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Determinants for the Use of Ambulation Aids in a Geriatric Rehabilitation Care Unit: A Retrospective Study
JAMDA 13 (2012) 279e283
JAMDA journal homepage: www.jamda.com
Original Study
Determinants for the Use of Ambulation Aids in a Geriatric Rehabilitation Care Unit: A Retrospective Study Amine El Helou Eng, MSc a, *, Sylvie Bastuji-Garin MD, PhD b, c, Elena Paillaud MD, PhD b, d, Jean-Michel Gracies MD, PhD a, e, f, Wafa Skalli PhD a, Philippe Decq MD, PhD a, e, g a
Arts et Métiers ParisTech, Laboratoire de Biomécanique (LBM), Paris, France Université Paris Est, Laboratoire d’Investigation Clinique, Créteil, France c AP-HP, Département de Recherche Clinique et Santé Publique, Hôpital Henri-Mondor, Créteil, France d AP-HP, Service de Gériatrie, Hôpital Henri-Mondor, Créteil, France e Université Paris est Créteil (UPEC), Créteil Cedex, France f AP-HP, Service de Médecine Physique et de Réadaptation, Unité de Neurorééducation, Groupe Hospitalier Henri Mondor, Créteil, France g AP-HP, Service de Neurochirurgie, Groupe Hospitalier Henri Mondor, Créteil, France b
a b s t r a c t Keywords: Aging rehabilitation comorbidity assistive device
Objectives: This study aimed at assessing the profile of ambulation aid users among patients admitted for geriatric rehabilitation care. Design: Retrospective chart review. Setting: Geriatric Rehabilitation Department of the Hôpital Albert Chenevier, Créteil, France. Participants: The sample comprised 206 records of patients aged 65 or older with no previous use of assistive device before admission and length of stay longer than 7 days. Measurements: Ambulation levels were classified as independent ambulators (IA, reference category), ambulation aid users (AA), or nonambulatory patients (NA). we explored age, gender, purpose of initial admission, comorbidities, and past medical history as factors potentially associated with ambulation levels, using multinomial logistic regression. Results: The study population (mean age 84 years [6.1 standard deviation], 68.5 % women) comprised 110 IA (53.4% of the overall population), 72 AA (34.9%), and 24 NA (11.6%). Factors independently associated with AA use were the following: older age (odds ratio ¼ 1.17; [95% confidence interval 1.09e1.25]), previous history of lower limb surgery (2.15; [1.0e4.73]), and admission for hip surgery (8.14; [2.60e 25.53]). Factors independently associated with NA were the following: older age (1.12 [1.02e1.23]) and low Mini-Mental State Exam score (0.77 [0.70e0.85]). A borderline association was observed for visual impairment (3.36 [0.93e12.95]). Cardiac disease, respiratory disease, falls, and dementia were not associated with ambulation aid use. Conclusions: History of lower-limb surgery, particularly recent hip surgery, and old age are the primary predictive factors of ambulation aid use in a geriatric rehabilitation hospital. Copyright Ó 2012 - American Medical Directors Association, Inc.
In elderly patients, the ability to stand and walk without assistance may be compromised by cardiovascular, respiratory, neurologic, metabolic, and/or musculoskeletal impairment. In these conditions, ambulation aids (such as canes or walkers) are often prescribed to reduce the risk of falls1,2 and facilitate or improve mobility during activities of daily living (ADLs).3 In clinical routine,
This work was supported by the French National Research Agency (ANR) through the TecSan program (project MIRAS n ANR-08-TECS-009). * Address correspondence to Amine El Helou, Eng, MSc, Laboratoire de Biomécanique, Arts et Métiers ParisTech, 151, Boulevard de l’Hôpital, F-75013 Paris, France. E-mail address: [email protected] (A. El Helou).
the prescription of an assistive device is often a subjective decision, based on factors such as balance, mental status, strength, coordination, and age.4 Overall, canes are typically recommended for patients with moderate level of impairment, and walkers for more marked impairment. There has been a body of work reporting adverse effects and constraints related to walker use:5 high energy expenditure,6 increased risk of falls,7 altered gait patterns,8e10 and upper limb pain and need for sufficient upper body strength.11 User dissatisfaction was reported in some situations.12 In recent years, there have been important advances in the design of mechanical/robotic aids.13e18 However, studies were performed on heterogeneous cohorts comprising various gait disorders and/or visual impairments, and the clinical meaningfulness of findings
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remains uncertain. The lack of background information about ambulation aid users may have contributed to conflicting results. We believe that there is a need for a more comprehensive and accurate description of patients who may require or benefit from ambulation aids so as to guide the design and evaluation of new robotic aids. To our knowledge, no extensive studies have been carried out on large samples of elderly users. The aim of this study was thus to investigate the profile of ambulation aids users in an elderly population admitted for geriatric rehabilitation care. Methods Population We retrospectively reviewed the medical charts of all patients consecutively admitted to the Geriatric Rehabilitation Department of the Albert Chenevier-Henri Mondor University Hospital in Créteil (France) from January 2008 to June 2009. Based on the hypothesis that almost a third of this population might be ambulation aid users, an inclusion of at least 200 records would yield such an estimation with an accuracy lower than 0.10 (alpha ¼ 0.05). We were also aware of the mean length of stay in our clinical department, so the period of patient recruitment chosen for the study was determined accordingly. Patients were eligible if they met the following inclusion criteria: (1) age 65 or older, (2) independent ambulation (no use of ambulation aids) before admission, and (3) length of stay longer than 7 days.
walker user (standard or rollator) (AAw) or cane/crutch user (AAc); and nonambulatory (NA), ie, wheelchair user/bed-bound. Data Analysis Patient characteristics were described and compared among the 3 ambulation-level groups. Continuous variables (age, weight, height, body mass index, MMSE, duration of bed rest, length of stay, number of comorbidities) were reported as mean (SD) or median and minimum-maximum range as appropriate. Categorical variables (comorbidities, gender, and reason for initial admission) were reported as numbers (%). An overall comparison of the 3 groups was first performed using Fisher’s exact or chi-square tests, analysis of variance, or Kruskal-Wallis tests as appropriate. We then performed multinomial logistic regression models to estimate the ageadjusted odds ratios (OR) with their 95% confidence interval (95% CI). The 3 ambulation-level groups were considered as the possible values of a nominal qualitative outcome variable with the IA group as reference. The ORs (95% CIs) were estimated only for variables emerging with a P value less than .15 in the overall comparison. Bivariate analyses were used to assess potential confounding and first-order interaction. Then, to identify factors independently associated with ambulation level, we performed multivariate analysis, using exact logistic regression models. Statistical calculations did not replace missing data. All comparisons were 2-sided and P values of .05 or lower were considered significant. No adjustments for multiple comparisons were performed. All analyses were performed using Stata software (SE II, StataCorp 2009; College Station. TX).
