| Literature DB >> 33168906 |
Antonio Pérez-Rueda1, Gracia Castro-Luna2.
Abstract
This paper aims to calculate a relevance model of visual limitation (V.L.) in keratoconus patients based on refractive and topographic parameters. A cross-sectional study was carried out in Torrecárdenas Hospital, Almería, Spain, between February 2018 and July 2019. It included 250 keratoconus patients. Two groups were created according to a grading system of V.L. based on RETICS (Red Temática de Investigación Cooperativa en Salud) classification: keratoconus patients with no V.L. (best spectacle-corrected visual acuity (BSCVA) ≤ 0.05 logMAR) and keratoconus patients with V.L. (BSCVA > 0.05 logMAR). Correlations and a binary logistic regression were established. V.L. was correlated with maximum curvature (r = 0.649, p < 0.001) and root mean square higher-order aberrations (HOARMS) (r = 0.625, p < 0.001). Binary logistic regression included V.L. as the dependent variable and spherical equivalent, HOARMS, spherical aberration and interaction between the anterior and posterior vertical coma as independent variables. The model was a good fit. Area under the curve (A.U.C.) of receiver operating characteristic (R.O.C.) curve was 0.924, sensitivity 91.90%, specificity 83.60%, accuracy 88.94%; and precision 91.17%. Binary logistic regression model of V.L. is a good fit model to predict the early loss of visual acuity in keratoconus patients.Entities:
Mesh:
Year: 2020 PMID: 33168906 PMCID: PMC7652865 DOI: 10.1038/s41598-020-76489-1
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Demographic characteristics of V.L. and no V.L. groups.
| No V.L | V.L | |
|---|---|---|
| Patients n (%) | 99 (39.6) | 151 (60.4) |
| Age (mean ± SD) | 33.70 ± 11.53 | 37.63 ± 15.63 |
| Right n (%) | 47 (47.5) | 93 (61.6) |
| Left n (%) | 52 (52.5) | 58 (38.4) |
| Male n (%) | 53 (53.5) | 74 (49.1) |
| Female n (%) | 46 (46.5) | 77 (50.9) |
| SKC n (%) | 38 (38.4) | 2 (1.3) |
| Grade 1 n (%) | 59 (59.6) | 62 (41.1) |
| Grade 2 n (%) | 2 (2) | 54 (35.8) |
| Grade 3 n (%) | 0 (0) | 19 (12.6) |
| Grade 4 n (%) | 0 (0) | 14 (9.3) |
| Sphere (mean ± SD) | − 1.16 ± 2.29 | − 4.05 ± 4.71 |
| Cylinder (mean ± SD) | − 1.56 ± 1.20 | − 3.48 ± 1.80 |
| Spherical equiv (mean ± SD) | − 1.80 ± 2.12 | − 5.46 ± 4.74 |
| Decimal scale | 0.98 ± 0.04 | 0.45 ± 0.26 |
| LogMAR scale | 0.01 ± 0.19 | 0.43 ± 0.30 |
SPSS Statistics for Windows, version 25.0 (SPSS Inc., Chicago, Il, USA).
V.L. visual limitation, SKC subclinical keratoconus, BSCVA best spectacle-corrected visual acuity, logMAR logarithm of the minimum angle of resolution.
Refractive and topographic parameters and correlation with V.L.
| r (p-value) | R2 | |
|---|---|---|
| Spherical equivalent | − 0.446 (0.001) | 0.199 |
| Kmax | 0.649 (0.001) | 0.421 |
| Q | − 0.499 (0.001) | 0.249 |
| K2 | − 0.571 (0.001) | 0.326 |
| MCT | − 0.456 (0.001) | 0.208 |
| HOARMS | 0.625 (0.001) | 0.390 |
| Corneal vertical coma | − 0.515 (0.001) | 0.265 |
| Vertical anterior coma | − 0.503 (0.001) | 0.253 |
| Vertical posterior coma | 0.453 (0.001) | 0.205 |
| Spherical aberration | − 0.477 (0.001) | 0.228 |
SPSS statistics for windows, version 25.0 (SPSS Inc., Chicago, Ill., USA).
V.L. visual limitation, Kmax maximum curvature, Q asphericity, K2 major posterior curvature, MCT minimum corneal thickness, HOARMS root mean square high order aberrations.
Variables of the binary logistic model for V.L. in keratoconus patients.
| Variable | β | p-value | OR (exp β) | CI 95% for OR | |
|---|---|---|---|---|---|
| Spherical equivalent | − 0.241 | 0.002 | 0.786 | 0.674 | 0.917 |
| HOARMS | 2.458 | 0.0001 | 11.681 | 4.808 | 28.380 |
| Anterior vertical coma*posterior vertical coma | 1.050 | 0.0001 | 2.857 | 1.729 | 4.723 |
| Spherical aberration | − 2.221 | 0.003 | 0.108 | 0.025 | 0.473 |
| Constant | − 3.188 | 0.0001 | 0.041 | ||
Anterior Vertical Coma*Posterior Vertical Coma, interaction between anterior and posterior vertical coma; Hosmer and Lemeshow test (p = 0.169). R, version 3.5.1. (R core Team, 2018).
OR odds ratio, CI confidence interval, RMS root mean square, HOA high order aberrations.
Classification table for logistic regression of the V.L. in keratoconus patients.
| Observed | Total | ||
|---|---|---|---|
| V.L | No V.L | ||
| V.L | 124 | 12 | 136 |
| No V.L | 11 | 61 | 72 |
| Total | 135 | 73 | 208 |
Sensitivity = 91.90%; specificity = 83.60%; accuracy = 88.94%; precision = 91.17%; lost cases = 50; R, version 3.5.1. (R core Team, 2018).
V.L. visual limitation.
Figure 1R.O.C. curve for logistic regression for V.L. in keratoconus patients. The A.U.C. of the R.O.C. curve for the binary logistic regression model was 0.924 (CI 95% 0.885–0.963). This means the 92.4% of the predicted “keratoconus with V.L.” would be real “keratoconus with V.L.” if our model would be applied. V.L. visual limitation, A.U.C. area under the curve, R.O.C. receiver operating characteristic. R, version 3.5.1. (R core Team, 2018).