May 2007
Volume 48, Issue 13
ARVO Annual Meeting Abstract  |   May 2007
Database for Correlation of Demographic, Clinical Photo Documentation and Genetic Data
Author Affiliations & Notes
  • M. Busuioc
    Ophthalmology, Columbia Univ-Harkness Eye Inst, New York, New York
  • R. T. Smith
    Ophthalmology, Columbia Univ-Harkness Eye Inst, New York, New York
  • N. Lee
    BME, Columbia Univ, New York, New York
  • R. Allikmets
    Ophthalmology, Columbia Univ-Harkness Eye Inst, New York, New York
  • Footnotes
    Commercial Relationships M. Busuioc, None; R.T. Smith, None; N. Lee, None; R. Allikmets, None.
  • Footnotes
Investigative Ophthalmology & Visual Science May 2007, Vol.48, 2597. doi:
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      M. Busuioc, R. T. Smith, N. Lee, R. Allikmets; Database for Correlation of Demographic, Clinical Photo Documentation and Genetic Data. Invest. Ophthalmol. Vis. Sci. 2007;48(13):2597.

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      © ARVO (1962-2015); The Authors (2016-present)

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Purpose:: To present a database for integration of research data with clinical and demographic data, that can allow extended collaboration between different sites through VPN connections.

Methods:: For a secure storage and analysis system we custom designed a database for demographics, clinical phenotype information correlated with genotype information and image analysis subsystem. The database is developed on a modified three tiers model, in which the client interface was designed in Microsoft’s FoxPro, object oriented language, with a SQL 2005 Server back-end support for security and scalability. The system resides on a Windows 2003 Server Standard edition with Terminal Services. For added security and easy upgrades the terminal client connection is used for access from any individual computer. In this way we benefit from all security provided by Microsoft connection and encryption. No information resides on individual workstations. The system is automatically disconnected after 10 min of inactivity. Password access is used at this time, and we established HIPPA compliance through internal procedures, in place at Columbia University.The database consist of one main table with demographic information and multiple children tables with clinical, grading, and genetic information. The design took into account flexible structure for modifications and upgrades. The screens are clutter free, ordered accordingly to subject in the questionnaires used. The clinical information is specific tailored to AMD study, but can be modified for any other study with ease. We opted for a balance between restricted entries and free text for minimizing data entry errors, and assuring powerful queries with correct output.The grading is done in drop down boxes with fast selection cues. The program can present and modify digital images and assist the grading of drusen in AMD studies. Previously presented algorithms for image enhancement and drusen segmentation can be applied through the integrated analysis interface.

Results:: Different report generation features, for complex queries, were implemented, making easy for researcher to have a comprehensive analysis done at a press of a button. Also the system can export all the data or specific queries in different formats including XML. The export also can be done in HIPPA compliant deidentified format.

Conclusions:: The program can be used to document the research and speed-up the grading process whenever quantified and very accurate data is needed.

Clinical Trial:: IRB-AAAA7543

Keywords: age-related macular degeneration • computational modeling • genetics 

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