Predict Walking Ability Research Articles

R3-Walk and R6-Walk, Simple Clinical Equations to Accurately Predict Independent Walking at 3 and 6 Months After Stroke: A Prospective, Cohort Study

ObjectiveTo investigate if independent walking at 3 and 6 months poststroke can be accurately predicted within the first 72 hours, based on simple clinical bedside tests. DesignProspective observational cohort study with 3-time measurements: immediately after stroke, and 3 and 6 months poststroke. SettingPublic hospital. ParticipantsAdults with first-ever stroke evaluated at 3 (N=263) and 6 (N=212) months poststroke. InterventionNot applicable. Main Outcome MeasuresThe outcome of interest was independent walking at 3 and 6 months after stroke. Predictors were age, walking ability, lower limb strength, motor recovery, spatial neglect, continence, and independence in activities of daily living. ResultsThe equation for predicting walking 3 months poststroke was 3.040 + (0.283 × FAC baseline) + (0.021 × Modified Barthel Index), and for predicting walking 6 months poststroke was 3.644 + (-0.014 × age) + (0.014 × Modified Barthel Index). For walking ability 3 months after stroke, sensitivity was classified as high (91%; 95% CI: 81–96), specificity was moderate (57%; 95% CI: 45–69), positive predictive value was high (76%; 95% CI: 64–86), and negative predictive value was high (80%; 95% CI: 60–93). For walking ability 6 months after stroke, sensitivity was classified as moderate (54%; 95% CI: 47–61), specificity was high (81%; 95% CI: 61–92), positive predictive value was high (87%; 95% CI: 70–96), and negative predictive value was low (42%; 95% CI: 50–73). ConclusionsThis study provided 2 simple equations that predict walking ability 3 and 6 months after stroke. This represents an important step to accurately identify individuals, who are at high risk of walking dependence early after stroke.

Predicting factors for walking ability of postoperative patients with hemiarthroplasty at Wahidin Sudirohusodo Hospital in Makassar

Background: The ability to make early predictors in post-surgery includes health workers preparing patients for outpatient care. The purpose of this study is to determine the factors that influence the ability to walk postoperative hemiarthroplasty patients when patients are admitted. We hypnotized that age, sex, preoperative walking status, time interval between injury to surgery, preoperative hemoglobin level, muscle weakness, muscle atrophy, anxiety level and body mass index would be predictive factors for walking ability post hemiarthroplasty surgery.Method: An descriptive-analytic study with a cross sectional retrospective approach was conducted at the Wahidin Sudirohusodo Hospital in Makassar 2020. Patients with fractures of the proximal femur had undergone hemiarthroplasty surgery and were over 50 years of age at admission from September 2019 to October 2020. Bivariate and multivariate with logistic regression was usedResult: 39 samples according to inclusion criteria were analyzed. Muscle atrophy has a significant correlation with p = 0,04 (p<0,05). Body mass index and muscle atrophy have the most dominant factors for predict walking ability post hemiarthroplasty (EXP (B) 7,282 & EXP (B) 0,083) eventhough not significant statistically (p = 0,116 & p = 0,073)Conclusion: The muscle atrophy variable in this study was the most significant factor in prediction walking ability post hemiarthroplasty surgery. Also, patient with normal BMI will encourage early walk after surgery better than abnormal BMI in the same muscle-wasting condition

Cortico-reticular Tract Integrity does not Predict Walking Ability in Acute Stroke Patients: A Diffusion Tensor Imaging Study

Cortico-reticular Tract Integrity does not Predict Walking Ability in Acute Stroke Patients: A Diffusion Tensor Imaging Study

New scoring system at admission to predict walking ability at discharge for patients with hip fracture

