Combined survival analysis of cardiac patients by a Cox PH model and a Markov chain.

The control and treatment of dyslipidemia is a major public health challenge, particularly for patients with coronary heart diseases. In this paper we propose a framework for survival analysis of patients who had a major cardiac event, focusing on assessment of the effect of changing LDL-cholesterol level and statins consumption on survival. This framework includes a Cox PH model and a Markov chain, and combines their results into reinforced conclusions regarding the factors that affect survival time. We prospectively studied 2,277 cardiac patients, and the results show high congruence between the Markov model and the PH model; both evidence that diabetes, history of stroke, peripheral vascular disease and smoking significantly increase hazard rate and reduce survival time. On the other hand, statin consumption is correlated with a lower hazard rate and longer survival time in both models. The role of such a framework in understanding the therapeutic behavior of patients and implementing effective secondary and primary prevention of heart diseases is discussed here.

Computerized community cholesterol control (4C): meeting the challenge of secondary prevention.

BACKGROUND: Dyslipidemia remains underdiagnosed and undertreated in patients with coronary artery disease. The Computer-based Clinical Decision Support System provides an opportunity t close these gaps. OBJECTIVES: To study the impact of computerized intervention on secondary prevention of CAD. METHODS: The CDSS was programmed to automatically detect patients with CAD and to evaluate the availability of an updated lipoprotein profile and treatment with lipid-lowering drugs. The program produced automatic computer-generated monitoring and treatment recommendations. Adjusted primary clinics were randomly assigned to intervention (n=56) or standard care arms (n=56). Reminders were mailed to the primary medical teams in the intervention arm every 4 months updating them with current lipid levels and recommendations for further treatment. Compliance and lipid levels were monitored. The study group comprised all patients with CAD who were alive at least 3 months after hospitalization. RESULTS: Follow-up was available for 7448 patients (median 19.8 months, range 6-36 months). Overall, 51.7% of patients were adequately screened, and 55.7% of patients were compliant with treatment to lower lipid level. In patients with initial low density lipoprotein >120 mg/dl, a significant decrease in LDL levels was observed in both arms, but was more pronounced in the intervention arm: 121.9 +/- 34.2 vs. 124.3 +/- 34.6 mg/dl (P < 0.02). A significantly lower rate of cardiac rehospitalizations was documented in patients who were adequately treated with lipid-lowering drugs, 37% vs. 40.9% (P < 0.001). CONCLUSIONS: This initial assessment of our data represent a real-world snapshot where physicians and CAD patients often do not adhere to clinical guidelines, presenting a major obstacle to implementing effective secondary prevention. Our automatic computerized reminders system substantially facilitates adherence to guidelines and supports wide-range implementation.

Estimation of mortality savings due to a national program for diabetes care.

BACKGROUND: Diabetes-related complications can be reduced by better control of glycemia, lipid abnormalities and blood pressure. In recent years, efforts at improving diabetes care in Israel have been made. This study aims to estimate mortality savings related to a national program for diabetes care in Israel. METHODS: Total population data for Israel was projected to 2020. Current diabetes prevalence and disease management data were obtained from a national program of diabetes care. Projections of the program's effect were based on two models: improvement in glycemic control, reflected in Hb A1c levels, and improvement in overall diabetes care, reflected in the percentage with LDL<100 mg/dl, a proxy for multi-factorial control. Potential years of life lost (PYLL) and quality-adjusted life years (QALYs) saved were calculated. RESULTS: A drop in average Hb A1c values from 8.13% at baseline to 7.36% in 2020 is expected, and as a result 4216 deaths from diabetes will be prevented over the period 2001-2020, saving around 47,773 life years or 34,342 QALYs. Overall diabetes care, reflected in improving the control rate of LDL levels to <100 mg/dl from 36% in 2000 to 58% in 2020, is estimated to prevent around 4803 deaths from diabetes over the period 2001-2020., so the program will save around 47,127 PYLL or 32,862 QALYs. CONCLUSIONS: A nationwide program of diabetes care is estimated to result in significant reductions of overall, as well as CHD-related, mortality.

A national study on lipid management.

BACKGROUND: Hyperlipidemia remains a major cause of morbidity in Western countries. The objective of this study was to document the percentage of adults who underwent periodical LDL measurement, and the percentage of patients with diabetes and post-angioplasty who were treated to goal. METHODS: Using a national database, data were obtained on the percentage of adults who had an LDL performed and the percentage of adults with an LDL at pre-specified levels. We also assessed the attainment of target LDL levels in diabetic and post-angioplasty patients. Data were also collected from patients with an acute coronary syndrome (ACS) admitted to seven hospitals within a 5 year period (2000-2004). RESULTS: Primary prevention: In 2005, 64.6% of the total population of 754,910 aged 35-44 had at least one record of LDL cholesterol measurement documented. This figure was 79.6% in the 717,617 adults aged 45-54. Secondary prevention: Of 253,233 diabetics in 2005, 220,023 (86.9%) have undergone at least one annual LDL measurement. The percentage of patients on statin therapy 3 and 12 months after an ACS admission increased significantly during the years 2000-2004 and reached 87%. Of the 42,292 patients who underwent PTCA during 2005, 34,346 (81.2%) have purchased at least 3 prescriptions of statins during 2005, 35,261 (83.4%) have performed at least one LDL measurement and 57.8% attained an LDL level of <100 mg/dl. CONCLUSIONS: We have shown an improvement in primary and secondary preventions of CV disease as documented by LDL measured and attainment of treatment goals, but further efforts are needed.

Do patients with diabetes and low socioeconomic status receive less care and have worse outcomes? A national study.

PURPOSE: The objective of the study was to assess the influence of socioeconomic status (SES) on the care of patients with diabetes. METHODS: Quality indicators for patients who were taking medication for diabetes were established. Overall compliance with the quality indicators, as well as prevalence of diabetes by age, were obtained from a national database. Patients with national tax exemptions (used as a marker for low SES) were compared to those without. RESULTS: Of 4,110,852 citizens aged 18-74, 210,988 (5.1%) were receiving medication for diabetes. The prevalence of diabetes reached 19.9% in people aged 65-74. 495,392 citizens had an exemption, and they had a higher prevalence of diabetes that those who did not (15.4% vs. 3.7%). Patients with an exemption had a higher rate of having a yearly HbA1c done, a yearly LDL level done, a yearly eye exam, a yearly urinary protein exam, of being treated with insulin for an elevated HbA1c than those without an exemption. In patients with an exemption there was a lower percentage with an HbA1c less than 7%, a higher percentage with an HbA1c greater than 9%, and a lower percentage with an LDL less than 130. Multivariate analysis showed that exemption status was a predictor of better performance on process measures (LDL test done, OR-1.03, 95% CI 1.01-1.06, HbA1c test done, OR 1.03, 95% CI- 1.01-1.05) and of worse outcomes (high LDL, OR 0.92, 95% CI, 0.90-0.95 and high HbA1c, OR, 0.85, 95% CI, 0.83-0.87). CONCLUSIONS: In a country with universal healthcare, patients from a lower SES had an increased prevalence of diabetes and had greater adherence to preventive healthcare measures However, they were less successful in meeting target treatment goals.