Dataset Information

Comparison of visual field severity classification systems for glaucoma.

ABSTRACT: PURPOSE:To compare categorical severity classification systems for glaucoma. METHODS:This cross-sectional study included 1,921 eyes (49.5% right eye) from 1,137 participants from the Diagnostic Innovations in Glaucoma Study and African Descent and Glaucoma Evaluation Study. Standard automated perimetry fields were classified using the: (1) Advanced Glaucoma Intervention Study scoring system (AGIS), (2) Glaucoma Severity Staging system (GSS), and (3) Enhanced Glaucoma Severity Staging system (eGSS). Systems were characterized using the following continuous measures of severity: mean deviation, pattern standard deviation, and visual field index. Classifications between systems and with optic disc stereophotograph assessment were compared (?) and some stages were consolidated to evaluate severity classification across systems (Wilcoxon test). RESULTS:Mean deviation, pattern standard deviation, and visual field index were significantly different between GSS and AGIS, and GSS and eGSS in normal and abnormal fields (P<0.005). Agreement between AGIS and eGSS was substantial (?=0.715±0.012); agreement between GSS and eGSS (?=0.559±0.014) and AGIS (?=0.519±0.016) was moderate. eGSS tended to stage abnormal fields most severely followed by GSS and then AGIS (P<0.001). CONCLUSIONS:The presence of glaucomatous optic neuropathy increases with staging severity for all systems. However, different systems led to different severity staging. Of the systems examined in this study, eGSS may be the better choice for its ease of use for both clinicians and researchers.

SUBMITTER: Ng M

PROVIDER: S-EPMC3246042 | biostudies-literature | 2012 Oct-Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comparison of visual field severity classification systems for glaucoma.

Ng Minna M Sample Pamela A PA Pascual John P JP Zangwill Linda M LM Girkin Chris A CA Girkin Chris A CA Liebmann Jeffrey M JM Weinreb Robert N RN Racette Lyne L

Journal of glaucoma 20121001 8

<h4>Purpose</h4>To compare categorical severity classification systems for glaucoma.<h4>Methods</h4>This cross-sectional study included 1,921 eyes (49.5% right eye) from 1,137 participants from the Diagnostic Innovations in Glaucoma Study and African Descent and Glaucoma Evaluation Study. Standard automated perimetry fields were classified using the: (1) Advanced Glaucoma Intervention Study scoring system (AGIS), (2) Glaucoma Severity Staging system (GSS), and (3) Enhanced Glaucoma Severity Stag ...[more]

PMID: 21878817

Similar Datasets

Project description:PurposeTo quantify the central visual field (VF) loss patterns in glaucoma using artificial intelligence.DesignRetrospective study.ParticipantsVFs of 8712 patients with 13 951 Humphrey 10-2 test results from 13 951 eyes for cross-sectional analyses, and 824 patients with at least 5 reliable 10-2 test results at 6-month intervals or more from 1191 eyes for longitudinal analyses.MethodsTotal deviation values were used to determine the central VF patterns using the most recent 10-2 test results. A 24-2 VF within a 3-month window of the 10-2 tests was used to stage eyes into mild, moderate, or severe functional loss using the Hodapp-Anderson-Parrish scale at baseline. Archetypal analysis was applied to determine the central VF patterns. Cross-validation was performed to determine the optimal number of patterns. Stepwise regression was applied to select the optimal feature combination of global indices, average baseline decomposition coefficients from central VFs archetypes, and other factors to predict central VF mean deviation (MD) slope based on the Bayesian information criterion (BIC).Main outcome measuresThe central VF patterns stratified by severity stage based on 24-2 test results and a model to predict the central VF MD change over time using baseline test results.ResultsFrom cross-sectional analysis, 17 distinct central VF patterns were determined for the 13 951 eyes across the spectrum of disease severity. These central VF patterns could be divided into isolated superior loss, isolated inferior loss, diffuse loss, and other loss patterns. Notably, 4 of the 5 patterns of diffuse VF loss preserved the less vulnerable inferotemporal zone, whereas they lost most of the remaining more vulnerable zone described by the Hood model. Inclusion of coefficients from central VF archetypical patterns strongly improved the prediction of central VF MD slope (BIC decrease, 35; BIC decrease of >6 indicating strong prediction improvement) than using only the global indices of 2 baseline VF results. Eyes with baseline VF results with more superonasal and inferonasal loss were more likely to show worsening MD over time.ConclusionsWe quantified central VF patterns in glaucoma, which were used to improve the prediction of central VF worsening compared with using only global indices.