Data Collection Results Patient Characteristics: Comorbidities For each patient we collected demographics (age, gender); anthropometric data (weight, height, body mass index); reasons for initial admission; identifying factors such as cardiovascular or respiratory disorders (eg, cardiac failure, myocardial infarction, pulmonary embolism), orthopedic surgery, stroke, and others; length of stay in the geriatric rehabilitation unit; score on Folstein et al’s Mini-Mental-State Exam19 (MMSE); list of comorbid diseases in the past history at time of admission; complications during the hospital stay; need for human assistance in ADLs (eg, transferring from bed to chair, chair-rise, walking) persisting during the whole stay; and duration of bed rest before admission. In orthopedic surgery cases, the latter was defined as the delay from surgery date (or date of trauma/fall) to the day when limb loading was reauthorized, and otherwise as the overall duration of continuous hospitalization in other units preceding rehabilitation admission. We classified the more prevalent reasons for admission into the following groups: (1) cardiovascular or respiratory disease, (2) hip surgery (eg, total/partial replacement owing to severe trauma/ osteoarthritis), and (3) other, miscellaneous reasons (eg, stroke, nontraumatic falls, frailty or loss of independence, orthopedic interventions excluding hip). Ambulation Level The level of ambulation during the rehabilitation stay was determined from the medical chart, answering the following questions: Was an ambulation aid used? If so, what was the most significant assistive device used at any time during the stay? For example, if a patient initially required a walker, then a cane, and ended up independent, the classification was recorded as “walker user.” Ambulation aids used only during physical therapy sessions were not considered. Ambulation levels were then defined as the following: independent ambulator (IA), when the patient did not use ambulation aids; ambulation aid user (AA), subdivided into
A total of 206 patients met the inclusion criteria in the defined period of analysis. Mean age was 84 (6.1 SD) years; 141 (68.5%) were women. Patient characteristics are described in Table 1. During the stay, more than half the patients (110; 53.4%) did not need ambulation aids and were classified in the IA group. Seventy-two (35%; 95% confidence interval [28.4e41.5]) used ambulation aids and comprised the AA group, in which 48 (23.3%) used a walker (wheeled or standard, AAw) and 24 (11.6%) used canes/crutches (AAc). The remaining patients (n ¼ 24; 11.6%) were using only a wheelchair and/or were bed-bound (NA group). In the walker users group (AAw, Table 1), 72.9% were women; mean age was 86.4 (5.8). The main purposes of initial admission in this group were hip surgery, generally owing to trauma/fall, severe osteoarthritis or prosthesis dislocation (n ¼ 15; 31.2% of users) with possible total/partial hip replacement, and severe cardiovascular or respiratory disease (n ¼ 13; 27.0% of users). However, when pooling all neurological cases (as comorbidity or admission purpose, Parkinson’s, Alzheimer’s, epilepsy, essential tremor, stroke, myelopathy, spinal cord injury), 35.4% (n ¼ 17 of 48) of walker users had at least one neurological condition (versus 30.9% (n ¼ 34 of 110) in the IA group). Comparison between Groups Ambulation aid users (AA) were older (OR ¼ 1.16; 95% CI ¼ [1.10e1.23]), had more often a history of lower-limb surgery (2.31; [1.1e4.85]), and a more substantial need for human assistance in ADLs (2.86; [1.10e7.19]) than subjects in the IA group. Nonambulatory patients (NA) were also older (1.15 [1.07e1.25]) and had more often serious conditions, such as malnutrition (2.83 [1.09e7.32]), balance impairment (2.97 [1e9.46]), important need of human assistance in ADLs (21.88 [7.0e68.44]), prevalence of a neurologic condition (4.24 [1.6e11.24]), and a lower MMSE score
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Table 1 Description of Sample and Walker Users (AAw) Variable
All (206)
Age, y Gender, female Height, m Weight, kg BMI Bed rest duration, days, median (range) Length of stay, days, median (range) No. of comorbidities,* median (range) Arterial hypertension Cardiac disease Peripheral arterial/vascular disease Respiratory disease Malnutrition Anemia Diabetes History of lower-limb trauma/surgery History of upper-limb trauma/surgery History of falls Balance impairment Need of human assistance in ADL Visual impairment Depression Dementia Neurologicy Stroke - transient ischemic attack Behavioral impairment/confusion Alzheimer’s Epilepsy Parkinson’s Other MMSE, median (range) Initial admission purpose Cardiovascular/Respiratory disease Hip surgery Other Stroke Frailty/loss of independence Lower-limb surgery (excluding hip) Falls (nontraumatic) Others
84 141 1.59 58 24 18 35 4.5 148 107 101 84 80 35 33 48 22 36 31 39 38 46 39 75 28 14 13 12 9 7 22
(6.2) (68.5) (0.1) (31e115) (5.3) (1e115) (6e216) (1e12) (71.8) (51.9) (49.0) (40.7) (38.8) (16.9) (16.0) (23.3) (10.6) (17.4) (15.0) (18.9) (18.4) (22.3) (18.9) (36.4) (13.6) (6.8) (6.3) (5.8) (4.3) (3.4) (3e30)
72 28 106 18 18 15 14 41
(34.9) (13.6) (51.4) (8.7) (8.7) (7.3) (6.8) (19.9)
Missing Data 0 111 100 103 110 1 0
51
AAw (48) 86.4 35 1.59 62.1 23.9 18 59.5 4.5 36 20 21 19 24 7 8 20 6 13 10 11 13 6 5 17 7 2 4 3 2 0 21 13 15 20 2 3 7 2 6
(5.7) (72.9) (0.09) (15.5) (5.8) (1e97) (6e198) (1e10) (75.0) (41.7) (43.8) (39.6) (50.0) (14.6) (16.7) (41.7) (12.5) (27.1) (20.8) (22.9) (27.1) (12.5) (10.4) (35.4) (14.6) (4.2) (8.3) (6.3) (4.2) (0) (7e30)
Missing Data 0 20 18 20 19 0 0
11
(27.0) (31.2) (41.6) (4.1) (6.2) (14.6) (4.1) (12.5)
Quantitative variables are expressed as mean ( SD) except otherwise specified. Qualitative variables are expressed in numbers (%). ADL, activities of daily living; BMI, body mass index; MMSE, mini mental state exam. * Concomitant condition at the time of admission AND complications during patient’s stay. y At least one of the listed neurologic conditions.
