The macular mapping test:a reliability study

Background: Age-related macular degeneration (ARMD) is the leading cause of visual disability in people over 60 years of age in the developed world. The success of treatment deteriorates with increased latency of diagnosis. The purpose of this study was to determine the reliability of the macular mapping test (MMT), and to investigate its potential as a screening tool. Methods: The study population comprised of 31 healthy eyes of 31 participants. To assess reliability, four macular mapping test (MMT) measurements were taken in two sessions separated by one hour by two practitioners, with reversal of order in the second session. MMT readings were also taken from 17 age-related maculopathy (ARM), and 12 AMD affected eyes. Results: For the normal cohort, average MMT scores ranged from 85.5 to 100.0 MMT points. Scores ranged from 79.0 to 99.0 for the ARM group and from 9.0 to 92.0 for the AMD group. MMT scores were reliable to within ± 7.0 points. The difference between AMD affected eyes and controls (z = 3.761, p = < 0.001) was significant. The difference between ARM affected eyes and controls was not significant (z = -0.216, p = 0.829). Conclusion: The reliability data shows that a change of 14 points or more is required to indicate a clinically significant change. This value is required for use of the MMT as an outcome measure in clinical trials. Although there was no difference between MMT scores from ARM affected eyes and controls, the MMT has the advantage over the Amsler grid in that it uses a letter target, has a peripheral fixation aid, and it provides a numerical score. This score could be beneficial in office and home monitoring of AMD progression, as well as an outcome measure in clinical research. © 2005 Bartlett et al; licensee BioMed Central Ltd.

Detecting and monitoring the symptoms of Parkinson's disease using smartphones:a pilot study

Background: Remote, non-invasive and objective tests that can be used to support expert diagnosis for Parkinson's disease (PD) are lacking. Methods: Participants underwent baseline in-clinic assessments, including the Unified Parkinson's Disease Rating Scale (UPDRS), and were provided smartphones with an Android operating system that contained a smartphone application that assessed voice, posture, gait, finger tapping, and response time. Participants then took the smart phones home to perform the five tasks four times a day for a month. Once a week participants had a remote (telemedicine) visit with a Parkinson disease specialist in which a modified (excluding assessments of rigidity and balance) UPDRS performed. Using statistical analyses of the five tasks recorded using the smartphone from 10 individuals with PD and 10 controls, we sought to: (1) discriminate whether the participant had PD and (2) predict the modified motor portion of the UPDRS. Results: Twenty participants performed an average of 2.7 tests per day (68.9% adherence) for the study duration (average of 34.4 days) in a home and community setting. The analyses of the five tasks differed between those with Parkinson disease and those without. In discriminating participants with PD from controls, the mean sensitivity was 96.2% (SD 2%) and mean specificity was 96.9% (SD 1.9%). The mean error in predicting the modified motor component of the UPDRS (range 11-34) was 1.26 UPDRS points (SD 0.16). Conclusion: Measuring PD symptoms via a smartphone is feasible and has potential value as a diagnostic support tool.