The Cataract National Dataset electronic multi-centre audit of 55,567 operations: risk indicators for monocular visual acuity outcomes
- PMID: 22441022
- PMCID: PMC3376295
- DOI: 10.1038/eye.2012.51
The Cataract National Dataset electronic multi-centre audit of 55,567 operations: risk indicators for monocular visual acuity outcomes
Abstract
Aims: To report risk factors for visual acuity (VA) improvement and harm following cataract surgery using electronically collected multi-centre data conforming to the Cataract National Dataset (CND).
Methods: Routinely collected anonymised data were remotely extracted from the electronic patient record systems of 12 participating NHS Trusts undertaking cataract surgery. Following data checks and cleaning, analyses were performed to identify risk indicators for: (1) a good acuity outcome (VA 6/12 or better), (2) the pre- to postoperative change in VA, and (3) VA loss (doubling or worse of the visual angle).
Results: In all, 406 surgeons from 12 NHS Trusts submitted data on 55,567 cataract operations. Preoperative VA was known for 55,528 (99.9%) and postoperative VA outcome for 40,758 (73.3%) operations. Important adverse preoperative risk indicators found in at least 2 of the 3 analyses included older age (3), short axial length (3), any ocular comorbidity (3), age-related macular degeneration (2), diabetic retinopathy (3), amblyopia (2), corneal pathology (2), previous vitrectomy (2), and posterior capsule rupture (PCR) during surgery (3). PCR was the only potentially modifiable adverse risk indicator and was powerfully associated with VA loss (OR=5.74).
Conclusion: Routinely collected electronic data conforming to the CND provide sufficient detail for identification and quantification of preoperative risk indicators for VA outcomes of cataract surgery. The majority of risk indicators are intrinsic to the patient or their eye, with a notable exception being PCR during surgery.
Comment in
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The impact of outsourcing on cataract training in the UK.Eye (Lond). 2017 Jun;31(6):827. doi: 10.1038/eye.2017.35. Epub 2017 Mar 3. Eye (Lond). 2017. PMID: 28257131 Free PMC article. No abstract available.
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