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October 1995

Prediction of Visual Function After Cataract SurgeryA Prospectively Validated Model

Author Affiliations

From the Divisions of Clinical Epidemiology (Drs Mangione, Orav, and Goldman) and General Medicine (Drs Mangione and Goldman), Department of Medicine, Brigham; and Women's Hospital; the Division of Clinical Epidemiology, Beth Israel Hospital (Drs Phillips and Goldman); the Epidemiology Unit (Dr Seddon) and General Eye Service (Dr Lawrence), Department of Ophthalmology, Massachusetts Eye and Ear Infirmary, Harvard Medical School; and the Departments of Biostatistics (Dr Orav) and Epidemiology (Dr Seddon), Harvard School of Public Health, Boston, Mass. Dr Mangione is now with the Division of General Medicine and Health Services Research and the Division of Geriatrics, Department of Medicine, Center for the Health Sciences, University of California-Los Angeles. Dr Goldman is now chairman of the Department of Medicine, University of California-San Francisco.

Arch Ophthalmol. 1995;113(10):1305-1311. doi:10.1001/archopht.1995.01100100093037

Objective:  To develop a model to predict visual functional improvement after cataract extraction with intraocular lens implantation based on preoperative data. Design: A prospective study with serial evaluations of visual function preoperatively and at 3 and 12 months after surgery.

Setting:  The General Eye Service of the Massachusetts Eye and Ear Infirmary, Boston, Mass, and 33 ophthalmology practices in Boston.

Patients:  Patients (N=426; ages, ≥65 years) who were undergoing cataract surgery.

Methods:  Twelve-month improvement in visual function was measured by using the Activities of Daily Vision Scale (ADVS). Ordinal logistic regression was used to identify correlates of improved ADVS scores in 281 patients (derivative set). Potential factors included the preoperative visual acuity, preoperative ADVS score, four chronic ocular diseases, eight medical conditions, and demographic characteristics. Five predictors were identified and used to construct a prediction rule. The accuracy of the prediction rule was evaluated in an independent group of 145 patients (validation set).

Results:  Postoperatively, 40% of the 281 patients in the derivative set had substantial improvement in their ADVS scores, and 53 (19%) had some improvement. Predictors of improvement included younger age (P<.001), a poorer preoperative ADVS score (P<.001), posterior sub-capsular cataract (P=.09), and absence of age-related macular degeneration (P=.07) and/or diabetes (P=.006). When applied to the independent sample of 145 patients, these five characteristics classified the patients into three groups in which the probabilities of substantial improvement were 85%, 34%, and 3%, thus verifying the discriminatory power of the prediction rule.

Conclusions:  Preoperative data can identify patients who are likely to have improvements in visual function after cataract surgery. Such findings may be useful in the selection of patients for this high-volume procedure.

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