Impact of Prematriculation Course Withdrawals on First Year Pharmacy School Success.

OBJECTIVE: Determine the impact of prematriculation course withdrawals on first year pharmacy school (P1) success, defined as on-time progression to the second (P2) year without remediation. METHODS: A retrospective review of students matriculating to a four-year private institution from 2018 to 2021 was conducted. Potential predictors of P1 year success including age, sex, highest degree achieved, prematriculation grade point average (GPA), and course withdrawals were collected. RESULTS: Bivariate analysis indicates that age, cumulative GPA, science GPA, and prematriculation course withdrawals were significantly different between students who were successful vs unsuccessful in the first year of pharmacy school. Out of 220 students analyzed, 40.9% (n = 90) were unsuccessful in the first year. Of those 90 P1 students, 52% did not progress to the P2 year, and 48% progressed but required course remediation. Multivariate analysis demonstrated that independent predictors of P1 success included cumulative GPA and having less than two prematriculation course withdrawals. In addition, the number of prematriculation course withdrawals, cumulative GPA, and having a bachelor's degree or higher were independent predictors of P1 GPA. CONCLUSION: Prematriculation course withdrawal was an independent predictor of both P1 success and P1 GPA. Students with less than two prematriculation course withdrawals were more likely to be successful during the first year of pharmacy school. College of pharmacy admission committees may consider prematriculation course withdrawal frequency when making admission decisions or to identify students that may need additional academic support during the first year of pharmacy school.

Corticosteroids for Blastomycosis-Induced Acute Respiratory Distress Syndrome: A Case Report and Literature Review.

We describe a case report of a patient with Blastomycosis-induced acute respiratory distress syndrome (ARDS) and severe hypoxemia requiring mechanical ventilation, prone positioning, and neuromuscular blockade whose clinical condition rapidly improved with the use of corticosteroids resulting in the patient being discharged home without the need for supplemental oxygen.

Hypertension Statistics for US Adults: An Open-Source Web Application for Analysis and Visualization of National Health and Nutrition Examination Survey Data.

BACKGROUND: Data from the US National Health and Nutrition Examination Survey are freely available and can be analyzed to produce hypertension statistics for the noninstitutionalized US population. The analysis of these data requires statistical programming expertise and knowledge of National Health and Nutrition Examination Survey methodology. METHODS: We developed a web-based application that provides hypertension statistics for US adults using 10 cycles of National Health and Nutrition Examination Survey data, 1999 to 2000 through 2017 to 2020. We validated the application by reproducing results from prior publications. The application's interface allows users to estimate crude and age-adjusted means, quantiles, and proportions. Population counts can also be estimated. To demonstrate the application's capabilities, we estimated hypertension statistics for noninstitutionalized US adults. RESULTS: The estimated mean systolic blood pressure (BP) declined from 123 mm Hg in 1999 to 2000 to 120 mm Hg in 2009 to 2010 and increased to 123 mm Hg in 2017 to 2020. The age-adjusted prevalence of hypertension (ie, systolic BP≥130 mm Hg, diastolic BP≥80 mm Hg or self-reported antihypertensive medication use) was 47.9% in 1999 to 2000, 43.0% in 2009 to 2010, and 44.7% in 2017 to 2020. In 2017 to 2020, an estimated 115.3 million US adults had hypertension. The age-adjusted prevalence of controlled BP, defined by the 2017 American College of Cardiology/American Heart Association BP guideline, among nonpregnant US adults with hypertension was 9.7% in 1999 to 2000, 25.0% in 2013 to 2014, and 21.9% in 2017 to 2020. After age adjustment and among nonpregnant US adults who self-reported taking antihypertensive medication, 27.5%, 48.5%, and 43.0% had controlled BP in 1999 to 2000, 2013 to 2014, and 2017 to 2020, respectively. CONCLUSIONS: The application developed in the current study is publicly available at https://bcjaeger.shinyapps.io/nhanesShinyBP/ and produced valid, transparent and reproducible results.