IntroductionA reliable scoring system that predicts the walking ability of hip fracture patients would be useful for clinicians. Here we developed a scoring system for hip fracture patients and evaluated its predictive ability. HypothesisWe hypothesized that age, sex, presence of dementia, walking ability before the injury, fracture type, serum hemoglobin level, serum albumin level and interval in days between admission and surgery would be the predictive factors of the walking ability at discharge. Material and methodsData from 409 patients who underwent hip fracture surgery were included. We analyzed factors that affected walking ability and developed a scoring system that predicts the probability of walking unaided or with a cane at discharge. ResultsThe mean age of the patients was 81.3 years. A total of 164 (40%) patients could walk unaided or with a cane at discharge. Multivariate logistic regression analysis showed that the obstructive factors for the ability to walk unaided or with a cane at discharge were older age (odds ratio [OR]=0.962, p=0.002), dementia (OR=0.126, p<0.001), use of a cane before injury (OR=0.396, p<0.001), trochanteric fracture (OR=0.571, p=0.027) and low serum albumin level (OR=4.15, p<0.001) at admission. The scoring system used the following formula: Score=5−0.04×age+albumin−2(with dementia)− 1(with use of a cane before injury)−1(with trochanteric fracture). The C-statistics for the scoring system was 0.81 (95% confidence interval, 0.77–0.85). DiscussionThis newly developed scoring system of information at admission predicted the discharge mobility of hip fracture patients. In addition to the previously known risk factors, serum albumin level at admission was detected as a new predictor for mobility at discharge. Level of proofIV, retrospective study.

Wednesday, September 26, 2018 10:35 AM – 12:00 PM Cervical Spine Trauma: 22. A simplified clinical prediction rule for prognosticating independent walking after spinal cord injury: a prospective study from a Canadian multicenter spinal cord injury registry

BACKGROUND CONTEXT Models for predicting recovery in patients affected with traumatic spinal cord injury (tSCI) have been developed in recent years to optimize patient-centered care. Several databases and analytical models have been validated in their ability to predict tSCI recovery, yet recent findings have queried the accuracy of these models in patients whose prognoses are least predictable, ie, AIS B and C patients. PURPOSE To examine the predictive accuracy of van Middendorp's five-variable and Hicks’ three-variable LR models in the subset of AIS B and C patients. Secondly, to assess the predictive accuracy of a novel, seven-variable logistic regression model in this cohort. Thirdly, to investigate the utility of advanced computing models based on artificial intelligence in the context of AIS B and C prognostication. STUDY DESIGN/SETTING Prospective cohort study using the Rick Hansen Spinal Cord Injury Registry, a pan-Canadian prospective observational registry. PATIENT SAMPLE Patients who sustained tSCI between 2004 and 2016. OUTCOME MEASURES Neurological severity (AIS) at time of admission and level of injury was assessed within 15 days of injury according to the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI). Independent walking ability was assessed by the FIM at ≥12 months from time of injury, by which time neurologic and functional outcomes are known to plateau (16-20). METHODS Three logistic regression models and two artificial intelligence models were evaluated for their ability to predict walking ability one-year postinjury. Comparison of prognostic performance between models was calculated by area under the receiver operating characteristic curve (AUC). RESULTS A total of 675 tSCI patients within the RHSCIR were identified for our study. From 160 AIS B and C patients, our modified LR model demonstrated an AUC of 0.854 (95% CI 0.808–0.900). For the same cohort, van Middendorp et al.’s LR model generated an AUC of 0.833 (95% CI 0.771–0.895), while the artificial intelligence model presenting the highest degree of prognostic ability (neural networking) generated an AUC of 0.872. There were no significant differences in predictive accuracy between models (p>.05). The AUC for 515 AIS A and D patients utilizing van Middendorp et al.’s LR model was 0.954. CONCLUSIONS Application of our novel, seven-variable LR model, two previously tested LR models, and two artificial intelligence models demonstrated limited predictive accuracy for AIS B and C patients. These findings suggest that former models achieved strong prognostic accuracy through a high proportion of AIS A and D patients in their analysis cohort; furthermore, present models cannot effectively predict ambulatory outcomes in AIS B and C patients, regardless of methodology. FDA DEVICE/DRUG STATUS This abstract does not discuss or include any applicable devices or drugs.

Berg Balance Scale score at admission can predict walking suitable for community ambulation at discharge from inpatient stroke rehabilitation.

