Abstract
Background
Multidisciplinary interventions for fallers have provided conflicting results in part due to the diversity of fallers' profiles.
Objectives
to determine the characteristics of the subgroup of patients with a positive response to a multidisciplinary fall prevention program initiated in a geriatric day hospital.
Design
Prospective observational study in day hospital.
Methods
Patients > 75 years referred for falls during the last 3 months benefited from a multidisciplinary assessment to record their characteristics at baseline and to tailor a risk-based multidisciplinary intervention for fall prevention. Patients free from falls at the 3rd or 6th month were compared to persistent fallers for baseline characteristics.
Results
Sixty-nine patients were assessed at baseline (mean age 85.2 y (SD=0.6)), 44 at the 3rd month and 21 at the 6th month. Baseline characteristics of the patients free from falls at the 3rd month were the lower number of previous non-serious falls (p=0.013), living in nursing home (p=0.045), a higher Berg balance score (p=0.02) and a better mental health-related quality of life (M HQol, p=0.045). On multivariate analysis restricted to home-dwelling patients, the positive predictive factors were less isolation at home (OR=0.028, 95%CI [0–0.813], p=0.037), a lower number of non-serious previous falls (OR= 0.526 [0.309–0.894], p=0.018), a better M HQol (OR=1.205 [1.000–1.452], p=0.050) and a trend for younger age (OR= 0.662, [0.426–1.027], p=0.066).
Conclusion
Being able to call upon a support person (familial or institutional) to apply advice and a less serious risk of falling may be preliminary conditions for success in a multidisciplinary intervention initiated in a day hospital.
Key words: Fall, mulitdisciplinary intervention, observational study
Introduction
Frequency of falling rises with aging and leads to an increase in the rate of injuries, disability, mortality and costs for the community (1., 2., 3., 4., 5., 6., 7., 8.). Many risk factors of falling have been identified and have been used to develop screening tools (2-3, 5, 9-13) and to tailor multidisciplinary interventions for fall prevention (3-5, 14-18). According to three recent meta-analyses, multifactorial interventions may be more efficient in reducing falling in comparison to usual care (19., 20., 21.). However, some randomized controlled trials failed to demonstrate a reduction in falling, although they conducted guidelines-based multidisciplinary interventions in older people (22., 23., 24., 25., 26., 27., 28.). These conflicting results may be due to the different intensity/frequency with which the interventions were conducted, and the characteristics of the screened populations in these trials (29., 30.). For example, Salminem et al. failed to demonstrate any benefit of a multifactorial one-year fall prevention program, although subgroup analyses showed a significant reduction in falling in patients with baseline depressive symptoms, more than 3 previous falls and with a self-perceived risk of falling (26). Indeed, among old people at high risk of falling, there are many profiles (25), and they may correspond to different personalized programs. Given the central role of the day hospital in implementing multifactorial assessment and organizing subsequent management (31., 32., 33.), we sought to determine which particular subgroup of patients stopped falling after a risk-based fall prevention program in this setting. A set of criteria for identifying potential non-responders could be used to propose alternative disease management programs.
For this purpose, we conducted a prospective study including patients with recent falls who were assessed at baseline, then 3 and 6 months after a multifactorial intervention in a day hospital. We sought which baseline characteristics were predictive of stopping falls.
Methods
Study design
This prospective observational study was conducted from 2009 January to 2010 July in the day hospital of the Geriatric Department in University Hospital of Bordeaux, France. A multidisciplinary assessment was performed at baseline to record patients’ characteristics and to tailor a risk-based multidisciplinary intervention for fall prevention according to guidelines (3, 18). Patients were reassessed in the day hospital at the 3rd then 6th month by the same multidisciplinary team and to record the number of falls. Compliance was defined as a rate of advice followed higher than 50% according to patients’ and relatives’ claims at interview.
To determine predictive factors for success in the multidisciplinary intervention, comparison of patients’ baseline characteristics was performed between those with a further positive response and those with a negative response to the intervention at the 3rd and 6th month visit. A positive response to the intervention was defined as stopping falls by the 3rd and 6th month assessment.