(0.83 [0.75e0.91]) than subjects in the IA group. Length of stay differed across groups, with independent ambulators staying less time than the other 2 groups (IA, median 31; range 7e216 days; AD, 42.5 [6e198]; NA, 56 [16e167]; P < .001). In addition, within the subgroup of patients admitted for a cardiovascular or respiratory decompensation, bed rest duration had been longer for walker users (27 [7e70] days) than for ambulatory patients (17 [1e43] days; P ¼ .02) (data not shown). Univariate Analysis Table 2 displays overall associations between ambulation level (IA, AA, and NA) and patient characteristics. Ambulation level was associated with age (P < .001), gender (P ¼ .02), concomitant respiratory disease (P ¼ .02), diabetes (P ¼ .02), history of lowerlimb trauma (P ¼ .02), need for human assistance in ADLs (P < .001), subsistence of a neurologic condition (P ¼ .004), the MMSE score (P < .001), and the purpose of initial admission (P ¼ .001). A nonsignificant association (P < .15) was observed between ambulation level and the following comorbidities: malnutrition (P ¼ .08), falls (P ¼ .13), balance impairment (P ¼ .14), visual impairment (P ¼ .09), depression (P ¼ .07), and Parkinson’s disease (P ¼ .06). Admission for hip surgery was associated (8.31 [2.68e25.75]) with
ambulation aid use but not with bed-bound condition (4.55 [0.85e24.67]). Cardiac disease (P ¼ .51), respiratory disease (0.76 [0.39e1.47]), falls (1.93 [0.83e4.52]), and dementia (P ¼ .15) were not associated with ambulation aid use.
Multivariate Analysis In multivariate analysis (Table 3), older age (1.17 [1.09e1.24]), history of lower-limb trauma (2.15 [1e4.73]), and admission for hip surgery (8.14 [2.6e25.53]) remained significantly associated with AA use. Factors associated with nonambulation (NA) were older age (1.12 [1.02e1.23]) and low MMSE scores (0.77 [0.69e0.85]). A borderline association was observed for visual impairment (3.36 [0.93e12.95]).
Discussion The present study suggests that ambulation aid users are older (86.4 [5.7 SD] years), and more often admitted after lower-limb surgery and for longer stays in rehabilitation care than independent ambulators. Neurological conditions as a group were associated with low ambulation level.
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Table 2 Univariate Analysis Variable
IA (110)
AA (72)
NA (24)
P*
Age, y Gender, female Height, m Weight, kg, median (range) BMI Bed rest duration, days, median (range) Length of stay, days, median (range) No. of comorbidities,z median (range) Arterial hypertension Cardiac disease Peripheral arterial/vascular disease Respiratory disease Malnutrition Anemia Diabetes History of lower-limb trauma/surgery History of upper-limb trauma/surgery Falls Balance impairment Need for human assistance in ADL Visual impairment Depression Dementia Neurologicx Stroke - transient ischemic attack Behavioral impairment/confusion Alzheimer Epilepsy Parkinson Other MMSE, median (range) Reason for initial admission Cardiovascular/Respiratory disease Hip surgery Other
81.8 75 1.59 58 24.6 17 31 5 76 60 55 46 34 20 23 19 10 14 12 8 16 26 20 34 11 9 6 5 4 4 23
86.6 51 1.60 59 23.8 17 42.5 4 56 37 36 30 31 10 10 25 10 16 13 15 14 11 11 25 11 2 4 4 2 2 23
84 15 1.54 55 22.9 26 56 4 16 10 10 8 5 5 0 4 2 6 6 16 8 9 8 16 6 3 3 3 3 1 11
<.0001 .02 .22 .54 .57 .23 <.0001 .27 .37 .51 .74 .02 .08 .62 .02 .02 .54 .13 .14 <.0001 .09 .07 .15 .004 .16 .2 .34 .32 .06 .96 .0002 .001
(5.4) (68.2) (0.08) (31e115) (5.6) (1e115) (7e216) (1e10) (69.1) (54.5) (50.0) (41.8) (30.9) (18.2) (20.9) (17.2) (9.1) (12.7) (10.9) (7.2) (14.5) (23.6) (18.2) (30.9) (10.0) (8.2) (5.4) (4.5) (3.6) (3.6) (3e30)
45 (40.9) 6 (5.4) 59 (53.6)
(5.5) (70.8) (0.09) (39 -99) (5.1) (1e97) (6e198) (1e10) (77.8) (51.4) (50.0) (41.7) (43.1) (13.9) (13.9) (34.7) (13.9) (22.2) (18.0) (20.8) (19.4) (15.3) (15.3) (34.7) (15.3) (2.8) (5.6) (5.6) (2.8) (2.8) (7e30)
21 (29.1) 19 (26.4) 32 (44.4)
(6.2) (62.5) (0.07) (42e71) (4.9) (1e95) (16e167) (2e12) (66.7) (41.7) (41.7) (33.3) (20.8) (20.8) (0.0) (16.7) (8.3) (25.0) (25.0) (66.7) (33.3) (37.5) (33.3) (66.7) (25.0) (12.5) (12.5) (12.5) (12.5) (4.1) (5e28)
6 (25.0) 3 (12.5) 15 (62.5)
Multinomial Logistic Regression Odds Ratio [95% Confidence Interval]y IA (ref.)
AA
NA
1 1
1.16 [1.10e1.23] 1.13 [0.59e2.16]
1.15 [1.07e1.25] 0.77 [0.31e1.95]
1 1
0.76 [0.39e1.47] 1.25 [0.64e2.44]
0.53 [0.2e1.41] 2.83 [1.09e7.32]
1 1
0.88 [0.37e2.12] 2.31 [1.1e4.85]
e 0.87 [0.26e2.92]
1 1 1 1 1
1.93 1.97 2.86 1.14 0.54
2.25 [0.73e6.92] 2.97 [0.93e9.46] 21.88 [7.0e68.44] 2.4 [0.85e6.74] 1.81 [0.68e4.81]
1
1.32 [0.67e2.6]
4.24 [1.6e11.24]
1
1 [0.95e1.07]
0.83 [0.75e0.91]
1 1 1
8.31 [2.68e25.75] 1.42 [0.68e2.95]
4.55 [0.85e24.67] 2.31 [0.80e6.69]
[0.83e4.52] [0.78e4.96] [1.10e7.19] [0.5e2.65] [0.23e1.25]
Quantitative variables are expressed as mean (SD) except otherwise specified. Qualitative variables are expressed in numbers (%). IA, independent ambulators; AA, ambulation aid users; NA, nonambulatory patients; BMI, body mass index; ADL, activities of daily living; MMSE, Mini-Mental State Exam. * Chi-square or Fisher’s exact testeanalysis of variance or Kruskal-Wallis as appropriate. y Age-adjusted odds ratios and confidence intervals (CI) were estimated using exact multinomial logistic regression models, the IA group being the reference category. z Concomitant condition at the time of admission AND complications during patient’s stay. x At least one of the listed neurologic conditions. Bold indicates P Values lower than 0.15.