This retrospective cohort study identified inpatient rehabilitation admission variables that predict walking ability at discharge and established Berg Balance Scale cut-off scores to predict the extent of improvement in walking. Participants (n=123) were assessed for various cognitive and physical outcomes at admission to inpatient stroke rehabilitation. Multivariate logistic regression identified admission predictors of regaining community ambulation (gait speed ≥0.8 m/s) or unassisted ambulation (no physical assistance) after 4 weeks. Receiver operating characteristic curve analysis identified cut-off admission Berg Balance Scale scores. Mini-Mental State Examination (odds ratio (OR) 1.60, 95% confidence interval (95% CI) 1.19-2.14) was a significant predictor when coupled with admission walking speed for regaining community ambulation speed; stroke type (haemorrhagic/ischaemic) was a significant predictor (OR=0.19, 95% CI 0.05-0.77) when coupled with Berg Balance Scale (OR 1.14, 95% CI 1.09-1.20). Only Berg Balance Scale was a significant predictor of regaining unassisted ambulation (OR 1.11, 95% CI 1.05-1.17). A cut-off Berg Balance Scale score of 29 on admission predicts that an individual will go on to achieve community walking speed (n=123, area under the curve (AUC)=0.88, 95% CI 0.81-0.95); a cut-off score of 12 predicts a non-ambulator to regain unassisted ambulation (n=84, AUC 0.73, 95% CI 0.62-0.84). The Berg Balance Scale can be used at rehabilitation admission to predict the degree of improvement in walking for patients with stroke.

Walking ability in patients with glioblastoma: prognostic value of the Berg Balance Scale and the 10meter walk test.

Primary brain tumors frequently cause considerable functional impairments and the survival time when diagnosed with glioblastoma is 14.6months. The aim of this study was to examine if baseline postural control and walking ability in patients with glioblastoma could predict long term walking ability and 1year mortality. Data were gathered from prospective recordings in a brain cancer database supplemented by retrospective review of electronic patient records. We included 109 patients with glioblastoma, 47 women and 62 men with mean age 65years. At admission 84 patients were tested with Berg Balance Scale and 57 were tested with 10meter walk test. Binary logistic regression analysis showed no statistical significance in favour of the 10meter walk test. Berg Balance Scale showed an ability to predict walking ability 4-8months after admission. The risk of dying within a year was 6.9 times higher in patients who lost their ability to walk within 4-8months of the first admission. This study showed that Berg Balance Scale has some ability to predict the loss of walking ability 4-8months after admission. This could be an important indicator pin pointing patients most in need of more intensive specialized neurorehabilitation efforts early in the disease course.

The influence of cognitive status on outcome and walking ability after hemiarthroplasty for femoral neck fracture: a prospective cohort study

IntroductionFemoral neck fracture (FNF) is a devastating injury with serious medical and social consequences. One-third of these patients have some degree of impaired cognitive status. Despite this, a high proportion of hip fracture trials exclude patients with cognitive impairment (CI). We aimed to evaluate whether moderate to severe CI could predict walking ability, quality of life, functional outcome, reoperations and mortality in elderly patients with displaced FNF treated with hemiarthroplasty (HA).MethodsThis cohort study included a consecutive series of 188 patients treated with HA for a displaced FNF. Patients were assessed for estimated preoperative and 1 year postoperatively with regard to walking ability, cognitive status, quality of life with EQ-5D and hip function with Harris hip score.ResultsThere were 188 patients who met the inclusion criteria. A total of 130 patients were in the control group, and 58 were in the CI group. At 1-year follow-up, 31 patients (24%) had died in the control group and 22 patients (38%) had died in the cognitive impaired group. This difference in reoperation and mortality rate was statistically significant (log-rank test, p = 0.016). The CI had a significantly higher incidence of being non-walker (28 vs. 4%, OR 9.2, p = 0.001). The EQ-5D was higher in the control group, while the Harris hip score was comparable in the two groups.ConclusionsModerate to severe CI was associated with a high incidence of non-walking ability, worse quality of life, high mortality and re-operation rate after femoral neck fractures treated with HA.