Participants
Patients were included on the morning of their arrival if > 75 y and if referred by their personal physician for one or more falls during the last 3 months. Patients were excluded if they showed Parkinsonism requiring a particular program, if their Timed Up and Go test (TUG) was lower than 12 seconds indicating no gait troubles, and if they had already benefited from a comprehensive geriatric assessment. All of these patients were considered at risk of falling. All the participants gave their oral consent for use of their personal data for research purposes. Briefly, characteristics recorded at baseline were the following: socio-demographic data, number of falls during the last 3 months, fall-related diagnosis (for instance, hyponatremia), clinical and biological assessment, such as creatinine clearance, and health-related quality of life according to the MOS SF12 (34) with the mental and physical component score (MCS and PCS) (Table 1).
Table 1.
Baseline characteristics of included patients (n= 69)
| Variables | Baseline |
|---|---|
| Socio-demographic data | |
| Age | |
| mean, years (SD) | 85,2 (5,06) |
| Gender | |
| male/female | 20/49 |
| Home living | |
| yes, n (%) | 59 (85,5) |
| Home professional help | |
| yes, n (%) | 43 (72,8) |
| Social isolation from family | |
| yes, n (%) | 37 (62,7) |
| Number of falls per patient during | |
| the last 3 months | |
| Non serious | |
| mean (SD) | 3,043 (0,45) |
| Serious | |
| mean (SD) | 0,70 (0,97) |
| Diagnosis | |
| Undernutrition: MNA<17 | |
| yes, n (%) | 12 (17,9) |
| Anemia [<11 g/dl in female; <12 g/dl in male] | |
| yes, n (%) | 17 (24,6) |
| Hyponatremia [<135 mmol/l] | |
| yes, n (%) | 8 (11,59) |
| Inflammatory syndrome [CRP>10 mg/l] | |
| yes, n (%) | 15 (29,4) |
| Vitamine D deficiency [<10 ng/ml] | |
| yes, n (%) | 24 (34,8) |
| Visual impairment [Snellen eye chart < 20/50] | |
| yes, n (%) | 24 (34,8) |
| Heart conduction trouble | |
| yes, n (%) | 19 (27,5) |
| Orthostatic hypotension | |
| yes, n (%) | 10 (14,5) |
| Assessment | |
| BMI | |
| kg/m2, mean (SD) | |
| MMS [0-30] | |
| mean (SD) | 20,45 (6,15) |
| GDS-SF [0-15] | |
| mean (SD) | 7,43 (3,4) |
| TUG test | |
| seconds, mean (SD) | 27,8 (14,8) |
| SPPB [0-12] | |
| mean (SD) | 3,61 (2,42) |
| BBS score [0-56] | |
| mean (SD) | 33,44 (11,7) |
| ADL [0-12] | |
| mean (SD) | 3,49 (2,93) |
| IADL [0-8] | |
| mean (SD) | 3,58 (2,45) |
| CIRS-G [0-56] | |
| mean (SD) | 1,87 (0,33) |
| Number of drugs | |
| mean (SD) | 7,09 (3,16) |
| Number of psychotropic drugs | |
| mean (SD) | 1,46 (1,26) |
| Clearance of creatinine (Cockcroft formulae) | |
| ml/min, mean (SD) | 51,98 (14,90) |
| Serum albumin concentration | |
| g/l, mean (SD) | 40,37 (4,03) |
| Health related Quality of life | |
| SF12-Mental Component Summary Scale [0-100] | |
| mean (SD) | 46, 09 (7,75) |
| SF12-Physical Component Summary Scale [0-100] | |
| mean (SD) | 35,71 (9,82) |
SD: Standard deviation
Intervention
According to guidelines (3, 18), a personalized risk-based intervention was proposed to the patient and explained to the relatives as well as to the patient’s personal physician, a medical report being sent within two days. A detailed personal prescription of physiotherapy was given and technical aids were added if necessary. The social worker assessed the appropriateness of providing professional human assistance regarding the patient’s disability. During the session, psychological support was provided to patients and relatives by the psychotherapist. Treatment revision was recommended when the health status did not warrant continuing psychotropic or cardiovascular drugs. Care for orthostatic hypotension consisted in treatment revision and prescription of compression stockings. Nutritional care for undernourished subjects was proposed with dietary counseling and oral supplements. After screening, patients were referred to appropriate specialists if necessary and metabolic abnormalities such as hyponatremia or vitamin deficiency (D, B9, B12) were corrected.
Fall assessment
The number of falls was determined according to the interview with patients, their relatives or their personal physician. A serious fall was defined as the need to be hospitalized or to go to the emergency department immediately after the fall.