Although these findings are consistent with previous cohort studies,10,18,20e27 limitations of this work included the traditional drawbacks of retrospective studies, eg, issues with hospital record accuracy, diagnostic criteria potentially variable across physicians, coding errors, lack or loss of information, and potential biases in case of important numbers from specific population subgroups. Some of the associations between purposes of initial admission and ambulation level were anticipated. For example, a patient admitted for hip trauma/surgery would be expected to require a walker during the recovery process to reduce weight bearing on lower extremities.28e31 In our sample, most patients who had a hip surgery (n ¼ 19 of 28: 68% of hip fracture patients) needed ambulation aids to gradually re-load the affected limb. These findings concur with previous studies, in which ambulation aid use remained important 6 and 12 months after fracture.3,27 Past history of lower-limb surgery (hip, knee, or ankle owing to fall/trauma or severe osteoarthritis), an expected reason for walker use,3,4 was also found in 42% (n ¼ 20 of 48) of users versus only 16% to 17% of independent ambulators or nonambulatory patients (P ¼ .02). The differences in bed rest time between walker users and independent ambulators (within patients admitted for a cardiovascular or respiratory purpose) suggest that walker use may have become necessary after an extended bed rest (to assist with balance recovery), often a consequence of the cardiorespiratory
decompensation itself. The high MMSE median score in the AA group (equal to the IA group score) might reflect the need for cognitive competence for proficiency in ambulation aids use,10,32 an interpretation in line with the cognitive load known to be associated with walker use.33 Walker users were not distinguished by a higher prevalence of concomitant respiratory disorders compared with independent ambulators; however, a significant proportion (n ¼ 19 of 48, 40%) did have a concomitant respiratory disorder. These subjects may have been helped by walker use to reduce cardiorespiratory demands (metabolic cost, dyspnea, oxygen uptake).20,34e36 Unexpectedly, a history of falls was not associated with ambulation aid use.20,31,37 Factors such as depression, visual impairment, need for help in ADLs, and reduced strength owing to malnutrition were associated with nonambulatory status, which may be related to their potential impediment of ambulation aid use. Conclusions This article reports a retrospective analysis of ambulation aid use (with an emphasis on the walker) in an elderly population admitted for rehabilitation care in a geriatric unit. The purpose of the study was to determine the profile of community-dwelling subjects who had used an ambulation aid (eg, walker and cane)
A. El Helou et al. / JAMDA 13 (2012) 279e283 Table 3 Multivariate Analysis Ambulation Level
Odds Ratio*
IA
(Base Outcome)
AA Age MMSE Visual impairment History of lower-limb trauma Reason for initial admission Cardiovascular/Respiratory disease Hip surgery Other NA Age MMSE Visual impairment History of lower-limb trauma Reason for initial admission Cardiovascular/Respiratory disease Hip surgery Other
[95% Confidence Interval]*
P
1.17 1.00 1.14 2.15
1.09 0.94 0.47 1.00
1.25 1.07 2.78 4.73
.00 .95 .77 .05
1.00 8.14 1.48
d 2.6 0.70
d 25.53 3.15
d .00 .30
1.12 0.77 3.36 1.79
1.02 0.70 0.90 0.43
1.23 0.85 12.95 7.43
.02 .00 .08 .42
1.00 5.31 2.14
d 0.71 0.57
d 39.70 8.00
d .10 .26
IA, independent ambulators; AA, ambulation aid users; NA, nonambulatory patients; MMSE, Mini-Mental State Exam. * Odds ratios and 95% confidence intervals were estimated using exact multivariate multinomial logistic regression model; IA group was the reference category.
during their stay, also examining the possible influence of comorbid or physiological conditions on their ambulation capacity. Causative relationships between these risk factors and ambulation aid use were not investigated in this retrospective study. Our findings show that ambulation aid users are not necessarily fallers. The main risk factors of ambulation aid use are older age, post lower-limb surgery status, and history of lower-limb trauma. Although the present findings need confirmation using prospective studies and diversified samples, they may contribute as a resource for assistive device developers. They may also assist geriatric rehabilitation physicians by setting up preventive exercise programs for older people with these identified risk factors.
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9. Liu HH, McGee M, Wang W, Persson M. Comparison of gait characteristics between older rolling walker users and older potential walker users. Arch Gerontol Geriatr 2009;48:276e280. 10. Gracies JM. [Neurorehabilitation in parkinsonian syndromes.]. Rev Neurol (Paris) 2010;166:196e212. French. 11. Bachschmidt RA, Harris GF, Simoneau GG. Walker-assisted gait in rehabilitation: A study of biomechanics and instrumentation. IEEE Trans Neural Syst Rehabil Eng 2001;9:96e105. 12. Brandt Ã, Iwarsson S, Stahl A. Satisfaction with rollators among communityliving users: a follow-up study. Disabil Rehabil 2003;25:343e353. 13. Dickstein R, Smolinski Z, Pillar T. Self-propelled weight-relieving walker for gait rehabilitation. J Biomed Eng 1992;14:351e355. 14. Lacey G, MacNamara S. User involvement in the design and evaluation of a smart mobility aid. J Rehabil Res Dev 2000;37:709e723. 15. Wasson G, Gunderson J, Graves S, Felder R. An assistive robotic agent for pedestrian mobility. Paper presented at: Proceedings of the 5th International Conference on Autonomous Agents; May 28eJune 1, 2001; Montreal, Quebec. 16. Glover J, Thrun S, Matthews JT. Learning user models of mobility-related activities through instrumented walking aids. Paper presented at: Proceedings of the IEEE International Conference on Robotics and Automation; April 26eMay 1, 2004; New Orleans, LA. 17. Spenko M, Yu H, Dubowsky S. Robotic personal aids for mobility and monitoring for the elderly. IEEE Trans Neural Syst Rehabil Eng 2006;14: 344e351. 18. Rentschler AJ, Simpson R, Cooper RA, Boninger ML. Clinical evaluation of Guido robotic walker. J Rehabil Res Dev 2008;45:1281e1293. 19. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12:189e198. 