Logistical burden of offers and allocation inefficiency in circle-based liver allocation.

Recent changes to liver allocation replaced donor service areas with circles as the geographic unit of allocation. Circle-based allocation might increase the number of transplantation centers and candidates required to place a liver, thereby increasing the logistical burden of making and responding to offers on organ procurement organizations and transplantation centers. Circle-based allocation might also increase distribution time and cold ischemia time (CIT), particularly in densely populated areas of the country, thereby decreasing allocation efficiency. Using Scientific Registry of Transplant Recipient data from 2019 to 2021, we evaluated the number of transplantation centers and candidates required to place livers in the precircles and postcircles eras, nationally and by donor region. Compared with the precircles era, livers were offered to more candidates (5 vs. 9; p < 0.001) and centers (3 vs. 5; p < 0.001) before being accepted; more centers were involved in the match run by offer number 50 (9 vs. 14; p < 0.001); CIT increased by 0.2 h (5.9 h vs. 6.1 h; p < 0.001); and distribution time increased by 2.0 h (30.6 h vs. 32.6 h; p < 0.001). Increased burden varied geographically by donor region; livers recovered in Region 9 were offered to many more candidates (4 vs. 12; p < 0.001) and centers (3 vs. 8; p < 0.001) before being accepted, resulting in the largest increase in CIT (5.4 h vs. 6.0 h; p < 0.001). Circle-based allocation is associated with increased logistical burdens that are geographically heterogeneous. Continuous distribution systems will have to be carefully designed to avoid exacerbating this problem.

Life expectancy without a transplant for status 1A liver transplant candidates.

Status 1A liver transplant candidates are given the highest medical priority for the allocation of deceased donor livers. Organ Procurement and Transplantation Network (OPTN) policy requires physicians to certify that a candidate has a life expectancy without a transplant of less than 7 days for that candidate to be given status 1A. Additionally, candidates receiving status 1A must have one of six medical conditions listed in policy. Using Scientific Registry of Transplant Recipients data from all prevalent liver transplant candidates from 2010 to 2020, we used a bias-corrected Kaplan-Meier model to calculate the survival of status 1A candidates and to determine their life expectancy without a transplant. We found that status 1A candidates have a life expectancy without a transplant of 24 (95% CI 20-46) days-over three times longer than what policy requires for status 1A designation. We repeated the analysis for subgroups of status 1A candidates based on the medical conditions that grant status 1A. We found that none of these subgroups met the life expectancy requirement. Harmonizing OPTN policy with observed data would sustain the integrity of the allocation process.

The Precise Relationship Between Model for End-Stage Liver Disease and Survival Without a Liver Transplant.

BACKGROUND AND AIMS: Scores from the Model for End-Stage Liver Disease (MELD), which are used to prioritize candidates for deceased donor livers, are widely acknowledged to be negatively correlated with the 90-day survival rate without a liver transplant. However, inconsistent and outdated estimates of survival probabilities by MELD preclude useful applications of the MELD score. APPROACH AND RESULTS: Using data from all prevalent liver waitlist candidates from 2016 to 2019, we estimated 3-day, 7-day, 14-day, 30-day, and 90-day without-transplant survival probabilities (with confidence intervals) for each MELD score and status 1A. We used an adjusted Kaplan-Meier model to avoid unrealistic assumptions and multiple observations per person instead of just the observation at listing. We found that 90-day without-transplant survival has improved over the last decade, with survival rates increasing >10% (in absolute terms) for some MELD scores. We demonstrated that MELD correctly prioritizes candidates in terms of without-transplant survival probability but that status 1A candidates' short-term without-transplant survival is higher than that of MELD 40 candidates and lower than that of MELD 39 candidates. Our primary result is the updated survival functions themselves. CONCLUSIONS: We calculated without-transplant survival probabilities for each MELD score (and status 1A). The survival function is an invaluable tool for many applications in liver transplantation: awarding of exception points, calculating the relative demand for deceased donor livers in different geographic areas, calibrating the pediatric end-stage liver disease score, and deciding whether to accept an offered liver.

Fully nonparametric survival analysis in the presence of time-dependent covariates and dependent censoring.

In the presence of informative right censoring and time-dependent covariates, we estimate the survival function in a fully nonparametric fashion. We introduce a novel method for incorporating multiple observations per subject when estimating the survival function at different covariate values and compare several competing methods via simulation. The proposed method is applied to survival data from people awaiting liver transplant.

GC/MS method for positive detection of Bacillus anthracis endospores.

A simple method was developed for detection of Bacillus anthracis (BA) endospores and for differentiation of them from other species in the Bacillus cereus group. Chemical profiles that include lipids (i.e., fatty acids), carbohydrates (i.e., sugars), and the spore-specific biomarker, dipicolinic acid, were generated by one-step thermochemolysis (TCM) at 140 °C in 5 min to provide specific biomarker signatures. Anthrose, which is a biomarker characteristic of the B. cereus group of bacteria, was determined from a fragment produced by TCM. Surprisingly, several virulent BA strains contained very low levels of anthrose, which confounded their detection. A statistical discrimination algorithm was constructed using a combination of biomarkers, which was robust against different growth conditions (medium and temperature). Fifteen endospore-forming Bacillus species were confirmed in a statistically designed test (~90%) using the algorithm, including six BA strains (four virulent isolates), five B. thuringiensis (BT) isolates, and one isolate each for B. cereus (BC), B. mycoides (BM), B. atrophaeus (BG), and B. subtilis (BS). The detection limit for B. anthracis was found to be 50,000 endospores, on the basis of the GC/MS detection limits for 3-methyl-2-butenoic acid methyl ester, which is the biomarker derived from TCM of anthrose.