DOI 10.1097/00006324-199808000-00025
The repeatability of tear mucus ferning grading.
Аннотация
PURPOSE: Rolando's classification system for tear mucus ferning patterns subjectively assigns grades based on the size and spacing between ferns. Grade 1 and 2 patterns are considered "normal," whereas grade 3 and 4 patterns are often associated with keratoconjunctivitis sicca. This study was designed to examine the intraobserver and interobserver repeatability of Rolando's system.
METHODS
Photographic slides (N = 418) of portions of tear ferning patterns were randomly assembled, numbered, and graded by two investigators (I1 and I2). I1 graded the slides twice; the slides were remixed under masked conditions between the first and second runs. I2 graded the slides once, independent of I1.
RESULTS
For the four-grade system, intraobserver agreement was 85.41% (simple kappa = 0.75; 95% confidence interval ]CI] = 0.69-0.82). Interobserver agreement was 80.62% (kappa = 0.67; CI = 0.60-0.74) and 86.12% (kappa = 0.75; CI = 0.68-0.83) for the first and second runs of I1, respectively. Analysis of the ability to simply classify normal (grade 1 and 2) from abnormal (grade 3 and 4) patterns revealed intraobserver repeatability of 94.50% (kappa = 0.76; CI = 0.67-0.86). Interobserver agreement was 92.10% (kappa = 0.65; CI = 0.56-0.75) and 94.26% (kappa = 0.71; CI = 0.62-0.81) for the first and second runs, respectively.
CONCLUSION
Based on the high rate of agreement between intraobserver and interobserver trials, Rolando's grading system appears to be an easy and consistent method for the classification of tear ferning patterns.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
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.
Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.