Moderating effect of number of prescribed ATC codes on health care costs during first quarter of PIM use.

<p>Moderating effect of number of prescribed ATC codes on health care costs during first quarter of PIM use.</p

Predictive margins of growth curves for total health care costs in balanced EG and NEG, at mean of the number of prescribed ATC codes (mean 4.8), balanced by weights based on entropy balancing.

<p>Fig is based on fully saturated linear mixture regression model with maximum likelihood estimators with a quadratic term for the number of prescribed ATC codes.</p

Dried-Blood-Spot Technique to Monitor Direct Oral Anticoagulants: Clinical Validation of a UPLC–MS/MS-Based Assay

Plasma concentrations of direct oral anticoagulants (DOACs) vary largely between individuals, and they correlate well with desired and adverse outcomes. Although regular concentration monitoring of DOACs is not recommended, information on DOAC exposure could be useful in situations when multiple DOAC-clearance pathways are impaired or nonadherence is suspected. Self-sampling techniques, like the use of dried-blood spots (DBSs), would be particularly useful because they enable the collection of information in ambulatory patients at relevant points in time of the dosing interval (e.g., trough). We developed and validated a DBS-based assay to quantify all currently marketed DOACs (apixaban, dabigatran, edoxaban, and rivaroxaban) in a single ultraperformance-liquid-chromatography–tandem-mass-spectrometry assay. It fulfilled all validation standards within a hematocrit range of 0.33–0.65 and was linear over the calibration ranges of 2.5–750 ng/mL (apixaban and rivaroxaban), 4.4–750 ng/mL (dabigatran), and 9.3–750 ng/mL (edoxaban). Only minor ion suppression (matrix effect ≤13%) was present, inter- and intra-assay precision was ≤13%, and inter- and intra-assay accuracies ranged between 88 and 110%. All DOACs were stable in DBSs up to 52 days at room temperature, if the DBSs were protected from light and humidity. The correlation between (whole blood) DBS and plasma concentrations was assessed in 33 patients under regular DOAC therapy. Deming-regression coefficients between simultaneously collected capillary DBSs and plasma samples were used to predict plasma concentrations from DBSs. Bland–Altman plots revealed a strong agreement between predicted and observed plasma concentrations, thus confirming the suitability of DBSs for DOAC monitoring as an important step toward the important aim of self-sampling at home

Growth curves for total health care costs (per quarter) in EG and balanced/unbalanced NEG for pre-and post-period, each spanning 4 quarters.

<p>Fig is based on fully saturated linear mixture regression model with maximum likelihood estimators, balancing of NEG is based on weights from entropy balancing.</p

Growth curves for the number of prescribed ATC codes (per quarter) in EG and balanced/unbalanced NEG for pre-and post-period, each spanning 4 quarters.

<p>Fig is based on fully saturated linear mixture regression model with maximum likelihood estimators, balancing of NEG is based on weights from entropy balancing.</p

Presence of medication underuse was associated with frailty, BMI, and the number of drugs.

<p>Selected model variables and their association with medication underuse in a multivariate logistic regression model (*** < 0.001; ** < 0.01; and * < 0.05).</p

Medication underuse did not affect cardiovascular outcomes, but rather deaths due to non-cardiovascular causes.

<p>(A) Kaplan-Meier plot of relevant cardiovascular events for appropriate use and medication underuse (<i>P</i> value calculated by the log-rank test). (B) cumulative incidence functions of relevant (black) and competing events (gray) according to status of medication underuse (<i>P</i> value calculated by the Gray test) (solid line: appropriate use; dotted line: underuse).</p

Adapted START criteria for determination of cardiovascular medication underuse.

<p>^a a documented history of atherosclerotic coronary, cerebral, or peripheral vascular disease included previous myocardial infarction, stroke, coronary intervention (bypass surgery or balloon catheterization of the coronary arteries), pulmonary embolism, and deep vein thrombosis.</p><p>^b hypertension, hypercholesterolemia, and smoking history</p><p>Adapted START criteria for determination of cardiovascular medication underuse.</p