Table 4. Analysis of image quality between groups.
| Parameter | Group 1, (HR ≤60), (n=855) | Group 2, (HR 60–80), n=807 | P value |
|---|---|---|---|
| Median Likert Score [IQR] | 4 [3, 4] | 4 [3, 4] | <0.01 |
| Likert score | |||
| Uninterpretable | 2 (0.2%) | 6 (0.7%) | 0.13 |
| (I) Poor | 9 (1.0%) | 13 (1.6%) | 0.32 |
| (II) Adequate | 21 (2.4%) | 73 (9.0%) | <0.01 |
| (III) Good | 258 (30.2%) | 242 (30.0%) | 0.93 |
| (IV) Very good | 446 (52.2%) | 380 (47.1%) | 0.04 |
| (V) Excellent | 119 (13.9%) | 93 (11.5% | 0.14 |
| Predicted probabilities | |||
| (I) Poor | 0.014 | 0.019 | |
| (II) Adequate | 0.035 | 0.049 | |
| (III) Good | 0.281 | 0.347 | |
| (IV) Very good | 0.527 | 0.481 | |
| (V) Excellent | 0.144 | 0.104 | |
| Ordinal logistic regression β coefficient | –0.371 (95% CI: –0.57, –0.17) | <0.01 | |
| Binary logistic regression β coefficient (interpretable vs. non-interpretable) | –0.19 (95% CI: –1.00, 0.61) | 0.64 | |
Predicted probabilities as based on ordinal logit. Ordinal logistic regression co-efficient as based on ordinal outcome variable Likert 1 to 5. Binary logistic regression coefficient as based on non-interpretable (Likert <2) vs. interpretable (Likert ≥2) segments.