Computational fluid dynamics modeling of aerosol particle transport through lung airway mucosa.

Delivery of aerosols to the lung can treat various lung diseases. However, the conducting airways are coated by a protective mucus layer with complex properties that make this form of delivery difficult. Mucus is a non-Newtonian fluid and is cleared from the lungs over time by ciliated cells. Further, its gel-like structure hinders the diffusion of particles through it. Any aerosolized treatment of lung diseases must penetrate the mucosal barrier. Using computational fluid dynamics, a model of the airway mucus and periciliary layer was constructed to simulate the transport of impacted aerosol particles. The model predicts the dosage fraction of particles of a certain size that penetrate the mucus and reach the underlying tissue, as well as the distance downstream of the dosage site where tissue concentration is maximized. Reactions that may occur in the mucus are also considered, with simulated data for the interaction of a model virus and an antibody.

High-Evidence, Actionable Phenotype Gene Distribution in a Multispecialty, Tertiary Care Clinic: Potentially Actionable Genes and a Referring Department Profile.

Background There has been a trend in recent years toward individualized medicine. Pharmacogenomics (PGx) is the use of patient-specific genetic variations to guide medication selection and treatment. Objective: The primary objective was to characterize the population of referring department patients and identify the number of high-evidence, actionable phenotype (HEAP) genes in this referred population to help guide marketing efforts to the most applicable patient populations and departments. Practice description: Located in a destination, tertiary care clinic. Providers refer patients to a Pharmacogenomics (PGx) specialist for a comprehensive medication review using their pharmacogenomic results. Practice Innovation: The practice is innovative because it has been using PGx in the pharmacy and medical practices since 2016 and has been routinely developing and incorporating PGx best practice alerts (BPAs) into the electronic medical record (EMR) since 2020. Evaluation Methods Genetic results were analyzed from a 27-gene PGx panel test which tests for both pharmacokinetic and pharmacodynamic genes. High-Evidence Actionable Phenotypes (HEAP) are defined as phenotypes with guideline support that may suggest an action by healthcare provider. Low-Evidence Nonactionable Phenotypes (LENP) are defined as phenotypes that do not recommend action. Results There were 1,236 atypical phenotypes identified in the 154 patients referred. Of the atypical genes, 39.97% were HEAP and 60.03% were LENP. Of the HEAP's identified, the majority came from CYP2D6, VKORC1, and UGT1A1. At least 1 HEAP was found in 98.7% of patients (n=152). Conclusion There are a variety of High Evidence Actionable Phenotypes (HEAPs) with a high likelihood of at least one HEAP gene in every patient. These phenotypes can result in serious safety concerns when combined with a medication impacted by one of these HEAP genes. Thus, referral to a pharmacogenomics consultation service may lead to an overall decrease in morbidity and mortality with potential cost avoidance.

Factor VIII inhibitor bypass activity and recombinant activated factor VII in cardiac surgery.

OBJECTIVE: Postcardiopulmonary bypass hemorrhage remains a serious complication of cardiac surgery. Given concerns regarding adverse effects of blood product transfusion and limited efficacy of current antifibrinolytics, procoagulant medications, including recombinant factor VIIa (rFVIIa) and factor eight inhibitor bypass activity (FEIBA), increasingly have been used in managing refractory bleeding. While effective, these medications are associated with thromboembolic complications. This study compared the efficacy and risk of adverse events of rFVIIa and FEIBA in cardiac surgical patients with refractory bleeding. DESIGN: This retrospective study evaluated 168 patients who underwent cardiac surgery and received either FEIBA or rFVIIa to manage postbypass hemorrhage. Demographic, clinical, and outcomes data were collected and statistical analysis performed to compare thromboembolic event rates, relative efficacy, and 30-day mortality following administration of these medications. SETTING: Single university hospital. PARTICIPANTS: Patients undergoing cardiac surgery. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULT: Sixty-one patients received rFVIIa, and 107 received FEIBA. Demographics, surgical procedures, and preoperative anticoagulation were similar between the cohorts; however, the rFVIIa cohort had longer durations of cardiopulmonary bypass (305.1 v 243.8 min, p<0.01). There were no significant differences in the number of thromboembolic events, 30-day mortality, or rates of revision surgery. Neither group demonstrated a clear relationship between dosage and occurrence of thromboembolic events. The rFVIIa cohort received more platelets than the FEIBA cohort (3.13 v 1.67 units, p = 0.01), but transfusion rates of other blood products were similar. CONCLUSIONS: This study suggests that rFVIIa and FEIBA have similar efficacy and adverse event profiles in managing intractable postbypass hemorrhage in cardiac surgical patients. Further prospective studies are required.