Characteristics of Atrial Fibrillation Patients with a Family History of Atrial Fibrillation.

BACKGROUND: Family history has been shown to be associated with increased risk of atrial fibrillation (AF). However, the specific AF characteristics that travel with a family history have not yet been elucidated. The purpose of this study was to determine whether a family history of AF is associated with specific patient characteristics in a worldwide, remote cohort. METHODS: From the Health eHeart Study, an internet-based prospective cohort, we performed a cross-sectional analysis of AF participants who reported their family history and completed questionnaires regarding their medical conditions and AF symptoms. We assessed demographics, cardiovascular comorbidities, and AF symptom characteristics in AF participants with and without a family history of AF. RESULTS: In multivariable analysis of 5,884 participants with AF (mean age 59.9 ± 14.5, 59% male, 92% white), female sex (odds ratio [OR]=1.35, 95% CI, 1.17-1.54, p<0.0001) and birth in the U.S. (OR=2.54, 95% CI, 2.12-3.05, p<0.0001) were independently associated with having a family history of AF. Having a family history of AF was also more commonly associated with symptoms of shortness of breath (OR=1.40, 95% CI, 1.07-1.82, p=0.014), chest pain, pressure, or discomfort (OR=1.95, 95% CI, 1.22-3.13, p=0.0052), and feeling generally "off" about oneself (OR=1.84, 95% CI, 1.27-2.67, p=0.0013). CONCLUSIONS: Patients with a family history of AF are more likely to be female, be US-born, and experience symptoms of AF, suggesting underlying mechanistic differences between those with and without family history of AF.

Smartphone-Based Geofencing to Ascertain Hospitalizations.

BACKGROUND: Ascertainment of hospitalizations is critical to assess quality of care and the effectiveness and adverse effects of various therapies. Smartphones, mobile geolocators that are ubiquitous, have not been leveraged to ascertain hospitalizations. Therefore, we evaluated the use of smartphone-based geofencing to track hospitalizations. METHODS AND RESULTS: Participants aged ≥18 years installed a mobile application programmed to geofence all hospitals using global positioning systems and cell phone tower triangulation and to trigger a smartphone-based questionnaire when located in a hospital for ≥4 hours. An in-person study included consecutive consenting patients scheduled for electrophysiology and cardiac catheterization procedures. A remote arm invited Health eHeart Study participants who consented and engaged with the study via the internet only. The accuracy of application-detected hospitalizations was confirmed by medical record review as the reference standard. Of 22 eligible in-person patients, 17 hospitalizations were detected (sensitivity 77%; 95% confidence interval, 55%-92%). The length of stay according to the application was positively correlated with the length of stay ascertained via the electronic medical record (r=0.53; P=0.03). In the remote arm, the application was downloaded by 3443 participants residing in all 50 US states; 243 hospital visits at 119 different hospitals were detected through the application. The positive predictive value for an application-reported hospitalization was 65% (95% confidence interval, 57%-72%). CONCLUSIONS: Mobile application-based ascertainment of hospitalizations can be achieved with modest accuracy. This first proof of concept may ultimately be applicable to geofencing other types of prespecified locations to facilitate healthcare research and patient care.

Nurse and Medical Provider Perspectives on Antibiotic Stewardship in Nursing Homes.

OBJECTIVES: To examine perspectives on antibiotic use and antibiotic stewardship of nurses and medical providers in nursing homes (NHs). DESIGN: Cross-sectional survey. SETTING: NHs in North Carolina (N = 31). PARTICIPANTS: Nursing staff (n = 182) and medical providers (n = 50). MEASUREMENTS: Respondents completed a self-administered questionnaire about their perspectives on antibiotic use in their NH, the influence of residents and families on antibiotic prescribing decisions, and readiness to improve antibiotic stewardship. Open-ended questions on barriers to antibiotic stewardship were also asked. Linear mixed modeling was used to analyze differences between respondent groups and to test for associations with individual and organizational characteristics. RESULTS: All respondents supported reducing antibiotic use, although medical providers' support was significantly stronger (P = .005). When asked about their perception of residents' and family members' preference for antibiotic use in the case of suspected infection and the influence of that preference on antibiotic-prescribing decisions, respondents indicated that residents and families favor antibiotic use and influence prescribing decisions. Nurses reported a stronger perception than medical providers that families prefer antibiotics (P = .04) and influence prescribing decisions (P = .02). All respondents reported commitment and efficacy to change practices (mean 4.0-4.1 for nurses and 3.6-3.9 for medical providers on a 5-point scale). Four significant associations related to organizational and individual characteristics were found: directors of nursing and specialist nurses reported greater self-efficacy for changing practice than other nurses (P = .003), medical providers with a subspecialty (e.g., geriatrics) reported greater self-efficacy (P = .007) and commitment to change (P = .001) than those without a subspecialty, and medical providers specializing in hospice and palliative care rated family influence (P = .006) higher than those with other subspecialties. CONCLUSION: Nursing staff and medical providers share a commitment to reducing unnecessary antibiotic use. Antibiotic stewardship interventions should foster cooperation and build competency to implement alternative management approaches and to educate residents and families. Nurse leaders and medical providers with long-term care training may be especially effective champions for antibiotic stewardship.

