TABLE 3.
Results of logistic regression to predict whether a subject will be in the worst tertile for subsequent rate of change (defined according to each of the two slopes in turn)
| Predictor | |||||
|---|---|---|---|---|---|
| MD | PSD | ||||
| Outcome | OR | R2 | OR | R2 | |
| GON cohort | SlMD | 0.76 (0.58–0.99) | 0.332 | 1.25 (0.91–1.72) | 0.278 |
| SlPSD | 0.94 (0.72–1.22) | 0.052 | 1.06 (0.76–1.48) | 0.086 | |
| Non-GON cohort | SlMD | 0.72 (0.46–1.12) | 0.309 | 1.99 (0.88–4.48) | 0.321 |
| SlPSD | 0.89 (0.66–1.20) | 0.103 | 1.27 (0.71–2.25) | 0.098 | |
The baseline value of each global index is used to predict the probability of being in the worst tertile, using a backward-elimination regression model as outlined in the Methods section. The table shows the odds ratio, with 95% confidence interval in brackets (the multiplicative change in the probability of being in the worst tertile when the baseline index value increases by 1dB) and the Nagelkerke’s pseudo-R2 coefficient obtained (a measure of the goodness of fit of the model).