Background In the context of an aging end-stage renal disease population with multiple comorbidities, transplantation professionals face challenges in evaluating the global health of patients awaiting kidney transplantation. Functional status might be useful for identifying which patients will derive a survival benefit from transplantation versus dialysis. Study Design Retrospective cohort study of wait-listed patients using data on functional status from a national dialysis provider linked to United Network for Organ Sharing registry data. Setting & Participants Adult kidney transplant candidates added to the waiting list between the years 2000 and 2006. Predictor Physical function scale of the Medical Outcomes Study 36-Item Short Form Healthy Survey, analyzed as a time-varying covariate. Outcomes Kidney transplantation; Survival benefit of transplantation versus remaining wait-listed. Measurements We used multivariable Cox regression to assess the association between physical function with study outcomes. In survival benefit analyses, transplant status was modeled as a time-varying covariate. Results The cohort comprised 19,242 kidney transplant candidates (median age, 51 years; 36% black race) receiving maintenance dialysis. Candidates in the lowest baseline physical function quartile were more likely to be inactivated (adjusted HR vs. highest quartile, 1.30; 95% CI, 1.21-1.39) and less likely to undergo transplantation (adjusted HR vs. highest quartile, 0.64; 95% CI, 0.61-0.68). After transplantation, worse physical function was associated with shorter 3-year survival (84% vs. 92% for the lowest vs. highest function quartiles). However, compared to dialysis, transplantation was associated with a statistically significant survival benefit by 9 months for patients in every function quartile. Limitations Functional status is self-reported. Conclusions Even patients with low function appear to live longer with kidney transplantation versus dialysis. For waitlisted patients, global health measures like functional status may be more useful in counseling patients about the probability of transplantation than in identifying who will derive a survival benefit from it.

Background It is becoming increasingly important to study common and distinct etiologies, clinical and pathological features, and mechanisms related to neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), and frontotemporal lobar degeneration (FTLD). These comparative studies rely on powerful database tools to quickly generate data sets which match diverse and complementary criteria set by the studies. Methods In this paper, we present a novel Integrated NeuroDegenerative Disease (INDD) database developed at the University of Pennsylvania (Penn) through a consortium of Penn investigators. Since these investigators work on AD, PD, ALS and FTLD, this allowed us to achieve the goal of developing an INDD database for these major neurodegenerative disorders. We used Microsoft SQL Server as the platform with built-in “backwards” functionality to provide Access as a front-end client to interface with the database. We used PHP hypertext Preprocessor to create the “front end” web interface and then integrated individual neurodegenerative disease databases using a master lookup table. We also present methods of data entry, database security, database backups, and database audit trails for this INDD database. Results We compare the results of a biomarker study using the INDD database to those using an alternative approach by querying individual database separately. Conclusions We have demonstrated that the Penn INDD database has the ability to query multiple database tables from a single console with high accuracy and reliability. The INDD database provides a powerful tool for generating data sets in comparative studies across several neurodegenerative diseases.