To describe trends in benzodiazepine prescriptions and overdose mortality involving benzodiazepines among US adults.
We examined data from the Medical Expenditure Panel Survey and ...multiple-cause-of-death data from the Centers for Disease Control and Prevention.
Between 1996 and 2013, the percentage of adults filling a benzodiazepine prescription increased from 4.1% (95% confidence interval CI = 3.8%, 4.5%) to 5.6% (95% CI = 5.2%, 6.1%), with an annual percent change of 2.5% (95% CI = 2.1%, 3.0%). The quantity of benzodiazepines filled increased from 1.1 (95% CI = 0.9, 1.2) to 3.6 (95% CI = 3.0, 4.2) kilogram lorazepam equivalents per 100 000 adults (annual percent change = 9.0%; 95% CI = 7.6%, 10.3%). The overdose death rate increased from 0.58 (95% CI = 0.55, 0.62) to 3.07 (95% CI = 2.99, 3.14) per 100 000 adults, with a plateau seen after 2010.
Benzodiazepine prescriptions and overdose mortality have increased considerably. Fatal overdoses involving benzodiazepines have plateaued overall; however, no evidence of decreases was found in any group. Interventions to reduce the use of benzodiazepines or improve their safety are needed.
: Pharmacoepidemiology is the study of the use and effects of medications in populations. Large health care databases are often used to address research questions within pharmacoepidemiology. This ...paper briefly describes the kinds of research questions that can be addressed using pharmacoepidemiology databases, provides an overview of pharmacoepidemiologic databases, describes some differences between medical records and administrative databases, discusses factors that should be considered when choosing a database for a particular study, and considers what the future holds.
Abstract Background Stages of activity limitation based on activities of daily living (ADLs) and instrumental activities of daily living (IADLs) have been found to predict mortality in persons aged ...70 years and older but have not been examined in Medicare beneficiaries aged 65 years and older using data that are routinely collected. Objective To examine the association between functional stages based on items of ADLs and IADLs with 3-year mortality in Medicare beneficiaries aged 65 years and older, accounting for baseline sociodemographics, health status, smoking, subjective health, and psychological well-being. Design A cohort study using the Medicare Current Beneficiary Survey (MCBS) and associated health care utilization data. Setting Community administered survey. Participants The study included 9698 Medicare beneficiaries aged 65 years and older who participated in the MCBS in 2005-2007. Main Outcome Measures Death within 3 years of cohort entry. Results The overall mortality rate was 3.6 per 100 person years, and 3-year cumulative mortality was 10.3%. Unadjusted 3-year mortality was monotonically associated with both ADL stage and IADL stage. Adjusted 3-year mortality was associated with ADL and IADL stages, except that in some models the hazard ratio for stage III (which includes persons with atypical activity limitation patterns) was numerically lower than that for stage II. Conclusion We found nearly monotonic relationships between ADL and IADL stage and adjusted 3-year mortality. These findings could aid in the development of population health approaches and metrics for evaluating the success of alternative economic, social, or health policies on the longevity of older adults with activity limitations.
Abstract
Objective
We address a first step toward using social media data to supplement current efforts in monitoring population-level medication nonadherence: detecting changes to medication ...treatment. Medication treatment changes, like changes to dosage or to frequency of intake, that are not overseen by physicians are, by that, nonadherence to medication. Despite the consequences, including worsening health conditions or death, 50% of patients are estimated to not take medications as indicated. Current methods to identify nonadherence have major limitations. Direct observation may be intrusive or expensive, and indirect observation through patient surveys relies heavily on patients’ memory and candor. Using social media data in these studies may address these limitations.
Methods
We annotated 9830 tweets mentioning medications and trained a convolutional neural network (CNN) to find mentions of medication treatment changes, regardless of whether the change was recommended by a physician. We used active and transfer learning from 12 972 reviews we annotated from WebMD to address the class imbalance of our Twitter corpus. To validate our CNN and explore future directions, we annotated 1956 positive tweets as to whether they reflect nonadherence and categorized the reasons given.
Results
Our CNN achieved 0.50 F1-score on this new corpus. The manual analysis of positive tweets revealed that nonadherence is evident in a subset with 9 categories of reasons for nonadherence.
Conclusion
We showed that social media users publicly discuss medication treatment changes and may explain their reasons including when it constitutes nonadherence. This approach may be useful to supplement current efforts in adherence monitoring.
Recent genetic data can offer important insights into the roles of lipoprotein subfractions and particle sizes in preventing coronary artery disease (CAD), as previous observational studies have ...often reported conflicting results. We used the LD score regression to estimate the genetic correlation of 77 subfraction traits with traditional lipid profile and identified 27 traits that may represent distinct genetic mechanisms. We then used Mendelian randomization (MR) to estimate the causal effect of these traits on the risk of CAD. In univariable MR, the concentration and content of medium high-density lipoprotein (HDL) particles showed a protective effect against CAD. The effect was not attenuated in multivariable analyses. Multivariable MR analyses also found that small HDL particles and smaller mean HDL particle diameter may have a protective effect. We identified four genetic markers for HDL particle size and CAD. Further investigations are needed to fully understand the role of HDL particle size.
