Dataset Information

Keratoplasty for corneal endothelial disease, 2001-2009.

ABSTRACT:

Purpose

To determine the rates of keratoplasty for corneal endothelial disease (CED) from 2001 to 2009 in a large managed care network in the United States, factors that affect which patients undergo this procedure and surgical outcomes.

Design

A retrospective review of data from a longitudinal cohort study.

Participants

Beneficiaries with CED aged ? 40 years who were receiving eye care during 2001 to 2009.

Methods

Rates of keratoplasty for CED were determined at 6-month intervals from January 2001 to December 2009. The mean number of postoperative visits and rates of severe adverse events in the year after keratoplasty surgery were monitored over the course of the decade. Univariable and multivariable logistic regression were performed to identify sociodemographic and other factors associated with undergoing keratoplasty for CED.

Main outcome measures

Odds of undergoing keratoplasty with 95% confidence intervals, changes in the number of postoperative visits, and rates of adverse events in the year after keratoplasty.

Results

Of the 38 648 enrollees who met the inclusion criteria, 2187 underwent ? 1 keratoplasty surgeries from January 2001 to December 2009. After adjustment for confounding factors, individuals with CED had 47% increased odds of undergoing keratoplasty during 2007-2009 relative to 2001-2006. The mean number of postoperative visits to eyecare providers in the year after keratoplasty declined from 12.6 in 2001-2006 to 10.5 in 2007-2008. There was no difference in the proportion of enrollees who developed adverse events after keratoplasty over time.

Conclusions

In this analysis of claims data, from 2001 to 2009, a period during which there was an increase in the rate of endothelial keratoplasty, we observed a trend of greater rates of keratoplasty in patients with CED and fewer visits for postoperative care in the later years of the decade compared with the earlier years, along with no change in rates of severe adverse events.

SUBMITTER: Shtein RM

PROVIDER: S-EPMC3389206 | biostudies-literature | 2012 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Keratoplasty for corneal endothelial disease, 2001-2009.

Shtein Roni M RM Raoof-Daneshvar Duna D Lin Hsien-Chang HC Sugar Alan A Mian Shahzad I SI Nan Bin B Stein Joshua D JD

Ophthalmology 20120417 7

<h4>Purpose</h4>To determine the rates of keratoplasty for corneal endothelial disease (CED) from 2001 to 2009 in a large managed care network in the United States, factors that affect which patients undergo this procedure and surgical outcomes.<h4>Design</h4>A retrospective review of data from a longitudinal cohort study.<h4>Participants</h4>Beneficiaries with CED aged ≥ 40 years who were receiving eye care during 2001 to 2009.<h4>Methods</h4>Rates of keratoplasty for CED were determined at 6-m ...[more]

PMID: 22512985

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Project description:Purpose To develop a model to predict corneal improvement after Descemet membrane endothelial keratoplasty (DMEK) for Fuchs endothelial corneal dystrophy (FECD) from Scheimpflug tomography. Design Cross-sectional study. Participants Forty-eight eyes (derivation group) and 45 eyes (validation group) with a range of severity of FECD undergoing DMEK. Methods Scheimpflug images were obtained before and after DMEK. Before DMEK, pachymetry map and posterior elevation map patterns were quantified by a special image analysis program measuring tomographic features of edema (loss of regular isopachs, displacement of the thinnest point of the cornea, posterior surface depression). Image-derived novel parameters were combined with instrument-derived parameters, and the relative influences of parameters associated with the change in central corneal thickness (CCT) after DMEK in the derivation group were determined by using a gradient boosting machine learning model. The parameters with highest relative influence were then fit in a linear regression model. The derived model was applied to the validation group. Correlations and agreement were assessed between predicted and observed changes in CCT. Main Outcome Measures Predictive power (R2) and mean difference between predicted and observed change in CCT. Results The gradient boosting machine model identified 4 novel parameters of isopach circularity and eccentricity and 1 instrument-derived parameter (posterior surface radius); preoperative CCT was a poor predictor. In the derivation group, the model strongly predicted the change in CCT after DMEK (R2 = 0.80; 95% confidence interval [CI], 0.71–0.89) and the mean difference between predicted and observed change was, by definition, 0 μm. When the same 5 parameters were fit to the validation group, the model performed very highly (R2 = 0.89; 95% CI, 0.84–0.94). When the coefficient estimates from the derivation model were used to predict the change in CCT in the validation group, the predictive power was also high (R2 = 0.78; 95% CI, 0.68–0.88), and the mean difference was 4 μm (predicted minus observed). Conclusions Scheimpflug tomography maps of corneas with FECD can predict the improvement in CCT after DMEK, independent of preoperative corneal thickness measurement. The model could be applied in clinical practice or for clinical research of FECD.

Dataset Information

Keratoplasty for corneal endothelial disease, 2001-2009.

Purpose

Design

Participants

Methods

Main outcome measures

Results

Conclusions

Publications

Keratoplasty for corneal endothelial disease, 2001-2009.

Similar Datasets

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