor of the improvement in the functional independence measure score in subacute stroke patients with cognitive impairment

OBJECTIVES

To investigate the effect of motivation on improvements in the Functional Independence Measure (FIM) scores in subacute stroke patients with cognitive impairment.

METHODS

This retrospective cohort study included 358 consecutive subacute stroke patients with first-ever stroke and Mini-Mental State Examination score ≤23 at admission. We determined motivation and rehabilitation outcome using the vitality index and FIM-motor gain, respectively. Stepwise multiple regression analysis was performed to identify the factors at admission related to FIM-motor gain.

RESULTS

Of 80 participants enrolled in this study (mean age: 74.2 ± 11.3 years). The median (interquartile range) vitality index at admission and FIM-motor gain were 7 (4) and 23 (22) points, respectively. Stepwise multiple regression analysis revealed that age (B, -0.43; 95% confidence interval [CI], -0.65-(-0.21); β, -0.31; P <.001), duration from stroke onset to admission (B, -0.18; 95% CI, -0.33-(-0.04); β, -0.20; P =.014) and Stroke Impairment Assessment Set-motor function (B, 1.27; 95% CI, 0.92-1.61; β, 0.78; P <.001), FIM-motor (B, -0.80; 95% CI, -1.01-(-0.60); β, -0.95; P <.001), and vitality index (B, 3.79; 95% CI, 2.37-5.21; β, 0.50; P <.001) scores at admission were significantly associated with the FIM-motor gain.

DISCUSSION

The vitality index was significantly associated with FIM improvement in subacute stroke patients with cognitive impairment.

Effect of intensive rehabilitation on improvement of activity of daily living after intracerebral hemorrhage: a retrospective observational study

Between 2008 and 2012, the intensity of rehabilitation therapy for the recovery phase of stroke was gradually increased at our hospital in line with the policy of Japan's National Insurance System. Training hours increased from 0.8 to 2.5 hours/day without introducing any new techniques, programs, or equipment. The aim of this study was to investigate the effectiveness of the increased intensity of rehabilitation on the improvement of activity of daily living of patients with intracerebral hemorrhage. We retrospectively compared patient outcomes for the periods 2013-2017 (N = 162) and 2003-2007 (N = 116) using the gain in Barthel Index as an indicator of improvement in activity of daily living. The median (interquartile range) gain was significantly higher in 2013-2017 than in 2003-2007 [30 (20-45) vs. 15 (5-30); P < 0.001]. A stratified analysis showed that this improvement was independent of sex, the patient's Barthel Index on admission, or the side of the brain lesion, but it varied with age or time to admission from onset of the disease. These results, based on a considerable difference in the intensity of rehabilitation between the two periods, support the consensus that increased time spent on rehabilitation results in better functional outcome in post-stroke patients. The results also suggest that age and the timing of starting rehabilitation are important factors to examine the effectiveness of intense rehabilitation in patients with intracerebral hemorrhage.