Journal of cataract and refractive surgery · 2013
Validation of metrics for the detection of subclinical keratoconus in a new patient collective.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Bühren Jens, Schäffeler Thomas, Kohnen Thomas
Аннотация
PURPOSE: To validate the discriminative ability of wavefront- and pachymetry-based corneal topographic metrics to detect subclinical keratoconus in a new patient collective.
SETTING: Department of Ophthalmology, Goethe-University, Frankfurt am Main, Germany.
DESIGN: Retrospective cross-sectional study.
METHODS: Normal fellow eyes with early keratoconus and preoperative eyes with an uneventful follow-up without signs of iatrogenic keratectasia 12 months after laser in situ keratoconus were included. Zernike coefficients from the anterior and posterior surfaces and corneal thickness spatial profiles and corresponding discriminant functions were assessed for their usefulness to discriminate between eyes with subclinical keratoconus and normal eyes using receiver-operating-characteristic (ROC) curve analysis. Discriminant functions were obtained from a previous study and constructed de novo from the present collective.
RESULTS: The anterior C(1,-1) and C(3,-1) coefficients had the highest area under the ROC curve (both 0.87). The anterior 5th-order root mean square (RMS) was the RMS value with the maximum area under the ROC curve (0.90). The discriminant function with input from anterior and posterior Zernike coefficients (DAP) and DAP including pachymetry data (DAPT) performed best (area under ROC curve 0.864 and 0.857, respectively). Applying cutoff values from a previous study resulted in a minimal drop in accuracy (0.0% to 1.3%). The construction of discriminant functions from the present dataset resulted in a gain in accuracy of between 3.5% and 9.6%, with DAPT reaching the maximum area under the ROC curve of 0.956.
CONCLUSION: Validation in a new and larger patient collective proved the usefulness of metrics based on corneal wavefront and pachymetry for the detection of subclinical keratoconus.
FINANCIAL DISCLOSURE: No author has a financial or proprietary interest in any material or method mentioned.
SETTING: Department of Ophthalmology, Goethe-University, Frankfurt am Main, Germany.
DESIGN: Retrospective cross-sectional study.
METHODS: Normal fellow eyes with early keratoconus and preoperative eyes with an uneventful follow-up without signs of iatrogenic keratectasia 12 months after laser in situ keratoconus were included. Zernike coefficients from the anterior and posterior surfaces and corneal thickness spatial profiles and corresponding discriminant functions were assessed for their usefulness to discriminate between eyes with subclinical keratoconus and normal eyes using receiver-operating-characteristic (ROC) curve analysis. Discriminant functions were obtained from a previous study and constructed de novo from the present collective.
RESULTS: The anterior C(1,-1) and C(3,-1) coefficients had the highest area under the ROC curve (both 0.87). The anterior 5th-order root mean square (RMS) was the RMS value with the maximum area under the ROC curve (0.90). The discriminant function with input from anterior and posterior Zernike coefficients (DAP) and DAP including pachymetry data (DAPT) performed best (area under ROC curve 0.864 and 0.857, respectively). Applying cutoff values from a previous study resulted in a minimal drop in accuracy (0.0% to 1.3%). The construction of discriminant functions from the present dataset resulted in a gain in accuracy of between 3.5% and 9.6%, with DAPT reaching the maximum area under the ROC curve of 0.956.
CONCLUSION: Validation in a new and larger patient collective proved the usefulness of metrics based on corneal wavefront and pachymetry for the detection of subclinical keratoconus.
FINANCIAL DISCLOSURE: No author has a financial or proprietary interest in any material or method mentioned.