Mechanical and biological results of short-stem hip implants: consideration on a series of 74 cases.

BACKGROUND: The aim of this survey was to show mid-term outcomes of a short-stem cementless hip prosthesis with metaphyseal fit and fill. METHODS: Case series is on 74 implants in 67 patients, implanted from June 2006 to December 2010 with an average follow-up of 48 months (range 36-90 months). RESULTS: In their case series, authors found some pitfalls as varus or valgus alignment, heterotopic ossification, aseptic mobilization with subsidency, and malpositioning. According to Harris Hip Score, postoperative clinical outcomes were excellent-good (84 %) and fair-poor (16 %). CONCLUSIONS: At a mid-term follow-up, the investigated implant showed a strong stability and some well-tolerated mechanical and biological pitfalls.

Use of the Halstead Category Test as a cognitive predictor of functional recovery in the hemiplegic upper limb: a cross-validation study.

Current motor learning theory suggests that recovery in the hemiplegic upper limb partially depends on the client's cognitive ability to maximize sensory feedback in order to activate appropriate efferent motor pathways. Study 1 investigated the use of the Category Test as a predictor of functional recovery. Initial scores on the Upper Extremity Function Test and the Category Test explained 81% of the variance of the discharge Upper Extremity Function score (N = 29). Psychological factors such as the client's attitude and motivation were less significant than more direct measures of the biological event. Study 2 (N = 16) confirmed these results and also found that stroke survivors who made fewer errors on the Category Test performed better on a functional disability test. Survivors making the fewest errors on the Category Test also showed the greatest amount of change in arm and hand function. The results are discussed in terms of the role of cognitive and biological factors that might influence recovery.

Neural network modeling accurately predicts the functional outcome of stroke survivors with moderate disabilities.

OBJECTIVE: To predict the place of discharge or discharge Functional Independence Measure (FIM) score for stroke survivors with moderate disability using neural network modeling. Our previous work demonstrated that the FIM predicts the level of recovery for stroke survivors with either severe or mild disabilities. DESIGN: Neural network analysis. SETTING: Tertiary care rehabilitation program. PATIENTS: One hundred forty-seven consecutive stroke survivors admitted for rehabilitation with admission FIM scores between 37 and 96 were used as the training and internal test set. Seventeen other randomly selected stroke survivors were used as the external test set. INTERVENTION: A neural network model was developed using a small set of clinical variables and the admission FIM score. MAIN OUTCOME MEASURE: Neural network model predicting place of discharge or discharge FIM score. RESULTS: A working and accurate model was developed to predict the discharge FIM score. The model was able to predict the 17 external test cases with an accuracy = 88%, sensitivity = 83%, specificity = 91%, positive predictive value = 83%, and negative predictive value = 91%. CONCLUSION: Neural network modeling is useful in the prediction of functional recovery and helps in discharge planning and allocation of rehabilitation resources.

The functional independence measure: its use to identify rehabilitation needs in stroke survivors.

To explore the potential of the Functional Independence Measure (FIM) as a prognostic indicator of outcome in stroke survivors, 113 consecutive patients were observed from admission until discharge. Patients received assessment and treatment by a multidisciplinary team in a regional tertiary care stroke-specific rehabilitation program. The FIM, Chedoke-McMaster Stroke Assessment, and discharge location were used as the main outcome measures. The results suggested that; (1) impairment variables alone are insufficient as prognostic indicators of outcome; (2) the absolute admission FIM score, not the change in the FIM score, is the best predictor of outcome disability and place of discharge; and (3) subgroups of stroke survivors with differing rehabilitation needs can be identified. The FIM allows us to classify stroke survivors according to their needs; therefore, attention should be redirected to the development of prognostic indicators for groups of stroke survivors.

Measuring physical impairment and disability with the Chedoke-McMaster Stroke Assessment.

BACKGROUND AND PURPOSE: The Chedoke-McMaster Stroke Assessment measures the physical impairments and disabilities that impact on the lives of individuals with stroke. This measure has three overall purposes: 1) to stage motor recovery to classify individuals in terms of clinical characteristics, 2) to predict rehabilitation outcomes, and 3) to measure clinically important change in physical function. This study was carried out to evaluate the ability of this measure to yield reliable and valid results. METHODS: Thirty-two subjects from a stroke rehabilitation treatment unit were assessed by research and treating physical therapists using multiple measures on multiple occasions. The measure's three purposes dictated the study objectives and design. RESULTS: Intrarater, interrater, and test-retest reliabilities of the impairment and disability inventories were estimated. Reliability coefficients for the total scores ranged from 0.97 to 0.99. Construct and concurrent validities were studied by examining the correlations between this and other measures. A priori hypothetical constructs stated that these correlations should exceed 0.60. These constructs were confirmed; the impairment inventory total score was found to correlate with the Fugl-Meyer Test (r = 0.95, p < 0.001) and the disability inventory with the Functional Independence Measure (r = 0.79, p < 0.05). Additional study hypotheses were also substantiated. CONCLUSIONS: This study confirms that the Chedoke-McMaster Stroke Assessment yields both reliable and valid results. With the evaluation study now completed, the Chedoke-McMaster Stroke Assessment can be used with confidence as both a clinical and a research tool that can discriminate among subjects and evaluate patient outcomes.