As the elderly population is increasing worldwide [1], the number of stroke patients is also rapidly rising; the number of first time stroke patients worldwide was 16.9 million in 2010 [2]. These patients often suffer from neural sequelae such as hemiparesis, which results in disabilities whereby the patient requires assistance for their activities in daily living (ADL) [3]. This aspect imposes a heavy burden on both medical and social welfare costs. The goals of rehabilitative treatment for stroke patients are to alleviate patients’ disabilities and to thus reduce social costs. To design an effective rehabilitative treatment, outcome prediction is critically important.

Several test scales have been used in daily clinical practices for stroke patients. In the acute stage, the National Institute of Health Stroke Scale (NIHSS) is the most commonly used because of its practical applicability at the bedside [4]. However, this impairment assessment may undermine its applicability for the long-term outcome prediction when disability in ADL is often considered to be the most serious clinical concern.

The Functional Independence Measure (FIM) [5] is also a frequently used assessment tool for stroke patients. FIM calculates 13 motor and 5 cognitive items in reference to ADL, and directly reflects the burdens of care. Nevertheless, scoring FIM is often difficult within a few days after the onset at the bedside, where activities of FIM items are usually not allowed (e.g., bathing and/or stairs climb). In contrast to NIHSS, which is often assessed during the acute stage, FIM is often used in long-term rehabilitation settings, several months after onset.

As mentioned above, a long-term outcome prediction is needed in terms of ADL from the acute stage, when only impairment level assessment is currently possible. However, only a few studies have been carried out that outline the association between NIHSS in the acute stage and FIM motor items several months later. In this study, we assessed the relationships between NIHSS and FIM motor assessment items with adjustments made to demographic and clinical data such as age and lesion size in order to address this gap. To minimize variability of stroke symptoms, we focused on cerebral infarct in the middle cerebral artery (MCA) areas, the most common type of stroke [6].

This is a retrospective cohort study. The Ethics and Hospital Committees of Goshi Hospital approved this study.

Fig. 2 presents the flow diagram of patients. Of the total 118 patients, 79 MCA region infarcted patients fulfilled the criteria, while 29 were excluded due to comorbidities or complications, 2 were excluded due to rehabilitation refusal, and 8 were excluded due to missing information. Hence, we allocated these 79 patients into two groups at a 2:1 ratio (53 in the model-development group and 26 in the confirmatory group). Table 1 shows the demographic profiles of these two groups. No statistically significant differences were found in age, gender, mRS, lesion laterality, DWI-ASPECTS+W, infarct type, contents of infarct therapy, length of stay of acute and rehabilitation facilities, and hospital day when the rehabilitative treatment began. Fig. 3 presents the characteristics of the 53 patients of the model-development group. The scatter diagrams show the relevance between the total score of NIHSS and the independence/dependence of each motor item of FIM.

Tables 2 and 3 indicate the results obtained from the multiple logistic regression analyses performed in the model-development group. A statistically significant correlation was found for at least one single NIHSS item for each FIM motor item. Of the NIHSS items, the most commonly involved factor was the affected lower extremity item. Among the 13 FIM motor items, affected lower extremity item contributed to 11 regression equations, but did not contribute to the eating and shower transfer items, indicating the importance of the lower extremity function of the affected side for the long-term ADL outcome. The second commonly involved NIHSS item was the affected upper extremity item, which accounted for 7 regression equations for the items of eating, grooming, bathing, toileting, bed transfer, toilet transfer, and shower transfer.

To adjust the correlation analyses between the NIHSS and FIM motor items, we added parameters from demographic and clinical data. Of these items, in combination with several NIHSS items, age showed statistically significant relationships for six items including grooming, toileting, bladder management, bed transfer, toilet transfer, and shower transfer. For example, the result for the FIM item for bed transfer produces the prediction equation of 19.63-(0.20×Age)-(3.39×Affected upper extremity 3rd)-(3.91×Affected lower extremity 2nd) (Table 2). Fig. 4 shows the logistic curve obtained from this formula. When the value of the affected upper extremity is under 3 and that of the affected lower extremity is under 2, these values can be converted to 0 (referring to Fig. 1). The positive number of this equation indicates independence: $19.63-(0.20\times \text{Age})>, \text{namely}\frac{19.63}{0.20}=98.15>\text{Age}$. This means that a patient under 98 years old who can show anti-gravitational upper extremity movement and hold the affected lower extremity at 30° in the supine position (NIHSS definition) during the acute phase, is predicted to regain the ability to transfer between a bed and a wheelchair referring to Fig. 4. Apart from age, mRS before stroke onset was also detected as having statistically significant relationships for 5 items including upper body dressing, lower body dressing, bowel management, bladder management, and stairs climb (Tables 2 and 3).