Background & Aims:
Endogenous hyperinsulinemia in the context of type 2 diabetes mellitus is potentially associated with an increased risk of colorectal cancer. We aimed to determine whether insulin ...therapy might increase the risk of colorectal cancer among type 2 diabetes mellitus patients.
Methods:
We conducted a retrospective cohort study among all patients with a diagnosis of type 2 diabetes mellitus in the General Practice Research Database from the United Kingdom. We excluded patients with <3 years of colorectal cancer-free database follow-up after the diabetes diagnosis as well as those insulin users who developed colorectal cancer after <1 year of insulin therapy. The remaining insulin users and the noninsulin-using type 2 diabetic patients were followed for the occurrence of colorectal cancer. Hazard ratios (HR) were determined in Cox proportional hazard analysis. A nested case-control study was conducted to perform multivariable analysis and to determine a duration-response effect.
Results:
The incidence of colorectal cancer in insulin users (n = 3160) was 197 per 100,000 person-years, compared with 124 per 100,000 person-years in type 2 diabetes mellitus patients not receiving insulin (n = 21,758). The age- and sex-adjusted HR of colorectal cancer associated with ≥1 year of insulin use was 2.1 (95% CI: 1.2–3.4,
P = 0.005). The positive association strengthened after adjusting for potential confounders. The multivariable odds ratio associated with each incremental year of insulin therapy was 1.21 (95% CI: 1.03–1.42,
P = 0.02).
Conclusions:
Chronic insulin therapy significantly increases the risk of colorectal cancer among type 2 diabetes mellitus patients.
Drug‐drug interactions (DDIs) with oral anticoagulants may lead to under‐anticoagulation and increased risk of thromboembolism. Although warfarin is susceptible to numerous DDIs, few studies have ...examined DDIs resulting in thromboembolism or those involving direct‐acting oral anticoagulants (DOACs). We aimed to identify medications that increase the rate of hospitalization for thromboembolic events when taken concomitantly with oral anticoagulants. We conducted a high‐throughput pharmacoepidemiologic screening study using Optum Clinformatics Data Mart, 2000–2016. We performed self‐controlled case series studies among adult users of oral anticoagulants (warfarin, dabigatran, rivaroxaban, apixaban, and edoxaban) with at least one hospitalization for a thromboembolic event. Among eligible patients, we identified all oral medications frequently co‐prescribed with oral anticoagulants as potential interacting precipitants. Conditional Poisson regression was used to estimate rate ratios comparing precipitant exposed vs. unexposed time for each anticoagulant‐precipitant pair. To minimize within‐person confounding by indication for the precipitant, we used pravastatin as a negative control object drug. Multiple estimation was adjusted using semi‐Bayes shrinkage. We screened 1,622 oral anticoagulant‐precipitant drug pairs and identified 226 (14%) drug pairs associated with statistically significantly elevated risk of thromboembolism. Using pravastatin as the negative control object drug, this list was reduced to 69 potential DDI signals for thromboembolism, 33 (48%) of which were not documented in the DDI knowledge databases Lexicomp and/or Micromedex. There were more DDI signals associated with warfarin than DOACs. This study reproduced several previously documented oral anticoagulant DDIs and identified potential DDI signals that deserve to be examined in future etiologic studies.
Bleeding is the most common and worrisome adverse effect of warfarin therapy. One of the factors that might increase bleeding risk is initiation of interacting drugs that potentiate warfarin. We ...sought to evaluate whether initiation of an antidepressant increases the risk of hospitalization for gastrointestinal bleeding in warfarin users.
Medicaid claims data (1999-2005) were used to perform an observational case-control study nested within person-time exposed to warfarin in those ≥18 years. In total, 430,455 warfarin users contributed 407,370 person-years of warfarin use. The incidence rate of hospitalization for GI bleeding among warfarin users was 4.48 per 100 person-years (95% CI, 4.42-4.55). Each gastrointestinal bleeding cases was matched to 50 controls based on index date and state. Warfarin users had an increased odds ratio of gastrointestinal bleeding upon initiation of citalopram (OR = 1.73 95% CI, 1.25-2.38), fluoxetine (OR = 1.63 95% CI, 1.11-2.38), paroxetine (OR = 1.64 95% CI, 1.27-2.12), amitriptyline (OR = 1.47 95% CI, 1.02-2.11). Also mirtazapine, which is not believed to interact with warfarin, increased the risk of GI bleeding (OR = 1.75 95% CI, 1.30-2.35).
Warfarin users who initiated citalopram, fluoxetine, paroxetine, amitriptyline, or mirtazapine had an increased risk of hospitalization for gastrointestinal bleeding. However, the elevated risk with mirtazapine suggests that a drug-drug interaction may not have been responsible for all of the observed increased risk.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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