Frequency of Course Remediation and the Effect on North American Pharmacist Licensure Examination Pass Rates.

Objective. Remediation is a tool that allows students to correct an academic deficiency after earning an unsatisfactory grade. There is a lack of data on remediation processes and their impact on future academic performance. This study aimed to evaluate the impact of remediation frequency on North American Pharmacist Licensure Examination (NAPLEX) performance.Methods. The primary analysis was the relationship between the NAPLEX first-time pass rate and the frequency of course remediations (no remediations, one remediation, and two or more remediations). Additional analyses included the correlation between the NAPLEX scaled score and the number of course remediations and characteristics of the course remediated.Results. A total of 116 students with NAPLEX data were included for analysis. Compared to students who never remediated, NAPLEX first-time pass rates were similar among those who remediated only one course; however, students who remediated two or more courses had significantly lower NAPLEX pass rates. Remediation in courses mapped to Pharmacy Curriculum Outcomes Assessment (PCOA) area 4.0 (clinical sciences), and courses with mixed PCOA content areas were negatively correlated with NAPLEX scaled scores. A significant negative correlation existed between remediation in students' second or third years in pharmacy school and the NAPLEX scaled score, but this correlation was not significant for students in their first year.Conclusion. Multiple course remediations are negatively correlated with NAPLEX scaled scores and a reduced first-time NAPLEX pass rate, but a single course remediation has no effect. Institutions should aim to evaluate their current remediation practices and assess whether additional support should be provided to students with multiple course remediations.

Chronic Heart Failure: A Pharmacologic Review.

Chronic heart failure affects over 6 million Americans and is the main reason that people older than 65 years get admitted to the hospital (Centers for Disease Control and Prevention, 2020). Management of heart failure requires interdisciplinary efforts involving primary care physicians, cardiologists, nurses, and pharmacists among other providers. Nurses can play a key role in identifying patients at risk for heart failure exacerbation and are often at the front lines providing education regarding medication adherence. This article summarizes the medications used in chronic heart failure and describes common side effects, dosing considerations, and counseling points that are essential for appropriate management.

Acute Decompensated Heart Failure: A Pharmacologic Review.

Chronic heart failure (CHF) is a growing disease in the United States. Exacerbations of CHF can lead to acute decompensated heart failure (ADHF) and hospitalizations. Nurses play a key role in the treatment of ADHF as they administer medications, monitor patients' response to therapy, and can prompt providers to alter therapy if therapeutic outcomes are not being achieved. Nurses also play a vital role in discharge education for patients who are hospitalized for ADHF, as they can counsel patients on ways to reduce further hospitalizations. It is important for nurses to understand and recognize symptoms of ADHF, pharmacologic treatments for ADHF, and common etiologies of ADHF to help improve patient outcomes.

Impact of faculty interviewers on student matriculation following pharmacy school offer of admission.

INTRODUCTION: Acceptance to pharmacy school relies on data such as grade point average (GPA) and Pharmacy College Admission Test (PCAT) scores in addition to holistic review. The interview is the final step in finding successful applicants. This study sought to identify if faculty interviewers had an impact on prospective students' decisions to accept an offer of admission to our college of pharmacy. METHODS: A seven-year retrospective review of applicants granted an offer of admission was conducted. Analyses determined if interviewer assignment impacted yield of students matriculating into the program. RESULTS: Fifty-two different faculty interviewed 1634 applicants who were subsequently offered admission during the seven-years of review; of these applicants, 482 matriculated (yield 29.5%). Ten faculty interviewers provided 1020 (62.4%) of these interviews, with 302 applicants matriculating (yield 29.6%). Univariate analysis of these 10 interviewers did not find a significant difference in yield. Matriculation between the highest and lowest yielding faculty members trended toward a difference but was not statistically significant. Lower cumulative GPA, lower quantitative PCAT, lack of a bachelor's degree or higher, and interviewing later in the admissions cycle correlated with a higher matriculation yield (P < 0.05). CONCLUSIONS: Faculty interviewers did not impact an applicant's decision to accept an offer of admission to pharmacy school. Interviewing late in the admissions cycle, not having a bachelor's degree, lower cumulative GPA, and lower quantitative PCAT score correlated with increased matriculation yield.

