Hanneke Stam1, Otto R Maarsingh2, Martijn W Heymans3, Henk C P M van Weert4, Johannes C van der Wouden2, Henriëtte E van der Horst2. 1. Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Iniversiteit Amsterdam, Amsterdam, The Netherlands stam.h@vumc.nl. 2. Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Iniversiteit Amsterdam, Amsterdam, The Netherlands. 3. Department of Clinical Epidemiology and Biostatistics, Amsterdam UMC, Vrije Iniversiteit Amsterdam, Amsterdam, The Netherlands. 4. Department of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Abstract
PURPOSE: Because dizziness in older people is often chronic and can substantially affect daily functioning, it is important to identify those at risk for an unfavorable course of dizziness to optimize their care. We aimed to develop and externally validate a prediction model for an unfavorable course of dizziness in older patients in primary care, and to construct an easy-to-use risk prediction tool. METHODS: We used data from 2 prospective cohorts: a development cohort with 203 patients aged 65 years or older who consulted their primary care physician for dizziness and had substantial dizziness-related impairment (Dizziness Handicap Inventory [DHI] ≥30), and a validation cohort with 415 patients aged 65 years or older who consulted their primary care physician for dizziness of any severity. An unfavorable course was defined as presence of substantial dizziness-related impairment (DHI ≥30) after 6 months. RESULTS: Prevalence of an unfavorable course of dizziness was 73.9% in the development cohort and 43.6% in the validation cohort. Predictors in the final model were the score on the screening version of the DHI, age, history of arrhythmia, and looking up as a provoking factor. The model showed good calibration and fair discrimination (area under the curve = 0.77). On external validation, discriminative ability remained stable (area under the curve = 0.78). The constructed risk score was strongly correlated with the prediction model. Performance measures for risk score cut-off values are presented to determine the optimal cut-off point for clinical practice. CONCLUSIONS: We developed an easy-to-use risk score for dizziness-related impairment in primary care. The risk score, consisting of only 4 predictors, will help primary care physicians identify patients at high risk for an unfavorable course of dizziness.
PURPOSE: Because dizziness in older people is often chronic and can substantially affect daily functioning, it is important to identify those at risk for an unfavorable course of dizziness to optimize their care. We aimed to develop and externally validate a prediction model for an unfavorable course of dizziness in older patients in primary care, and to construct an easy-to-use risk prediction tool. METHODS: We used data from 2 prospective cohorts: a development cohort with 203 patients aged 65 years or older who consulted their primary care physician for dizziness and had substantial dizziness-related impairment (Dizziness Handicap Inventory [DHI] ≥30), and a validation cohort with 415 patients aged 65 years or older who consulted their primary care physician for dizziness of any severity. An unfavorable course was defined as presence of substantial dizziness-related impairment (DHI ≥30) after 6 months. RESULTS: Prevalence of an unfavorable course of dizziness was 73.9% in the development cohort and 43.6% in the validation cohort. Predictors in the final model were the score on the screening version of the DHI, age, history of arrhythmia, and looking up as a provoking factor. The model showed good calibration and fair discrimination (area under the curve = 0.77). On external validation, discriminative ability remained stable (area under the curve = 0.78). The constructed risk score was strongly correlated with the prediction model. Performance measures for risk score cut-off values are presented to determine the optimal cut-off point for clinical practice. CONCLUSIONS: We developed an easy-to-use risk score for dizziness-related impairment in primary care. The risk score, consisting of only 4 predictors, will help primary care physicians identify patients at high risk for an unfavorable course of dizziness.
Authors: Jacquelien Dros; Otto R Maarsingh; Leo Beem; Henriëtte E van der Horst; Gerben ter Riet; François G Schellevis; Henk C P M van Weert Journal: Health Qual Life Outcomes Date: 2011-06-16 Impact factor: 3.186
Authors: Otto R Maarsingh; Hanneke Stam; Peter M van de Ven; Natasja M van Schoor; Matthew J Ridd; Johannes C van der Wouden Journal: BMC Geriatr Date: 2014-12-15 Impact factor: 3.921
Authors: Hanneke Stam; Thomas Harting; Marjolijn van der Sluijs; Rob van Marum; Henriëtte van der Horst; Johannes C van der Wouden; Otto R Maarsingh Journal: Scand J Prim Health Care Date: 2016-04-06 Impact factor: 2.581
Authors: Vincent A van Vugt; Gülsün Bas; Johannes C van der Wouden; Jacquelien Dros; Henk C P M van Weert; Lucy Yardley; Jos W R Twisk; Henriëtte E van der Horst; Otto R Maarsingh Journal: Ann Fam Med Date: 2020-03 Impact factor: 5.166
Authors: Vincent A van Vugt; Johannes C van der Wouden; Rosie Essery; Lucy Yardley; Jos W R Twisk; Henriëtte E van der Horst; Otto R Maarsingh Journal: BMJ Date: 2019-11-05
Authors: Vincent A van Vugt; Martijn W Heymans; Johannes C van der Wouden; Henriëtte E van der Horst; Otto R Maarsingh Journal: BMJ Open Date: 2020-10-16 Impact factor: 2.692