Statistical analyses
Values were expressed as means and standard deviation (SD), as percentage (%) or as number (n). Baseline characteristics were compared between non-fallers (i.e. patients with a positive response to intervention) and fallers at the 3rd month and 6th month using univariate then multivariate tests. For quantitative variables, unpaired t-tests or Mann-Whitney t-tests were used, whereas chi-square or Fisher tests were performed for categorical variables. Multivariate analyses were performed with a step-by-step backward logistical regression. All the analyses were performed with Graphpad prism® software (version 5.01), except logistic regression with SPSS software (Version 12). P values <0.05 were considered to be statistically significant.
Results
Flow of participants
During the inclusion period, 96 people were referred to the day hospital by their personal physician (Figure 1). Sixty-nine patients with mean age of 85.2 years (5.06) [range: 75 to 98 years]) were included. Baseline characteristics are shown in table 1. Forty-four patients were reassessed at the 3rd month and 21 at the 6th month. Among the 44 patients assessed at the 3rd month, a positive response to the intervention was noted in 20 (46%), and sustained response was noted in 5 (24%) at the 6th month. Compliance was similar at the 3rd and 6th months (82% (36/44) and 76% (16/21) respectively).
Figure 1.
Predictive factors of a positive response to the day hospital-based intervention at 3rd month
Baseline characteristics of patients with a positive response to the intervention (i.e. non-fallers) were the lower number of previous non-serious falls (2.00 (1.59) versus 4.70 (4.34), p=0.013), living in a nursing home (25.0% versus 4.2% in fallers p=0.045), a higher Berg balance score (37.28 (10.16) versus 30.50 (9.79) in fallers, p=0.02) and a better mental health-related quality of life (MCS 48.3 (7.73) versus 43.38 in fallers (6.95), p=0.045) (Table 2). A trend was also noted for a higher baseline number of psychotropic drugs (1.75 (1.33) versus 1.13 (1.39) in fallers, p=0.09), a younger age (84.25 (4.67) versus 86.83 (4.58) in fallers, p=0.07) and less isolation at home (40.0% versus 69.6% in fallers p=0.07).
Table 2.
Third month univariate and multivariate comparisons of baseline characteristics between non fallers and fallers
| Variables |
3rd month non |
3rd month |
p value |
3rd month multivariate model (p=0,001) |
|
|---|---|---|---|---|---|
| fallers (n=20) | fallers (n=24) | (univariate analysis) | OR (95%CI) | p | |
| Socio-demographic data | |||||
| Age | |||||
| mean, years (SD) | 84,25 (4,67) | 86,83 (4,57) | 0,072 | 0,662 [0,426-1,027] | 0,066 |
| Gender | |||||
| male/female | 5/15 | 6/18 | 1.00 | − | − |
| Home living * | |||||
| yes, n (%) | 15/20 (75) | 23/24 (95,8) | 0,045 | ||
| Home professional help | |||||
| yes, n (%) | 11 (73,3) | 16 (69,6) | 0,809 | − | − |
| Social isolation from family | |||||
| yes, n (%) | 6 (40) | 16 (69,6) | 0,075 | 0,028 [0,001-0,813] | 0,037 |
| Number of falls per patient during the last 3 months | |||||
| Non serious | |||||
| mean (SD) | 2,00 (1,59) | 4,67 (4,34) | 0,013 | 0,526 [0,309-0,894] | 0,018 |
| Serious | |||||
| mean (SD) | 0,70 (1,17) | 0,75 (1,03) | 0,881 | − | − |
| Diagnosis | |||||
| Undernutrition: MNA<17 | |||||
| yes, n (%) | 3 (15) | 3 (12,5) | 0,806 | − | − |
| Anémia [<11 g/dl in female; <12 g/dl in male] | |||||
| yes, n (%) | 5 (25) | 7 (29,2) | 0,764 | − | − |
| Hyponatrémie [<135 mmol/l] | |||||
| yes, n (%) | 2 (11,1) | 2 (8,3) | 0,852 | − | − |
| Inflammatory syndrome [CRP>10 mg/l] | |||||
| yes, n (%) | 1 (8,3) | 6 (33,3) | 0,121 | − | − |
| Vitamine D deficiency [<10 ng/ml] | |||||
| yes, n (%) | 7 (35) | 9(39,1) | 0,786 | − | − |
| Visual impairment [Snellen eye chart < 20/50] | |||||
