ABSTRACT
Objective
This study was conducted to identify factors associated with visual outcome in patients
with open globe injuries (OGIs).
Design
Retrospective case series of OGIs presenting to a tertiary eye care institute in North
India from October 2009 to December 2016.
Methods
A total of 157 patients with open globe injury have been included in the study. Multivariate
analysis to ascertain the effects of different identified variables on the likelihood
of poor visual outcome was done using binomial logistic regression. “Visual survival”
(counting fingers or better) versus “minimal/no vision” (hand motion, light perception,
and no light perception) was predicted using the classification and regression tree
(CART) model. Main outcome measures were visual outcomes, risk factors, and rates
of postoperative complications.
Results
Univariate analysis determined 9 predictors associated with poor visual outcome. Out
of these, presence of relative afferent pupillary defect (RAPD), poor presenting visual
acuity, presence of adnexal injuries, and location of injuries were the most significant
predictors of vision loss. Absence of RAPD led to 79% chance of vision survival. Sixty-eight
percent of patients with RAPD and initial visual acuity (VA) of less than 6/60 resulted
in poor vision.
Conclusion
The CART model is useful in predicting final VA based on some prognostic factors present
initially.
Résumé
Objectif
Cette étude visait à identifier les facteurs qui déterminaient les résultats visuels
chez des patients ayant subi un traumatisme oculaire à globe ouvert.
Nature
Étude rétrospective d'une série de cas portant sur des sujets ayant subi un traumatisme
à globe ouvert (TGO) et qui se sont présentés à un établissement de soins oculaires
tertiaires dans le nord de l'Inde d'octobre 2009 à décembre 2016.
Méthodes
Au total, 157 patients qui présentaient un TGO ont pris part à l’étude. On a réalisé
une analyse multivariée reposant sur une régression logistique binomiale pour vérifier
les effets de différentes variables prédéterminées sur le risque de résultats visuels
médiocres. On a ainsi émis des prévisions de type « survie visuelle » (pouvoir au
moins compter des doigts) vs « vision minime/absence de vision » (mouvement de la
main, perception de la lumière et absence de perception de la lumière) en s'appuyant
sur le modèle CART (classification and regression tree). Les principaux paramètres de mesure étaient les suivants : résultats visuels, facteurs
de risque et taux de complications postopératoires.
Résultats
L'analyse univariée a établi 9 facteurs de prédiction associés à des résultats visuels
médiocres. De ce nombre, la présence d'un déficit pupillaire afférent relatif (DPAR),
la faible acuité visuelle initiale, la présence de lésions des annexes et la localisation
des blessures étaient les facteurs de prédiction les plus significatifs d'une perte
de vision. L'absence de DPAR s'accompagnait d'un taux de 79 % de survie visuelle.
Soixante-huit pour cent des patients qui avaient un DPAR et une acuité visuelle initiale
de moins de 6/60 finissaient par avoir des résultats visuels médiocres.
Conclusion
Le modèle CART est utile pour prédire l'acuité visuelle finale en fonction de la présence
de certains facteurs pronostiques au départ.
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Article info
Publication history
Published online: October 19, 2018
Accepted:
August 2,
2018
Received in revised form:
July 31,
2018
Received:
May 19,
2018
Identification
Copyright
© 2018 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.
