Predicting those who will walk after rehabilitation in a specialist stroke unit

Prediction of Factors Affecting Mobility in Patients with Stroke and Finding the Mediation Effect of Balance on Mobility: A Cross-Sectional Study

(1) Background: Regaining mobility after stroke is essential to facilitate patient independency in activities of daily living. Predicting post-stroke mobility is clinically important and plays a significant part in rehabilitation programs. The purpose of this study is to find the factors affecting mobility in patients with stroke and to analyze the mediation effect of balance on mobility. (2) Methods: This cross-sectional study included forty-one patients with stroke averaging an age of 57.2 ± 88.6. The Rivermead Mobility Index (RMI) was used for measuring the mobility, Timed Up and Go (TUG) to measure the walking speed, Berg Balance Scale (BBS) to assess the balance and a handheld dynamometer (HHD) was used for measuring the isometric strength of the ankle and knee. (3) Results: In regression analysis balance (β=0.58; p≤ 0.0001) and walking speed (β=-0.27; p=0.04) were the significant factors predicting mobility. (4) Conclusions: Balance and gait speed were the factors that influenced mobility in stroke patients, indicating the utility of measuring these aspects in order to provide appropriate rehabilitation programs.

Prediction of Independent Walking in People Who Are Nonambulatory Early After Stroke: A Systematic Review

BACKGROUND AND PURPOSE

One systematic review has examined factors that predict walking outcome at one month in initially nonambulatory patients after stroke. The purpose of this systematic review was to examine, in nonambulatory people within a month of stroke, which factors predict independent walking at 3, 6, and 12 months.

METHODS

Prognostic factors: Any factors measured within one month after stroke with the aim of predicting independent walking. Outcome of interest: Independent walking defined as walking with or without an aid but with no human assistance.

RESULTS

Fifteen studies comprising 2344 nonambulatory participants after stroke were included. Risk of bias was low in 7 studies and moderate in 8 studies. Individual meta-analyses of 2 to 4 studies were performed to calculate the pooled estimate of the odds ratio for 12 prognostic factors. Younger age (odds ratio [OR], 3.4, P<0.001), an intact corticospinal tract (OR, 8.3, P<0.001), good leg strength (OR, 5.0, P<0.001), no cognitive impairment (OR, 3.5, P<0.001), no neglect (OR, 2.4, P=0.006), continence (OR, 2.3, P<0.001), good sitting (OR, 7.9, P<0.001), and independence in activities of daily living (OR 10.5, P<0.001) predicted independent walking at 3 months. Younger age (OR, 2.1, P<0.001), continence (OR, 13.8, P<0.001), and good sitting (OR, 19.1, P<0.001) predicted independent walking at 6 months. There were insufficient data at 12 months.

CONCLUSIONS

Younger age, an intact corticospinal tract, good leg strength, continence, no cognitive impairment, no neglect, good sitting, and independence in activities of daily living in patients who are nonambulatory early after stroke predict independent walking at 3 months. Registration: URL: https://www.crd.york.ac.uk/prospero/; Unique identifier: CRD42018108794.

Eating and Grooming Abilities Predict Outcomes in Patients with Early Middle Cerebral Infarction: A Retrospective Cohort Study

Patients with cerebrovascular disorders are often forced to rest, with early prognosis made by bedside examination. However, overloading, for example, talking for a long time, may worsen the condition. We hypothesized that activities of daily living (ADL) from the Functional Independence Measure (FIM) that were actually performed regularly are useful to predict prognosis. The present study was aimed at determining the predictive items related to predicting prognosis from the status of early motor paralysis and ADL in patients with acute middle cerebral artery (MCA) infarction. We examined 367 patients with MCA infarction for Brunnstrom recovery stage (BRS) and FIM within 4 days of admission and modified the Rankin Scale before onset and just before discharge. Logistic regression analysis was used to compare two groups of patients based on their postdischarge destination (Home/another hospital or facility). The logistic regression analysis showed the following: BRS Hand: odds ratio (OR) 1.641 (95% CI 1.642 (1.336–2.017), p < 0.001); FIM Grooming: OR 1.279 (95% CI 1.220–1.807, p < 0.001); and FIM Eating: OR 1.280 (95% CI 1.102–1.488, p < 0.001). On the other hand, the ROC analysis showed the ROC area for Eating to be 0.830 (95% CI 0.787–0.874), for Grooming to be 0.81 (95% CI 0.765–0.865), and for BRS Hand to be 0.805 (95% CI 0.760–0.851). The BRS Hand and FIM Eating and Grooming domains were identified as predictive factors using the following cutoff points: BRS Hand stage V and FIM scores of 5 for Eating and 4 for Grooming. The cutoff points for the BRS Hand and FIM Eating revealed that, at a minimum, such patients can use the nonaffected hand. The presence of cognitive dysfunction or dysphagia affects these domains. Therefore, these results suggested that Eating and Grooming are appropriate as evaluation items.