| yes, n (%) | 7 (35) | 9 (37,5) | 0,786 | − | − |
| Heart conduction trouble | |||||
| yes, n (%) | 6 (30) | 5 (20,8) | 0,496 | − | − |
| Orthostatic hypotension | |||||
| yes, n (%) | 2 (10) | 2 (8,3) | 1,000 | − | − |
| Assessment | |||||
| BMI | |||||
| kg/m2, mean (SD) | 26,56 (3,97) | 28,23 (4,26) | 0,194 | − | − |
| MMS [0-30] | |||||
| mean (SD) | 19,65 (7,12) | 21,00 (6,28) | 0,508 | − | − |
| GDS-SF [0-15] | |||||
| mean (SD) | 6,21 (3,51) | 7,75 (2,75) | 0,114 | − | − |
| TUG test | |||||
| seconds, mean (SD) | 25,42 (13,02) | 28,78 (16,43) | 0,474 | − | − |
| SPPB [0-12] | |||||
| mean (SD) | 3,89 (2,81) | 3,05 (1,75) | 0,261 | − | − |
| BBS score [0-56] | |||||
| mean (SD) | 37,28 (10,16) | 30,50 (9,79) | 0,039 | − | − |
| ADL [0-12] | |||||
| mean (SD) | 3,74 (3,40) | 3,29 (2,94) | 0,648 | − | − |
| IADL [0-8] | |||||
| mean (SD) | 4,53 (2,67) | 3,30 (2,16) | 0,127 | − | − |
| CIRS-G [0-56] | |||||
| mean (SD) | 1,83 (0,06) | 1,88 (0,35) | 0,661 | − | − |
| Number of drugs | |||||
| mean (SD) | 7,20 ((3,74) | 6,50 (2,93) | 0,490 | − | − |
| Number of psychotropic drugs | |||||
| mean (SD) | 1,75 (1,33) | 1,13 (1,39) | 0,138 | − | − |
| Clearance of creatinine (Cockcroft formulae) | |||||
| ml/min, mean (SD) | 53,34 (12,54) | 51,24 (16,65) | 0,645 | − | − |
| Serum albumin concentration | |||||
| g/l, mean (SD) | 39,40 (3,19) | 40,06 (4,54) | 0,586 | − | − |
| Health related Quality of life | |||||
| SF12-Mental Component Summary Scale [0-100] | |||||
| mean (SD) | 48,32 (7,73) | 43,38 (6,95) | 0,048 | 1,205 [1,000-1,452] | 0,050 |
| SF12-Physical Component Summary Scale [0-100] | |||||
| mean (SD) | 38,89 (10,67) | 34,61 (8,35) | 0,180 | − | − |
| Compliance to the intervention | |||||
| n (%) | 14 (70) | 22 (92) | 0,064 | − | − |
SD: Standard deviation.
not included in the final model of multivariate analysis.
Multivariate analysis was performed only in people living at home. The independent predictive factors of a positive response to the intervention were less isolation at home (OR=0.028, 95%CI [0-0.813], p=0.037), a lower number of previous non-serious falls (OR= 0.526 [0.309-0.894], p=0.018), a better MCS score (OR=1.205 [1.000-1.452], p=0.050) and a trend for younger age (OR= 0.662, [0.426-1.027], p=0.066).
Predictive factors of a positive response to the day hospital-based intervention at 6th month
Non-fallers also tended to have higher baseline Berg balance scores than fallers (40.40 (5.98) versus 31.20 (11.14), p=0.054). There was a trend for higher scores for SPPB in non-fallers (6 (2.16) versus 3.3 (2.21) in fallers, p=0.07) as well as for IADL (6.25 (2.22) versus 3.73 (2.34) in fallers, p=0.07), whereas ADL scores were lower in non-fallers (0.25 (0.50) versus 2.8 (2.56) in fallers, p=0.03), indicating better baseline autonomy.
Discussion
In this study, we have identified a set of characteristics in older fallers that are predictive of a positive response at the 3rd month to a multidisciplinary intervention initiated in a day hospital: lower number of previous non-serious falls, a higher
Berg balance score indicating a better physical performance, a better mental health-related quality of life and less isolation (i.e. no isolation at home or living in a nursing home). Data at the 6th month indicate that patients who stopped falling tended to have higher baseline BBS and SPPB scores, corresponding to a lower risk of falling. They also had higher IADL and lower ADL scores, indicating less disability and a lower risk of falling (10). As a low number of non-serious falls appeared to be one of the predictors of stopping falls, we hypothesized that such a multidisciplinary day hospital intervention might be inefficient in patients at high risk of falling. These patients may need more intense physiotherapy and follow-up in a rehabilitation unit.