Evaluation of drug interaction software to identify alerts for transplant medications.

BACKGROUND: The ability of computerized physician order entry (CPOE) systems to identify clinically significant drug interactions is dependent upon the integrity of the drug information populating the software. A CPOE system with incomplete or inaccurate drug information will fail to identify clinically important drug interactions and, therefore, fail to reduce preventable adverse drug events (pADEs). OBJECTIVE: To evaluate, from the prescribers' perspective, the ability of a common drug interaction database to identify clinically important drug interactions involving drugs used in transplantation. METHODS: The clinical significance of drug interactions involving 5 transplant drugs was evaluated by an expert panel to determine whether alerts should be generated for physicians not involved in the transplant at the time of order entry. Drug interactions included in the analysis were generated from the expert panel, a common drug interaction database, and 2 standard drug interaction references. Responses on the clinical significance were used to calculate the sensitivity, specificity, and positive and negative predictive values for each severity setting of a common electronic drug interaction database. RESULTS: Overall, the database failed to identify approximately 70% of interactions considered significant by the expert panel. Of the alerts that were generated, >85% were considered clinically significant. The database was most deficient in identifying interactions resulting from additive toxicity. CONCLUSIONS: To expect a decrease in pADEs caused by drug interactions, the information used to populate CPOE systems must be validated. Establishing consistency and integrity of this information may be a future role for pharmacists.

Evaluation of estimated and measured creatinine clearances for predicting the pharmacokinetics of vancomycin in adult liver transplant recipients.

This study examined the pharmacokinetics and dosing requirements of vancomycin in adult liver transplant recipients and also evaluated the predictability of determining vancomycin-dosing requirements utilizing an estimated creatinine clearance (CrCl) approach. Twenty adult liver transplant recipients were included in this analysis. Vancomycin pharmacokinetic parameters and dosing requirements calculated from estimated CrCl and population-based pharmacokinetic equations were compared with values calculated using serum concentrations and assuming a one-compartment model. Compared with the values obtained using equations to estimate the CrCl and vancomycin pharmacokinetics (t, Cl, and Vd), the actual values were statistically different for half-life and clearance (11.0 vs. 16.4 hours and 52 vs. 36 mL/min, respectively; P < 0.01). Additionally, CrCl that were estimated using population-based formulas significantly overestimated actual CrCl calculated using 24-hour urine collections (65-78 vs. 43 mL/min; P < 0.05). The results from this study indicate that serum creatinine concentrations do not adequately predict glomerular filtration rates (GFR) or vancomycin clearance in adult liver transplant recipients. Based on these results, the use of 24-hour urine CrCl to predict GFR and serum concentrations to properly dose vancomycin is advocated.

Tacrolimus dosing requirements and concentrations in adult living donor liver transplant recipients.

Living donor liver transplantation in adult recipients is becoming increasingly common. The liver metabolizes most drugs, including immunosuppressive agents. Right-lobe grafts used in adult living donor liver transplantation consist of only 50% to 60% of the total liver. The purpose of this study is to determine whether there is a difference between tacrolimus doses and concentrations in patients who received a partial liver transplant from a living donor (LRD) versus those who received a whole-liver transplant from a cadaveric donor (CAD). Thirteen LRD recipients and 13 CAD recipients who underwent transplantation between April 1998 and July 2000 were included in this analysis. A CAD control group matched for age, sex, and race was used for comparison. Tacrolimus doses and concentrations were analyzed weekly for the first 4 weeks, then monthly for 6 months posttransplantation. There was no difference in acute rejection rates, renal and liver function test results, or number of potentially interacting medications administered between groups. LRD recipients required significantly lower doses of tacrolimus compared with CAD recipients at 2 weeks (0.058 v 0.110 mg/kg/d; P <.01), 3 weeks (0.068 v 0.123 mg/kg/d; P <.02), 4 weeks (0.086 v 0.141 mg/kg/d; P <.02), 2 months (0.097 v 0.141 mg/kg/d; P <.03), and 3 months (0.099 v 0.138 mg/kg/d; P <.03). Tacrolimus 12-hour trough concentrations were similar between groups at all times except for 2 weeks posttransplantation, when LRD recipients' concentrations were significantly greater than those of CAD recipients (12.4 v 9.5 ng/mL; P <.03). In addition, in the first month posttransplantation, LRD recipients were more likely to have greater concentrations of tacrolimus (>15 ng/mL; 22.1% v 9.2%; P <.01). In conclusion, LRD recipients have significantly decreased tacrolimus dosing requirements compared with CAD recipients during the first 3 months posttransplantation despite having similar tacrolimus concentrations.