Prediction of Independent Walking Ability for Severely Hemiplegic Stroke Patients at Discharge from a Rehabilitation Hospital

It is important to predict walking ability for stroke patients, because rehabilitation programs are planned on such predictions. We therefore examined predictive factors that are available before discharge from a rehabilitation hospital. Seventy-two consecutive patients with a first attack of stroke with severe hemiplegia were included in this study. We retrospectively evaluated background factors (age, gender, time from stroke onset, paresis side, and stroke type). Other neurological and physical parameters were collected by means of the modified National Institutes of Health Stroke Scale, the Mini-Mental State Examination, the Trunk Control Test (TCT), and the knee extension strength/body weight ratio on the unaffected side (KES/BW-US) at the time of admission. We divided the patients into 2 groups, the independent group (n = 49) and the dependent group (n = 23), on the basis of the Barthel Index of mobility at the time of discharge. We then compared the 2 groups with respect to the aforementioned parameters. We also performed stepwise discriminant analyses to ascertain which parameters are the best predictors of walking ability at the time of discharge. Age, TCT score, and the KES/BW-US ratio were significantly different between the groups. Discriminant analysis revealed that younger age and a higher KES/BW-US ratio were significantly associated with walking ability at discharge, which could be precisely predicted using the following formula: Y = .093 × (age) - 4.316 × (KES/BW-US) - 4.984. At the time of admission, age and the KES/BW-US ratio permit the prediction of independent walking ability at the time of discharge. Our formula predicts walking ability with an accuracy of more than 91%.

Clinical values of control over pain and pain coping strategies in surgical treatment for patients with lumbar spinal stenosis.

Control over pain and pain coping strategies are associated with pain intensity as well as psychological status and subjective disability in patients experiencing pain. The present study assessed the clinical values of control over pain and pain coping strategies in surgical treatment for patients with lumbar spinal stenosis using mediation analysis. Sixty-two patients with lumbar spinal stenosis (median age, 70 years; 34 men, 28 women) were evaluated before surgery. The pain intensity and area, psychological status/subjective disability (Japanese Orthopaedic Association Back Pain Evaluation Questionnaire), and control over pain/pain coping strategies (Coping Strategies Questionnaire) were assessed. Mediation analysis, which consisted of serial regression analyses, mainly tested whether (1) control over pain/pain coping strategies were predicted by pain characteristics and (2) control over pain/pain coping strategies predicted psychological status/subjective disability after controlling for pain characteristics. Control over pain was predicted by pain intensity (regression coefficient, -0.33; p = 0.01); moreover, it predicted walking ability (standardized partial regression coefficient, 0.31; p = 0.01) and social function (0.38; p = 0.00) after controlling for pain intensity. Although increasing activity level, one pain coping strategy, was predicted by pain intensity (regression coefficient, -0.30; p = 0.02), it did not predict walking ability (standardized partial regression coefficient, 0.07; p = 0.53) or social function (0.13; p = 0.33) when considering pain intensity. In this cohort, mediation analysis demonstrated that pain intensity did not directly affect perceived walking ability or social function, but did affect control over pain; moreover, control over pain affected walking ability and social function. These findings are useful for a deep understanding of the relationships between pain and subjective disability in preoperative patients with lumbar spinal stenosis. More attention should be given to patients' thoughts about pain such as control over pain.

Factors that predict walking ability with a prosthesis in lower limb amputees

Identification of predictive factors for walking ability with a prosthesis, after lower limb amputation, is very important in order to define patient’s potentials and realistic rehabilitation goals, however challenging they are. The objective of this study was to investigate whether variables determined at the beginning of rehabilitation process are able to predict walking ability at the end of the treatment using support vector machines (SVMs). This research was designed as a retrospective clinical case series. The outcome was defined as three-leveled ambulation ability. SVMs were used for predicting model forming. The study included 263 patients, average age 60.82 ± 9.27 years. In creating SVM models, eleven variables were included: age, gender, cause of amputation, amputation level, period from amputation to prosthetic rehabilitation, Functional Comorbidity Index (FCI), presence of diabetes, presence of a partner, restriction concerning hip or knee extension, residual limb hip extensor strength, and mobility at admission. Six SVM models were created with four, five, six, eight, 10, and 11 variables, respectively. Genetic algorithm was used as an optimization procedure in order to select the best variables for predicting the level of walking ability. The accuracy of these models ranged from 72.5% to 82.5%. By using SVM model with four variables (age, FCI, level of amputation, and mobility at admission) we are able to predict the level of ambulation with a prosthesis in lower limb amputees with high accuracy.

