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Walking performance: correlation between energy cost of walking and walking participation. new statistical approach concerning outcome measurement.

Franceschini M, Rampello A, Agosti M, Massucci M, Bovolenta F, Sale P - PLoS ONE (2013)

Bottom Line: The multivariable binary logistical regression analysis has produced a statistical model with good characteristics of fit and good predictability.This model generated a cut-off value of.40, which enabled us to classify correctly the cases with a percentage of 85.0%.We have been also identifying a cut-off value of CW cost, which makes a distinction between those who can walk in the community and those who cannot do it.

View Article: PubMed Central - PubMed

Affiliation: Department of NeuroRehabilitation IRCCS San Raffale, Pisana, Rome.

ABSTRACT
Walking ability, though important for quality of life and participation in social and economic activities, can be adversely affected by neurological disorders, such as Spinal Cord Injury, Stroke, Multiple Sclerosis or Traumatic Brain Injury. The aim of this study is to evaluate if the energy cost of walking (CW), in a mixed group of chronic patients with neurological diseases almost 6 months after discharge from rehabilitation wards, can predict the walking performance and any walking restriction on community activities, as indicated by Walking Handicap Scale categories (WHS). One hundred and seven subjects were included in the study, 31 suffering from Stroke, 26 from Spinal Cord Injury and 50 from Multiple Sclerosis. The multivariable binary logistical regression analysis has produced a statistical model with good characteristics of fit and good predictability. This model generated a cut-off value of.40, which enabled us to classify correctly the cases with a percentage of 85.0%. Our research reveal that, in our subjects, CW is the only predictor of the walking performance of in the community, to be compared with the score of WHS. We have been also identifying a cut-off value of CW cost, which makes a distinction between those who can walk in the community and those who cannot do it. In particular, these values could be used to predict the ability to walk in the community when discharged from the rehabilitation units, and to adjust the rehabilitative treatment to improve the performance.

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Model to identify a cut-off value of Energy Cost of walk (CW).The CW is the energy cost per kilogram per unit of distance covered (mlO2*Kg−1*min−1). C is the criterion. J = sensitivity (C)+specificity (C). J finding the best cut-off point that is equivalent to measuring the J of Youden Index. Youden Index is the greatest vertical distance between ROC curve and the diagonal line.
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pone-0056669-g001: Model to identify a cut-off value of Energy Cost of walk (CW).The CW is the energy cost per kilogram per unit of distance covered (mlO2*Kg−1*min−1). C is the criterion. J = sensitivity (C)+specificity (C). J finding the best cut-off point that is equivalent to measuring the J of Youden Index. Youden Index is the greatest vertical distance between ROC curve and the diagonal line.

Mentions: Once we defined a predictive model of walking in the community, we investigated whether there was a cut-off point of the energy cost of walking (the independent variables) that could predict membership of each subject in one of the two WHS categories. If a reference criterion was available, receiver-operating characteristic (ROC) analyses offered an elaborate method for the construction of cut-off points [20]. Having used a continuous variable such as Cost of Walking (CW), in which the sensitivity and specificity have for us the same statistical weight, the best cut-off point for obtaining a positive result from the test is the maximum value which can be obtained for both of these aspects of which the sum is the highest possible. This is necessary in order to identify the patients that cannot develop a walk in the context of the community. With this procedure, the determination of the cut-off point is equivalent to the achievement of the minimum value of false negative and false positive, which are dependent on mistakes in classification. The cut-off point obtained with this method has the characteristic of reaching the best expected objective, that is to say: maximize the potential for correct diagnosis and minimize the errors of classification. In the case in which c is the best cut-off point of the test results, Youden introduced the following index for ROC curve: J = sensitivity (c)+specificity (c). Moreover, finding the best cut-off point is equivalent to measuring the J of Youden Index. This index is an important synthesis of ROC curve. From the point of view of the graph, the Youden Index is the greatest vertical distance between ROC curve and the diagonal line (Fig. 1). It presents itself as having a complete and optimal potential measurement of the diagnostic capacity regarding clinical activity. ROCs describe the relation between sensitivity and specificity for different cut-off points. ROC analyses provide an evaluation of the ability of the diagnostic instruments to discriminate between health and disease.


