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Use of a clustering method to describe the clinical profiles of older fallers: the value of a multidisciplinary consultation

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Key summary points

AbstractSection Aim

To use a clustering method with no preconceived ideas to identify older fallers living in the community and thus to suggest appropriate treatment plans.

AbstractSection Findings

we found three different functional clusters: (i) a low-mobility cluster of individuals who had difficulty getting up from the floor unaided and needed a mobility aid for walking, (ii) an intermediate group of rather sedentary individuals with a high body mass index and a gait speed of ~ 0.6 m s-1, and (iii) active participants who performed well in physical tests.

AbstractSection Message

The population of older fallers referred for a multidisciplinary geriatric consultation is heterogeneous; when combined with simple tests, the presence of certain clinical characteristics can contribute to determine the most appropriate pathways.

Abstract

Objectives

The population of older adults is particularly heterogeneous with regard to frailty and the risk of falling, the two of which are linked. We conducted an exploratory, analysis (with no preconceived ideas) of data collected during multidisciplinary falls consultations (MFCs), to identify people with similar profiles.

Materials and methods

We performed an observational, multicentre study of older patients (aged 75 and over) having been evaluated in an MFC. We excluded adults with a Mini Mental State Examination score < 14/30, an activities of daily living score < 4/6, or an unstable medical condition. Each participant underwent a clinical interview, impedancemetry, and a physical activity assessment (a questionnaire, and use of an activity tracker on 5 consecutive days). The K-means method and ascending hierarchical clustering were used to identify clusters of people with common characteristics.

Results

Of the 106 participants, the median [IQR] mean number of falls in the previous 6 months was 1 [2]. Three functional clusters were identified: (i) fallers with poor mobility, difficulty getting up off the ground after a fall, and using a mobility aid for walking; (ii) an intermediate sedentary group with a gait speed of ~ 0.6 m s−1, and (iii) active people with a timed “up and go” test time below 15 s and a gait speed above 0.8 m s−1.

Conclusions

The population of older fallers referred for an MFC is heterogeneous. The presence of certain clinical characteristics enabled the definition of three patient clusters, which might help physicians to determine the most appropriate care objectives and pathways.

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Data availability

The data are available by contacting the principal author as the data are at the Orléans hospital centre.

References

  1. Montero-Odasso M, Van der Velde N, Martin FC et al (2022) World guidelines for falls prevention and management for older adults: a global initiative. Age Ageing 51:1–36. https://doi.org/10.1093/ageing/afac205

    Article  Google Scholar 

  2. Blain H, Bloch F, Borel L et al (2015) Activité physique et prévention des chutes chez les personnes âgées. Doctoral dissertation, Institut national de la santé et de la recherche médicale (INSERM), Paris: Inserm: Editions EDP Sciences (ISSN: 1264-1782)/518.p.ffinserm-02102899f

  3. Ensrud K, Ewing S, Taylor B et al (2007) Frailty and risk of falls, fracture, and mortality in older women: the study of osteoporotic fractures. J Gerontol A Biol Sci Med Sci 62(7):744–751

    Article  PubMed  Google Scholar 

  4. Panel on Prevention of Falls in Older Persons, American Geriatrics Society and British Geriatrics Society (2011) Summary of the updated American geriatrics society/British geriatrics society clinical practice guideline for prevention of falls in older persons. J Am Geriatr Soc 59(1):148–157

    Article  Google Scholar 

  5. Clemson L, Cumming RG, Kendig H et al (2004) The effectiveness of a community-based program for reducing the incidence of falls in the elderly: a randomized trial. J Am Geriatr Soc 52(9):1487–1494

    Article  PubMed  Google Scholar 

  6. Tinetti M-E, Baker D, Mcavay G et al (1994) A multifactorial intervention to reduce the risk of falling among elderly people living in the community. N Engl J Med 331(13):821–827

    Article  CAS  PubMed  Google Scholar 

  7. Hogan D, Macdonald F, Betts J et al (2001) A randomized controlled trial of a community-based consultation service to prevent falls. CMAJ 165(5):537–543

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Chang J, Morton S, Rubenstein L et al (2004) Interventions for the prevention of falls in older adults: systematic review and meta-analysis of randomised clinical trials. BMJ 328:680–687

    Article  PubMed  PubMed Central  Google Scholar 

  9. Folstein MF, Folstein S, Mc Huth PR (1975) Mini mental state: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12:189–198

    Article  CAS  PubMed  Google Scholar 

  10. Katz S (1983) Assessing self-maintenance: activities of daily living, mobility, and instrumental activities of daily living. J Am Geriatr Soc 31(12):721–727

