This meta-analysis provides strongest evidence supporting that Type 2 diabetes is significantly inversely associated with risk of developing prostate cancer.

Background. Hypertension management is of a paramount importance in diabetic patients for cardiovascular risk reduction. Aim. To evaluate prescribing pattern of antihypertensive in T2DM (type 2 diabetes) patients and compare with existing recent guidelines. Methods. A cross-sectional study involving evaluation of all T2DM patients referred to endocrinology unit at tertiary care centre for hypertension, comorbid complications, and recording prescription. Utilization of 5 different antihypertensive drug classes was compared for all patients receiving 1, 2, 3, 4, or more drugs. Logistical regression was used to assess likelihood of prescription of drugs and/or therapy for specific conditions mentioned in the guidelines. Results. Out of 1358, T2DM enrolled patients 1186 (87%) had hypertension (males 52%, females 48%). The median duration (IQ) of hypertension diabetics was 4 (1–10) years. A total of 25% patients had controlled BP and 75% with uncontrolled blood pressure (13% isolated systolic hypertension, 6% isolated diastolic hypertension, and 55% both elevated). Overall, ACE inhibitors (ACEIs) were prescribed the highest (59%) followed by angiotensin receptor blockers (ARBs) (52%), calcium channel blockers (CCBs) (29%), diuretics (27%), and beta-blockers (14%). Overall, 55% of T2DM patients were on polytherapy, 41% on monotherapy, and 4% had no antihypertensive treatment. Polytherapy was more predominant with age, duration of diabetes, duration of hypertension, and comorbid complications. Conclusion. Although prescribing pattern of antihypertensive showed adherence to existing evidence-based guidelines, higher proportion of uncontrolled hypertensive patients was found.

BackgroundTo prevent medication errors in prescribing, one needs to know their types and relative occurrence. Such errors are a great cause of concern as they have the potential to cause patient harm. The aim of this study was to determine the nature and types of medication prescribing errors in an Indian setting.MethodsThe medication errors were analyzed in a prospective observational study conducted in 3 medical wards of a public teaching hospital in India. The medication errors were analyzed by means of Micromedex Drug-Reax database.ResultsOut of 312 patients, only 304 were included in the study. Of the 304 cases, 103 (34%) cases had at least one error. The total number of errors found was 157. The drug-drug interactions were the most frequently (68.2%) occurring type of error, which was followed by incorrect dosing interval (12%) and dosing errors (9.5%). The medication classes involved most were antimicrobial agents (29.4%), cardiovascular agents (15.4%), GI agents (8.6%) and CNS agents (8.2%). The moderate errors contributed maximum (61.8%) to the total errors when compared to the major (25.5%) and minor (12.7%) errors. The results showed that the number of errors increases with age and number of medicines prescribed.ConclusionThe results point to the establishment of medication error reporting at each hospital and to share the data with other hospitals. The role of clinical pharmacist in this situation appears to be a strong intervention; and the clinical pharmacist, initially, could confine to identification of the medication errors.

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Lipohypertrophy has been suggested as an outcome of lipogenic action of insulin and/or injection-related tissue trauma. In a cross-sectional study, we evaluated the predictors of lipohypertrophy in 372 type 1 diabetes patients (mean age 17.1 years) receiving subcutaneous insulin with pen and/or syringes for ≥3 months. On examining injection sites with inspection and palpation technique, 62.1% patients demonstrated lipohypertrophy. Univariate analysis showed that gender, BMI, HbA1c, injection device, rotation, injection area, needle length, insulin regimen, and total daily dose of insulin were associated with lipohypertrophy (p < 0.05). Notably, the mean needle reuse was comparable in patients with or without lipohypertrophy (8.1 vs. 7.2, p = 0.534). In multivariate logistic regression, gender, HbA1c, TDD, injection devices, and needle length lost its significance. Further, injections over smaller area (≤8.5 × 5.5 cm) and non-rotation of sites were found to be strongest independent predictor of lipohypertrophy (p < 0.0005 for both) with increased odds of 23.2 (95% CI 9.1–59.2) and 6.3 (95% CI 3.4–11.9) times, respectively. Being underweight was also a significant independent predictor (odds ratio [OR] 13.0 [95% CI 2.2–75.2], p = 0.004). Compared to rapid plus long-acting analogs, regular insulin plus long-acting analogs and conventional premixed insulin users had 3.2 (95% CI 1.5–6.8, p = 0.003) and 4.6 (95% CI 1.4–15.7, p = 0.014) fold higher risk of lipohypertrophy (mean injection frequency 4.01 vs. 4.01 vs. 2.09, respectively). Sub-group analysis showed that lipohypertrophy was 79% less likely in patients with multiple daily injections (≥4) than twice-daily regimen (OR 0.21, p < 0.0005). Moreover, lipohypertrophy was reduced to half with bolus doses of rapid-acting insulin analogs than regular insulin (p = 0.003), even though mean injection frequency was comparable (4.01 vs. 3.93, p = 0.229). This difference was statistically insignificant for basal doses with NPH or long-acting analogs (p = 0.069). Therefore, injection area, rotation, BMI, and insulin regimen are the best predictors of lipohypertrophy and together could correctly identify lipohypertrophy status in 84.4% patients with excellent discrimination capability (AUC = 0.906, p < 0.0005). In conclusion, findings of our study suggest that delivering rapidly absorbed insulin analogs over large injection area along with greater split of total daily doses reduce insulin-induced lipogenesis and outplay tissue trauma added through frequent injections and needle reuse.

The results show that PIM prescribing is common among hospitalized elderly Indian patients. It is feasible to reduce this practice through the provision of appropriate unbiased information to healthcare professionals.

*Background: In view of the multiple co-morbidities, the elderly patients receiving drugs are prone to suffer with drug interactions since they receive a greater number of drugs. Objective: The study was undertaken to determine the prevalence of drug interactions, as well as their predictors. Method: The prescriptions of a total of 1510 inpatients were collected prospectively for 1.5 years from inpatients wards of public tertiary care teaching hospital. All the prescriptions were checked for drug interactions using the Micromedex® Drug-Reax database-2010 and Stockley's Drug Interactions. Regression analyses sought to determine predictors for the drug interaction. Results: The patients, with the average age of 67.2 ±0.2 years, were prescribed an average of 9.15 ±0.03 medications. It was found that out of 1510 prescriptions of inpatients, 126 (8.3%) prescriptions had one or more than one drug interaction. All the identified interactions were severe in nature. The top most interacting drugs were acetylsalicylic acid and anticoagulant (n=59). The second top most interacting drug combination was clopidogrel and proton pump inhibitors (n=51). The most commonly involved drugs in interactions were C (cardiovascular system) and A (alimentary tract and metabolism). Using multivariate binary logistic regression, multiple drugs (Odds Ratio=4.5; 95% Confidence Interval: -2.38 -9.47) and multiple diagnoses (Odds Ratio=2.6; were found to be significant predictors for drug interaction. Conclusion:The results of this study substantiate the occurrence of severe drug interactions among Indian elderly inpatients. In order to provide safer pharmaceutical care, the active involvement of clinical pharmacists is a potential option.

Reimbursement, patient's dialysis status, habits, and comorbidities were found to have a significant effect on the direct cost of treatment.