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1.  The effect of different criteria on the number of patients blind from open-angle glaucoma 
BMC Ophthalmology  2011;11:31.
Background
The prevalence of blindness and visual impairment from glaucoma is influenced by the criteria used to define these entities, which differ between countries and regions, as well as among published reports. The objective of the present study was to ascertain the extent to which different criteria of blindness and visual impairment influence estimates of the number of patients classified as blind or visually impaired by glaucoma in a clinic-based population.
Methods
We conducted a retrospective chart review of 914 patients with open-angle glaucoma to compare numbers of patients identified as visually impaired with and without considering visual field status. We also compared proportions classified using World Health Organisation (WHO) and United States (US) blindness criteria, and applying a new US Social Security Administration (SSA) disability criterion: perimetric mean deviation (MD) ≤ -22 dB.
Results
Forty patients (4.4%) were bilaterally blind from glaucoma by the WHO criteria. Fifty-two (5.7%) were blind by the the US criterion. Assessing only visual acuity, 14 (1.5%) patients were blind by the WHO criteria and 24 (2.6%) by the US definition. Eighty-five (9.3%) met the US SSA disability criterion. Among those, 52 were impaired also by the WHO definition. No patients impaired according to the WHO criteria had MD values better than -22 dB.
Conclusions
Excluding visual field status will seriously underestimate the prevalence of glaucoma blindness. In our patient population, 30% more patients were classified as blind by the US than by the WHO definition. Also, 60% more were identified as visually impaired by the US SSA criterion than by the WHO criteria. Visual field assessment is vital to determine visual impairment caused by glaucoma.
doi:10.1186/1471-2415-11-31
PMCID: PMC3247062  PMID: 22074185
2.  Integration and fusion of standard automated perimetry and optical coherence tomography data for improved automated glaucoma diagnostics 
BMC Ophthalmology  2011;11:20.
Background
The performance of glaucoma diagnostic systems could be conceivably improved by the integration of functional and structural test measurements that provide relevant and complementary information for reaching a diagnosis. The purpose of this study was to investigate the performance of data fusion methods and techniques for simple combination of Standard Automated Perimetry (SAP) and Optical Coherence Tomography (OCT) data for the diagnosis of glaucoma using Artificial Neural Networks (ANNs).
Methods
Humphrey 24-2 SITA standard SAP and StratusOCT tests were prospectively collected from a randomly selected population of 125 healthy persons and 135 patients with glaucomatous optic nerve heads and used as input for the ANNs. We tested commercially available standard parameters as well as novel ones (fused OCT and SAP data) that exploit the spatial relationship between visual field areas and sectors of the OCT peripapillary scan circle. We evaluated the performance of these SAP and OCT derived parameters both separately and in combination.
Results
The diagnostic accuracy from a combination of fused SAP and OCT data (95.39%) was higher than that of the best conventional parameters of either instrument, i.e. SAP Glaucoma Hemifield Test (p < 0.001) and OCT Retinal Nerve Fiber Layer Thickness ≥ 1 quadrant (p = 0.031). Fused OCT and combined fused OCT and SAP data provided similar Area under the Receiver Operating Characteristic Curve (AROC) values of 0.978 that were significantly larger (p = 0.047) compared to ANNs using SAP parameters alone (AROC = 0.945). On the other hand, ANNs based on the OCT parameters (AROC = 0.970) did not perform significantly worse than the ANNs based on the fused or combined forms of input data. The use of fused input increased the number of tests that were correctly classified by both SAP and OCT based ANNs.
Conclusions
Compared to the use of SAP parameters, input from the combination of fused OCT and SAP parameters, and from fused OCT data, significantly increased the performance of ANNs. Integrating parameters by including a priori relevant information through data fusion may improve ANN classification accuracy compared to currently available methods.
doi:10.1186/1471-2415-11-20
PMCID: PMC3167760  PMID: 21816080
3.  The Effect of Education on the Assessment of Optic Nerve Head Photographs for the Glaucoma Diagnosis 
BMC Ophthalmology  2011;11:12.
Background
To evaluate the effect of one lesson of continuing medical education (CME) of subjective assessment of optic nerve head appearance on sensitivity and specificity for the diagnosis of glaucoma.
Methods
Ophthalmologists and residents in ophthalmology attending an international glaucoma meeting arranged at Malmö University Hospital, Malmö, Sweden, were asked to grade optic nerve head (ONH) photographs of healthy and glaucomatous subjects at two sessions separated by a lecture on glaucoma diagnosis by ONH assessment. Each grader had access to an individual portfolio of 50 ONH photographs randomly selected from a web-based data bank including ONH photographs of 73 glaucoma patients and 123 healthy subjects. The individual portfolio of photographs was graded before and after the lecture, but in different randomized order.
Results
Ninety-six doctors, 91% of all attending the meeting, completed both assessment sessions. The number of correct classifications increased from 69 to 72% on the average. Diagnostic sensitivity increased significantly (p < 0.0001) from 70% to 80%, and the number of photographs classified as uncertain decreased significantly (p < 0.0001) from 22% to 13%. Specificity remained at 68%, and intra-grader agreement decreased.
Conclusion
CME had only a small effect on the assessment of ONH for the glaucoma diagnosis. Sensitivity increased and the amount of uncertain classifications decreased, while specificity was unchanged.
doi:10.1186/1471-2415-11-12
PMCID: PMC3120800  PMID: 21595936

Results 1-3 (3)