Prognostic Factors of Functional Outcome Assessed by Using the Modified Rankin Scale in Subacute Ischemic Stroke

Background

Most stroke survivors spent their lifetime with disability which not only affects the clients themselves and the family but also brings economic cost to the country. Therefore, this retrospective cohort study aimed to identify independent prognostic determinants associated with functional recovery in ischemic stroke within 6 months after onset.

Methods

Data from all first-onset ischemic stroke patients admitted to the acute stroke unit of the tertiary, university hospital were reviewed for 5 years consecutively. The functional outcome of the patients was recorded during 6-month follow-up by using the modified Rankin Scale (mRS). Baseline characteristics, motor assessment and all stroke-related variables were assessed during first week after stroke and 6-month follow-up. In order to derive clinical predictors, the backward stepwise multivariable risk regression analyses were used with the generalized linear model.

Results

The result revealed that in the 358 patients recruited into this study, 255 (71.2%) were in the functional recovery group (mRS score of 1 - 3) within 6 months after onset. The final model of multivariable risk regression analysis, with generalized linear model, demonstrated that the independent variables of functional recovery were leg score with a risk ratio (RR = 1.92, 95% confidence interval (CI): 1.14 - 3.21, P = 0.013), arm score (RR = 1.75, 95% CI: 1.02 - 3.01, P = 0.042) and age older than 75 years (RR = 1.36, 95% CI: 1.04 - 1.77, P = 0.025).

Conclusions

Achieving functional recovery during 6 months post stroke was related to age and motor improvement. With limited resources, continuity of rehabilitation training in the community system or allocation of caregiver training should be a part of discharge planning to promote recovery.

Impact of long term care and mortality risk in community care and nursing homes populations

OBJECTIVES

To identify the survival time, the mortality risk factors and the individuals' characteristics associated with cognitive and physical status at discharge, among the Portuguese long-term care (LTC) populations.

SETTINGS

Home-and-Community-Based Services (HCBS) and three types of Nursing Homes (NH).

PARTICIPANTS

20,984 individuals admitted and discharged in 2015.

MEASUREMENTS

The Kaplan-Meier survival analysis and the Cox Proportional Hazards Models were used to study the mortality risk; the Wilcoxon signed-rank test to identify the number of individuals with cognitive and physical changes between admission and discharge; two cumulative odds ordinal logistic regressions to predict the cognitive and physical dependence levels at discharge RESULTS: The mortality rate at HCBS was 30%, and 17% at the NH, with a median survival time of 173 and 200 days, respectively. The main factors associated with higher mortality were older age, male gender, family/neighbour support, neoplasms and cognitive/physical dependence at admission. In NH/HCBS, 26%/18% of individuals improve their cognitive status, while in physical status the proportion was 38%/27%, respectively. Finally, older age, being illiterate and being classified at the lowest cognitive and physical status at admission decrease the likelihood of achieving a higher level of cognitive and physical independence at discharge.

CONCLUSIONS

The adoption of a robust and complete assessment tool, the definition of guidelines to enable a periodical assessment of individuals' autonomy and the adoption of benchmark metrics allowing the comparison of results between similar units are some of the main goals to be taken into account for future developments of this care in Portugal.

Prediction of Walking and Arm Recovery after Stroke: A Critical Review

Clinicians often base their predictions of walking and arm recovery on multiple predictors. Multivariate prediction models may assist clinicians to make accurate predictions. Several reviews have been published on the prediction of motor recovery after stroke, but none have critically appraised development and validation studies of models for predicting walking and arm recovery. In this review, we highlight some common methodological limitations of models that have been developed and validated. Notable models include the proportional recovery model and the PREP algorithm. We also identify five other models based on clinical predictors that might be ready for further validation. It has been suggested that neurophysiological and neuroimaging data may be used to predict arm recovery. Current evidence suggests, but does not show conclusively, that the addition of neurophysiological and neuroimaging data to models containing clinical predictors yields clinically important increases in predictive accuracy.

Non-motor Factors Associated with the Attainment of Community Ambulation after Stroke

OBJECTIVE

Detect the main predictive non-motor factors related to independent community ambulation after stroke. Furthermore, we propose a scale to estimate the probability of a stroke patient achieving independent community ambulation after 6 months of rehabilitation.

DESIGN AND SETTINGS

Prospective cohort. Subjects treated in a rehabilitation center in a large metropolitan area. Independent community ambulation was evaluated after rehabilitation according to the Hoffer classification. Functional ambulation was assessed at four levels: nonambulatory, nonfunctional ambulation, household ambulation, and community ambulation.

PARTICIPANTS

Patients (n=201) with a moderate disability after stroke.

RESULTS

The average time of hospitalization was 19.3 days. However, only 32.8% of the patients started the rehabilitation program during the first 6 months after stroke. We found that 121 patients achieved community ambulation (60.2%), 40 achieved household ambulation (19.9%), 12 achieved therapeutic ambulation (5.9%), and 28 were non-ambulatory after 6 months of treatment. Based on our final model, a scoring scale was created in order to evaluate the probability of stroke patients achieving independent community ambulation after 6 months of rehabilitation. Higher scores were associated with better chances of community ambulation within 6 months.

CONCLUSIONS

The scale that evaluated these factors proved to have acceptable sensitivity and specificity to establish the prognosis of community ambulation after 6 months of rehabilitation.

What is the Probability of Patients who are Nonambulatory after Stroke Regaining Independent Walking? a Systematic Review

Patients after stroke who are nonambulatory require resources, and independent walking becomes a major determinant of the ability to participate in activities of daily living. Our objective was to determine the probability of walking for patients who are nonambulatory in the first month after stroke. We performed a systematic review and meta-analysis of consecutive, prospective studies of nonambulatory patients within the first month after stroke in rehabilitation and acute units. The outcomes were the probability of achieving independent walking at three-, six- and 12 months after stroke. Twenty-six studies were included in the review. Seventeen studies comprising 2856 participants were entered into meta-analyses. For initially nonambulatory stroke patients managed in a rehabilitation unit, the probability of independent walking was 0·60 (95% CI 0·47–0·74, 1373 participants) at three-months, 0·65 (95% CI 0·53–0·77, 444 participants) at six-months and 0·91 (95% CI 0·81–1·00, 24 participants) at 12 months. For patients managed in an acute unit, the probability of independent walking was 0·39 (95% CI 0·27–0·52, 634 participants) at three-months, 0·69 (95% CI 0·46–0·92, 405 participants) at six-months and 0·74 (95% CI 0·59–0·88, 34 participants) at 12 months. 60% of patients managed in a rehabilitation unit who are nonambulatory in the first month after stroke will regain independent walking compared with 39% of those managed in an acute unit. This information can be used clinically to make decisions about allocation of rehabilitation resources, education of patients and carers, and for discharge planning.

Predictors of Poststroke Mobility: Systematic Review

Regaining poststroke mobility is considered a primary goal of the stroke patient in early rehabilitation. Predictive recovery of poststroke mobility is clinically important, and provides important information to healthcare professionals, patients and their families. We conducted a systematic review aimed at identifying the predictive or associated baseline factors, assessed within one-week of stroke onset, and the recovery of poststroke mobility within 30 days. A comprehensive search strategy was applied to all major electronic databases to identify potentially relevant studies. Included in the review are two studies that evaluate the predictive value of baseline factors by developing a prognostic model, and three studies that assess the baseline factors that were associated with the outcome by univariate analysis. Walking is the most commonly assessed mobility outcome; age, the severity of paresis, reduced leg power, presence of hemianopia, size of brain lesion and type of stroke were shown to be predictive or associated with walking within 30 days poststroke. This review has identified the potential predictors of the recovery of mobility poststroke. There is a need to explore and validate these predictors in other patient cohorts, and consider additional factors believed to be associated with mobility. The recovery of mobility other than walking also needs investigation. In order to move prognostic research in stroke forward, a collaborative approach to sharing and collecting data is recommended.

