For the logistic regression algorithm, we determined the independent variables that contributed the most to the overall regression equation. For the full-test mode, these variables were superior-nasal ratio, maximum modulation, and average thickness. A probability of glaucoma of. This algorithm was also applied to the screening mode results. Two parameters contributed significantly to the overall regression equation, maximum modulation and superior maximum.
A probability of glaucoma being detected of. The number was not available in the screening mode Table 4. A TSNIT image abnormality was determined to be present when the measured nerve fiber layer thickness dropped below the range of normal in the superior or inferior quadrant. The ROC curves were determined for each algorithm that had continuous outcomes and multiple potential cutoff points for abnormality. The area under the curve for each algorithm in early, moderate, and severe glaucomatous damage is shown in Table 6.
We wished to assess the possibility that the misclassification of glaucoma status was related to confounding factors such as vision, astigmatism, or pseudophakia. Misclassification was defined as an incorrect classification of a patient's eye by the number algorithm cutoff, 35 compared with our clinical assessment gold standard described earlier. We then evaluated whether misclassification errors were more likely with decreased vision, greater astigmatism, or pseudophakia. This suggests that misclassification errors by laser scanning polarimetry were not related to these variables.
This study was done to measure the diagnostic accuracy of scanning laser polarimetry. When measuring the diagnostic accuracy of a new test, care must be taken in choosing the standard against which it is compared. This standard should be the best available method of differentiating between those with and without disease. It should effectively discriminate these groups across the full spectrum of disease.
For example, an experienced observer can often determine whether a patient has glaucoma before visual field defects occur by performing a careful stereoscopic optic nerve evaluation. This is particularly important when the test may be good at detecting early glaucoma. Scanning laser polarimetry has been reported to measure nerve fiber layer thickness, and because defects of the retinal nerve fiber layer have been reported 3 , 5 to be present long before visual defects occur, it could be inferred that this technique has promise in the early detection of glaucoma.
The current standard for the diagnosis of glaucoma must at least include a careful examination of the optic nerve by an experienced observer, evaluation of a reliable threshold perimetric examination, and the measurement of the intraocular pressure. In this study, this information was provided to 3 separate experienced observers. To further maximize the likelihood of proper classification, a unanimous agreement was required to place an eye in the "glaucoma" or "normal" group.
If there was not unanimous agreement, the result was categorized as uncertain, and the eye was not analyzed further. Sensitivity and specificity of a test will depend on the cutoff used to judge the result as abnormal. With comparable specificity between the algorithms, the sensitivities can be easily compared to determine the more accurate algorithms, at least at that cutoff level.
Algorithm results detailing both higher and lower specificity and the associated sensitivities are also provided in Table 3 , Table 4 , and Table 5 to allow a more comprehensive assessment of the performance of each algorithm. The number provided the greatest accuracy of the algorithms tested. Preliminary work by the manufacturer has suggested that scores of 0 to 30 are normal, whereas scores above 70 tend to indicate the presence of glaucoma.
Two scenarios wherein a more accurate and objective method of diagnosing glaucoma is needed include population screening and when clinically it is uncertain whether a patient has early glaucoma. Objective, accurate, and rapid testing is ideal for screening purposes. It is particularly important for a glaucoma screening test to detect patients who have severe manifestation of disease because substantial morbidity may ensue. Because of the large number of subjects tested and the relatively low prevalence of glaucoma, even in a selected population, specificity needs to be high to avoid overdiagnosing the disease.
This does not compare favorably with the Henson perimetry test. Frequency-doubling perimetry has shown promise as a screening method for glaucoma. There is little difficulty in diagnosing a patient as having glaucoma who demonstrates moderate neural rim loss on stereoscopic examination. It is not uncommon, however, to be faced with a patient who may have some early optic nerve changes, but the findings are somewhat equivocal. Typically, definitive visual field defects will not be present at this early stage of disease.
In such a patient, the use of this procedure might be considered because of the theoretical potential for detecting defects of the retinal nerve fiber layer. This is also called the positive predictive power of the test and is defined as the ratio of true-positive results to the sum of true- and false-positive results. This is the negative predictive value of the test and is defined as the ratio of true-negative results to the sum of true- and false-negative results.
The positive and negative predictive values are dependent on sensitivity, specificity, and pretest probability. So if the test result is positive, there is a sufficient likelihood of glaucoma being present to alter follow-up frequency, and some physicians may feel comfortable initiating treatment. If the test result is negative, then there is only a marginal increase in confidence that the patient does not have glaucoma. They used 3 ratios in their algorithm for classifying a subject. They used the "squares calculation method" to determine ratios. In brief, for the superior, inferior, and nasal segments, they chose 6 squares of pixels each that were devoid of blood vessels.
These were handpicked by the investigator. The values were averaged for each segment, and the superior-nasal, inferior-nasal, and superior-inferior ratios were calculated. The current software 9 does not provide an inferior-nasal ratio with normative database comparison. In their study, We found that this ratio also called "symmetry" by the software identified only 6 of 51 eyes with early, 5 of 42 eyes with moderate, and 0 of 32 eyes with severe glaucoma.
Accuracy of Scanning Laser Polarimetry in the Diagnosis of Glaucoma
However, the superior-nasal ratio was more accurate, detecting 11 of 51 eyes with early, 19 of 42 eyes with moderate, and 15 of 32 eyes with severe glaucoma. Other differences between the studies include a blood vessel removal algorithm for our data and their requirement of the glaucoma hemifield test measuring outside normal limits. As would be expected, a number of eyes in our study showing early glaucoma would not meet their requirements for entry.
However, 70 of 73 eyes with moderate or severe glaucoma did have results of a glaucoma hemifield test that were outside normal limits. Therefore, despite having similar levels of visual field damage, the diagnostic accuracy for moderate and severe glaucoma in this study was still well below their reported levels. Our group was older than their group mean age of subjects with normal eyes, As with our study, they tested a largely white population. In summary, the reason for poorer accuracy in our study is unclear.
It does not appear to clearly relate to the fact that some glaucomatous eyes had normal visual fields because the diagnostic accuracy was also much lower for moderate and severe glaucoma. A limitation of this or any similar study involves the need to restrict the number of diagnostic algorithms tested.
Although we may be able to derive a more accurate algorithm with further analysis, the possibility that this will be the result of chance alone also increases. Nevertheless, an exploration of the data, with testing of a large number of possible diagnostic algorithms, might prove interesting, particularly if then applied to an independent data set for validation. If we weight borderline results equal to outside normal limits, then accuracy improves modestly.
Further work is needed to optimize our use of the information provided. This study evaluated the diagnostic accuracy of this procedure in glaucoma. We did not attempt to validate or disprove its ability to accurately measure nerve fiber layer thickness. The best algorithm for the screening test was less sensitive, particularly for those with severe glaucoma. The demonstrated accuracy in detecting severe glaucoma with scanning laser polarimetry appears to be much lower than with existing perimetric screening devices, but studies involving direct comparisons of the techniques are needed.
This Issue. Citations View Metrics. Clinical Sciences. John R. Trible, MD ; Richard O. Schultz, MD ; James C. Robinson, MD ; et al Terri L. Subjects and methods.
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Statistical analysis. Full-Test Mode. Number of Abnormalities. Logistic Regression. Screening Test Mode. Sign in to access your subscriptions Sign in to your personal account. Create a free personal account to download free article PDFs, sign up for alerts, and more. Product code : Leading Destination Sites Websites where people were diverted to from uworld.
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Self-Assessment in Optic and Refraction by Prof Chua, Dr. Chieng, Dr.ngo and Dr. Alhady
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