| Literature DB >> 20738840 |
Azlyn-Azwa Jasman1, Bakiah Shaharuddin, Raja-Azmi M Noor, Shatriah Ismail, Zulkifli A Ghani, Zunaina Embong.
Abstract
BACKGROUND: Despite growing number of intraocular lens power calculation formulas, there is no evidence that these formulas have good predictive accuracy in pediatric, whose eyes are still undergoing rapid growth and refractive changes. This study is intended to compare the prediction error and the accuracy of predictability of intraocular lens power calculation in pediatric patients at 3 month post cataract surgery with primary implantation of an intraocular lens using SRK II versus Pediatric IOL Calculator for pediatric intraocular lens calculation. Pediatric IOL Calculator is a modification of SRK II using Holladay algorithm. This program attempts to predict the refraction of a pseudophakic child as he grows, using a Holladay algorithm model. This model is based on refraction measurements of pediatric aphakic eyes. Pediatric IOL Calculator uses computer software for intraocular lens calculation.Entities:
Mesh:
Year: 2010 PMID: 20738840 PMCID: PMC2936388 DOI: 10.1186/1471-2415-10-20
Source DB: PubMed Journal: BMC Ophthalmol ISSN: 1471-2415 Impact factor: 2.209
Figure 1A screen capture of the Pediatric IOL Calculator.
Distribution of patients according to gender and ethnic group
| SRK II | Pediatric IOL Calculator | |
|---|---|---|
| n = 11 | n = 13 | |
| n (%) | n (%) | |
| Gender | ||
| Boy | 8 (61.54%) | 5 (38.46%) |
| Girl | 5 (45.45%) | 6 (54.55%) |
| Ethnic | ||
| Malay | 12 (92.31%) | 1 (7.69%) |
| Chinese | 1 (7.69%) | 1 (9.09%) |
| Indian | 0 | 1 (9.09%) |
Distribution of eyes according to age at time of surgery
| Number of Eyes | Total of Eyes | ||
|---|---|---|---|
| Age at surgery | SRK II | Pediatric IOL Calculator | n(%) |
| < 3 years old | 2 | 2 | 4 (13%) |
| ≥ 3 years old | 14 | 13 | 27 (87%) |
Figure 2Distribution of axial lengths in both groups in pediatric population.
Mean axial length and keratometry in both groups
| Overall | SRK II | Pediatric IOL Calculator | *p value | ||
|---|---|---|---|---|---|
| Axial length (mm) | [mean (SD)] | 22.51 (1.88) | 22.61 (1.86) | 22.39 (1.96) | 0.75 |
| [range] | 18.93 - 27.04 | 20.16 - 27.04 | 18.93 - 26.60 | ||
| Keratometry (diopter) | [mean (SD)] | 44.22 (2.60) | 44.71 (2.69) | 43.70 (2.48) | 0.28 |
| [range] | 37.01 - 50.13 | 40.06 - 50.13 | 37.01 - 46.37 | ||
* Independent-Samples T Test
p value < 0.05 (significant)
Figure 3Distribution of keratometry in both groups in pediatric population.
The mean predicted refraction, observed refraction and prediction error between SRK II and Pediatric IOL Calculator
| SRK II | Pediatric IOL Calculator | *p value | |
|---|---|---|---|
| Mean Predicted Refraction (Diopter, SD) | -0.06 (1.17) | 1.19 (2.35) | |
| Mean Observed Refraction (Diopter, SD) | -0.84 (1.31) | 0.10 (1.74) | |
| Mean Prediction Error (Diopter, SD) | 1.03 (0.69) | 1.14 (1.19) | 0.74 |
* Independent-Samples T Test
p value < 0.05 (significant)
Mean prediction errors for the subgroup data
| Mean Prediction Error (Diopter, SD) | |||
|---|---|---|---|
| SRK II | Pediatric IOL Calculator | * p value | |
| Age | |||
| Age < 3 years | 1.55 (1.46) | 3.54 (0.33) | 0.201 |
| Age ≥ 3 years | 0.94 (0.57) | 0.77 (0.74) | 0.488 |
| Axial length | |||
| Axial length < 22 mm | 0.91 (0.77) | 1.47 (1.65) | 0.439 |
| Axial length ≥ 22 mm | 1.11 (0.64) | 0.91 (0.80) | 0.580 |
| Keratometry | |||
| Keratometry < 46D | 0.93 (0.61) | 1.20 (1.26) | 0.525 |
| Keratometry ≥ 46D | 1.22 (0.86) | 0.72 (0.65) | 0.499 |
* Independent-Samples T Test
p value < 0.05 (significant)
Accuracy of predictability between SRK II and Pediatric IOL Calculator
| Observed refraction ( | SRK II (n = 16) | Pediatric IOL Calculator (n = 15) | Overall (n = 31) | * p value |
|---|---|---|---|---|
| ≤ ± 2.0 Diopter | ||||
| | ||||
| 0.0 D to ± 0.5 D | 3 (18.75%) | 7 (46.67%) | 10 (32.26%) | 0.097 |
| | ||||
| > ± 0.5 D to ± 1.0 D | 7 (43.75%) | 0 (0.00%) | 7 (22.58%) | |
| > ± 1.0 D to ± 2.0 D | 4 (25.00%) | 5 (33.33%) | 9 (29.03%) | |
| > ± 2.0 Diopter | 2 (12.50%) | 3 (20.00%) | 5 (16.13%) |
* Pearson chi-square test
p < 0.05 (significant)