Predicting Walking Function of Patients One Month Poststroke Using Modified Rivermead Mobility Index on Admission

Being able to predict walking ability of patients with stroke at an early stage is useful in formulating realistic rehabilitation goals and facilitating early discharge planning, which are beneficial not only to the patients but their family members and health care providers. This study aimed to use the modified Rivermead mobility index (MRMI) of the stroke patients on day 3 of their admission to predict their independent walking ability on day 28 postadmission. A total of 232 patients with acute stroke who were admitted to the acute hospital were recruited. Fifty-three percent of them (n = 123) were able to achieve independent walking ability after 28 days of admission whereas 47.0% of them (n = 109) failed to do so. The receiver operating characteristics curve analysis was performed. The optimal cutoff score with the highest sum of sensitivity and specificity was found to be 18.5 (sensitivity, 85.0%; specificity, 75.0%) and the area under the curve was .880. In conclusion, MRMI on day 3 of admission maybe useful in predicting independent walking ability 1 month after stroke.

The 6-Minute Walk test indoors is strongly related to walking ability outdoors in persons with late effects of polio

Objective: To assess whether gait performance indoors can predict walking ability outdoors in persons with late effects of polio. Design: Descriptive analyses of a convenience sample. Setting: A university hospital rehabilitation medicine outpatient department. Participants: Sixty-three individuals with prior polio (32 men and 31 women, mean age 68 ± 6 years). Main outcome measures: The 6-Minute Walk Test (6MWT) and a 340-m-long distance were used to assess gait performance indoors and walking ability outdoors, respectively. The Borg Rating of Perceived Exertion (RPE) Scale was used to assess perceived exertion after the gait performance tests. Results: Significant correlations (p < 0.01) were found between the 6MWT and the outdoor walking with regard to gait speed (r = 0.92) and perceived exertion (rho = 0.68). A majority of the participants walked significantly (p < 0.001) faster outdoors than indoors; the average gait speed was 1.3 ± 0.3 m/s outdoors and 1.2 ± 0.3 m/s indoors. There was no significant difference in perceived exertion; median RPE was 13 (range 11–19) after the outdoor walking and 13 (range 9–17) after the 6MWT. Conclusion: The strong relationship between gait speed indoors and gait speed outdoors indicates that the 6MWT is a useful test for physiotherapists to predict walking ability in everyday life in ambulatory persons with mild to moderate late effects of polio.

Arterial Stiffness and Walk Time in Patients with End-Stage Renal Disease

Background: End-stage renal disease patients experience increased prevalence of cardiovascular disease. Heart-artery interaction may be shifted, impacting blood pressure lability, and exercise tolerance. The coupling ratio consists of the ratio of indexed arterial elastance (EaI, arterial load) to ElvI, a measure of cardiac contractility or stiffness. Our purpose was to explore the relationship between elastances and functional capacity. We hypothesized that arterial stiffness (central pulse wave velocity, PWV) and elastances would be correlated to shuttle walk time. Methods: We used applanation tonometry, ultrasonography, and a shuttle walk test to evaluate our hypothesis. Spearman's correlations were used to assess relationships between variables. Block regression was also performed. Results: Forty-two subjects on maintenance hemodialysis participated. Average age=44±5 years, body surface area=2.01 kg/m². Mean EaI=4.45 and mean ElvI=6.89; the coupling ratio=0.82. Mean aortic pulse pressure=51 mmHg and PWV=9.6 m/s. PWV(r=-0.385) and EaI (r=-0.424) were significantly and inversely related to walking time while stroke volume index (SVI) was positively correlated to shuttle walk time (r=0.337), p<0.05 for all. Conclusions: We conclude that, like other clinical populations, both arterial and heart function predict walking ability and represent potential targets for intervention; arterial stiffness and SVI are strongly related to shuttle walk time in patients with ESRD.

