K Matthew McKay1, Durga S Borkar, Giannis A Moustafa, Miriam J Haviland, Carolyn E Kloek. 1. From the Department of Ophthalmology, Massachusetts Eye and Ear Infirmary (McKay, Borkar, Moustafa, Kloek), Department of Epidemiology, Boston University School of Public Health (Haviland), Boston, Massachusetts, and Wills Eye Hospital Retina Service (Borkar), Philadelphia, Pennsylvania, USA.
Abstract
PURPOSE: To identify preoperative clinical characteristics affecting cataract surgery operative time. SETTING: Academic center. DESIGN: Large-scale retrospective cohort study. METHODS: All cases of cataract extraction by phacoemulsification and intraocular lens insertion performed by Comprehensive Ophthalmology at Massachusetts Eye and Ear between January 1, 2014, and December 31, 2014, were reviewed. Clinically relevant predictors of operative time were identified a priori, and a multivariate analysis was used to identify which predictors were associated with operative time. To quantify the surgeon effect, 2 regression models were built, one inclusive of surgeon identity and the other with years of experience and the training level of the supervised resident instead of identity. RESULTS: Overall, 1349 cataract surgeries in 1072 patients were included. The mean operative time was 22.1 ± 7.8 minutes. Multiple clinical factors were significantly associated with operative time, with attending surgeon identity being the most important. In the multivariate model with surgeon identity, longer operative time was associated with male sex, increased body mass index, first-eye surgery, left operative eye, advanced cataract, use of iris hooks, use of Malyugin ring, use of trypan blue, history of diabetic retinopathy, short axial length, and shallow anterior chamber depth. The R value for the model inclusive of attending identity was 0.42, significantly higher than the R value of 0.23 for the model exclusive of identity. CONCLUSION: Preoperative clinical characteristics, such as patient demographics, biometry data, and cataract severity, significantly correlate with operative time. Surgeon identity is highly correlated with operative time. Incorporating these results into predictive algorithms may allow for more predictable surgical scheduling and more efficient use of operative resources.
PURPOSE: To identify preoperative clinical characteristics affecting cataract surgery operative time. SETTING: Academic center. DESIGN: Large-scale retrospective cohort study. METHODS: All cases of cataract extraction by phacoemulsification and intraocular lens insertion performed by Comprehensive Ophthalmology at Massachusetts Eye and Ear between January 1, 2014, and December 31, 2014, were reviewed. Clinically relevant predictors of operative time were identified a priori, and a multivariate analysis was used to identify which predictors were associated with operative time. To quantify the surgeon effect, 2 regression models were built, one inclusive of surgeon identity and the other with years of experience and the training level of the supervised resident instead of identity. RESULTS: Overall, 1349 cataract surgeries in 1072 patients were included. The mean operative time was 22.1 ± 7.8 minutes. Multiple clinical factors were significantly associated with operative time, with attending surgeon identity being the most important. In the multivariate model with surgeon identity, longer operative time was associated with male sex, increased body mass index, first-eye surgery, left operative eye, advanced cataract, use of iris hooks, use of Malyugin ring, use of trypan blue, history of diabetic retinopathy, short axial length, and shallow anterior chamber depth. The R value for the model inclusive of attending identity was 0.42, significantly higher than the R value of 0.23 for the model exclusive of identity. CONCLUSION: Preoperative clinical characteristics, such as patient demographics, biometry data, and cataract severity, significantly correlate with operative time. Surgeon identity is highly correlated with operative time. Incorporating these results into predictive algorithms may allow for more predictable surgical scheduling and more efficient use of operative resources.
Authors: Michele Lanza; Robert Koprowski; Rosa Boccia; Katarzyna Krysik; Sandro Sbordone; Antonio Tartaglione; Adriano Ruggiero; Francesca Simonelli Journal: Front Med (Lausanne) Date: 2020-12-11
Authors: Ahmad M Mansour; Anastasios G P Konstas; Hana A Mansour; Abdul R Charbaji; Khalil M El Jawhari Journal: Middle East Afr J Ophthalmol Date: 2021-04-30