Table 4 presents the accuracy rates of the model-development and confirmatory groups.

We employed the criteria using an accuracy rates 25% higher than the value based on the chance rate. According to that, our confirmatory group items were excellent except a stairs climb item. Thus, the prediction models derived from the multiple logistic models were confirmed for within-institutional validity for FIM motor items except stairs climb.

By using multivariate logistic regression statistics employing NIHSS assessed within a few days after stroke and adjusting factors such as age and pre-stroke independence level, we were able to develop prediction models for the long-term outcomes of FIM motor items. At least one single NIHSS item correlated with each FIM motor item, implying the applicability of acute phase NIHSS for the long-term outcome prediction in terms of disability. The accuracy rates in the confirmatory group were as high as those for the model-development group.

Of all NIHSS items, the degrees of paralysis in the affected upper and lower extremities most evidently affected the long-term FIM outcomes. In particular, the score for affected lower extremity was predictive for the FIM motor items, except for eating and shower transfer, implying that gross assessment of hemiparesis may be predictive for long-term ADL outcomes. In the daily clinical practice for stroke treatment, clinicians often use the manual muscle test (MMT/MRC) [13,14] to assess the gross levels of hemiparesis in the upper extremity and lower extremity. This method may be more widely used than NIHSS because NIHSS is an evaluation used specifically by stroke specialists. In reality, some stroke patients who are treated by general physicians are unfamiliar with NIHSS. The present findings suggest that the gross assessment of hemiparesis such as MMT/MRC in the acute stage may be partially predictive for long-term ADL.

In addition to NIHSS, age was shown to be a statistically significant contributing factor for the prediction of the long-term outcome assessed by FIM motor items. The previous studies indicated a correlation of age with general independence at a few months after the onset [15,16] and with walking independence at 6 months [17]. In this study, among the explanatory variables, statistics revealed that age had the greatest effect on the outcomes. However, age is only one explanatory variable that was assessed on an interval scale. Such an aspect might contribute to the greatest predictive power. Careful consideration should be given to the difference of the scales (nominal, ordinal, or interval) when the relative importance among explanatory variables is to be discussed.

In contrast to the previous studies on this topic [18,19], we included several patients who were not fully independent before the onset. Indeed, some patients in our database were recurrent stroke cases who were affected by previous episodes. To address this concern, in this study, we assessed ADL before the onset by using mRS. Analysis results showed that ADL status before stroke was also a powerful predictive factor for the long-term outcomes assessed by FIM motor items. In actual clinics, stroke cases often show recurrence and are accompanied with disability in ADL. The methodology in the present study may be more practical than that used in the previous studies on stroke outcome, in which only data on firstever stroke cases who were fully independent before the onset were collected [20-22].

In this study, to assess the within-institutional validity, we employed the confirmatory group. The results obtained from the confirmatory group were very similar to those obtained from the model-development group (Table 4), indicating the obtained prediction models were sufficient. However, the results for stairs climb were negative. Previous studies indicated that the stairs climb item is the most difficult among the FIM motor items [10,11]. The negative finding for this item could be partially attributed to the ceiling effect, under which most of patients can gain a goal for its easiness. In addition, cognitive factors, one of which is considered to be falling risks [23], may influence the lower accuracy rate of stairs climb because NIHSS is not sufficient for the assessment of cognitive functions in terms of ADL [24].

This study has several limitations. First, the sample size was small, with only 53 cases in the model-development group and 26 cases in the confirmatory group. However, we detected statistically significant models for all 13 FIM motor items in the model-development group, and the validity of the success of all models except stair climb was confirmed. Despite the small sample size, the results from our analyses were relatively positive. Second, due to the nature of our sample, the findings need careful consideration when applying the models to wider stroke populations. The study samples were collected from patients who were transferred to long-term rehabilitative facilities after acute medical services. Therefore, mild or severe cases were omitted in the study sample; mild cases are usually discharged because of their minimum impairment, and severe ones are transferred to nursing facilities. Third, inter-facility validation was not assessed. For the study, to avoid variability of the treatment methodology during the acute medical service, we collected patients who were treated in a single acute hospital. The obtained results were positive. To further confirm the validity of the present study, a well-designed study for inter-facility validation is needed. Fourth, in this study, to simplify our analytical procedures, we defined ‘independence’ for the bathing, shower transfer, and stairs climb items as including supervision levels (FIM 5). Original FIM terminology does not include supervision as independence. However, as the patients with MCA infarct often suffer from severe hemiparesis, retaining supervision level (FIM 5) could be a realistic goal for these difficult items. We therefore employed a modified terminology for this study.