Israel Medical Association Journal

Background: Dyslipidemia remains underdiagnosed and undertreated in patients with coronary artery disease. The Computer-based Clinical Decision Support System provides an opportunity to close these gaps.

Objectives: To study the impact of computerized intervention on secondary prevention of CAD[1].

Methods: The CDSS[2] 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 with CAD (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 recommended to lower lipid level. A significant decrease in low density lipoprotein 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.

Objective: To study the attitude of physicians to obesity by examining discharge letters of overweight patients with ischemic heart disease.

Methods: We used the HOLEM database for this analysis. The HOLEM project was designed to study the NCEP (National Cholesterol Education Program) guideline implementation among patients with IHD[1] at hospital discharge. We documented the recording of risk factors and treatment recommendations for IHD by reviewing the discharge letters of 2994 IHD patients admitted to four central hospitals in Israel between 1998 and 2000. A follow-up visit was held 6–8 weeks after discharge, at which time the diagnosis of IHD was verified, risk factor status was checked, height and weight were measured and drug treatment was reviewed.

Results: Mean body mass index was 28.3 kg/m² and 32% were obese (BMI[2] ³ 30 kg/m²). Only 39.6% of the obese patients and 65.8% of the morbidly obese patients (BMI ³ 40 kg/m²) had "obesity" noted in their discharging letters, and weight loss recommendation was written in only 15% of the obese patients' discharge letters. Acute episodes like acute myocardial infarction and unstable angina did not influence the notation of obesity, and only BMI and the number of additional risk factors were positively correlated with the notation of this risk factor.

Conclusions: Despite the importance of obesity, weight status was not noted and weight loss was not recommended in most of the discharge letters of obese IHD patients.

Objectives: To examine whether the treatment recommendations given to ischemic heart disease patients at hospital discharge are compatible with the guidelines of the Israeli Medical Societies and the U.S. National Cholesterol Education Program for coronary artery disease prevention; and to study the effects of brief educational sessions on the adherence of physicians with the guidelines.

Methods: We included consecutive IHD[1] patients admitted to four central hospitals in Israel between 1998 and 2000. The study was conducted in two phases. In phase 1, we reviewed discharge letters to document treatment recommendations given to each patient. In phase 2 we educated the practitioners by reviewing the Israeli Medical Societies and the NCEP[2] guidelines and the quality of their recommendations in phase 1, after which we reevaluated the discharge letters.

Results: The study included 2,994 patients: 627 in phase 1 and 2,367 in phase 2. Of the patients who needed cholesterol-lowering according to their low density lipoprotein levels, 37.4% were not prescribed such drugs at discharge (under-treatment group). This proportion was reduced by education to 26.6% (P < 0.001) in phase 2. Of the treated patients, 65.6% did not reach the target LDL[3] goal in phase 1 (under-dosage group) as compared to 60.2% in phase 2 (P = 0.23). In phase 2 there was an increase in the percent of patients reaching LDL levels <130 mg/day (69.3% vs. 63.8% of patients prescribed medication, P = 0.01), but the percent of patients reaching LDL levels <100 was not different in phase 2 after adjusting for age and gender (the odds ratio for reaching target LDL was 1.16, with 95% confidence interval of 0.95–1.43).

Conclusions: Physician recommendations to IHD patients discharged from hospital were suboptimal. We documented a high proportion of under-treated and under-dosage patients. Brief educational sessions have a beneficial effect on the usage of statins; however, additional effort in guideline implementations is needed.

Background: Previous studies have suggested that prolactin may serve as an indicator of disease progression in breast cancer.

Objectives: To evaluate the use of PRL as a serum tumor marker in patients with breast cancer.

Methods: PRL serum level was determined in 99 breast cancer patients and compared with CA 15-3 serum level.

Results: Elevated serum level of PRL (>20 ng/ml) was found in 8 of 99 patients (8.1%). A stratified analysis of prolactin levels according to therapy revealed that PRL levels was increased in 8 of 55 untreated patients (14.5%), but not in patients who received hormonal or chemotherapy in the 3 months preceding the test (0/42 patients, P=0.009). However, mean PRL level was similar in patients with no evidence of disease activity and in patients with active disease (10.2 vs. 8.2 ng/ml, NS). In comparison, CA 15-3 mean level was significantly lower in patients with no evidence of disease as compared to patients with active disease (18.2 vs. 144.7 units/ml, P<0.001). PRL level was increased in 6 of 60 patients (10%) with no evidence of disease and in 2 of 39 (5.2%) with active disease (NS). In comparison, CA 15-3 level was increased in 3 of 60 patients (5%) with no evidence of disease and in 24 of 39 (61.5%) with active disease (P<0.001).

Conclusions: PRL levels are decreased following hormonal or chemotherapy in patients with breast cancer and there is no correlation between PRL serum level and the state of disease. Further studies are needed to clarify a possible clinical significance of hyperprolactinemia in a subset of patients with breast cancer.

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PRL = prolactin