20. Andersen DA, Roos BA, Stanziano DC, et al. Walker use, but not falls, is associated with lower physical functioning and health of residents in an assistedliving environment. Clin Interv Aging 2007;2:123e137. 21. Eggermont LH, van Heuvelen MJ, van Keeken BL, et al. Walking with a rollator and the level of physical intensity in adults 75 years of age or older. Arch Phys Med Rehabil 2006;87:733e736. 22. Nawata K, Nitta A, Watanabe S, Kawabuchi K. An analysis of the length of stay and effectiveness of treatment for hip fracture patients in Japan: Evaluation of the 2002 Revision of the Medical Service Fee Schedule. J Health Econ 2006;25: 722e739. 23. Maeda A, Nakamura K, Higuchi S, et al. Postural sway during cane use by patients with stroke. Am J Phys Med Rehabil 2001;80:903e908. 24. Jaeger RJ, Yarkony GM, Roth EJ. Rehabilitation technology for standing and walking after spinal cord injury. Am J Phys Med Rehabil 1989;68:128e133. 25. Elmamoun M, Mulley G. Walking sticks and frames for patients with neurological disorders. Pract Neurol 2007;7:24e31. 26. Holder CG, Haskvitz EM, Weltman A. The effects of assistive devices on the oxygen cost, cardiovascular stress, and perception of nonweight-bearing ambulation. J Orthop Sports Phys Ther 1993;18:537e542. 27. Williamson VC. Management of lower extremity fractures. Orthop Nurs 1998; 17:84e87. 28. Marottoli RA, Berkman LF, Cooney LM Jr. Decline in physical function following hip fracture. J Am Geriatr Soc 1992;40:861e866. 29. Fox KM, Hawkes WG, Magaziner J, et al. Markers of failure to thrive among older hip fracture patients. J Am Geriatr Soc 1996;44:371e376. 30. Palombaro KM, Craik RL, Mangione KK, Tomlinson JD. Determining meaningful changes in gait speed after hip fracture. Phys Ther 2006;86:809e816. 31. Graafmans WC, Lips P, Wijlhuizen GJ, et al. Daily physical activity and the use of a walking aid in relation to falls in elderly people in a residential care setting. Z Gerontol Geriatr 2003;36:23e28. 32. Wright DL, Kemp TL. The dual-task methodology and assessing the attentional demands of ambulation with walking devices. Phys Ther 1992;72:306e312. discussion 313e305. 33. Honeyman P, Barr P, Stubbing DG. Effect of a walking aid on disability, oxygenation, and breathlessness in patients with chronic airflow limitation. J Cardiopulm Rehabil 1996;16:63e67. 34. Hill K, Goldstein R, Gartner EJ, Brooks D. Daily utility and satisfaction with rollators among persons with chronic obstructive pulmonary disease. Arch Phys Med Rehabil 2008;89:1108e1113. 35. Gupta RB, Brooks D, Lacasse Y, Goldstein RS. Effect of rollator use on healthrelated quality of life in individuals with COPD. Chest 2006;130:1089e1095. 36. Probst VS, Troosters T, Coosemans I, et al. Mechanisms of improvement in exercise capacity using a rollator in patients with COPD. Chest 2004;126: 1102e1107. 37. Hogue CC. Falls and mobility in late life: An ecological model. J Am Geriatr Soc 1984;32:858e861.
JAMDA journal homepage: www.jamda.com
Original Study
Determinants for the Use of Ambulation Aids in a Geriatric Rehabilitation Care Unit: A Retrospective Study Amine El Helou Eng, MSc a, *, Sylvie Bastuji-Garin MD, PhD b, c, Elena Paillaud MD, PhD b, d, Jean-Michel Gracies MD, PhD a, e, f, Wafa Skalli PhD a, Philippe Decq MD, PhD a, e, g a
Arts et Métiers ParisTech, Laboratoire de Biomécanique (LBM), Paris, France Université Paris Est, Laboratoire d’Investigation Clinique, Créteil, France c AP-HP, Département de Recherche Clinique et Santé Publique, Hôpital Henri-Mondor, Créteil, France d AP-HP, Service de Gériatrie, Hôpital Henri-Mondor, Créteil, France e Université Paris est Créteil (UPEC), Créteil Cedex, France f AP-HP, Service de Médecine Physique et de Réadaptation, Unité de Neurorééducation, Groupe Hospitalier Henri Mondor, Créteil, France g AP-HP, Service de Neurochirurgie, Groupe Hospitalier Henri Mondor, Créteil, France b
a b s t r a c t Keywords: Aging rehabilitation comorbidity assistive device
Objectives: This study aimed at assessing the profile of ambulation aid users among patients admitted for geriatric rehabilitation care. Design: Retrospective chart review. Setting: Geriatric Rehabilitation Department of the Hôpital Albert Chenevier, Créteil, France. Participants: The sample comprised 206 records of patients aged 65 or older with no previous use of assistive device before admission and length of stay longer than 7 days. Measurements: Ambulation levels were classified as independent ambulators (IA, reference category), ambulation aid users (AA), or nonambulatory patients (NA). we explored age, gender, purpose of initial admission, comorbidities, and past medical history as factors potentially associated with ambulation levels, using multinomial logistic regression. Results: The study population (mean age 84 years [6.1 standard deviation], 68.5 % women) comprised 110 IA (53.4% of the overall population), 72 AA (34.9%), and 24 NA (11.6%). Factors independently associated with AA use were the following: older age (odds ratio ¼ 1.17; [95% confidence interval 1.09e1.25]), previous history of lower limb surgery (2.15; [1.0e4.73]), and admission for hip surgery (8.14; [2.60e 25.53]). Factors independently associated with NA were the following: older age (1.12 [1.02e1.23]) and low Mini-Mental State Exam score (0.77 [0.70e0.85]). A borderline association was observed for visual impairment (3.36 [0.93e12.95]). Cardiac disease, respiratory disease, falls, and dementia were not associated with ambulation aid use. Conclusions: History of lower-limb surgery, particularly recent hip surgery, and old age are the primary predictive factors of ambulation aid use in a geriatric rehabilitation hospital. Copyright Ó 2012 - American Medical Directors Association, Inc.
In elderly patients, the ability to stand and walk without assistance may be compromised by cardiovascular, respiratory, neurologic, metabolic, and/or musculoskeletal impairment. In these conditions, ambulation aids (such as canes or walkers) are often prescribed to reduce the risk of falls1,2 and facilitate or improve mobility during activities of daily living (ADLs).3 In clinical routine,
This work was supported by the French National Research Agency (ANR) through the TecSan program (project MIRAS n ANR-08-TECS-009). * Address correspondence to Amine El Helou, Eng, MSc, Laboratoire de Biomécanique, Arts et Métiers ParisTech, 151, Boulevard de l’Hôpital, F-75013 Paris, France. E-mail address: [email protected] (A. El Helou).
