Predictive factors for ambulation in stroke patients in the rehabilitation setting: A multivariate analysis
Introduction
Stroke is the most common cause of adult disability in Italy; recent studies have shown that in Italy there are 194,000 new stroke cases every year and about 35% of them survive with important motor deficits [1], [2]. This signifies a continuous increase in health care costs, particularly in terms of hospital care, nursing, and home assistance. These high incidence rates and large numbers of disabled individuals have led to an ever increasing demand for rehabilitation, paralleled with a growing need to optimize the efficiency and efficacy of limited resources [3]. Therefore, a valid prognosis for each stroke patient is needed as early as possible after stroke onset to initiate optimal rehabilitation according to realistic rehabilitation goals [4]. This applies in particular to recovery of ambulation, which is frequently affected in stroke patients and requires specific rehabilitation interventions. Regaining walking ability is of great importance to patients with stroke and is a major goal of all rehabilitation programs [5]. This is probably because changes in walking function are among the most frequent causes of physical dependency in these patients. Results have shown that 12 weeks after stroke, 95% of subjects reached their best function [6]. Wade et al. [7] who had used the Functional Ambulation Classification (FAC), found that 55% of stroke survivors achieved independent walking after 3 months, but 45% of patients were discharged with residual gait impairment [8]. Although many studies have been published, the prognostic factors in ambulatory recovery of stroke patients are not well defined, despite the fact that walking is a key goal in stroke rehabilitation [9]. Initial degree of severity of sensory and motor dysfunction of the paretic leg, disability at rehabilitation admission, urinary incontinence, sitting balance, and age are generally regarded as the most important predictors for walking recovery. However, it is not yet possible to accurately predict the occurrence and extent of motor ambulation recovery in individual patients during the (sub)acute phase of their stroke [10], [11], [12], [13]. Nevertheless, knowledge about these predictors would be useful in selecting optimal rehabilitation treatment strategies for improving gait after stroke. The aim of this study was to identify factors that predict ambulatory recovery, as measured by the FAC score, in a group of subjects with ischemic or haemorrhagic stroke, admitted to intensive rehabilitation treatment.
Section snippets
Patient population
This study was based on 185 patients with hemiplegia at their first hemispheric stroke, consecutively admitted to inpatient rehabilitation treatment from January 2004 to December 2005. The diagnosis of stroke was based on clinical (presence of motor and possibly sensory deficits) and confirmed by instrumental assessment (computerized axial tomography or nuclear magnetic resonance), in accordance with World Health Organization criteria [14]. The recruited hemiplegic patients came directly from
Results
Consideration was taken of 150 of the total 185 subjects; the other 35 were excluded from the study because they did not meet the inclusion criteria. The population was split into two consecutive sets: the first (100 patients) was the construction set (to develop the model), the second (50 patients) was the validation set (to estimate the performance of the model) (Fig. 1). Table 2 shows the population's demographic and clinical characteristics and the median values of the upMI and lowMI, TCT,
Discussion
It is very important for rehabilitation clinicians to be able to predict motor and functional recovery after stroke, particularly from the point of view of optimizing specific interventions and available resource allocation [3]. In two recent reviews, Hendricks et al. [24] and Meijer et al. [25], pointed out that our knowledge on post-stroke motor and functional recovery is not yet sufficiently accurate, in either qualitative or quantitative terms. This knowledge may contribute to determining
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