High out-of-pocket medication costs negatively impact adherence in transplantation. We evaluated the association of "medication trade-offs"-defined as choosing to spend money on other expenses over medications-with medication nonadherence and transplant outcomes. From 2011 to 2012, we performed a prospective study of 201 transplanted recipients (n = 103 liver, n = 98 kidney and) at two large US transplant centers. Structured interviews assessed socio-demographics, medication adherence, and medication trade-offs. Multivariable models assessing risk factors for medications trade-offs and the association between medications trade-offs and post-transplant hospital admissions were performed. A total of 17% of patients reported medication trade-offs; the most common trade-offs were inability to afford a prescription in the past 12 months and making choices between prescriptions and food. In multivariable analysis, insurance type (RR: 2.97, 95% CI: 1.19-7.40), limited health literacy (RR: 2.64, 95% CI: 1.23-5.64), and ≥3 comorbid conditions (RR: 2.48, 95% CI: 1.09-5.62; all P < 0.05) were associated with trade-offs. Patients with trade-offs were more likely to report nonadherence to medications (mean adherence: 77 ± 23% with trade-offs vs. 89 ± 19% without trade-offs, P < 0.01). The presence of medication trade-offs was associated with post-transplant hospital admissions (RR 1.64, 95% CI 1.14-2.35, P < 0.01). Assessments of financial barriers are warranted in clinical practice to identify nonadherence and improve post-transplant outcomes.

Supplemental Digital Content is available in the text.

BACKGROUND AND AIMS Kidney allograft loss is a common cause of end-stage renal disease but accurate prediction models of kidney allograft loss are lacking in children. The iBOX system has been broadly validated among adults. We aimed to validate the iBOX system in a large international cohort of pediatric kTx recipients. METHOD In this observational study, we used data from pediatric (&lt;21) patients transplanted between 2005 and 2017 from 20 institutions in Europe and the USA. Patients with functional parameters (eGFR and UPCR), donor specific antibody and biopsy results (Banff scores g, ptc, cg, i, t and IFTA) were included. Individual predictions of allograft loss were obtained by applying the iBOX score on our data. The prediction performances of the model in our population were assessed via discrimination (c-statistics) and calibration. RESULTS A total of 573 kTx recipients were included. Median time from transplantation to evaluation was 1.0 (0.5–2.0) year with a mean age at evaluation at 12.1 (5.5) years and mean follow-up after transplantation 5.1 (2.8) years. Five-year death-censored graft survival from evaluation was 95%. At the time of evaluation, mean eGFR and uPCR were 65.5 (29.6) mL/min/1.73 m2 and 0.25 (1.2) g/g, respectively. A total of 118 (20.6%) of the patients had DSA. The iBOX system showed good discrimination with a c-statistic of 0.81 and good calibration (Figure 1). CONCLUSION The iBOX system demonstrated high accuracy in predicting kidney allograft loss in children with performances similar to those reported in adults.

No abstract

Medical Care Survey (NHAMCS) were compiled and analyzed. Variables were coded to agglomerate all ICD codes which correspond to the concussion.Results: During the period studied 1,416,876 patients received the diagnosis of concussion in the ED. These patients had an average age of 30.8 years (95% CI 28.9-32.6 P<0.0001) and 55.2% were male (95% CI 51.3-59.0 P<0.0001). The most common chief complaint of patients diagnosed with concussion was head injury (35.5%, 95% CI 31.7-39.4, P<0.0001) followed by headache (15.8%, 95% CI 13.3-18.7, P<0.0001). Of these, 77.5% received a CT scan (95% CI 74.1-80.5 P<0.0001) and 1.3% received MRI (95% CI 0.7-2.4 P<0.0001). Among these patients. 5.8% admitted to the inpatient service, and 3.5% of patients returned to ED within 72 hours. During the years studied, CT use experienced a relative decrease in the use of 7.8%, while MRI experienced a relative increase of 10.0%. When compared to patients who did not receive a CT, those who did were more likely to be admitted (6.4%, 95% CI 4.7-8.6, P<0.0001).Conclusions: The majority of patients presented to ED continue to receive diagnostic tests including CT imaging. Medical professionals should continue to use the guideline, and "Choosing Wisely" approach to assess patients with concussions and relay instead on imaging-sparing approaches such as observation and close follow-ups.