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Background: Over 5 million patients in the United States have type 2 diabetes mellitus (T2D) with chronic kidney disease (CKD); antidiabetic drug selection for this population is complex and has important implications for outcomes. Objective: To better understand how providers choose antidiabetic drugs in T2D with CKD Design: Mixed methods. Interviews with providers underwent qualitative analysis using grounded theory to identify themes related to antidiabetic drug prescribing. A provider survey used vignettes and direct questions to quantitatively assess prescribers' knowledge and preferences. A retrospective cohort analysis of real-world prescribing data assessed the external validity of the interview and survey findings. Participants: Primary care physicians, endocrinologists, nurse-practitioners, and physicians' assistants were eligible for interviews; primary care physicians and endocrinologists were eligible for the survey; prescribing data were derived from adult patients with serum creatinine data. Main Measures: Interviews were qualitative; for the survey and retrospective cohort, proportion of patients receiving metformin was the primary outcome. Key Results: Interviews with 9 providers identified a theme of uncertainty about guidelines for prescribing antidiabetic drugs in patients with T2D and CKD. The survey had 105 respondents: 74 primary care providers and 31 endocrinologists. Metformin was the most common choice for patients with T2D and CKD. Compared to primary care providers, endocrinologists were less likely to prescribe metformin at levels of kidney function at which it is contraindicated and more likely to correctly answer a question about metformin's contraindications (71% versus 41%) (p <.05). Real-world data were consistent with survey findings, and further showed low rates of use of sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide 1 receptor agonists (<10%) in patients with eGFR below 60 ml/min/1.73m2. Conclusions: Providers are unsure how to treat T2D with CKD and incompletely informed as to existing guidelines. This suggests opportunities to improve care. [ABSTRACT FROM AUTHOR]

Background: Expanding our understanding of the effects of maternal medication exposure through research is a public health priority and will help inform both clinical and policy decision making, ultimately improving outcomes for pregnant women and their children. Objective: Our objective was to describe a linked-data research platform that facilitates studies of pregnancy medication exposures and policy changes on maternal and child health outcomes. Methods: Mothers receiving Medicaid benefits were probabilistically linked with newborns in the Tennessee Medicaid program (TennCare) through three distinct linkage processes. Medicaid claims data and state birth and fetal death certificate records (vital records) were used to identify and link potential mothers, deliveries, and newborn children. The linkage process started with the creation of a merged pool of potential mothers and eligible deliveries, which was linked to vital records and to children's records. In the last step, linked records from the preceding steps were combined into the final Mother–child linked records. For each data linkage step, rubrics and scoring systems for exact and partial matches and mismatches among key linkage fields were applied and used to examine the strength of the probabilistic linkages. Summary linkage yields for year 2013 are reported for illustration purposes. Results: Among the 84,253 potential deliveries, 1,761,557 eligible potential mothers, and 51,400 eligible children identified in Tennessee Medicaid records in 2013, a total of 60,265 of these records were uniquely linked to vital records, including 46,172 (77%) with linked mother–child–vital records. Among the 51,400 eligible children records identified in Tennessee Medicaid for that year, 97% (50,053) had at least one link to vital records or a mother–delivery record. In linked records, the median maternal age was 24 years, and the median gestational age was 39 weeks. About 33% of pregnant women underwent cesarean birth, and 1% of births were classified as complicated deliveries. Conclusions: Supplementing existing Medicaid claims data with birth certificate records complements administrative claims information and allows for detailed assessments of pregnancy exposures and policy changes on mother and child outcomes. [ABSTRACT FROM AUTHOR]

Metformin is the consensus first-line medication for type 2 diabetes mellitus.[1] However, metformin was until recently contraindicated in patients with even modestly elevated serum creatinine (corresponding roughly to an estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73 m SP 2 sp ) due to concerns that metformin may increase the risk of lactic acidosis in chronic kidney disease (CKD).[2] On April 8, 2016, in response to two citizen petitions summarizing evidence that metformin is safe in mild-to-moderate CKD, the Food and Drug Administration (FDA) revised the label to permit providers to initiate metformin at eGFR levels of >= 45 and continue metformin as long as eGFR remains above 30 mL/min/1.73 m [2]. Secondary analysis, restricted to patients taking non-insulin diabetes drugs, also showed a significant upward trend only in the eGFR 30-44 mL/min/1.73-m SP 2 sp group, from 34% (95% CI, 15 to 61%) to 62% (95% CI, 38 to 81%) I (P = i 0.04). Secondary analyses limited the cohort to patients taking non-insulin diabetes drugs in order to exclude patients with type 1 diabetes, for whom metformin is not indicated. [Extracted from the article]

