JIACM 2013; 14(3-4): 247-52 Vitamin D deficiency: A new risk factor for cardiovascular disease Biswajit Das*, Trinath Kumar Mishra**, Satya Narayan Routray**, Chhabi Satpathy*, Hrudananda Mishra*** Vitamin D deficiency is emerging as a new risk factor for various cardio-vascular diseases (CVDs), specifically atherosclerotic vasculardisease. A number of epidemiological studies have shown that vitamin D deficiency is prevalent among many populations cuttingacross all ethnicities and among all age groups. With the growing menace of the epidemic of CAD, emergence of another commonlyprevalent risk factor for the same is a matter of concern. Although the link between vitamin D deficiency and CAD has beenconsistently proven, interventional trials with supplementation of vitamin D or calcium have been disappointing in terms of riskreduction. Further research in this direction is underway and is likely to improve our understanding, and open up newer avenuesfor reducing the risk of CAD.
Microsoft powerpoint - peter rose.ppsComputerised anticoagulation The historical perspective of monitoring vitamin K antagonists Australia - Human Brain (low ISI) Canada - Rabbit (high ISI) Hong Kong - Human Brain (low ISI) South Africa - Human Brain (low ISI) Sweden - Rabbit (high ISI) U.K - Human Brain (low ISI) Zimbabwe - Rabbit (high ISI) USA - Rabbit (high ISI) 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 Mean Warfarin dose in different geographical locations Poller L, Taberner DA, 1982: BJ Haem 51:479-485 Therapeutic Quality Assurance How to measure therapeutic quality control of treatment with vitamin K 1.Percentage of results in range one standard deviation from mean 3.Percentage time in range ‘Surrogate Markers' Therapeutic quality assurance evidence based / individualised risk Therapeutic Quality Control Do publications give evidence of adequate therapeutic quality control? • Evidence of adequate anticoagulation • Evidence of inadequate anticoagulation in first 10 days • % time spent in range • Adverse events • Thromboplastin reagent / ISI value Effectiveness of CDSS Single centre data HillingdonN= 260 patientsAfter 16 months follow-up Computer assisted warfarin therapy is at least as good as those achieved manually Wilson R, et al, BM J 1984 Coventry688 Patients' visits over 8 months period showed38% improvement in achievement of therapeuticrange as compared to historical control Ryan PJ, et al. BMJ. 1989 Five centres using computer assisted dosage showing improvement in percentage of patients with in BCSH target over time P Rose, J Clin Pathol, 1996 Single centre randomised study Vadher, B. Et al. BMJ 1997 N=148 (Computer:72 Control: 76)both inpatient & outpatient warfarin therapy Median time to achieve a stable dose for computer group was significantly lower (7 days v 9 days, P = 0.01) TTR in computer group greater both as inpatients (59% v 52%) & outpatients (64% v 51%) CDSS is safe and effective and improves the quality of initiation and control of warfarin treatment Randomised trials • Poller, et al, 1998 Lancet 5 European centres Dawn AC version 4.07 Induction module/ Maintenance module n=285 (Computer= 137; traditional= 148) Computer significantly better ( mean TTR 63.3% vs 53.2% p=0.004) better INR control in stable warfanised patients Italian randomised trial • Manotti C, et al. Haematologica. 2001 335 patients in stabilization phase 916 patients in maintenance phase Computer assisted dosing group achieved stable state significantly faster (p<0.01) spent more TTR during maintenance (p<0.001) than controls. Cumulative percentage of patients reaching a stable state in first three months of anticoagulation with computer algorithm and manual decision-making Percentage of time spent in the scheduled therapeutic range External quality assurance • Lack of validation different software packages • No system like MHRA • No comparison for warfarin dosing and period of recall between different software packages • ? NEQAS to address • Limited information on validation of software in both secondary and primary care settings • Validation for both initiation and maintenance warfarin dosing • Validation of warfarin dosing for different indications ( eg. Mechanical heart valves) Systems currently in UK The Future of Anticoagulation Secondary care clinics have become overloaded.