Characteristics of Drug-Related Podcasts and This Medium's Potential as a Pharmacy Education Tool.

Objective. To analyze the publication frequency and characteristics of drug-related podcasts and describe the role of pharmacists in creating content for this audio-based educational medium. Methods. Podcasts that potentially included drug-related educational information were identified based on four podcast categories that were publicly available as of June 2016. Podcasts were screened by two reviewers to determine whether they contained at least five episodes with drug-related content and a minimum of 10 audio episodes. Metrics related to the podcast, audio episodes, and names of the content authors were collected and a descriptive analysis was conducted. Results. Of the 960 podcasts screened, 125 met the study criteria and were included in the descriptive analysis. These drug-related podcasts produced a median of two episodes per month and each episode lasted an average of 27 minutes. The most common professions represented by podcast hosts and guests were physicians (83.2%), followed by nurses and nurse practitioners (11.2%) and pharmacists (10.4%). Podcast content varied widely, with critical care and emergency medicine being the most common (18.4%), followed by general medicine (14.4%) and complementary and alternative medicine (13.6%). Conclusion. Drug-related podcasts are numerous and easily accessible; however, the quality and accuracy of their content cannot be easily determined as episodes do not consistently cite references. Pharmacists appear to be underrepresented in developing this particular genre of educational content, pharmacy educators should consider producing and disseminating educational material through podcasts for students and practitioners.

Nonlinear protein binding of phenytoin in clinical practice: Development and validation of a mechanistic prediction model.

AIMS: To individualize treatment, phenytoin doses are adjusted based on free concentrations, either measured or calculated from total concentrations. As a mechanistic protein binding model may more accurately reflect the protein binding of phenytoin than the empirical Winter-Tozer equation that is routinely used for calculation of free concentrations, we aimed to develop and validate a mechanistic phenytoin protein binding model. METHODS: Data were extracted from routine clinical practice. A mechanistic drug protein binding model was developed using nonlinear mixed effects modelling in a development dataset. The predictive performance of the mechanistic model was then compared with the performance of the Winter-Tozer equation in 5 external datasets. RESULTS: We found that in the clinically relevant concentration range, phenytoin protein binding is not only affected by serum albumin concentrations and presence of severe renal dysfunction, but is also concentration dependent. Furthermore, the developed mechanistic model outperformed the Winter-Tozer equation in 4 out of 5 datasets in predicting free concentrations in various populations. CONCLUSIONS: Clinicians should be aware that the free fraction changes when phenytoin exposure changes. A mechanistic binding model may facilitate prediction of free phenytoin concentrations from total concentrations, for example for dose individualization in the clinic.

Life-threatening idiopathic reaction to hydrochlorothiazide treated with veno-venous extracorporeal membrane oxygenation.

Hydrochlorothiazide has been shown to cause rare, but serious non-cardiogenic pulmonary edema. We present a case report of a patient with apparent septic shock and acute respiratory distress syndrome (ARDS) requiring life-sustaining veno-venous extracorporeal membrane oxygenation (VV-ECMO). Upon further review of the literature and the chronology of the patient's presentation, her condition was most likely due to an immune-mediated reaction to hydrochlorothiazide. This represents the first case, to our knowledge, of such a severe reaction to hydrochlorothiazide supported with ECMO therapy.

Characterization of Free Phenytoin Concentrations in End-Stage Renal Disease Using the Winter-Tozer Equation.