    Article  CAS  PubMed  Google Scholar 

  11. Delbaere K, Hauer K, Lord SR (2010) Evaluation of the incidental and planned activity questionnaire (IPEQ) for older people. Br J Sports Med 44:1029–1034

    Article  CAS  PubMed  Google Scholar 

  12. Beauchet O, Berrut G (2006) Marche et double tâche: définition, intérêts et perspectives chez le sujet âgé. Psychol Neuropsychiatr Vieil 4(3):215–225

    PubMed  Google Scholar 

  13. Podsialo D, Richardson S (1991) The timed up and go: a test of basic functionnal mobility for frail elderly persons. J Am Geriatr Soc 39:142–148

    Article  Google Scholar 

  14. Guralnik JM, Simonsick EM, Ferrucci L et al (1994) A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol 49:M85-94

    Article  CAS  PubMed  Google Scholar 

  15. Hamer M, Stamatakis E (2013) Screen-based sedentary behavior, physical activity, and muscle strength in the English longitudinal study of ageing. PLoS ONE 8(6):e66222

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Clement J, Nassif R, Leger J et al (1997) Development and contribution to the validation of a brief French version of the yesavage geriatric depression scale. L’encephale 23(2):91–99

    CAS  PubMed  Google Scholar 

  17. Vellas B, Guigoz Y, Garry PJ et al (1999) The Mini Nutritional assessment (MNA) and its use in grading the nutritional state of elderly patients. Nutrition 15(2):116–122

    Article  CAS  PubMed  Google Scholar 

  18. Charlson M, Szatrowski TP, Peterson J et al (1994) Validation of a combined comorbidity index. J Clin Epidemiol 47:1245–1251

    Article  CAS  PubMed  Google Scholar 

  19. Inouye S, Studenski S, Tinetti M et al (2007) Geriatric syndromes: clinical, research, and policy implications of a core geriatric concept. J Am Geriatr Soc 55(5):780–791

    Article  PubMed  PubMed Central  Google Scholar 

  20. R Core Team (2021) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

    Google Scholar 

  21. Dargent-Molina P, Breart G (1995) Epidemiology of falls and fall-related injuries in the aged. Rev Epidemiol Sante Publique 43(1):72–83

    CAS  PubMed  Google Scholar 

  22. Tinetti M, Liu WI, Noel EB (1993) Predictors and prognosis of inability to get up after falls among elderly persons. JAMA 269(1):65–70

    Article  CAS  PubMed  Google Scholar 

  23. Tournadre A, Vial G, Capel F et al (2019) La sarcopénie. Rev Rhum 86(1):39–45

    Article  Google Scholar 

  24. Rashedi V, Iranpour A, Mohseni M et al (2019) Risk factors for fall in elderly with diabetes mellitus type 2. Diabetes Metab Syndr 13(4):2347–2351

    Article  PubMed  Google Scholar 

  25. Schwartz A, Hillier T, Sellmeyer D et al (2002) Older women with diabetes have a higher risk of falls: a prospective study. Diabetes Care 25(10):1749–1754

    Article  PubMed  Google Scholar 

  26. Clegg A, Young J, Iliffe S et al (2013) Frailty in elderly people. Lancet 381(9868):752–762

    Article  PubMed  Google Scholar 

  27. Castelle MV, Sanchez M, Julian R et al (2013) Frailty prevalence and slow walking speed in persons age 65 ans older, implication for primary care. BMC Fam Pract 19(14):86

    Article  Google Scholar 

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Authors and Affiliations

Authors

Contributions

All authors conceived and designed the study. Dr MP, Dr JBG and Dr AV prepared material and collected and analyzed data. The first draft of the manuscript was written by Dr MP, and all authors commented on and revised subsequent versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to S. Mandigout.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflicts of interest with regard to the present study.

Ethical approval

The protocol was approved by the independent ethics committee at Orleans University Hospital (Orléans, France; reference: 2016-02, dated April 26, 2001) and the French National Consultative Committee on Information Processing in Medical Research at the French Ministry of Research (Paris, France; reference: 16.522, dated July 12, 2016).

Informed consent

All participants were given comprehensive written and verbal information on the study’s objectives and procedures, the right to refuse to participate, and the ability to withdraw from the study at any time.

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Pambet, M., Gauvain, J.B., Valery, A. et al. Use of a clustering method to describe the clinical profiles of older fallers: the value of a multidisciplinary consultation. Eur Geriatr Med 14, 1097–1104 (2023). https://doi.org/10.1007/s41999-023-00829-3

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  • DOI: https://doi.org/10.1007/s41999-023-00829-3

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