Lumbar lordosis angle (LLA) and leg strength predict walking ability in elderly males

There is an association between gait performance and spinal alignment in elderly females but it is unclear if this association is gender-dependent and postural changes would also predict gait performance in healthy elderly males. We measured thoracic kyphosis angle (TKA), LLA as indices of spinal alignment and maximal walking speed (WS), timed up and go test (TUG), 10-m obstacle walking time, and 6-min walk distance as indices of gait performance in healthy old males (n=124, age 73.0±7.2years). Knee extensor strength and one-leg standing time with eyes open were measures of physical function. The LLA but not TKA correlated with performance in each of the 4 gait test. Multiple-regression analyses showed that only the combination of knee extensor strength and LLA accounted for significant variation in gait performance. While previous studies showed that spinal alignment is associated with gait performance in elderly women, in healthy elderly males both functional (leg strength) and structural (spinal alignment) factors contribute to gait performance.

Can simple clinical tests predict walking ability after prosthetic rehabilitation?

To investigate whether simple clinical measures can predict walking ability after lower limb prosthetic rehabilitation. Prospective observational study. Ninety five adults who were assessed as suitable for lower limb prosthetic rehabilitation by the multidisciplinary team. Information regarding baseline clinical factors (amputation details, comorbidities, physical ability, mood and cognitive ability) was collected prior to provision of the prosthesis. Backward step linear regression was used to identify factors predictive of performance on the Timed Up and Go test following rehabilitation. Seventy one participants were able to complete this walking test and were included in the final analysis. The backward step regression model had an adjusted R2 of 0.588 and comprised 6 factors: age (p = 0.002), gender (p = 0.027), level of amputation (p = 0.000), presence of contracture (p = 0.088), ability to stand on one leg (p = 0.062) and Trail Making Tests A + B (p = 0.047), a test of cognitive flexibility. Cause of amputation (dysvascular or non-dysvascular) was not an independent predictor of walking outcome. These results indicate that simple clinical assessments completed prior to prosthetic provision can be used to predict mobility outcome. These findings need to be validated in a larger population across other amputee rehabilitation services and if confirmed could easily be incorporated into routine clinical practice.

Electrocardiographic and other clinical correlates of walking ability in older women

The purpose of this study was to examine how resting electrocardiographic (ECG) and other clinical variables, which can be included in a routine clinical examination, predict walking ability in older women. Three hundred and twenty women (63–75 years) without overt cardiac diseases and apparent mobility limitations were studied. Measurements performed were clinical examination (standard 12-lead resting ECG, assessment of physical activity level, presence of chronic diseases, use of beta-blockers, body mass index (BMI), ability to squat, resting blood pressure) and six-minute walking test. Participants walked 533 ± 75 m in the six-minute walking test. The best electrocardiographic predictors of long walking distance were high TV 5 and TII, but their explanation rates were small (4.5% and 3.8%, respectively). In hypertensive participants (systolic blood pressure = SBP ≥ 160 mmHg), the respective values were 9.3% and 5.8%. The best predictors of long walking distance were ability to squat without limitations and low BMI (15.5% and 13.6%, respectively). Altogether the studied variables explained 36% of the variation in walking distance. The data gathered in clinical examination give useful information for the assessment of walking ability in relatively healthy older women. Resting ECG does not give clinically significant additional information for the assessment in subjects without overt cardiac disease.

Walking ability and activity level after hip fracture in the elderly--a follow-up.

The purpose of this study was to investigate which variables can predict walking ability and activity level 1 year after hip fracture and to describe changes over time regarding functional capacity. One hundred and fifty-seven patients (111 women, 46 men), mean age 80.9 (SD 9.5) years, operated on for hip fracture, and able to participate either fully or to some extent in performance tests approximately 1 week after operation were included. Due to high mortality and fragility, only 57 patients participated in the 1-year follow-up. The patients were tested at discharge regarding physical performance, pain and bone mineral density. Status before fracture was evaluated by means of interview. At the 1-year follow-up, patients were also asked about their activities outside the home. A stepwise logistic regression was used for prediction. The patients had a significantly faster walking speed and better balance function after 1 year than before. The test "Timed up and go" was a strong predictor for both walking ability and activity level 1 year after hip fracture. Knowledge about the patient's walking habits outdoors before hip fracture and the degree of independent walking before hip fracture strengthened the prediction.