Aims/hypothesis: The aim of this study was to obtain epidemiological data on self-monitoring of blood glucose (SMBG) in type 2 diabetes and to investigate the relationship of SMBG with disease-related morbidity and mortality. Methods: The German multicentre Retrolective Study 'Self-monitoring of Blood Glucose and Outcome in Patients with Type 2 Diabetes' (ROSSO) followed 3,268 patients from diagnosis of type 2 diabetes between 1995 and 1999 until the end of 2003. Endpoints were diabetesrelated morbidity (non-fatal myocardial infarction, stroke, foot amputation, blindness or haemodialysis) and all-cause mortality. SMBG was defined as self-measurement of blood glucose for at least 1 year. Results: During a mean followup period of 6.5 years, 1,479 patients (45.3%) began SMBG prior to an endpoint and an additional 64 patients started SMBG after a non-fatal endpoint. Interestingly, many patients used SMBG while being treated with diet or oral hypoglycaemic drugs (808 of 2,515, 32%). At baseline, the SMBG cohort had higher mean fasting blood glucose levels than the non-SMBG cohort (p<0.001), suggesting that insufficient metabolic control was one reason for initiating SMBG. This was associated with a higher rate of microvascular endpoints. However, the total rate of nonfatal events, micro-and macrovascular, was lower in the SMBG group than in the non-SMBG group (7.2 vs 10.4%, p=0.002). A similar difference was found for the rate of fatal events (2.7 vs 4.6%, p=0.004). Cox regression analysis identified SMBG as an independent predictor of morbidity and mortality, with adjusted hazard ratios of 0.68 (95% CI 0.51-0.91, p=0.009) and 0.49 (95% CI 0.31-0.78, p=0.003), respectively. A better outcome for both endpoints was also observed in the SMBG cohort when only those patients who were not receiving insulin were analysed. Conclusions/interpretation: SMBG was associated with decreased diabetes-related morbidity and all-cause mortality in type 2 diabetes, and this association remained in a subgroup of patients who were not receiving insulin therapy. SMBG may be associated with a healthier lifestyle and/or better disease management.

Anthranoid-containing laxatives -aloe, cascara, franguda, and rheum -may play a role in colorectal cancer. This risk is particularly important in view of the wide abuse of self administered laxatives for chronic constipation. There are data on the genotoxic potential of anthranoids and there is evidence of a tumourigenic potential in rodents. A case report and cfinical-epidemiological studies have evaluated the cancer risk in patients who have abused anthranoid laxatives over a long period. Pseudomelanosis coli is a reliable parameter of chronic laxative abuse (>9-12 months) and is specific for anthranoid drugs. In a retrospective study of 3049 patients who underwent diagnostic colorectal endoscopy the incidence of pseudomelanosis coli was 3-13% in patients without pathological changes. In those with colorectal adenomas, the incidence increased to 8-64% (p<001), and in those with colorectal carcinomas it was 3*29%. This lower rate was probably caused by incomplete documentation of pseudomelanosis coli in those with carcinoma. In a prospective study of 1095 patients, the incidence of pseudomelanosis coli was 6-9% for patients with no abnormality seen on endoscopy, 9*8% (p=0.068) for patients with adenomas, and 18-6% for patients with colorectal carcinomas. From these data a relative risk of 3*04 (1.18, 4 90; 95% confidence interval) can be calculated for colorectal cancer as a result of anthranoid laxative abuse.

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The effect of heart rate on Doppler measurements of the resistive index (RI) in renal arteries was studied in eight patients by varying paced heart rate to eliminate intrinsic and extrinsic factors influencing renal vascular resistance. A Doppler spectrum was obtained in renal segmental arteries. The RI was calculated at increasing heart rates from 70 to 120 beats per minute. There was a statistically significant decrease in RI with increasing heart rate (heart rate of 70: RI = 0.7 +/- 0.06; heart rate of 120: RI = 0.57 +/- 0.06; P less than .001), while blood pressure and cardiac output remained constant. To overcome this source of variance, the observed RI can be corrected for heart rate by using the following regression equation. For a heart rate of 80 beats per minute, corrected RI = observed RI - 0.0026(80 - observed heart rate). In interpreting the RI in renal allograft examinations, the actual heart rate of a patient must be taken into account. However, the clinical significance of standardizing the RI for heart rate requires further investigation.