Dataset Information

Ocular Risk Factors for Exudative AMD: A Novel Semiautomated Grading System.

ABSTRACT: Purpose. To evaluate the contribution of the ocular risk factors in the conversion of the fellow eye of patients with unilateral exudative AMD, using a novel semiautomated grading system. Materials and Methods. Single-center, retrospective study including 89 consecutive patients with unilateral exudative AMD and ?3 years of followup. Baseline color fundus photographs were graded using an innovative grading software, RetmarkerAMD (Critical Health SA). Results. The follow-up period was 60.9 ± 31.3 months. The occurrence of CNV was confirmed in 42 eyes (47.2%). The cumulative incidence of CNV was 23.6% at 2 years, 33.7% at 3 years, 39.3% at 5 years, and 47.2% at 10 years, with a mean annual incidence of 12.0% (95%?CI = 0.088-0.162). The absolute number of drusen in the central 1000 and 3000? ? m (P < 0.05) and the absolute number of drusen ?125 µm in the central 3000 and 6000 µm (P < 0.05) proved to be significant risk factors for CNV. Conclusion. The use of quantitative variables in the determination of the OR of developing CNV allowed the establishment of significant risk factors for neovascularization. The long follow-up period and the innovative methodology reinforce the value of our results. This trial is registered with ClinicalTrials.gov NCT00801541.

SUBMITTER: Marques JP

PROVIDER: S-EPMC3910538 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Ocular Risk Factors for Exudative AMD: A Novel Semiautomated Grading System.

Marques João Pedro JP Costa Miguel M Melo Pedro P Oliveira Carlos Manta CM Pires Isabel I Cachulo Maria Luz ML Figueira João J Silva Rufino R

ISRN ophthalmology 20130730

Purpose. To evaluate the contribution of the ocular risk factors in the conversion of the fellow eye of patients with unilateral exudative AMD, using a novel semiautomated grading system. Materials and Methods. Single-center, retrospective study including 89 consecutive patients with unilateral exudative AMD and ≥3 years of followup. Baseline color fundus photographs were graded using an innovative grading software, RetmarkerAMD (Critical Health SA). Results. The follow-up period was 60.9 ± 31.3 ...[more]

PMID: 24555130

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Project description:Age-related Macular Degeneration (AMD) is a major cause of irreversible vision loss in individuals over 55 years old in the United States. One of the late-stage manifestations of AMD, and a major cause of vision loss, is the development of exudative macular neovascularization (MNV). Optical Coherence Tomography (OCT) is the gold standard to identify fluid at different levels within the retina. The presence of fluid is considered the hallmark to define the presence of disease activity. Anti-vascular growth factor (anti-VEGF) injections can be used to treat exudative MNV. However, given the limitations of anti-VEGF treatment, as burdensome need for frequent visits and repeated injections to sustain efficacy, limited durability of the treatment, poor or no response, there is a great interest in detecting early biomarkers associated with a higher risk for AMD progression to exudative forms in order to optimize the design of early intervention clinical trials. The annotation of structural biomarkers on optical coherence tomography (OCT) B-scans is a laborious, complex and time-consuming process, and discrepancies between human graders can introduce variability into this assessment. To address this issue, a deep-learning model (SLIVER-net) was proposed, which could identify AMD biomarkers on structural OCT volumes with high precision and without human supervision. However, the validation was performed on a small dataset, and the true predictive power of these detected biomarkers in the context of a large cohort has not been evaluated. In this retrospective cohort study, we perform the largest-scale validation of these biomarkers to date. We also assess how these features combined with other EHR data (demographics, comorbidities, etc) affect and/or improve the prediction performance relative to known factors. Our hypothesis is that these biomarkers can be identified by a machine learning algorithm without human supervision, in a way that they preserve their predictive nature. The way we test this hypothesis is by building several machine learning models utilizing these machine-read biomarkers and assessing their added predictive power. We found that not only can we show that the machine-read OCT B-scan biomarkers are predictive of AMD progression, we also observe that our proposed combined OCT and EHR data-based algorithm outperforms the state-of-the-art solution in clinically relevant metrics and provides actionable information which has the potential to improve patient care. In addition, it provides a framework for automated large-scale processing of OCT volumes, making it possible to analyze vast archives without human supervision.

Project description:ObjectiveThe objective of this study was to evaluate the existing Spetzler-Martin (SM), Spetzler-Ponce (SP), and Lawton-Young (LY) grading systems for cerebellar arteriovenous malformations (AVMs) and to propose a new grading system to estimate the risks associated with these lesions.MethodsData for patients with cerebellar AVMs treated microsurgically in two tertiary medical centers were retrospectively reviewed. Data from patients at institution 1 were collected from September 1999 to February 2013, and at institution 2 from October 2008 to October 2015. Patient outcomes were classified as favorable (modified Rankin Scale [mRS] score 0-2) or poor (mRS score 3-6) at the time of discharge. Using chi-square and logistic regression analysis, variables associated with poor outcomes were assigned risk points to design the proposed grading system. The proposed system included neurological status prior to treatment (poor, +2 points), emergency surgery (+1 point), age > 60 years (+1 point), and deep venous drainage (deep, +1 point). Risk point totals of 0-1 comprised grade 1, 2-3 grade 2, and 4-5 grade 3.ResultsA total of 125 cerebellar AVMs of 1328 brain AVMs were reviewed in 125 patients, 120 of which were treated microsurgically and included in the study. With our proposed grading system, we found poor outcomes differed significantly between each grade (p < 0.001), while with the SM, SP, and LY grading systems they did not (p = 0.22, p = 0.25, and p = 1, respectively). Logistic regression revealed grade 2 had 3.3 times the risk of experiencing a poor outcome (p = 0.008), while grade 3 had 9.9 times the risk (p < 0.001). The proposed grading system demonstrated a superior level of predictive accuracy (area under the receiver operating characteristic curve [AUROC] of 0.72) compared with the SM, SP, and LY grading systems (AUROC of 0.61, 0.57, and 0.51, respectively).ConclusionsThe authors propose a novel grading system for cerebellar AVMs based on emergency surgery, venous drainage, preoperative neurological status, and age that provides a superior prognostication power than the formerly proposed SM, SP, and LY grading systems. This grading system is clinically predictive of patient outcomes and can be used to better guide vascular neurosurgeons in clinical decision-making.

Dataset Information

Ocular Risk Factors for Exudative AMD: A Novel Semiautomated Grading System.

Publications

Ocular Risk Factors for Exudative AMD: A Novel Semiautomated Grading System.

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