Introduction: Valid algorithms for identification of cardiovascular (CV) deaths allow researchers to reliably assess the CV safety of medications, which is of importance to regulatory science, patient safety, and public health.Objective: The aim was to conduct a systematic review of algorithms to identify CV death in administrative health plan claims databases.Methods: We searched MEDLINE, EMBASE, and Cochrane Library for English-language studies published between January 1, 2012 and October 17, 2017. We examined references in systematic reviews to identify earlier studies. Selection included any observational study using electronic health care data to evaluate the sensitivity, specificity, positive predictive value (PPV), or negative predictive value (NPV) of algorithms for CV death (sudden cardiac death [SCD], myocardial infarction [MI]-related death, or stroke-related death) among adults aged ≥ 18 years in the United States. Data were extracted by two independent reviewers, with disagreements resolved through further discussion and consensus. The Quality Assessment of Diagnostic Accuracy Studies-2 instrument was used to assess the risk of bias.Results: Five studies (n = 4 on SCD, n = 1 on MI- and stroke-related death) were included after a review of 2053 citations. All studies reported algorithm PPVs, with incomplete reporting on other accuracy parameters. One study was at low risk of bias, three studies were at moderate risk of bias, and one study was at unclear risk of bias. Two studies identified community-occurring SCD: one identified events using International Classification of Disease, Ninth Revision (ICD-9) codes on death certificates and other criteria from medical claims (PPV = 86.8%) and the other identified events resulting in hospital presentation using first-listed ICD-9 codes on emergency department or inpatient medical claims (PPV = 92.3%). Two studies used death certificates alone to identify SCD (PPV = 27% and 32%, respectively). One study used medical claims to identify CV death (PPV = 36.4%), coronary heart disease mortality (PPV = 28.3%), and stroke mortality (PPV = 34.5%).Conclusion: Two existing algorithms based on medical claims diagnoses with or without death certificates can accurately identify SCD to support pharmacoepidemiologic studies. Developing valid algorithms identifying MI- and stroke-related death should be a research priority. PROSPERO 2017 CRD42017078745. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes patients often initiate treatment with a sulfonylurea and subsequently intensify their therapy with insulin. However, information on optimal treatment regimens for these patients is limited.Objective: To compare risk of cardiovascular disease (CVD) and hypoglycemia between sulfonylurea initiators who switch to or add insulin.Design: This was a retrospective cohort assembled using national Veterans Health Administration (VHA), Medicare, and National Death Index databases.Participants: Veterans who initiated diabetes treatment with a sulfonylurea between 2001 and 2008 and intensified their regimen with insulin were followed through 2011.Main Measures: The association between insulin versus sulfonylurea + insulin and time to CVD or hypoglycemia were evaluated using Cox proportional hazard models in a 1:1 propensity score-matched cohort. CVD included hospitalization for acute myocardial infarction or stroke, or cardiovascular mortality. Hypoglycemia included hospitalizations or emergency visits for hypoglycemia, or outpatient blood glucose measurements <60 mg/dL. Subgroups included age < 65 and ≥ 65 years and estimated glomerular filtration rate ≥ 60 and < 60 ml/min.Key Findings: There were 1646 and 3728 sulfonylurea monotherapy initiators who switched to insulin monotherapy or added insulin, respectively. The 1596 propensity score-matched patients in each group had similar baseline characteristics at insulin initiation. The rate of CVD per 1000 person-years among insulin versus sulfonylurea + insulin users were 49.3 and 56.0, respectively [hazard ratio (HR) 0.85, 95 % confidence interval (CI) 0.64, 1.12]. Rates of first and recurrent hypoglycemia events per 1000 person-years were 74.0 and 100.0 among insulin users compared to 78.9 and 116.8 among sulfonylurea plus insulin users, yielding HR (95 % CI) of 0.94 (0.76, 1.16) and 0.87 (0.69, 1.10), respectively. Subgroup analysis results were consistent with the main findings.Conclusions: Compared to sulfonylurea users who added insulin, those who switched to insulin alone had numerically lower CVD and hypoglycemia events, but these differences in risk were not statistically significant. [ABSTRACT FROM AUTHOR]