Impact of Donor and Recipient Cytokine Genotypes on Renal Allograft Outcome

Allelic differences in gene promoter or codifying regions have been described to affect regulation of gene expression, consequently increasing or decreasing cytokine production and signal transduction responses to a given stimulus. This observation has been reported for interleukin (IL)-10 (-1082 A/G; -819/-592 CT/CA), transforming growth factor (TGF)-beta (codon 10 C/T, codon 25 G/C), tumor necrosis factor (TNF)-alpha (-308 G/A), TNF-beta (+252 A/G), interferon (IFN)-gamma (+874 T/A), IL-6 (-174 G/C), and IL-4R alpha (+1902 G/A). To evaluate the influence of these cytokine genotypes on the development of acute or chronic rejection, we correlated the genotypes of both kidney graft recipients and cadaver donors with the clinical outcome. Kidney recipients had 5 years follow-up, at least 2 HLA-DRB compatibilities, and a maximum of 25% anti-HLA pretransplantation sensitization. The clinical outcomes were grouped as follows: stable functioning graft (NR, n = 35); acute rejection episodes (AR, n = 31); and chronic rejection (CR, n = 31). The cytokine genotype polymorphisms were defined using PCR-SSP typing. A statistical analysis showed a significant prevalence of recipient IL-10 -819/-592 genotype among CR individuals; whereas among donors, the TGF-beta codon 10 CT genotype was significantly associated with the AR cohort and the IL-6 -174 CC genotype with CR. Other albeit not significant observations included a strong predisposition of recipient TGF-beta codon 10 CT genotype with CR, and TNF-beta 252 AA with AR. A low frequency of TNF-alpha -308 AA genotype also was observed among recipients and donors who showed poor allograft outcomes.

Mortality after Discharge from Intensive Care: the Impact of Organ System Failure and Nursing Workload Use at Discharge

OBJECTIVES: Mortality after ICU discharge accounts for approx. 20-30% of deaths. We examined whether post-ICU discharge mortality is associated with the presence and severity of organ dysfunction/failure just before ICU discharge. PATIENTS AND METHODS: The study used the database of the EURICUS-II study, with a total of 4,621 patients, including 2,958 discharged alive to the general wards (post-ICU mortality 8.6%). Over a 4-month period we collected clinical and demographic characteristics, including the Simplified Acute Physiology Score (SAPS II), Nine Equivalents of Nursing Manpower Use Score, and Sequential Organ Failure Assessment (SOFA) score. RESULTS: Those who died in the hospital after ICU discharge had a higher SAPS II score, were more frequently nonoperative, admitted from the ward, and had stayed longer in the ICU. Their degree of organ dysfunction/failure was higher (admission, maximum, and delta SOFA scores). They required more nursing workload resources while in the ICU. Both the amount of organ dysfunction/failure (especially cardiovascular, neurological, renal, and respiratory) and the amount of nursing workload that they required on the day before discharge were higher. The presence of residual CNS and renal dysfunction/failure were especially prognostic factors at ICU discharge. Multivariate analysis showed only predischarge organ dysfunction/failure to be important; thus the increased use of nursing workload resources before discharge probably reflects only the underlying organ dysfunction/failure. CONCLUSIONS: It is better to delay the discharge of a patient with organ dysfunction/failure from the ICU, unless adequate monitoring and therapeutic resources are available in the ward.

Health-Related Quality of Life Impact of a Triple Combination of Olmesartan Medoxomil, Amlodipine Besylate and Hydrochlorotiazide in Subjects with Hypertension

BACKGROUND: A post-hoc analysis was performed on the data from a 54 weeks phase III study (ClinicalTrials.gov identifier: NCT00923091) to measure changes in the health-related quality of life (HRQoL) of 2,690 patients aged ≥18 with moderate-to-severe hypertension who received one of six doses of olmesartan/amlodipine/hydrochlorothiazide (OLM/AML/HCTZ), using the MINICHAL and EQ-5D instruments. METHODS: Descriptive statistics were used to assess blood pressure and HRQoL scores over the study period. Analysis of covariance (ANCOVA) was used to identify those factors that could possibly have influenced HRQoL. Linear regression was used to assess the relationship between changes in blood pressure and HRQoL scores. RESULTS: Patients' baseline MINICHAL mood and somatic domains scores were 5.5 and 2.6. Over the study period HRQoL improved as both MINICHAL scores decreased by 31-33%. Patients' baseline EQ-5D index and VAS scores were 0.9 and 73.4 respectively, increasing by 6% and 12% over the study period. Patients' QALY gain over the 54 weeks study period was estimated to be 0.029 QALYs. The ANCOVA showed that changes in patients' HRQoL was likely to have been influenced by patients' achievement of blood pressure control, the amount of concomitant medication and patients' last used dosage strength of antihypertensive. Linear regression showed that blood pressure improvement may have been associated with improved HRQoL. CONCLUSIONS: This study showed that OLM/AML/HCTZ reduced blood pressure and significantly increased blood pressure control whilst improving patients' HRQoL. Achieving blood pressure control, amount of concomitant medication and dosage strength of antihypertensive impacted on patients' HRQoL.