Creating "score" --> by adding ORs?

I have created a prognostic model using logistic regression. It predicts diabetes based on 6 independent variables (age, sex BMI, etc). I understand that Exp(Xi) = Odds Ratio of each (risk) factor in the model. I also understand that the probability of diabetes = exp(bo+ bi Xi) /((exp(bo + bi Xi) + 1) where Xi reflect relevant values for each predictor for an individual, and bo is the model intercept.

I would like to create a simple summary score based on the resulting (rounded?) beta coefficients. Can I simply sum the relevant ORs to make a score?

Thanks for your feedback..:yup:
A friend helped solve this problem. No, the score can't simply be sum of ORs -- it needs to be an expansion of the beta coefficients from dummy variables (say factor C =0.5 --> factor of 5). So Beta/C = score (then round the score). The probability of predicted outcome Y (dependent variable in logistic model) = 1 / (1 + exp(-z)) where z = b0 + C (point total) given b0 is the intercept term from logistic model. This is based on Sullivan LM et al, Tutorial in Biostatistics: Presentation of multivariate data for clinical use: The Framingham Study risk score functions. Statistics in Medicine 2004; 23:1631-1660