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. Author manuscript; available in PMC: 2016 Aug 1.
Published in final edited form as: Parkinsonism Relat Disord. 2015 May 16;21(8):960–963. doi: 10.1016/j.parkreldis.2015.05.008

Table 2.

Multivariate model coefficients and predicted probability of falling according to risk category for validation sample and development sample.

Predictor variable Validation sample
Development sample
Regression coefficient OR (95% CI) Regression coefficient OR (95% CI)
Fell in previous 12 mo, yes/no 2.83 (1.84, 3.81) 16.90 (6.30, 45.00) 1.76 (1.10, 2.42) 5.80 (3.00, 11.22)
FOG in past mo, yes/no 0.05 (30.76, 0.88) 1.06 (0.47, 2.40) 0.87 (0.17, 1.60) 2.39 (1.19, 4.80)
Self-selected gait speed <1.1 m/s, yes/no 0.87 (0.07, 1.67) 2.38 (1.07, 5.31) 0.62 (30.04, 1.27) 1.86 (0.96, 3.58)
Risk categorya Number of participants who fell/total number of participants scoring in this category Predicted (actual) probability of falling, % Number of participants who fell/total number of participants scoring in this category Predicted (actual) probability of falling, %
Low (0) 4/47 1 (9) 8/43 17 (19)
Med (>0 to <8) 15/53 30 (28) 36/73 51 (49)
High (>8) 47/71 66 (66) 76/89 85 (85)
a

Weights are assigned to each of the three predictor variables based on the regression coefficients of the 3-predictor regression (ie, falling in past month = 6, freezing of gait in the past month = 3, gait speed <1.1 m per second = 2). The sum of the predictor weights give a maximum score of 11 and a minimum score of 0. Probability of falling in the next 6 months is then classified (based on the sum of the predictor weights) as low (0), moderate (>0 to < 8) or high (≥8) [7].