Snelle inschatting van de kans op herhaald vallen bij ouderen

Research output: Contribution to journalArticleProfessional

Abstract

BACKGROUND: Thirty percent of people aged 65 years or older fall at least once a year, and about a quarter seek medical attention. Existing falls risk profiles are too complex for daily use. We describe a falls decision tree consisting of three simple questions that provides a quick indication of the risk of recurrent falls in older people who have recently fallen down. METHODS: We investigated simple, easy to measure predictors of repeated falls in 408 community-dwelling older people (65+ years) who had consulted a CP or gone to an accident and emergency (A&E) department after falling down. These predictors were then used to develop a falls decision tree, to indicate when a new fall can be expected. The decision tree was validated in a second sample of patients. RESULTS: Three predictors, namely, falls history, fear of falling, and use of a walking aid, in combination provided an adequate indication of the risk of a new fall. The risk of a new fall was 9% if none of the predictors was present and 42% if all three predictors were present. If high falls risk was defined as a higher than 30% risk of new falls, then 80% of the participants in the development sample and 70% of the participants in the validation sample were correctly classified as having a high falls risk. CONCLUSION: The falls decision tree is a simple tool for use in GP surgeries or in A&E departments to assess the risk of a new fall in older individuals who have recently fallen down.
Original languageDutch
Pages (from-to)186-191
JournalHuisarts en Wetenschap
Volume54
Issue number4
Publication statusPublished - 2011

Cite this

@article{7760093d842e4f8792fac650d570163b,
title = "Snelle inschatting van de kans op herhaald vallen bij ouderen",
abstract = "BACKGROUND: Thirty percent of people aged 65 years or older fall at least once a year, and about a quarter seek medical attention. Existing falls risk profiles are too complex for daily use. We describe a falls decision tree consisting of three simple questions that provides a quick indication of the risk of recurrent falls in older people who have recently fallen down. METHODS: We investigated simple, easy to measure predictors of repeated falls in 408 community-dwelling older people (65+ years) who had consulted a CP or gone to an accident and emergency (A&E) department after falling down. These predictors were then used to develop a falls decision tree, to indicate when a new fall can be expected. The decision tree was validated in a second sample of patients. RESULTS: Three predictors, namely, falls history, fear of falling, and use of a walking aid, in combination provided an adequate indication of the risk of a new fall. The risk of a new fall was 9{\%} if none of the predictors was present and 42{\%} if all three predictors were present. If high falls risk was defined as a higher than 30{\%} risk of new falls, then 80{\%} of the participants in the development sample and 70{\%} of the participants in the validation sample were correctly classified as having a high falls risk. CONCLUSION: The falls decision tree is a simple tool for use in GP surgeries or in A&E departments to assess the risk of a new fall in older individuals who have recently fallen down.",
author = "Geeske Peeters and Petra Elders and Paul Lips and Dorly Deeg",
year = "2011",
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volume = "54",
pages = "186--191",
journal = "Huisarts en Wetenschap",
issn = "0018-7070",
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}

Snelle inschatting van de kans op herhaald vallen bij ouderen. / Peeters, Geeske; Elders, Petra; Lips, Paul; Deeg, Dorly.

In: Huisarts en Wetenschap, Vol. 54, No. 4, 2011, p. 186-191.

Research output: Contribution to journalArticleProfessional

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N2 - BACKGROUND: Thirty percent of people aged 65 years or older fall at least once a year, and about a quarter seek medical attention. Existing falls risk profiles are too complex for daily use. We describe a falls decision tree consisting of three simple questions that provides a quick indication of the risk of recurrent falls in older people who have recently fallen down. METHODS: We investigated simple, easy to measure predictors of repeated falls in 408 community-dwelling older people (65+ years) who had consulted a CP or gone to an accident and emergency (A&E) department after falling down. These predictors were then used to develop a falls decision tree, to indicate when a new fall can be expected. The decision tree was validated in a second sample of patients. RESULTS: Three predictors, namely, falls history, fear of falling, and use of a walking aid, in combination provided an adequate indication of the risk of a new fall. The risk of a new fall was 9% if none of the predictors was present and 42% if all three predictors were present. If high falls risk was defined as a higher than 30% risk of new falls, then 80% of the participants in the development sample and 70% of the participants in the validation sample were correctly classified as having a high falls risk. CONCLUSION: The falls decision tree is a simple tool for use in GP surgeries or in A&E departments to assess the risk of a new fall in older individuals who have recently fallen down.

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