Living in a nursing home compared to living at home was found to be predictive of success of the day hospital-based intervention. In other trials, multifactorial programs within institutions proved efficient whatever the risk of falling (21, 35). Furthermore, the presence of close relatives at home appeared to be an independent factor of success in our study. These results concord with the fact that living alone was found by others to be associated with an increased risk of falling (36), whereas developing family support may reduce the risk (37). Social support, either at home with the family or in nursing home with the nursing staff, may function as a relay for applying the advice given at day hospital, and may help to decrease the fear of falling (38). The better quality of mental health as a strong predictive factor of success may also reflect a greater ability to follow the fall reduction intervention. Unlike others (22), we did not found that cognitive status was a factor influencing the success of our multifactorial intervention. Social support may be the best way to relay advice and to implement prescriptions, whatever the ability of the beneficiaries.
One limitation of our study is the weak statistical power of our results due to the low number of patients included, a figure lower than in trials assessing multifactorial fall prevention programs (in most trials between 100 and 200) (19., 20., 21.). However, the mean age of our population, around 85 years old, might be more representative of geriatric clinical care in comparison to other studies (5, 19., 20., 21.). This old age and the higher functional dependency of our dropout patients (higher baseline ADL score, (data not shown) may contribute to the attrition rate, which is similar to that of other trials (39) especially with a day hospital-based fall prevention program (28). For this reason, the number of patients assessed at the 6th month was not sufficient to reach statistical significance, although the same trend was observed in the predictive factors in comparison to the 3rd month, thus indicating coherent data.
Another limitation could be the duration of follow-up, which may not be long enough to ensure the success of the intervention. In a trial including 79-year-old patients considered to be at high risk of falling, the mean time to first fall was around 8 months (24). However, these home-dwelling patients were younger than in our study, had a history of only 2 falls in the previous year, and had better physical performance at baseline, indicating a lower probability of falling than in our patients. We also found that the number of serious and non-serious falls continued to decrease at the 3rd and 6th month with a functional improvement, as demonstrated by the increase in the SPPB score at the 3rd month (data not shown), whereas the natural history of falling is to recur and worsen (2-3, 5, 9-10).
Conclusion
In this study including 85-year-old patients with a recent history of falling, non-isolated patients (with social support or in institutions) with a low number of non-serious falls and with better mental health allowing them to comply with instructions were the best candidates for a multidisciplinary fall prevention intervention initiated in a day hospital. This raises the question of the management of non-responders. Should we wait longer to see whether a positive effect occurs or should we increase the frequency of the visits in the day hospital? Will they benefit more from hospitalization in a rehabilitation unit? Finally, patients with a history of severe falling may benefit more from a palliative intervention. Although evidence suggests that multidisciplinary interventions may be the most effective form of care to address the multifactorial risk factors of falling in older people, studies are needed to adapt the modalities of such interventions to selected profiles of fallers.
Acknowledgments
All the authors declare no conflicts of interest for the work under consideration for publication. Grant= no. Consulting fee or honorarium = no. Support to travel to meetings for the study or other purposes = no. Fees for participation in review activities such as data monitoring boards, statistical analysis, end point committees and the like = no. Payment for writing or reviewing the manuscript = no. Provision of writing assistance, medicines, equipment, or administrative support = no. Other = no.
