Biomedical subjects

S A Zenios

Publications and source records attributed to S A Zenios.

4 recordsLinked to original sources

PubMed2001

Primum non nocere: avoiding harm to vulnerable wait list candidates in an indirect kidney exchange.

BACKGROUND: One proposal to increase kidney transplantation is to exchange kidneys between pairs of ABO-incompatible (or cross-match-incompatible) living donors and their recipients. One variation that has greater potential exchanges living donor kidneys for cadaveric donor kidneys (indirect exchanges). A primary concern with indirect exchanges is the potential to disadvantage blood group O wait list candidates. Using wait list modeling, we examine whether this proposal would disadvantage cadaveric kidney blood group O wait list candidates, and present an approach for neutralizing these negative effects. METHODS: A probability model estimated the total number and blood type frequencies of donor-recipient pairs that would participate in indirect exchanges. A supply-to-demand model for the cadaveric kidney wait list estimated the mean wait time under different allocation policies and donor selection mechanisms for candidates on the wait list classified according to the candidates' race and blood type. RESULTS: Indirect exchanges will reduce the mean wait time for cadaveric kidney wait list candidates. The mean wait time of blood group O cadaveric kidney wait list candidates increases when the participating living donors self-select and when kidney allocation is determined by efficiency. This is neutralized when the transplant team preferentially selects blood group O living donors and cadaveric kidney allocation is determined by need. CONCLUSION: Indirect exchange programs will significantly shorten the wait times for cadaveric kidney wait list candidates. The wait times of blood group O candidates will not be affected adversely if blood group O living donors are selected preferentially and if allocation is based on need.

ABO Blood-Group System↗

PubMed1999

Evidence-based organ allocation.

BACKGROUND: There are not enough cadaveric kidneys to meet the demands of transplant candidates. The equity and efficiency of alternative organ allocation strategies have not been rigorously compared. METHODS: We developed a five-compartment Monte Carlo simulation model to compare alternative organ allocation strategies, accommodating dynamic changes in recipient and donor characteristics, patient and graft survival rates, and quality of life. The model simulated the operations of a single organ procurement organization and attempted to predict the evolution of the transplant waiting list for 10 years. Four allocation strategies were compared: a first-come first-transplanted system; a point system currently utilized by the United Network of Organ Sharing; an efficiency-based algorithm that incorporated correlates of patient and graft survival; and a distributive efficiency algorithm, which had an additional goal of promoting equitable allocation among African-American and other candidates. RESULTS: A 10-year computer simulation was performed. The distributive efficiency policy was associated with a 3.5%+/-0.8% (mean +/- SD) increase in quality-adjusted life expectancy (33.9 months vs 32.7 months), a decrease in the median waiting time to transplantation among those who were transplanted (6.6 months vs 16.3 months), and an increase in the overall likelihood of transplantation (61% vs 45%), compared with the United Network of Organ Sharing algorithm. Improved equity and efficiency were also seen by race (African-American vs other), sex, and age (<50 or > or =50 years). Sensitivity analyses did not appreciably change the qualitative results. CONCLUSION: Evidence-based organ allocation strategies in cadaveric kidney transplantation would yield improved equity and efficiency measures compared with existing algorithms.

Algorithms↗

PubMed1998

Pooled testing for HIV prevalence estimation: exploiting the dilution effect.

We study pooled (or group) testing as a method for estimating the prevalence of HIV; rather than testing each sample individually, this method combines various samples into a pool and then tests the pool. Existing pooled testing procedures estimate the prevalence using dichotomous test outcomes. However, HIV test outcomes are inherently continuous, and their dichotomization may eliminate useful information. To overcome this problem, we develop a parametric procedure that utilizes the continuous outcomes. This procedure employs a hierarchical pooling model and estimates the prevalence using the likelihood equation. The likelihood equation is solved using an iterative algorithm, and a simulation study shows that our procedure yields very accurate estimates at a fraction of the cost of existing procedures.

Algorithms↗

PubMed1997

Dynamic multidrug therapies for HIV: a control theoretic approach.

Motivated by the inability of current drug treatment to provide long-term benefit to HIV-infected individuals, we derive HIV therapeutic strategies by formulating and analyzing a mathematical control problem. The model tracks the dynamics of uninfected and infected CD4+ cells and free plasma virus, and allows the virus to mutate into various strains. At each point in time, several different therapeutic options are available, where each option corresponds to a combination of reverse transcriptase inhibitors. The controller observes the individual's current status and chooses among the therapeutic options in a dynamic fashion in order to minimize the total viral load. Our initial numerical results suggest that dynamic therapies have the potential to significantly outperform the static protocols that are currently in use; by anticipating and responding to the disease progression, the dynamic strategy reduces the total free virus, increases the uninfected CD4+ count, and delays the emergence of drug-resistant strains.

CD4-Positive T-Lymphocytes↗