Pine Sawyers (Coleoptera: Cerambycidae) Attracted to α-Pinene, Monochamol, and Ipsenol in North America.

Detection tools are needed for Monochamus species (Coleoptera: Cerambycidae) because they are known to introduce pine wilt disease by vectoring nematodes in Asia, Europe, and North America. In 2012-2014, we examined the effects of the semiochemicals monochamol and ipsenol on the flight responses of the sawyer beetles Monochamus carolinensis (Olivier), Monochamus clamator (LeConte), Monochamus mutator LeConte, Monochamus notatus (Drury), Monochamus obtusus Casey, Monochamus scutellatus (Say), and Monochamus titillator (F.) complex (Coleoptera: Cerambycidae) to traps baited with α-pinene. Experiments were set in pine forests in New Brunswick and Ontario (Canada), and Arizona, Georgia, Michigan, Montana, Oregon, South Carolina, Utah, and Washington (United States). In brief, 40 traps were placed in 10 blocks of 4 traps per block per location. Traps were baited with: 1) α-pinene; 2) α-pinene + monochamol; 3) α-pinene + ipsenol; and 4) α-pinene + monochamol + ipsenol. Monochamol increased catches of six species and one species complex of Monochamus with an additive effect of ipsenol for five species and one species complex. There was no evidence of synergy between monochamol and ipsenol on beetle catches. Monochamol had no effect on catches of other Cerambycidae or on any associated species of bark beetles, weevils, or bark beetle predators. We present a robust data set suggesting that the combination of α-pinene, ipsenol, and monochamol may be a useful lure for detecting Monochamus species.

SRTR program-specific reports on outcomes: a guide for the new reader.

Differences in outcomes indeed exist among transplant programs and organ procurement organizations (OPO). A growing set of tools are available from the Scientific Registry of Transplant Recipients (SRTR) to measure and assess these outcomes in the different phases of the transplant process. These tools are not intended to compare two individual programs, rather to help identify programs whose practices may need further scrutiny, to be either avoided, corrected or emulated. To understand which differences in outcomes might be due to underlying differences in populations served and which might be due to differences in treatment, it is important to compare outcomes to 'risk-adjusted' expected values. Further, it is important to recognize and assess the role that random chance may play in these outcomes by considering the p-value or confidence interval of each estimate. We present the reader with a basic explanation of these tools and their interpretation in the context of reading the SRTR Program-Specific Reports. We describe the intended audience of these reports, including patients, monitoring and process improvement bodies, payers and others such as the media. Use of these statistics in a way that reflects a basic understanding of these concepts and their limitations is beneficial for all audiences.

SRTR center-specific reporting tools: Posttransplant outcomes.

Measuring and monitoring performance--be it waiting list and posttransplant outcomes by a transplant center, or organ donation success by an organ procurement organization and its partnering hospitals--is an important component of ensuring good care for people with end-stage organ failure. Many parties have an interest in examining these outcomes, from patients and their families to payers such as insurance companies or the Centers for Medicare and Medicaid Services; from primary caregivers providing patient counseling to government agencies charged with protecting patients. The Scientific Registry of Transplant Recipients produces regular, public reports on the performance of transplant centers and organ procurement organizations. This article explains the statistical tools used to prepare these reports, with a focus on graft survival and patient survival rates of transplant centers--especially the methods used to fairly and usefully compare outcomes of centers that serve different populations. The article concludes with a practical application of these statistics--their use in screening transplant center performance to identify centers that may need remedial action by the OPTN/UNOS Membership and Professional Standards Committee.

Analytical methods and database design: implications for transplant researchers, 2005.

Understanding how transplant data are collected is crucial to understanding how the data can be used. The collection and use of Organ Procurement and Transplantation Network/Scientific Registry of Transplant Recipients (OPTN/SRTR) data continues to evolve, leading to improvements in data quality, timeliness and scope while reducing the data collection burden. Additional ascertainment of outcomes completes and validates existing data, although caveats remain for researchers. We also consider analytical issues related to cohort choice, timing of data submission, and transplant center variations in follow-up data. All of these points should be carefully considered when choosing cohorts and data sources for analysis. The second part of the article describes some of the statistical methods for outcome analysis employed by the SRTR. Issues of cohort and follow-up period selection lead into a discussion of outcome definitions, event ascertainment, censoring and covariate adjustment. We describe methods for computing unadjusted mortality rates and survival probabilities, and estimating covariate effects through regression modeling. The article concludes with a description of simulated allocation modeling, developed by the SRTR for comparing outcomes of proposed changes to national organ allocation policies.

Impact of pre-existing donor hypertension and diabetes mellitus on cadaveric renal transplant outcomes.