References
- 1.Tinetti M.E., Speechley M., Ginter S.F. Risk factors for falls among elderly persons living in the community. N Engl J Med. 1988;319:1701–1707. doi: 10.1056/NEJM198812293192604. 10.1056/NEJM198812293192604 PubMed PMID: 3205267. [DOI] [PubMed] [Google Scholar]
- 2.Persad C.C., Cook S., Giordani B. Assessing falls in the elderly: should we use simple screening tests or a comprehensive fall risk evaluation? Eur J Phys Rehabil Med. 2010;46:249–259. PubMed PMID: 20485227. [PubMed] [Google Scholar]
- 3.Guideline for the prevention of falls in older persons. American Geriatrics Society British Geriatrics Society, and American Academy of Orthopaedic Surgeons Panel on Falls Prevention. J Am Geriatr Soc. 2001;49:664–672. [PubMed] [Google Scholar]
- 4.Rubenstein L.Z. Falls in older people: epidemiology, risk factors and strategies for prevention. Age Ageing. 2006;35(Suppl2):ii37–ii41. doi: 10.1093/ageing/afl084. 10.1093/ageing/afl084 PubMed PMID: 16926202. [DOI] [PubMed] [Google Scholar]
- 5.Tinetti M.E., Kumar C. The patient who falls: “It’s always a trade-off”. JAMA. 2010;303:258–266. doi: 10.1001/jama.2009.2024. 10.1001/jama.2009.2024 PubMed PMID: 20085954. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Kannus P., Parkkari J., Niemi S., Palvanen M. Fall-induced deaths among elderly people. Am J Public Health. 2005;95:422–424. doi: 10.2105/AJPH.2004.047779. 10.2105/AJPH.2004.047779 PubMed PMID: 15727970. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Kannus P., Sievanen H., Palvanen M., Jarvinen T., Parkkari J. Prevention of falls and consequent injuries in elderly people. Lancet. 2005;366:1885–1893. doi: 10.1016/S0140-6736(05)67604-0. 10.1016/S0140-6736(05)67604-0 PubMed PMID: 16310556. [DOI] [PubMed] [Google Scholar]
- 8.Carroll N.V., Slattum P.W., Cox F.M. The cost of falls among the community-dwelling elderly. J Manag Care Pharm. 2005;11:307–316. doi: 10.18553/jmcp.2005.11.4.307. PubMed PMID: 15871641. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Bloch F., Thibaud M., Dugue B., Breque C., Rigaud A.S., Kemoun G. Episodes of falling among elderly people: a systematic review and meta-analysis of social and demographic pre-disposing characteristics. Clinics (Sao Paulo) 2010;65:895–903. doi: 10.1590/S1807-59322010000900013. 10.1590/S1807-59322010000900013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Beauchet O., Dubost V., Revel Delhom C., Berrut G., Belmin J. How to manage recurrent falls in clinical practice: guidelines of the French Society of Geriatrics and Gerontology. J Nutr Health Aging. 2011;15:79–84. doi: 10.1007/s12603-011-0016-6. 10.1007/s12603-011-0016-6 PubMed PMID: 21267524. [DOI] [PubMed] [Google Scholar]
- 19.Gillespie LD, Robertson MC, Gillespie WJ, et al. Interventions for preventing falls in older people living in the community. Cochrane Database Syst Rev 2009:CD007146. [DOI] [PubMed]
- 20.Gates S., Fisher J.D., Cooke M.W., Carter Y.H., Lamb S.E. Multifactorial assessment and targeted intervention for preventing falls and injuries among older people in community and emergency care settings: systematic review and meta-analysis. BMJ. 2008;336:130–133. doi: 10.1136/bmj.39412.525243.BE. 10.1136/bmj.39412.525243.BE PubMed PMID: 18089892. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Cameron ID, Murray GR, Gillespie LD, et al. Interventions for preventing falls in older people in nursing care facilities and hospitals. Cochrane Database Syst Rev 2010:CD005465. [DOI] [PubMed]
- 22.Shaw F.E., Bond J., Richardson D.A., et al. Multifactorial intervention after a fall in older people with cognitive impairment and dementia presenting to the accident and emergency department: randomised controlled trial. BMJ. 2003;326:73. doi: 10.1136/bmj.326.7380.73. 10.1136/bmj.326.7380.73 PubMed PMID: 12521968. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Dyer C.A., Taylor G.J., Reed M., Dyer C.A., Robertson D.R., Harrington R. Falls prevention in residential care homes: a randomised controlled trial. Age Ageing. 2004;33:596–602. doi: 10.1093/ageing/afh204. 10.1093/ageing/afh204 PubMed PMID: 15381507. [DOI] [PubMed] [Google Scholar]