Walking performance: correlation between energy cost of walking and walking participation. new statistical approach concerning outcome measurement.

Franceschini M, Rampello A, Agosti M, Massucci M, Bovolenta F, Sale P - PLoS ONE (2013)

Model to identify a cut-off value of Energy Cost of walk (CW).The CW is the energy cost per kilogram per unit of distance covered (mlO2*Kg−1*min−1). C is the criterion. J = sensitivity (C)+specificity (C). J finding the best cut-off point that is equivalent to measuring the J of Youden Index. Youden Index is the greatest vertical distance between ROC curve and the diagonal line.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3585321&req=5

pone-0056669-g001: Model to identify a cut-off value of Energy Cost of walk (CW).The CW is the energy cost per kilogram per unit of distance covered (mlO2*Kg−1*min−1). C is the criterion. J = sensitivity (C)+specificity (C). J finding the best cut-off point that is equivalent to measuring the J of Youden Index. Youden Index is the greatest vertical distance between ROC curve and the diagonal line.
Mentions: Once we defined a predictive model of walking in the community, we investigated whether there was a cut-off point of the energy cost of walking (the independent variables) that could predict membership of each subject in one of the two WHS categories. If a reference criterion was available, receiver-operating characteristic (ROC) analyses offered an elaborate method for the construction of cut-off points [20]. Having used a continuous variable such as Cost of Walking (CW), in which the sensitivity and specificity have for us the same statistical weight, the best cut-off point for obtaining a positive result from the test is the maximum value which can be obtained for both of these aspects of which the sum is the highest possible. This is necessary in order to identify the patients that cannot develop a walk in the context of the community. With this procedure, the determination of the cut-off point is equivalent to the achievement of the minimum value of false negative and false positive, which are dependent on mistakes in classification. The cut-off point obtained with this method has the characteristic of reaching the best expected objective, that is to say: maximize the potential for correct diagnosis and minimize the errors of classification. In the case in which c is the best cut-off point of the test results, Youden introduced the following index for ROC curve: J = sensitivity (c)+specificity (c). Moreover, finding the best cut-off point is equivalent to measuring the J of Youden Index. This index is an important synthesis of ROC curve. From the point of view of the graph, the Youden Index is the greatest vertical distance between ROC curve and the diagonal line (Fig. 1). It presents itself as having a complete and optimal potential measurement of the diagnostic capacity regarding clinical activity. ROCs describe the relation between sensitivity and specificity for different cut-off points. ROC analyses provide an evaluation of the ability of the diagnostic instruments to discriminate between health and disease.

Bottom Line: The multivariable binary logistical regression analysis has produced a statistical model with good characteristics of fit and good predictability.This model generated a cut-off value of.40, which enabled us to classify correctly the cases with a percentage of 85.0%.We have been also identifying a cut-off value of CW cost, which makes a distinction between those who can walk in the community and those who cannot do it.

View Article: PubMed Central - PubMed

Affiliation: Department of NeuroRehabilitation IRCCS San Raffale, Pisana, Rome.

ABSTRACT
Walking ability, though important for quality of life and participation in social and economic activities, can be adversely affected by neurological disorders, such as Spinal Cord Injury, Stroke, Multiple Sclerosis or Traumatic Brain Injury. The aim of this study is to evaluate if the energy cost of walking (CW), in a mixed group of chronic patients with neurological diseases almost 6 months after discharge from rehabilitation wards, can predict the walking performance and any walking restriction on community activities, as indicated by Walking Handicap Scale categories (WHS). One hundred and seven subjects were included in the study, 31 suffering from Stroke, 26 from Spinal Cord Injury and 50 from Multiple Sclerosis. The multivariable binary logistical regression analysis has produced a statistical model with good characteristics of fit and good predictability. This model generated a cut-off value of.40, which enabled us to classify correctly the cases with a percentage of 85.0%. Our research reveal that, in our subjects, CW is the only predictor of the walking performance of in the community, to be compared with the score of WHS. We have been also identifying a cut-off value of CW cost, which makes a distinction between those who can walk in the community and those who cannot do it. In particular, these values could be used to predict the ability to walk in the community when discharged from the rehabilitation units, and to adjust the rehabilitative treatment to improve the performance.

Show MeSH
Related in: MedlinePlus