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עמוד בית
Thu, 21.11.24

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September 2000
Paul Froom, MD, Estela Kristal-Boneh, PhD, Samuel Melamed, PhD, Gil Harari, MSc, Jochanan Benbassat, MD and Joseph Ribak, MD, MPH

Background: The degree to which serum total cholesterol predicts cariovascular disease is uncertain. While most authors have placed TC among the most powerful risk indicators of CVD, some have claimed that it predicted CVD in women only, or even not at all.

Objective: To determine the predictive value of serum total cholesterol relative to diabetes, smoking, systolic blood pressure and body mass index (kg/m2), for cardiovascular disease mortality in 3,461 occupationally active Israeli males.

Methods: A prospective follow-up was carried out for the years 1987-1998 to determine the effect of age, smoking habits, a history of diabetes, SBP, BMI and TC, at entry, on CVD mortality.

Results: There were 84 CVD deaths during a total of 37,174 person-years follow up. The hazard ratios (95% confidence intervals) for CVD mortality with respect to variables at entry were: diabetes 5.2 (2.1-13.2), age 2.2 (1.7-2.9), smoking 1.3 (1.0-1.8), SBP 1.4 (1.1-2.0), TC 1.5 (1.0-2.1) and BMI 1.2 (0.7-2.2). Among non-obese, non-diabetic, normotensive subjects the hazard ratio of TC adjusted for age and smoking was 1.16 (1.09-1.22) per 10 mg/dl. In the remaining subjects it was 1.04 (0.98-1.12) only. There was a significant interaction between TC and diabetes, hypertension or obesity (P=0.003).

Conclusions: In this population of Israeli males we found an interaction between TC and other risk indicators for CVD. Confirmation is required for the unexpected finding that the predictive value of TC for CVD mortality among non-diabetic, non-obese and normotensive subjects exceeded that among subjects with either of these risk factors.
 

May 2000
Ziona Haklai MSc, Shimon Glick MD and Jochanan Benbassat MD

Background: The increasing utilization of general internal medicine hospital wards in Israel during the last decade is a source of concern for health policy makers.

Objectives: To report on the distribution of selected main and secondary diagnoses among GIM inpatients, and to estimate the proportion of disorders for which appropriate care in the community will reduce the need for hospital admissions and re-admissions.

Methods: Data from the Health Information and Computer Services of the Israel Ministry of Health (national hospitalization database) for a one year period were analyzed by distribution of diagnostic entities (ICD-9-CM) in GIM and in medical subspecialty wards.

Results: Of the 313,824 discharges from hospital divisions of medicine in 1995, 256,956 (81.9%) were from GIM and 56,868 (18.1%) from specialty wards. Main and secondary discharge diagnoses were available for 188,807 GIM and 35,992 specialty patients. Of all main diagnoses in GIM wards, 27% were coded as "general or systemic symptoms and signs" or as "abnormal laboratory or ill defined manifestations" (ICD-9-CM codes 780-799, 276,277), and heart diseases comprised another 27%. The remaining main diagnoses covered almost all medical conditions. The combined proportion of "ambulatory care sensitive hospital admissions" (bronchial asthma, hypertension, congestive heart failure, chronic obstructive pulmonary disease, diabetes) constituted 12% of all main diagnoses in GIM, and respiratory symptoms or signs comprised another 11%. A by-product of this analysis was an insight into the experience of undergraduate medical students in GIM.

Conclusions: Assuming that 12-75% of admissions for "ambulatory care sensitive disorders" are preventable, an improved review before hospital discharge and a closer outpatient follow-up may reduce the load on GIM wards by 1-17%. This wide range justifies controlled trials to determine the effect of improved community care on hospital utilization. GIM wards offer valuable learning opportunities, but they cannot be a substitute for primary care clinics. The unexplained high proportion of GIM inpatients who were discharged with an unspecified main diagnosis could be detrimental for the accuracy of hospitalization statistics, and justifies investigation by chart audits into physicians' habits of documentation.

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GIM= general internal medicine

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