Profiling Dizziness in Older Primary Care Patients: An Empirical Study

被引:12
作者
Dros, Jacquelien [1 ]
Maarsingh, Otto R. [2 ,3 ]
van der Windt, Danielle A. W. M. [2 ,3 ,4 ]
Oort, Frans J. [5 ]
ter Riet, Gerben [1 ]
de Rooij, Sophia E. J. A. [6 ]
Schellevis, Francois G. [2 ,3 ,7 ]
van der Horst, Henriette E. [2 ,3 ]
van Weert, Henk C. P. M. [1 ]
机构
[1] Univ Amsterdam, Acad Med Ctr, Dept Family Med, NL-1105 AZ Amsterdam, Netherlands
[2] Vrije Univ Amsterdam Med Ctr, Dept Family Med, Amsterdam, Netherlands
[3] Vrije Univ Amsterdam Med Ctr, EMGO Inst Hlth & Care Res, Amsterdam, Netherlands
[4] Keele Univ, Arthrit Res Campaign Natl Primary Care Ctr, Keele, Staffs, England
[5] Univ Amsterdam, Acad Med Ctr, Dept Med Psychol, NL-1105 AZ Amsterdam, Netherlands
[6] Univ Amsterdam, Acad Med Ctr, Dept Internal Med, Geriatr Med Sect, NL-1105 AZ Amsterdam, Netherlands
[7] Netherlands Inst Hlth Serv Res, NIVEL, Utrecht, Netherlands
关键词
PERSISTENT DIZZINESS; MULTIPLE IMPUTATION; GENERAL-PRACTICE; PREVALENCE; COMMUNITY; SYMPTOMS; UPDATE;
D O I
10.1371/journal.pone.0016481
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background: The diagnostic approach to dizzy, older patients is not straightforward as many organ systems can be involved and evidence for diagnostic strategies is lacking. A first differentiation in diagnostic subtypes or profiles may guide the diagnostic process of dizziness and can serve as a classification system in future research. In the literature this has been done, but based on pathophysiological reasoning only. Objective: To establish a classification of diagnostic profiles of dizziness based on empirical data. Design: Cross-sectional study. Participants and Setting: 417 consecutive patients of 65 years and older presenting with dizziness to 45 primary care physicians in the Netherlands from July 2006 to January 2008. Methods: We performed tests, including patient history, and physical and additional examination, previously selected by an international expert panel and based on an earlier systematic review. We used the results of these tests in a principal component analysis for exploration, data-reduction and finally differentiation into diagnostic dizziness profiles. Results: Demographic data and the results of the tests yielded 221 variables, of which 49 contributed to the classification of dizziness into six diagnostic profiles, that may be named as follows: "frailty'', "psychological'', "cardiovascular'', "presyncope'', "non-specific dizziness'' and "ENT''. These explained 32% of the variance. Conclusions: Empirically identified components classify dizziness into six profiles. This classification takes into account the heterogeneity and multicausality of dizziness and may serve as starting point for research on diagnostic strategies and can be a first step in an evidence based diagnostic approach of dizzy older patients.
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