the prescription of an assistive device is often a subjective decision, based on factors such as balance, mental status, strength, coordination, and age.4 Overall, canes are typically recommended for patients with moderate level of impairment, and walkers for more marked impairment. There has been a body of work reporting adverse effects and constraints related to walker use:5 high energy expenditure,6 increased risk of falls,7 altered gait patterns,8e10 and upper limb pain and need for sufficient upper body strength.11 User dissatisfaction was reported in some situations.12 In recent years, there have been important advances in the design of mechanical/robotic aids.13e18 However, studies were performed on heterogeneous cohorts comprising various gait disorders and/or visual impairments, and the clinical meaningfulness of findings
1525-8610/$ - see front matter Copyright Ó 2012 - American Medical Directors Association, Inc. doi:10.1016/j.jamda.2010.12.008
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remains uncertain. The lack of background information about ambulation aid users may have contributed to conflicting results. We believe that there is a need for a more comprehensive and accurate description of patients who may require or benefit from ambulation aids so as to guide the design and evaluation of new robotic aids. To our knowledge, no extensive studies have been carried out on large samples of elderly users. The aim of this study was thus to investigate the profile of ambulation aids users in an elderly population admitted for geriatric rehabilitation care. Methods Population We retrospectively reviewed the medical charts of all patients consecutively admitted to the Geriatric Rehabilitation Department of the Albert Chenevier-Henri Mondor University Hospital in Créteil (France) from January 2008 to June 2009. Based on the hypothesis that almost a third of this population might be ambulation aid users, an inclusion of at least 200 records would yield such an estimation with an accuracy lower than 0.10 (alpha ¼ 0.05). We were also aware of the mean length of stay in our clinical department, so the period of patient recruitment chosen for the study was determined accordingly. Patients were eligible if they met the following inclusion criteria: (1) age 65 or older, (2) independent ambulation (no use of ambulation aids) before admission, and (3) length of stay longer than 7 days.
walker user (standard or rollator) (AAw) or cane/crutch user (AAc); and nonambulatory (NA), ie, wheelchair user/bed-bound. Data Analysis Patient characteristics were described and compared among the 3 ambulation-level groups. Continuous variables (age, weight, height, body mass index, MMSE, duration of bed rest, length of stay, number of comorbidities) were reported as mean (SD) or median and minimum-maximum range as appropriate. Categorical variables (comorbidities, gender, and reason for initial admission) were reported as numbers (%). An overall comparison of the 3 groups was first performed using Fisher’s exact or chi-square tests, analysis of variance, or Kruskal-Wallis tests as appropriate. We then performed multinomial logistic regression models to estimate the ageadjusted odds ratios (OR) with their 95% confidence interval (95% CI). The 3 ambulation-level groups were considered as the possible values of a nominal qualitative outcome variable with the IA group as reference. The ORs (95% CIs) were estimated only for variables emerging with a P value less than .15 in the overall comparison. Bivariate analyses were used to assess potential confounding and first-order interaction. Then, to identify factors independently associated with ambulation level, we performed multivariate analysis, using exact logistic regression models. Statistical calculations did not replace missing data. All comparisons were 2-sided and P values of .05 or lower were considered significant. No adjustments for multiple comparisons were performed. All analyses were performed using Stata software (SE II, StataCorp 2009; College Station. TX).
Data Collection Results Patient Characteristics: Comorbidities For each patient we collected demographics (age, gender); anthropometric data (weight, height, body mass index); reasons for initial admission; identifying factors such as cardiovascular or respiratory disorders (eg, cardiac failure, myocardial infarction, pulmonary embolism), orthopedic surgery, stroke, and others; length of stay in the geriatric rehabilitation unit; score on Folstein et al’s Mini-Mental-State Exam19 (MMSE); list of comorbid diseases in the past history at time of admission; complications during the hospital stay; need for human assistance in ADLs (eg, transferring from bed to chair, chair-rise, walking) persisting during the whole stay; and duration of bed rest before admission. In orthopedic surgery cases, the latter was defined as the delay from surgery date (or date of trauma/fall) to the day when limb loading was reauthorized, and otherwise as the overall duration of continuous hospitalization in other units preceding rehabilitation admission. We classified the more prevalent reasons for admission into the following groups: (1) cardiovascular or respiratory disease, (2) hip surgery (eg, total/partial replacement owing to severe trauma/ osteoarthritis), and (3) other, miscellaneous reasons (eg, stroke, nontraumatic falls, frailty or loss of independence, orthopedic interventions excluding hip). Ambulation Level The level of ambulation during the rehabilitation stay was determined from the medical chart, answering the following questions: Was an ambulation aid used? If so, what was the most significant assistive device used at any time during the stay? For example, if a patient initially required a walker, then a cane, and ended up independent, the classification was recorded as “walker user.” Ambulation aids used only during physical therapy sessions were not considered. Ambulation levels were then defined as the following: independent ambulator (IA), when the patient did not use ambulation aids; ambulation aid user (AA), subdivided into
A total of 206 patients met the inclusion criteria in the defined period of analysis. Mean age was 84 (6.1 SD) years; 141 (68.5%) were women. Patient characteristics are described in Table 1. During the stay, more than half the patients (110; 53.4%) did not need ambulation aids and were classified in the IA group. Seventy-two (35%; 95% confidence interval [28.4e41.5]) used ambulation aids and comprised the AA group, in which 48 (23.3%) used a walker (wheeled or standard, AAw) and 24 (11.6%) used canes/crutches (AAc). The remaining patients (n ¼ 24; 11.6%) were using only a wheelchair and/or were bed-bound (NA group). In the walker users group (AAw, Table 1), 72.9% were women; mean age was 86.4 (5.8). The main purposes of initial admission in this group were hip surgery, generally owing to trauma/fall, severe osteoarthritis or prosthesis dislocation (n ¼ 15; 31.2% of users) with possible total/partial hip replacement, and severe cardiovascular or respiratory disease (n ¼ 13; 27.0% of users). However, when pooling all neurological cases (as comorbidity or admission purpose, Parkinson’s, Alzheimer’s, epilepsy, essential tremor, stroke, myelopathy, spinal cord injury), 35.4% (n ¼ 17 of 48) of walker users had at least one neurological condition (versus 30.9% (n ¼ 34 of 110) in the IA group). Comparison between Groups Ambulation aid users (AA) were older (OR ¼ 1.16; 95% CI ¼ [1.10e1.23]), had more often a history of lower-limb surgery (2.31; [1.1e4.85]), and a more substantial need for human assistance in ADLs (2.86; [1.10e7.19]) than subjects in the IA group. Nonambulatory patients (NA) were also older (1.15 [1.07e1.25]) and had more often serious conditions, such as malnutrition (2.83 [1.09e7.32]), balance impairment (2.97 [1e9.46]), important need of human assistance in ADLs (21.88 [7.0e68.44]), prevalence of a neurologic condition (4.24 [1.6e11.24]), and a lower MMSE score