BACKGROUND: The Winter-Tozer (WT) equation has been shown to reliably predict free phenytoin levels in healthy patients. In patients with end-stage renal disease (ESRD), phenytoin-albumin binding is altered and, thus, affects interpretation of total serum levels. Although an ESRD WT equation was historically proposed for this population, there is a lack of data evaluating its accuracy. OBJECTIVE: The objective of this study was to determine the accuracy of the ESRD WT equation in predicting free serum phenytoin concentration in patients with ESRD on hemodialysis (HD). METHODS: A retrospective analysis of adult patients with ESRD on HD and concurrent free and total phenytoin concentrations was conducted. Each patient's true free phenytoin concentration was compared with a calculated value using the ESRD WT equation and a revised version of the ESRD WT equation. RESULTS: A total of 21 patients were included for analysis. The ESRD WT equation produced a percentage error of 75% and a root mean square error of 1.76 µg/mL. Additionally, 67% of the samples had an error >50% when using the ESRD WT equation. A revised equation was found to have high predictive accuracy, with only 5% of the samples demonstrating >50% error. CONCLUSION: The ESRD WT equation was not accurate in predicting free phenytoin concentration in patients with ESRD on HD. A revised ESRD WT equation was found to be significantly more accurate. Given the small study sample, further studies are required to fully evaluate the clinical utility of the revised ESRD WT equation.

Unexplained increases in serum vancomycin concentration in a morbidly obese patient.

INTRODUCTION: To report a case of increases in vancomycin concentrations without additional vancomycin doses being given. CASE STUDY: A 64 year-old morbidly obese female received three total doses of vancomycin for surgical prophylaxis and for ventilator-associated pneumonia. Subsequent vancomycin concentrations from the patient's central venous catheter (CVC) demonstrated increasing drug levels from 27.1 to 45.9mcg/mL despite no additional vancomycin being given and proper line flushing prior to sample collection. There is no clear explanation for the increase in the patient's vancomycin concentration. Drug leaching from the CVC, enterohepatic recycling, drug redistribution from adipose or other tissues, and assay cross-reactivity with other medications are all potential explanations for the increased vancomycin concentrations. CONCLUSION: This case report describes an unexplained increase in vancomycin concentrations and reinforces both the fallibility of laboratory testing and that unusual circumstances do occur. Several potential causes are hypothesised with CVC drug leaching being the most likely. Nurses and other healthcare providers with similar scenarios should consider a peripheral blood sample to rule out the potential for CVC drug leaching as a possible explanation.

Characterization of unbound phenytoin concentrations in neurointensive care unit patients using a revised Winter-Tozer equation.

BACKGROUND: Prior studies examining the accuracy of the Winter-Tozer (WT) equation for correcting total phenytoin concentrations in critically ill patients have yielded conflicting results and are limited by small sample sizes and stringent exclusion criteria, which lessen external validity. OBJECTIVE: To determine whether the traditional WT equation is appropriate in correcting total phenytoin concentrations in a large sample of patients in a neurointensive care unit (NICU) and whether a new equation may be more predictive. METHODS: In a retrospective study, NICU patients with reports of a concurrent total and unbound phenytoin concentration and albumin level were analyzed. Two new predictive equations were generated using a revised WT equation and regression model of baseline and laboratory characteristics. Prediction error analysis using a 20% validation cohort was conducted on all 3 equations for comparison. RESULTS: A total of 140 adults were included for data analysis, with data on 80% used for derivation and 20% as validation of all equations. The mean unbound phenytoin concentration was 1.4 µg/mL, which represented a free fraction of 10%. Most samples were collected within 24 hours of NICU admission. Multivariate regression analysis demonstrated that albumin, total phenytoin concentration, sex, and creatinine clearance were predictive of measured unbound phenytoin concentrations. The traditional WT equation significantly underpredicted true unbound phenytoin concentrations, with 32.1% of patients having a prediction error of more than 50% in the validation cohort. CONCLUSIONS: The traditional WT equation was significantly biased in underpredicting true unbound phenytoin concentrations in neurointensive care unit patients and should not be used in this setting. Two modified equations were more accurate and precise and should be considered for use when unbound phenytoin concentrations are not readily available in an NICU population.