- 24.de Vries O.J., Peeters G.M., Elders P.J., et al. Multifactorial intervention to reduce falls in older people at high risk of recurrent falls: a randomized controlled trial. Arch Intern Med. 2010;170:1110–1117. doi: 10.1001/archinternmed.2010.169. 10.1001/archinternmed.2010.169 PubMed PMID: 20625015. [DOI] [PubMed] [Google Scholar]
- 25.Russell M.A., Hill K.D., Day L.M., et al. A randomized controlled trial of a multifactorial falls prevention intervention for older fallers presenting to emergency departments. J Am Geriatr Soc. 2010;58:2265–2274. doi: 10.1111/j.1532-5415.2010.03191.x. 10.1111/j.1532-5415.2010.03191.x PubMed PMID: 21143436. [DOI] [PubMed] [Google Scholar]
- 26.Salminen M.J., Vahlberg T.J., Salonoja M.T., Aarnio P.T., Kivela S.L. Effect of a risk-based multifactorial fall prevention program on the incidence of falls. J Am Geriatr Soc. 2009;57:612–619. doi: 10.1111/j.1532-5415.2009.02176.x. 10.1111/j.1532-5415.2009.02176.x PubMed PMID: 19392952. [DOI] [PubMed] [Google Scholar]
- 27.Hendriks M.R., Bleijlevens M.H., van Haastregt J.C., et al. Lack of effectiveness of a multidisciplinary fall-prevention program in elderly people at risk: a randomized, controlled trial. J Am Geriatr Soc. 2008;56:1390–1397. doi: 10.1111/j.1532-5415.2008.01803.x. 10.1111/j.1532-5415.2008.01803.x PubMed PMID: 18662214. [DOI] [PubMed] [Google Scholar]
- 28.Conroy S., Kendrick D., Harwood R., et al. A multicentre randomised controlled trial of day hospital-based falls prevention programme for a screened population of community-dwelling older people at high risk of falls. Age Ageing. 2010;39:704–710. doi: 10.1093/ageing/afq096. 10.1093/ageing/afq096 PubMed PMID: 20823124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Lamb S.E., Becker C., Gillespie L.D., et al. Reporting of complex interventions in clinical trials: development of a taxonomy to classify and describe fall-prevention interventions. Trials. 2011;12:125. doi: 10.1186/1745-6215-12-125. 10.1186/1745-6215-12-125 PubMed PMID: 21586143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Mahoney J.E. Why multifactorial fall-prevention interventions may not work: Comment on “Multifactorial intervention to reduce falls in older people at high risk of recurrent falls”. Arch Intern Med. 2010;170:1117–1119. doi: 10.1001/archinternmed.2010.193. 10.1001/archinternmed.2010.193 PubMed PMID: 20625016. [DOI] [PubMed] [Google Scholar]
- 31.Rainfray M., Bourdel-Marchasson I., Dehail P., Richard-Harston S. [Comprehensive geriatric assessment: a useful tool for prevention of acute situations in the elderly] Ann Med Interne (Paris) 2002;153:397–402. [PubMed] [Google Scholar]
- 32.Bourdel-Marchasson I., Berrut G. Caring the elderly diabetic patient with respect to concepts of successful aging and frailty. Diabetes Metab. 2005;31(Spec2):5S13–15S19. doi: 10.1016/s1262-3636(05)73647-8. 10.1016/S1262-3636(05)73647-8 PubMed PMID: 16415761. [DOI] [PubMed] [Google Scholar]
- 33.Spice C.L., Morotti W., George S., et al. The Winchester falls project: a randomised controlled trial of secondary prevention of falls in older people. Age Ageing. 2009;38:33–40. doi: 10.1093/ageing/afn192. 10.1093/ageing/afn192 PubMed PMID: 18829689. [DOI] [PubMed] [Google Scholar]
- 34.Ware J., Jr., Kosinski M., Keller S.D. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34:220–233. doi: 10.1097/00005650-199603000-00003. 10.1097/00005650-199603000-00003 PubMed PMID: 8628042. [DOI] [PubMed] [Google Scholar]