Intensive training of subjects with chronic hemiparesis on a motorized cycle combined with functional electrical stimulation (FES): a feasibility and safety study

BACKGROUND AND PURPOSE

This study tested the safety and ability of subjects with chronic hemiplegia to tolerate intensive training using a motorized cycle combined with functional electrical stimulation (FES) system.

METHODS

A case series of 10 subjects with chronic stroke participated in 30-minute three times per week cycling on a stationary motorized cycling system combined with FES (RT300(TM) ). The stimulation activated the dorsal and plantar flexors, the quadriceps and the hamstrings using four channels and a stimulation pattern that assisted cycling motion of the paretic lower limb. Patients were instructed to cycle as close as possible to 60 rpm and the resistance to cycling was gradually increased using a computer-based algorithm. The training lasted eight weeks.

RESULTS

All 10 participants completed the training without adverse reactions to the training or the FES. The kcal utilized during the training increased significantly (p = 0.0003) between session 1 (2.2 ± 0.47), session 12 (4.3 ± 1.2) and session 24 (7.5 ± 1.8). Peak pedaling power increased from 6.5 ± 0.5 W pre-training to 18.0 ± 5.4 W post-training. Locomotion variables that improved significantly were time to complete the get up and go test (45.4 ± 54.9 seconds vs. 34.0 ± 31.8 seconds) a 24.6% improvement (p = 0.03) and gait velocity, which increased 25.0% from 0.4 ± 0.3 m/sec to 0.5 ± 0.4 m/sec (p = 0.01).

CONCLUSION

Using a motorized cycle combined with FES intensive training appears safe and can be tolerated by patients with chronic stroke of wide age range, diverse severity of cardio-pulmonary deconditioning, motor loss and locomotor deficits.

Validity of the walking scale for spinal cord injury and other domains of function in a multicenter clinical trial

OBJECTIVE

To demonstrate criterion (concurrent and predictive) and construct validity of the Walking Index for Spinal Cord Injury (WISCI) scale and other walking measures in the Spinal Cord Injury Locomotor Trial (SCILT).

DESIGN

Prospective multicenter clinical trial of a walking intervention for patients with acute traumatic spinal cord injury (SCI). PARTICIPANTS/ METHODS: Body weight-supported treadmill training was compared to overground mobility training in 146 patients with incomplete SCI (C4 to L3) enrolled within 8 weeks of onset and treated for 12 weeks. Primary outcome measures were the Functional Independence Measure (FIM), 50-foot walking speed (50FW-S), and 6-minute walking distance (6MW-D), tested 3, 6, and 12 months after entry. Secondary measures were the Lower Extremity Motor Score (LEMS), Berg Balance Scale (BBS), WISCI, and FIM locomotor score (LFIM), assessed at 6 centers by blinded observers. Data for the 2 arms were combined since no significant differences in outcomes had been found.

RESULTS

Correlations with WISCI at 6 months were significant with BBS (r = .90), LEMS (r = .85), LFIM (r = .89), FIM (r = .77), 50FW-S (r = .85), and 6MW-D ( r = .79); similar correlations occurred at 3 and 12 months. Correlations of change scores from baseline WISCI were significant for change scores from baseline of LEMS/BBS/LFIM. Correlation of baseline LEMS and WISCI at 12 months were most significant (r = .73). The R(2) of baseline LEMS explained 57% of variability of WISCI levels at 3 months.

CONCLUSION

Concurrent validity of the WISCI scale was supported by significant correlations with all measures at 3, 6, and 12 months. Correlation of change scores supports predictive validity. The LEMS at baseline was the best predictor of the WISCI score at 12 months and explained most of the variance, which supported both predictive and construct validity. The combination of the LEMS, BBS, WISCI, 50FW-S, and LFIM appears to encompass adequate descriptors for outcomes of walking trials for incomplete SCI.