Initiation of vitamin B(12) supplementation was associated with chronic gastric acid suppression therapy.

Both the phenytoin and standard treatment groups showed progress over the study period. However, the phenytoin group demonstrated more rapid results in all aspects of ulcer healing.

Background:Anticholinergic (AC) adverse drug events (ADEs) are caused by inhibition of muscarinic receptors as a result of designated or off-target drug–receptor interactions. In practice, AC toxicity is assessed primarily based on clinician experience. The goal of this study was to evaluate a novel concept of integrating big pharmacological and healthcare data to assess clinical AC toxicity risks.Methods:AC toxicity scores (ATSs) were computed using drug–receptor inhibitions identified through pharmacological data screening. A longitudinal retrospective cohort study using medical claims data was performed to quantify AC clinical risks. ATS was compared with two previously reported toxicity measures. A quantitative structure–activity relationship (QSAR) model was established for rapid assessment and prediction of AC clinical risks.Results:A total of 25 common medications, and 575,228 exposed and unexposed patients were analyzed. Our data indicated that ATS is more consistent with the trend of AC outcomes than other toxicity methods. Incorporating drug pharmacokinetic parameters to ATS yielded a QSAR model with excellent correlation to AC incident rate (R2 = 0.83) and predictive performance (cross validation Q2 = 0.64). Good correlation and predictive performance (R2 = 0.68/Q2 = 0.29) were also obtained for an M2 receptor-specific QSAR model and tachycardia, an M2 receptor-specific ADE.Conclusions:Albeit using a small medication sample size, our pilot data demonstrated the potential and feasibility of a new computational AC toxicity scoring approach driven by underlying pharmacology and big data analytics. Follow-up work is under way to further develop the ATS scoring approach and clinical toxicity predictive model using a large number of medications and clinical parameters.

Study Objective Serotonergic adverse drug events (ADEs) are caused by enhanced intra-synaptic concentrations of 5-hydroxytryptamine (5-HT). No systematic process currently exists for evaluating cumulative 5-HT and off-target toxicity of serotonergic drugs. The primary study aim was to create a Serotonergic Expanded Bioactivity Matrix (SEBM) employing a molecular bioinformatics, poly-pharmacologic approach for assessing the participation of individual 5-HT drugs in serotonin syndrome (SS) reports. Data Sources Publicly available databases including the Food and Drug Association (FDA) Adverse Event Reporting System (FAERS), ChEMBL, DrugBank, PubChem, and Kyoto Encyclopedia of Genes and Genomes (KEGG) were queried for computational and pharmacologic data. Design An in-house bioinformatics TargetSearch program was used to characterize 71 serotonergic drugs interacting at 13 serotonin receptor subtypes, and serotonin re-uptake transporter protein (SERT). Additionally, off-target interactions at norepinephrine transporter (NET), monoamine oxidase (MAO), and muscarinic receptors were included to define 7 poly-pharmacologic drug cohorts. Serotonin syndrome reports for each serotonergic drug were extracted from FAERS using Sternbach’s and Hunter’s criteria. Measurements and Main Results A proportional reporting adverse drug reaction (ADR) ratio (PRR) was calculated from each drug’s total ADEs and SS case reports and aggregated by drug bioactivity cohorts. Triple receptor interactions had a disproportionately higher number of SS cases using both Hunter’s criteria (mean PRR 1.72; 95% C.I. 1.05 to 2.39) and Sternbach’s (mean PRR 1.54, 95% C.I. 1.29 to 1.79). 5-Hydroxtryptamine agonists were associated with a significantly lower proportion of SS cases using Hunter’s and Sternbach’s criteria, respectively (mean PRR 0.49, 95% C.I. 0.17 to 0.81 and mean PRR 0.49, 95% C.I. 0.15 to 0.83). Drugs with disproportionately higher participation in SS vary considerably between the 2 diagnostic criteria. Conclusion The SEBM model suggests a possible poly-pharmacologic role in SS. Although further research is needed, off-target receptor activity may help explain differences in severity of toxicity and clinical presentation.

The extent of medication use and drug information preferences was surveyed randomly from patients at six different pharmacy health care systems. Following verbal consultation, each patient was given one or more modified United States Pharmacopoeia drug information leaflets corresponding to the verbal information and a self-addressed, stamped questionnaire to complete. Chi-square analysis was performed on 317 responses with overwhelming acceptance (96 percent) of the medication information provided. Although a majority of respondents (62 percent) preferred a combination of both written and oral information, specific information preferences (oral, written, or both) were significantly related to educational level, pharmacy attended, and prescription status. Nearly 45 percent of the respondents indicated the information was responsible for changing their medication use. Subjects who were elderly, taking cardiovascular medications, or getting refill prescriptions were significantly less likely to change as a result of the information provided. Although 65 percent of the respondents were unwilling to pay an additional fee for the service, females and those who were 45-54 years and over 65 years old were significantly more willing to pay for the information. In addition, the willingness to pay tended to increase as the number of daily medications taken increased. Consideration of socioeconomic and prescription variables may help define subgroups with specific information preferences and counseling activities that may be directly reimbursable.