Therefore there has been a shift of from secondary into primary care • A better local service is provided to the patient • More time freed up for secondary care Anticoagulation Service Models in Use Venous sample / Near-patient testing (NPT) with A point of care testing system nurse-led practice clinic NPT with a point of care testing system hospital outreach teams pharmacy (chemist) Patient self- testing / monitoringWith a point of care testing system Models of Service Delivery in 1.Dosing by stand alone CDSS in surgery 2.Dosing via connection to central CDSS CDSS in primary care Randomised in 12 practices in Birmingham, England N=367(Intervention:122; Control Intrapractise : 102; Interpractise:143) BAP-PC software package for Computer assisted warfarin dosing TTR significantly better for computer group (p=0.008) Fitzmaurice DA, et al. Arch Intern Med. 2000 External quality assessment for warfarin dosing using Computerised decision Oppenkowski, TP et al. J Clin Pathol 2003 10 primary care centres using BAP-PC TTR : 69% (range: 60–76%) CDSS Dosing in Practice connected to central CDSS % time in therapeutic range Pathophysiol Haemost Thromb 2003/2004;33:366-371 Computerised Decision Support Systems and Costs Saving Variable costs (labour) Savings per patient **with Network Interface to ELECTRA, Main & Reception Modules Comparison between cost management of traditional prescription and computerised system (using P.A.R.M.A. system web strategy) Pathophysiol Haemost Thromb 2003/2004;33:366-371 Future perspectives • Ethnic and individual variability in warfarin dose is secondary to vitamin K epoxide reductase complex 1 (VKORC1) and Cytochrome P-450 2C9 gene polymorphisms • Dosing algorithm incorporating age, CYP2C9 and VKORC1 genotype, and height have been shown to lead to the best estimation of warfarin maintenance dose Sconce EA, et al. Blood. 2005 • Artificial neural networks incorporating these new variables might better predict warfarin dose • Changes in commissioning of anticoagulation service might necessitate widespread use of validated CDSS with proper external quality assurance assessment Artificial neural network • Artificial neural networks are algorithms for performing non-linear statistical modelling • Neural networks can predict the maintenance dose of warfarin prediction similar to linear regression model (r=0.823 vs. 0.80) Solomon I, et al. Isr Med Assoc J 2004 Anticoagulation Monitoring with a Point of Care Testing Device • Near-patient testing – INR estimation by healthcare professionals (in primary or secondary care) using a point of care testing device • Patient self-testing – INR estimation - dosage advice • Patient self-management – INR estimation and dosage management, IQC and EQA and general maintenance of equipment etc Telemanagement of Oral Data collection module Presentation module Presentation module Communication module Communication module Results of HAT Study • 93% of 29 patients trained in laboratory setting would use system at home • Improved quality of life dimensions • Improved client satisfaction Finkelstein J. AMIA Annu Symp Proc. 2003: 230-234 Design of Anticoagulation HAT • Individual treatment plans • Feedback to motivate patients • Notifies Clinicians of violations • Multi-media patient education • Prompting system for bleeding problems with high INR results • Facility to record bleeding/ thrombotic • Facility to assess thrombotic risk• Record results of thrombophilia screen• Identification of poorly controlled • Dosage recommendations according to validated algorithm • Evaluation of recommendation over full range of INR results • Patient recall to agreed criteria based on previous stability • Facility to over-ride computer • Alerting systems for discontinuation of • Flagging system for results outside • Flagging system for non-attendees• Generation of letters, lists• Ability to change clinic appointments• Database of drug interactions• Accessible data format for analysis and CDSS Conclusion in Secondary • Better than experienced Clinician • Enables nurse, pharmacy, MLSO led • Enables postal dosing CDSS in Primary Care • Enables regular review of risk / benefits of continuing anticoagulant therapy • Results not lost in post • Helps avoid hospital car parks • CDSS in secondary care improves management and enables Trust to cope with increasing large volume of patients • CDSS in Primary Care set to increase in line with ‘NICE commissioning' of Anticoagulant Services • CDSS patient self management • Not for average Villa / Brum City Supporter • only for the most ‘unusual' patients • Identification of risk of underlying • Predictive model to identify patients at minimal risk of malignancy Paneesha, S et al Poster, ASH 2006
Reishi or Ling Zhi (Ganoderma lucidum) Solomon P. WasserInstitute of Evolution, University of Haifa, Mount Carmel, Haifa, Israel and locust (Quercus, Acer, Alnus, Betula, Castanea,Coryolus, Fagus, Fraxinus, Populus, Pyrus, Magnolia, Ganoderma lucidum (reishi mushroom, Ling Zhi) has Tilia). G. lucidum is less frequently found on conifer- been an economically important species, particularly