Predicting fall risks in an elderly population: computer dynamic posturography versus electronystagmography test results.
OBJECTIVE
Falls are the leading cause of morbidity and mortality for persons aged 65 years and older, with more than 2 million people falling and sustaining serious injury annually. This study compared computer dynamic posturography (CDP) and electronystagmography (ENG) results as predictors of falls.


METHODS
Retrospective.


METHODS
Thirty-three patients over the age of 65 years who presented to a balance disorders and falls prevention clinic were used for this study (22 women and 11 men, with an average age of 78.0 y and a mean fall rate of 3.5 times). All had experienced at least one fall in the year before visiting the clinic and were tested with both CDP and ENG. The CDP results were divided into subcategories (sensory organization testing and limits of stability); ENG results were divided into four categories (ocular motor, rotational chair, positional, and caloric studies).


RESULTS
Test findings were classified as normal or abnormal based on age-matched normative data. Of the patients in the study, 27.3% were normal for one type of testing and abnormal for the other. Twenty-six patients (78.8%) had abnormal results on CDP, and 20 individuals (60.6%) showed ENG abnormalities (42.4% for ocular motor, 28.6% for positional, 13.6% for caloric, and 11.2% for rotational chair studies). The limits of stability category was significant in predicting multiple falls.


CONCLUSIONS
For this population, CDP was determined to be a more sensitive test for identifying patients who have fallen, with limits of stability testing the most significant part of the CDP battery; for ENG studies, the best falls indicator was the ocular motor battery.
Girardi
M
M
Division of Otolaryngology, Department of Surgery, Southern Illinois University School of Medicine, Springfield, Illinois 62794-9662, USA. mgirardi@siumed.edu
Konrad
H R
HR
Amin
M
M
Hughes
L F
LF
D000058:Accidental Falls / Q000517:prevention & control / Q000706:statistics & numerical data*; D017677:Age Distribution; D000368:Aged; D000704:Analysis of Variance; D016022:Case-Control Studies; D003936:Diagnosis, Computer-Assisted / Q000379:methods / Q000592:standards*; D004584:Electronystagmography / Q000379:methods / Q000592:standards*; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D008297:Male; D004856:Postural Balance; D011187:Posture; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors; D012678:Sensation Disorders / Q000150:complications* / Q000175:diagnosis* / Q000503:physiopathology; D017678:Sex Distribution