Hypertension (HTN) and diabetes mellitus (DM) predispose to systemic atherosclerosis with renal involvement. The prevalence of HTN and DM in cadaveric renal donors (affected donors) and the results of transplantation are unknown. We investigated these issues with national data from the US Renal Data System. A total of 4,035 transplants from affected donors were matched 1:1 with unaffected controls according to donor age and race, recipient race, and year of transplantation. Graft and patient survival were estimated. Among the 25,039 solitary renal transplantations performed between July 1, 1994, and June 30, 1997, cadaveric renal transplants from donors with HTN accounted for 15%, and donors with DM, 2%. Programs with 1-year cadaveric renal graft survival rates greater than 90% had 50% less affected donors compared with programs having 1-year cadaveric renal graft survival rates of 85% or less. Compared with donor-age-matched controls, transplants from affected donors were at minimally increased risk for primary nonfunction, delayed graft function, and acute rejection. Three-year graft survival rates were 71% in affected donor organs and 75% in controls (P = 0.001). Compared with controls, duration of HTN was an independent risk factor for graft survival (3-year graft survival rates, 75% versus 65%; relative risk = 1.36 for HTN >10 years; P < 0.001). A substantial fraction of cadaveric renal donors have preexisting HTN. Programs transplanting fewer affected donor kidneys had better than average results. Because the negative impact of donor HTN and DM on transplant outcome was of moderate degree except when the duration of donor HTN was greater than 10 years, use of affected donors should not be discouraged, but graft and patient survival analyses should account for their presence.

A practical approach to evaluate the potential donor pool and trends in cadaveric kidney donation.

BACKGROUND: The potential supply of transplantable cadaver kidneys is often expressed as donors per million population (pmp), which ignores some essential factors governing organ donation. METHODS: We performed a modeled analysis of kidney donor extraction rates by age, gender, race, cause of death, geographic region, and year in a cohort of evaluable deaths and actual cadaver donors between the ages of 1 and 65 years (1988-1993). Evaluable death was defined as an in-hospital death in patients between the ages of 1 and 65 years whose ICD-9-CM cause of death was not an obvious contraindication to kidney donation. The main outcome measures were the crude donation rate and an adjusted donor extraction rate (DER) per 1000 evaluable deaths. RESULTS: A total of 1.4x10(6) in-hospital deaths produced 300,502 evaluable deaths and 20,575 actual donors. Between 1989 and 1993, DER increased from 61.1 to 75 per 1,000 evaluable deaths. DERs were highest among the youngest age groups, declining significantly with age from 405.0 to 16.7/1,000 evaluable deaths for age groups 1-10 and 56-65 years, respectively. There was a small difference in donors pmp between blacks and whites (15 vs. 18). In contrast, DER was seven times higher in whites compared with blacks (112.5 vs. 16.5/1,000 evaluable deaths; P<0.001). The crude donation rate (per 1,000 evaluable deaths) was high for stroke (604.8) and trauma-related deaths (230.6), resulting in highly efficient donor extraction from these deaths. Region-specific DERs ranged from 49.4 to 83/1,000 evaluable deaths and differed significantly from the corresponding donors pmp. CONCLUSIONS: Estimating kidney donation relative to in-hospital evaluable deaths is a meaningful measure of organ procurement efficiency. Efforts to enhance cadaveric kidney donation should seek to understand and reduce the marked demographic and regional disparity in donor extraction rates.

Prognosis after primary renal transplant failure and the beneficial effects of repeat transplantation: multivariate analyses from the United States Renal Data System.

BACKGROUND: Survival of transplant recipients after primary renal allograft failure has not been well studied. METHODS: A cohort of 19,208 renal transplant recipients with primary allograft failure between 1985 and 1995 were followed from the date of allograft loss until death, repeat transplantation, or December 31, 1996. The mortality, wait-listing, and repeat transplantation rates were assessed. The mortality risks associated with repeat transplantation were estimated with a time-dependent survival model. RESULTS: In total, 34.5% (n=6,631) of patients died during follow-up. Of these deaths, 82.9% (n=5,498) occurred in patients not wait-listed for repeat transplantation, 11.9% (n=789) occurred in wait-listed patients, and 5.2% (n=344) occurred in second transplant recipients. Before repeat transplantation, the adjusted 5-year patient survival was 36%, 49%, and 65% for type I diabetes mellitus (DM), type II DM, and nondiabetic end-stage renal disease, respectively (P<0.001; DM vs. nondiabetics). The adjusted 5-year patient survival was lower in Caucasians (57%, P<0.001) compared with African-Americans (67%) and other races (64%). The 5-yr repeat transplantation rate was 29%, 15%, and 19%, whereas the median waiting time for a second transplant was 32, 90, and 81 months for Caucasians, African-Americans, and other races, respectively (P<0.0001 each). Repeat transplantation was associated with 45% and 23% reduction in 5-year mortality for type I DM and nondiabetic end-stage renal disease, respectively, when compared with their wait-listed dialysis counterparts with prior transplant failure. CONCLUSIONS: The loss of a primary renal allograft was associated with significant mortality, especially in recipients with type I DM. Repeat transplantation was associated with a substantial improvement in 5-year patient survival. Recipients with type I DM achieved the greatest proportional benefit from repeat transplantation.