- 35.Jensen J., Lundin-Olsson L., Nyberg L., Gustafson Y. Fall and injury prevention in older people living in residential care facilities. A cluster randomized trial. Ann Intern Med. 2002;136:733–741. doi: 10.7326/0003-4819-136-10-200205210-00008. PubMed PMID: 12020141. [DOI] [PubMed] [Google Scholar]
- 36.Elliott S., Painter J., Hudson S. Living alone and fall risk factors in communitydwelling middle age and older adults. J Community Health. 2009;34:301–310. doi: 10.1007/s10900-009-9152-x. 10.1007/s10900-009-9152-x PubMed PMID: 19333744. [DOI] [PubMed] [Google Scholar]
- 37.Faulkner K.A., Cauley J.A., Zmuda J.M., Griffin J.M., Nevitt M.C. Is social integration associated with the risk of falling in older community-dwelling women? J Gerontol A Biol Sci Med Sci. 2003;58:M954–M959. doi: 10.1093/gerona/58.10.m954. 10.1093/gerona/58.10.M954 PubMed PMID: 14570865. [DOI] [PubMed] [Google Scholar]
- 38.Howland J., Lachman M.E., Peterson E.W., Cote J., Kasten L., Jette A. Covariates of fear of falling and associated activity curtailment. Gerontologist. 1998;38:549–555. doi: 10.1093/geront/38.5.549. 10.1093/geront/38.5.549 PubMed PMID: 9803643. [DOI] [PubMed] [Google Scholar]
- 39.Chatfield M.D., Brayne C.E., Matthews F.E. A systematic literature review of attrition between waves in longitudinal studies in the elderly shows a consistent pattern of dropout between differing studies. J Clin Epidemiol. 2005;58:13–19. doi: 10.1016/j.jclinepi.2004.05.006. 10.1016/j.jclinepi.2004.05.006 PubMed PMID: 15649666. [DOI] [PubMed] [Google Scholar]
Uncited references
- 9.Deandrea S., Lucenteforte E., Bravi F., Foschi R., La Vecchia C., Negri E. Risk factors for falls in community-dwelling older people: a systematic review and meta-analysis. Epidemiology. 2010;21:658–668. doi: 10.1097/EDE.0b013e3181e89905. 10.1097/EDE.0b013e3181e89905 PubMed PMID: 20585256. [DOI] [PubMed] [Google Scholar]
- 11.Stalenhoef P.A., Diederiks J.P., Knottnerus J.A., Kester A.D., Crebolder H.F. A risk model for the prediction of recurrent falls in community-dwelling elderly: a prospective cohort study. J Clin Epidemiol. 2002;55:1088–1094. doi: 10.1016/s0895-4356(02)00502-4. 10.1016/S0895-4356(02)00502-4 PubMed PMID: 12507672. [DOI] [PubMed] [Google Scholar]
- 12.Stel V.S., Pluijm S.M., Deeg D.J., Smit J.H., Bouter L.M., Lips P. A classification tree for predicting recurrent falling in community-dwelling older persons. J Am Geriatr Soc. 2003;51:1356–1364. doi: 10.1046/j.1532-5415.2003.51452.x. 10.1046/j.1532-5415.2003.51452.x PubMed PMID: 14511154. [DOI] [PubMed] [Google Scholar]
- 13.Tromp A.M., Pluijm S.M., Smit J.H., Deeg D.J., Bouter L.M., Lips P. Fall-risk screening test: a prospective study on predictors for falls in community-dwelling elderly. J Clin Epidemiol. 2001;54:837–844. doi: 10.1016/s0895-4356(01)00349-3. 10.1016/S0895-4356(01)00349-3 PubMed PMID: 11470394. [DOI] [PubMed] [Google Scholar]
- 14.Tinetti M.E., Baker D.I., King M., et al. Effect of dissemination of evidence in reducing injuries from falls. N Engl J Med. 2008;359:252–261. doi: 10.1056/NEJMoa0801748. 10.1056/NEJMoa0801748 PubMed PMID: 18635430. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Tinetti M.E., Baker D.I., McAvay G., et al. A multifactorial intervention to reduce the risk of falling among elderly people living in the community. N Engl J Med. 1994;331:821–827. doi: 10.1056/NEJM199409293311301. 10.1056/NEJM199409293311301 PubMed PMID: 8078528. [DOI] [PubMed] [Google Scholar]
- 16.Moreland J., Richardson J., Chan D.H., et al. Evidence-based guidelines for the secondary prevention of falls in older adults. Gerontology. 2003;49:93–116. doi: 10.1159/000067948. 10.1159/000067948 PubMed PMID: 12574670. [DOI] [PubMed] [Google Scholar]
- 17.Feder G., Cryer C., Donovan S., Carter Y. Guidelines for the prevention of falls in people over 65. The Guidelines’ Development Group. BMJ. 2000;321:1007–1011. doi: 10.1136/bmj.321.7267.1007. 10.1136/bmj.321.7267.1007 PubMed PMID: 11039974. [DOI] [PMC free article] [PubMed] [Google Scholar]