A. El Helou et al. / JAMDA 13 (2012) 279e283
281
Table 1 Description of Sample and Walker Users (AAw) Variable
All (206)
Age, y Gender, female Height, m Weight, kg BMI Bed rest duration, days, median (range) Length of stay, days, median (range) No. of comorbidities,* median (range) Arterial hypertension Cardiac disease Peripheral arterial/vascular disease Respiratory disease Malnutrition Anemia Diabetes History of lower-limb trauma/surgery History of upper-limb trauma/surgery History of falls Balance impairment Need of human assistance in ADL Visual impairment Depression Dementia Neurologicy Stroke - transient ischemic attack Behavioral impairment/confusion Alzheimer’s Epilepsy Parkinson’s Other MMSE, median (range) Initial admission purpose Cardiovascular/Respiratory disease Hip surgery Other Stroke Frailty/loss of independence Lower-limb surgery (excluding hip) Falls (nontraumatic) Others
84 141 1.59 58 24 18 35 4.5 148 107 101 84 80 35 33 48 22 36 31 39 38 46 39 75 28 14 13 12 9 7 22
(6.2) (68.5) (0.1) (31e115) (5.3) (1e115) (6e216) (1e12) (71.8) (51.9) (49.0) (40.7) (38.8) (16.9) (16.0) (23.3) (10.6) (17.4) (15.0) (18.9) (18.4) (22.3) (18.9) (36.4) (13.6) (6.8) (6.3) (5.8) (4.3) (3.4) (3e30)
72 28 106 18 18 15 14 41
(34.9) (13.6) (51.4) (8.7) (8.7) (7.3) (6.8) (19.9)
Missing Data 0 111 100 103 110 1 0
51
AAw (48) 86.4 35 1.59 62.1 23.9 18 59.5 4.5 36 20 21 19 24 7 8 20 6 13 10 11 13 6 5 17 7 2 4 3 2 0 21 13 15 20 2 3 7 2 6
(5.7) (72.9) (0.09) (15.5) (5.8) (1e97) (6e198) (1e10) (75.0) (41.7) (43.8) (39.6) (50.0) (14.6) (16.7) (41.7) (12.5) (27.1) (20.8) (22.9) (27.1) (12.5) (10.4) (35.4) (14.6) (4.2) (8.3) (6.3) (4.2) (0) (7e30)
Missing Data 0 20 18 20 19 0 0
11
(27.0) (31.2) (41.6) (4.1) (6.2) (14.6) (4.1) (12.5)
Quantitative variables are expressed as mean ( SD) except otherwise specified. Qualitative variables are expressed in numbers (%). ADL, activities of daily living; BMI, body mass index; MMSE, mini mental state exam. * Concomitant condition at the time of admission AND complications during patient’s stay. y At least one of the listed neurologic conditions.
(0.83 [0.75e0.91]) than subjects in the IA group. Length of stay differed across groups, with independent ambulators staying less time than the other 2 groups (IA, median 31; range 7e216 days; AD, 42.5 [6e198]; NA, 56 [16e167]; P < .001). In addition, within the subgroup of patients admitted for a cardiovascular or respiratory decompensation, bed rest duration had been longer for walker users (27 [7e70] days) than for ambulatory patients (17 [1e43] days; P ¼ .02) (data not shown). Univariate Analysis Table 2 displays overall associations between ambulation level (IA, AA, and NA) and patient characteristics. Ambulation level was associated with age (P < .001), gender (P ¼ .02), concomitant respiratory disease (P ¼ .02), diabetes (P ¼ .02), history of lowerlimb trauma (P ¼ .02), need for human assistance in ADLs (P < .001), subsistence of a neurologic condition (P ¼ .004), the MMSE score (P < .001), and the purpose of initial admission (P ¼ .001). A nonsignificant association (P < .15) was observed between ambulation level and the following comorbidities: malnutrition (P ¼ .08), falls (P ¼ .13), balance impairment (P ¼ .14), visual impairment (P ¼ .09), depression (P ¼ .07), and Parkinson’s disease (P ¼ .06). Admission for hip surgery was associated (8.31 [2.68e25.75]) with
ambulation aid use but not with bed-bound condition (4.55 [0.85e24.67]). Cardiac disease (P ¼ .51), respiratory disease (0.76 [0.39e1.47]), falls (1.93 [0.83e4.52]), and dementia (P ¼ .15) were not associated with ambulation aid use.
Multivariate Analysis In multivariate analysis (Table 3), older age (1.17 [1.09e1.24]), history of lower-limb trauma (2.15 [1e4.73]), and admission for hip surgery (8.14 [2.6e25.53]) remained significantly associated with AA use. Factors associated with nonambulation (NA) were older age (1.12 [1.02e1.23]) and low MMSE scores (0.77 [0.69e0.85]). A borderline association was observed for visual impairment (3.36 [0.93e12.95]).
Discussion The present study suggests that ambulation aid users are older (86.4 [5.7 SD] years), and more often admitted after lower-limb surgery and for longer stays in rehabilitation care than independent ambulators. Neurological conditions as a group were associated with low ambulation level.
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Table 2 Univariate Analysis Variable
IA (110)
AA (72)
NA (24)
P*
Age, y Gender, female Height, m Weight, kg, median (range) BMI Bed rest duration, days, median (range) Length of stay, days, median (range) No. of comorbidities,z median (range) Arterial hypertension Cardiac disease Peripheral arterial/vascular disease Respiratory disease Malnutrition Anemia Diabetes History of lower-limb trauma/surgery History of upper-limb trauma/surgery Falls Balance impairment Need for human assistance in ADL Visual impairment Depression Dementia Neurologicx Stroke - transient ischemic attack Behavioral impairment/confusion Alzheimer Epilepsy Parkinson Other MMSE, median (range) Reason for initial admission Cardiovascular/Respiratory disease Hip surgery Other
81.8 75 1.59 58 24.6 17 31 5 76 60 55 46 34 20 23 19 10 14 12 8 16 26 20 34 11 9 6 5 4 4 23
86.6 51 1.60 59 23.8 17 42.5 4 56 37 36 30 31 10 10 25 10 16 13 15 14 11 11 25 11 2 4 4 2 2 23
84 15 1.54 55 22.9 26 56 4 16 10 10 8 5 5 0 4 2 6 6 16 8 9 8 16 6 3 3 3 3 1 11
<.0001 .02 .22 .54 .57 .23 <.0001 .27 .37 .51 .74 .02 .08 .62 .02 .02 .54 .13 .14 <.0001 .09 .07 .15 .004 .16 .2 .34 .32 .06 .96 .0002 .001
(5.4) (68.2) (0.08) (31e115) (5.6) (1e115) (7e216) (1e10) (69.1) (54.5) (50.0) (41.8) (30.9) (18.2) (20.9) (17.2) (9.1) (12.7) (10.9) (7.2) (14.5) (23.6) (18.2) (30.9) (10.0) (8.2) (5.4) (4.5) (3.6) (3.6) (3e30)
45 (40.9) 6 (5.4) 59 (53.6)
(5.5) (70.8) (0.09) (39 -99) (5.1) (1e97) (6e198) (1e10) (77.8) (51.4) (50.0) (41.7) (43.1) (13.9) (13.9) (34.7) (13.9) (22.2) (18.0) (20.8) (19.4) (15.3) (15.3) (34.7) (15.3) (2.8) (5.6) (5.6) (2.8) (2.8) (7e30)
21 (29.1) 19 (26.4) 32 (44.4)
(6.2) (62.5) (0.07) (42e71) (4.9) (1e95) (16e167) (2e12) (66.7) (41.7) (41.7) (33.3) (20.8) (20.8) (0.0) (16.7) (8.3) (25.0) (25.0) (66.7) (33.3) (37.5) (33.3) (66.7) (25.0) (12.5) (12.5) (12.5) (12.5) (4.1) (5e28)
6 (25.0) 3 (12.5) 15 (62.5)
Multinomial Logistic Regression Odds Ratio [95% Confidence Interval]y IA (ref.)
