OBJECTIVEThe objective of this study was to determine whether treatment with metformin in patients with renal impairment is associated with a higher risk of lactic acidosis or elevated lactate concentrations compared with users of a noninsulin antidiabetic drug (NIAD) who had never used metformin. RESEARCH DESIGN AND METHODSA cohort of 223,968 metformin users and 34,571 diabetic patients who had never used metformin were identified from the Clinical Practice Research Datalink (CPRD). The primary outcome was defined as either a CPRD READ code lactic acidosis or a record of a plasma lactate concentration >5 mmol/L. The associations between renal impairment, dose of metformin, and the risk of lactic acidosis or elevated lactate concentrations were determined with time-dependent Cox models and expressed as hazard ratios (HRs). RESULTSThe crude incidence of lactic acidosis or elevated lactate concentrations in current metformin users was 7.4 per 100,000 person-years (vs. 2.2 per 100,000 person-years in nonusers). Compared with nonusers, risk of lactic acidosis or elevated lactate concentrations in current metformin users was significantly associated with a renal function <60 mL/min/1.73 m 2 (adjusted HR 6.37 [95% CI 1.48-27.5]). The increased risk among patients with impaired renal function was further increased in users of ‡730 g of metformin in the preceding year (adjusted HR 11.8 [95% CI 2.27-61.5]) and in users of a recent high daily dose (>2 g) of metformin (adjusted HR 13.0 [95% CI 2.36-72.0]). CONCLUSIONSOur study is consistent with current recommendations that the renal function of metformin users should be adequately monitored and that the dose of metformin should be adjusted, if necessary, if renal function falls below 60 mL/min/1.73 m 2 .There is good evidence that metformin reduces the long-term incidence of macrovascular complications in type 2 diabetes mellitus, especially among overweight patients (1-3). In contrast to alternative oral noninsulin antidiabetic drugs (NIADs) and insulin, metformin is not associated with a risk of hypoglycemia (3-5). The most serious adverse event that has been observed during metformin use is lactic acidosis, which is
The advanced CDSS produced a higher proportion of clinically relevant medication alerts, but the number of irrelevant alerts remained high. To improve the PPV of the advanced CDSS, the algorithms should be optimized by identifying additional risk modifiers and more data should be made electronically available to improve the performance of the algorithms. Our study illustrates and corroborates the need for cyclic testing of technical improvements in information technology in circumstances representative of daily clinical practice.
Vancomycin is an important antibiotic for critically ill patients with Grampositive bacterial infections. Critically ill patients typically have severely altered pathophysiology, which leads to inefficacy or toxicity. Model-informed precision dosing may aid in optimizing the dose, but prospectively validated tools are not available for this drug in these patients. We aimed to prospectively validate a population pharmacokinetic model for purpose model-informed precision dosing of vancomycin in critically ill patients. Methods: We first performed a systematic evaluation of various models on retrospectively collected pharmacokinetic data in critically ill patients and then selected the best performing model. This model was implemented in the Insight Rx clinical decision support tool and prospectively validated in a multicentre study in critically ill patients. The predictive performance was obtained as mean prediction error and relative root mean squared error. Results: We identified 5 suitable population pharmacokinetic models. The most suitable model was carried forward to a prospective validation. We found in a prospective multicentre study that the selected model could accurately and precisely predict the vancomycin pharmacokinetics based on a previous measurement, with a mean prediction error and relative root mean squared error of respectively 8.84% (95% confidence interval 5.72-11.96%) and 19.8% (95% confidence interval 17.47-22.13%). Conclusion: Using a systematic approach, with a retrospective evaluation and prospective verification we showed the suitability of a model to predict vancomycin pharmacokinetics for purposes of model-informed precision dosing in clinical practice. The presented methodology may serve a generic approach for evaluation of pharmacometric models for the use of model-informed precision dosing in the clinic.
Objectives Depression is common in patients with diabetes, and the use of antidepressants may impair glycaemic control. We assessed the association between antidepressant use and hyper-and hypoglycaemia. Methods Based on spontaneous reports listed in the World Health Organization (WHO) Adverse Drug Reaction Database, a case-control study was conducted. The study base consisted of all adverse drug reactions (ADRs) ascribed to antidepressants, antipsychotics and benzodiazepines between 1969 and 2005. Cases were defined as reported ADRs classified as hyper-or hypoglycaemia and separated in different study populations. All other reports were considered as controls. Exposure to antidepressants was the primary determinant investigated. Benzodiazepines and antipsychotics were chosen as reference groups. Potential confounding factors, namely, age, gender, use of antidiabetic medication, use of hyper-or hypoglycaemiainducing comedication and reporting year, were determined on the index date. Multivariate logistic regression was used to evaluate the strength of the association, which was expressed as reporting odds ratios (RORs) with 95% confidence intervals (95% CI). Results Overall, the use of antidepressants was associated with hyperglycaemia [ROR 1.52 (95% CI: 1.20-1.93)] and of hypoglycaemia [ROR 1.84 (95% CI: 1.40-2.42)]. The association with hyperglycaemia was most pronounced for antidepressants with affinity for the 5-HT 2c receptor, histamine-1 receptor and norepinephrinic (NE) reuptake transporter. The association with hypoglycaemia was most pronounced for antidepressants with affinity for the serotonin reuptake transporter. Conclusion The results of this study strengthen the findings in individual case reports that the use of antidepressants is associated with disturbances in glucose homeostasis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.