WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• The contribution of (S)-warfarin to the clinical effect of rac-warfarin is well understood. The extent to which (R)-warfarin contributes to the clinical effect of rac-warfarin is unclear. WHAT THIS STUDY ADDS• Using unequivocally pure (R)-and (S)-warfarin we have demonstrated that (R)-warfarin contributes to the hypoprothrombinaemic effect of single large doses of warfarin.• The extent of the interaction is dependent on VKORC1 genotype. AIMS1) To determine the pharmacokinetics and pharmacodynamics of (R)-and (S)-warfarin given alone and in combination and 2) to determine whether the relative potency of (R)-and (S)-warfarin is dependent on VKORC1 genotype. METHODSA three way crossover study was conducted in which 17 healthy male subjects stratified by VKORC1 1173 C>T genotype and all CYP2C9 1*/1* received (R)-warfarin 80 mg, (S)-warfarin 12.5 mg and rac-warfarin sodium 25 mg. Plasma (R)-and (S)-warfarin unbound and total concentrations and prothrombin time were determined at multiple time points to 168 h. RESULTSPharmacokinetic parameters for (R)-and (S)-warfarin were similar to the literature. (R)-warfarin 80 mg alone resulted in a mean AUCPT (0,168 h) of 3550 s h (95% CI 3220, 3880). Rac-warfarin sodium 25 mg containing (S)-warfarin 11.7 mg produced a greater effect on AUCPT (0,168 h) than (S)-warfarin 12.5 mg (mean difference 250 s.h, 95% CI 110, 380, P < 0.002) given alone. In a mixed effects model the ratio of response between (R)-and (S)-warfarin (AUCPT((R)-warfarin) : AUCPT((S)-warfarin)) was 1.21 fold higher (95% CI 1.05, 1.41, P < 0.02) in subjects of VKORC1 TT genotype compared with the CC genotype. CONCLUSIONS(R)-warfarin has a clear PD effect and contributes to the hypoprothrombinaemic effect of rac-warfarin. VKORC1 genotype is a covariate of the relative R/S potency relationship. Prediction of drug interactions with warfarin needs to consider effects on (R)-warfarin PK and VKORC1 genotype.

ObjectiveTo evaluate a holistic multidisciplinary outpatient model of care on hospital readmission, length of stay and mortality in older patients with multimorbidity following discharge from hospital.Design and ParticipantsA pilot case-control study between March 2006 and June 2009 of patients referred on discharge to a multidisciplinary, integrated outpatient model of care that includes outpatient follow-up, timely GP communication and dial-in service compared with usual care following discharge, within a metropolitan, tertiary referral, public teaching hospital. Controls were matched in a 4:1 ratio with cases for age, gender, index admission diagnosis and length of stay.Main outcome measuresNon-elective readmission rates, total readmission length of stay and overall survival.ResultsA total of 252 cases and 1008 control patients were included in the study. Despite the patients referred to the multidisciplinary model of care had slightly more comorbid conditions, significantly higher total length of hospital stay in the previous 12 months and increased prevalence of diabetes and heart failure by comparison to those who received usual care, they had significantly improved survival (adjusted hazard ratio 0.70 95% CI 0.51–0.96, p = 0.029) and no excess in the number of hospitalisations observed.ConclusionFollowing discharge from hospital, holistic multidisciplinary outpatient management is associated with improved survival in older patients with multimorbidity. The findings of this study warrant further examination in randomised and cost-effectiveness trials.

Background: The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) is poorly understood and the relationships between systemic abnormalities in metabolism and AD/AMCI pathogenesis are unclear. Objective: The aim of the study was to compare the metabolomic and proteomic signature of saliva from cognitively normal and patients diagnosed with MCI or AD, to identify specific cellular pathways altered with the progression of the disease. Methods: We analyzed 80 saliva samples from individuals with MCI or AD as well as age- and gender-matched healthy controls. Saliva proteomic and metabolomic analyses were conducted utilizing mass spectrometry methods and data combined using pathway analysis. Results: We found significant alterations in multiple cellular pathways, demonstrating that at the omics level, disease progression impacts numerous cellular processes. Multivariate statistics using SIMCA showed that partial least squares-data analysis could be used to provide separation of the three groups. Conclusion: This study found significant changes in metabolites and proteins from multiple cellular pathways in saliva. These changes were associated with AD, demonstrating that this approach might prove useful to identify new biomarkers based upon integration of multi-omics parameters.