AA
NA
1 1
1.16 [1.10e1.23] 1.13 [0.59e2.16]
1.15 [1.07e1.25] 0.77 [0.31e1.95]
1 1
0.76 [0.39e1.47] 1.25 [0.64e2.44]
0.53 [0.2e1.41] 2.83 [1.09e7.32]
1 1
0.88 [0.37e2.12] 2.31 [1.1e4.85]
e 0.87 [0.26e2.92]
1 1 1 1 1
1.93 1.97 2.86 1.14 0.54
2.25 [0.73e6.92] 2.97 [0.93e9.46] 21.88 [7.0e68.44] 2.4 [0.85e6.74] 1.81 [0.68e4.81]
1
1.32 [0.67e2.6]
4.24 [1.6e11.24]
1
1 [0.95e1.07]
0.83 [0.75e0.91]
1 1 1
8.31 [2.68e25.75] 1.42 [0.68e2.95]
4.55 [0.85e24.67] 2.31 [0.80e6.69]
[0.83e4.52] [0.78e4.96] [1.10e7.19] [0.5e2.65] [0.23e1.25]
Quantitative variables are expressed as mean (SD) except otherwise specified. Qualitative variables are expressed in numbers (%). IA, independent ambulators; AA, ambulation aid users; NA, nonambulatory patients; BMI, body mass index; ADL, activities of daily living; MMSE, Mini-Mental State Exam. * Chi-square or Fisher’s exact testeanalysis of variance or Kruskal-Wallis as appropriate. y Age-adjusted odds ratios and confidence intervals (CI) were estimated using exact multinomial logistic regression models, the IA group being the reference category. z Concomitant condition at the time of admission AND complications during patient’s stay. x At least one of the listed neurologic conditions. Bold indicates P Values lower than 0.15.
Although these findings are consistent with previous cohort studies,10,18,20e27 limitations of this work included the traditional drawbacks of retrospective studies, eg, issues with hospital record accuracy, diagnostic criteria potentially variable across physicians, coding errors, lack or loss of information, and potential biases in case of important numbers from specific population subgroups. Some of the associations between purposes of initial admission and ambulation level were anticipated. For example, a patient admitted for hip trauma/surgery would be expected to require a walker during the recovery process to reduce weight bearing on lower extremities.28e31 In our sample, most patients who had a hip surgery (n ¼ 19 of 28: 68% of hip fracture patients) needed ambulation aids to gradually re-load the affected limb. These findings concur with previous studies, in which ambulation aid use remained important 6 and 12 months after fracture.3,27 Past history of lower-limb surgery (hip, knee, or ankle owing to fall/trauma or severe osteoarthritis), an expected reason for walker use,3,4 was also found in 42% (n ¼ 20 of 48) of users versus only 16% to 17% of independent ambulators or nonambulatory patients (P ¼ .02). The differences in bed rest time between walker users and independent ambulators (within patients admitted for a cardiovascular or respiratory purpose) suggest that walker use may have become necessary after an extended bed rest (to assist with balance recovery), often a consequence of the cardiorespiratory
decompensation itself. The high MMSE median score in the AA group (equal to the IA group score) might reflect the need for cognitive competence for proficiency in ambulation aids use,10,32 an interpretation in line with the cognitive load known to be associated with walker use.33 Walker users were not distinguished by a higher prevalence of concomitant respiratory disorders compared with independent ambulators; however, a significant proportion (n ¼ 19 of 48, 40%) did have a concomitant respiratory disorder. These subjects may have been helped by walker use to reduce cardiorespiratory demands (metabolic cost, dyspnea, oxygen uptake).20,34e36 Unexpectedly, a history of falls was not associated with ambulation aid use.20,31,37 Factors such as depression, visual impairment, need for help in ADLs, and reduced strength owing to malnutrition were associated with nonambulatory status, which may be related to their potential impediment of ambulation aid use. Conclusions This article reports a retrospective analysis of ambulation aid use (with an emphasis on the walker) in an elderly population admitted for rehabilitation care in a geriatric unit. The purpose of the study was to determine the profile of community-dwelling subjects who had used an ambulation aid (eg, walker and cane)
A. El Helou et al. / JAMDA 13 (2012) 279e283 Table 3 Multivariate Analysis Ambulation Level
Odds Ratio*
IA
(Base Outcome)
AA Age MMSE Visual impairment History of lower-limb trauma Reason for initial admission Cardiovascular/Respiratory disease Hip surgery Other NA Age MMSE Visual impairment History of lower-limb trauma Reason for initial admission Cardiovascular/Respiratory disease Hip surgery Other
[95% Confidence Interval]*
P
1.17 1.00 1.14 2.15
1.09 0.94 0.47 1.00
1.25 1.07 2.78 4.73
.00 .95 .77 .05
1.00 8.14 1.48
d 2.6 0.70
d 25.53 3.15
d .00 .30
1.12 0.77 3.36 1.79
1.02 0.70 0.90 0.43
1.23 0.85 12.95 7.43
.02 .00 .08 .42
1.00 5.31 2.14
d 0.71 0.57
d 39.70 8.00
d .10 .26
IA, independent ambulators; AA, ambulation aid users; NA, nonambulatory patients; MMSE, Mini-Mental State Exam. * Odds ratios and 95% confidence intervals were estimated using exact multivariate multinomial logistic regression model; IA group was the reference category.
during their stay, also examining the possible influence of comorbid or physiological conditions on their ambulation capacity. Causative relationships between these risk factors and ambulation aid use were not investigated in this retrospective study. Our findings show that ambulation aid users are not necessarily fallers. The main risk factors of ambulation aid use are older age, post lower-limb surgery status, and history of lower-limb trauma. Although the present findings need confirmation using prospective studies and diversified samples, they may contribute as a resource for assistive device developers. They may also assist geriatric rehabilitation physicians by setting up preventive exercise programs for older people with these identified risk factors.
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