Project description:ImportanceMacular function is important for daily activities but is underestimated when tested with 24-2 visual fields, which are often used to classify glaucoma severity.ObjectiveTo test the hypothesis that current glaucoma staging systems underestimate glaucoma severity by not detecting macular damage.Design, setting, and participantsThis cross-sectional study was carried out in a glaucoma referral practice. The eyes of participants with manifest glaucoma and 24-2 mean deviation (MD) better than -6 dB were included. All participants were tested with 24-2, 10-2 visual fields, and spectral-domain optical coherence tomography of the optic disc and macula.ExposuresMacular damage was based on the topographic agreement between visual field results and retinal ganglion cell plus inner plexiform layer probability plots. Classifications from the Hodapp-Parrish-Anderson (HPA), visual field index (VFI), and Brusini staging systems were examined and compared with visual field and spectral-domain optical coherence tomography results.Main outcomes and measuresThe association between the presence of macular damage and glaucoma severity scores.ResultsFifty-seven eyes of 57 participants were included; 33 participants (57%) were women, and 43 (75%) were white. Their mean (SD) age was 57 (14) years. Forty-eight of the eyes (84% [95% CI, 72%-92%]) had macular damage by the study definition. These had a 24-2 MD mean (SD) of -2.5 (1.8); corresponding results for the 10-2 MD were -3.0 (2.4) dB and for the VFI were 94.2% (4.5%). The HPA system classified 70% (95% CI, 55%-83%) of eyes with macular damage as having early defects; the VFI system classified 81% (95% CI, 67%-91%) of eyes with macular damage as having early defects, and the Brusini system 68% (95% CI, 53%-81%).Conclusions and relevanceThese findings suggest that current glaucoma staging systems based on 24-2 (or 30-2) visual fields underestimate disease severity and the presence of macular damage. If these results are confirmed and generalizable to other participants, new systems using macular measures (from 10-2 and spectral-domain optical coherence tomography results) might improve staging of glaucoma severity.

Project description:PurposeTo determine which patient-reported symptoms best distinguish patients with and without glaucoma and explain the most variance in visual field (VF) damage and to compare the amount of variance that can be explained by symptoms versus retinal nerve fiber layer (RNFL) thickness.DesignCross-sectional study.ParticipantsAdults diagnosed with glaucoma or suspicion of glaucoma (controls).MethodsWorse-eye VF damage was defined on the basis of perimetric testing. Thickness of RNFL was defined by OCT imaging. Patients rated their visual symptoms on questions collated from several published questionnaires, rating the frequency and severity of 28 symptoms on a scale of 1 (never/not at all) to 4 (very often/severe). Multivariable regression models identified patient-reported symptoms that contributed the highest variance in VF damage.Main outcome measuresPatient-reported symptoms that explained the most variance in VF damage and amount of variance in VF damage explained by patient-reported symptoms and RNFL.ResultsA total of 170 patients (mean age: 64 years; 58% female; 47% employed) completed testing, including 95 glaucoma suspects and 75 glaucoma patients. In glaucoma patients, median mean deviation of VF damage in the worse eye was -19.3 and ranged from -5.3 to -34.7 decibels. Symptoms more common among glaucoma patients compared with glaucoma suspects included better vision in 1 eye, blurry vision, glare, sensitivity to light, cloudy vision, missing patches of vision, and little peripheral vision. Worse severity ratings for the symptom "little peripheral vision" explained the most variance in VF damage (43%). A multivariable model including the frequency of cloudy vision, severity of having little peripheral vision, missing patches, 1 eye having better vision, and vision worsening, plus sociodemographic features, explained 62% of the variance in VF damage. Comparatively, a multivariable model of worse-eye RNFL thickness and sociodemographic features explained 42% of the variance in VF damage, whereas a model including only sociodemographic features explained 8% of the variance in VF damage.ConclusionsFive patient-reported symptoms explain a significant amount of the variance in VF damage. Asking patients about their symptoms may optimize patient-physician communication and be a useful adjunct to clinical testing in some patients to estimate disease severity.

Dataset Information

Comparison of visual field severity classification systems for glaucoma.

Publications

Comparison of visual field severity classification systems for glaucoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets