Prediction of fracture in nursing home residents.
OBJECTIVE
To investigate cross-validated methods of identifying patients at increased risk of fracture in nursing homes using readily available data.


METHODS
Prospective cohort study with 18 months of follow-up.


METHODS
Forty-seven randomly selected nursing homes in Maryland.


METHODS
One thousand four hundred twenty-seven white female nursing home residents aged 65 and older were followed for fracture for 18 months after baseline assessment.


METHODS
Fracture ascertained by physician note or x-ray from chart abstraction; demographic and baseline data extracted from the Minimum Data Set (MDS).


RESULTS
Exploratory analyses on a random subset (67%) of the data (development sample) identified variables that might be important in predicting subsequent fracture and included variables for how the resident moved between locations in her room or adjacent corridor (mobility), age, weight, height, independence in eating and dressing, urinary incontinence, resistance to care, falls in the previous 6 months, a dementia score, and other activities of daily living. A simple scoring algorithm derived from a subset of these MDS variables showed good sensitivity (.70) but low specificity (.39) in the random validation sample.


CONCLUSIONS
A scoring algorithm developed in more than 1,400 white females from 47 nursing homes in the state of Maryland shows high sensitivity for identifying women at increased risk for fracture and may be useful in targeting fracture prevention programs.
Girman
Cynthia J
CJ
Department of Epidemiology, Merck Research Laboratories, Blue Bell, Pennsylvania 19422, USA. girman@merck.com
Chandler
Julie M
JM
Zimmerman
Sheryl I
SI
Martin
Allison R
AR
Hawkes
William
W
Hebel
J Richard
JR
Sloane
Philip D
PD
Magaziner
Jay
J
D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D015519:Bone Density; D015331:Cohort Studies; D005260:Female; D005500:Follow-Up Studies; D005544:Forecasting; D050723:Fractures, Bone / Q000453:epidemiology / Q000517:prevention & control*; D006707:Homes for the Aged / Q000706:statistics & numerical data*; D006801:Humans; D015994:Incidence; D009735:Nursing Homes / Q000706:statistics & numerical data*; D010024:Osteoporosis; D011446:Prospective Studies; D011897:Random Allocation; D012306:Risk; D012307:Risk Factors; D013997:Time Factors