Patel, Parag C.

AbstractBackgroundSome cardiac transplant programs may upgrade listed patients to United Network for Organ Sharing (UNOS) 1A‐status during the holidays. Whether more transplants actually occur during holidays is unknown.MethodsWe assessed rates of single‐organ heart transplantation from 2001 to 2010 for recipients age ≥18 yr using the UNOS database. Patients were stratified by transplantation during holiday (±3 d, n = 2375) and non‐holiday periods (n = 16 112). Holidays included Easter/Spring break, Memorial Day, July 4th, Labor Day, Thanksgiving, and Christmas/New Years (winter holidays). Secondary analysis assessing transplant rates across seasons was also completed.ResultsDonor and recipient characteristics were similar between groups. Compared with non‐holidays, July 4th had higher transplant rates (5.69 vs. 5.09 transplants/d, p = 0.03) while the winter holiday had lower transplant rates (4.50 vs. 5.09 transplants/d, p < 0.01). There was a trend toward lower transplant rates for all holidays compared with non‐holidays (p = 0.06). Transplant rates were significantly different across seasons with greater rates in spring and summer (p < 0.01).ConclusionHeart transplant rates were higher during the July 4th and lower during the winter holidays. Although there was a higher likelihood of transplantation during the spring and summer seasons, upgrading patients to 1A status during most holidays may not improve their chances for transplantation.

Background— A noninvasive biomarker that could accurately diagnose acute rejection (AR) in heart transplant recipients could obviate the need for surveillance endomyocardial biopsies. We assessed the performance metrics of a novel high-sensitivity cardiac troponin I (cTnI) assay for this purpose. Methods and Results— Stored serum samples were retrospectively matched to endomyocardial biopsies in 98 cardiac transplant recipients, who survived ≥3 months after transplant. AR was defined as International Society for Heart and Lung Transplantation grade 2R or higher cellular rejection, acellular rejection, or allograft dysfunction of uncertain pathogenesis, leading to treatment for presumed rejection. cTnI was measured with a high-sensitivity assay (Abbott Diagnostics, Abbott Park, IL). Cross-sectional analyses determined the association of cTnI concentrations with rejection and International Society for Heart and Lung Transplantation grade and the performance metrics of cTnI for the detection of AR. Among 98 subjects, 37% had ≥1 rejection episode. cTnI was measured in 418 serum samples, including 35 paired to a rejection episode. cTnI concentrations were significantly higher in rejection versus nonrejection samples (median, 57.1 versus 10.2 ng/L; P <0.0001) and increased in a graded manner with higher biopsy scores ( P trend <0.0001). The c -statistic to discriminate AR was 0.82 (95% confidence interval, 0.76–0.88). Using a cut point of 15 ng/L, sensitivity was 94%, specificity 60%, positive predictive value 18%, and negative predictive value 99%. Conclusions— A high-sensitivity cTnI assay seems useful to rule out AR in cardiac transplant recipients. If validated in prospective studies, a strategy of serial monitoring with a high-sensitivity cTnI assay may offer a low-cost noninvasive strategy for rejection surveillance.

Objective To test a multidisciplinary approach to reduce heart failure (HF) readmissions that tailors the intensity of care transition intervention to the risk of the patient using a suite of electronic medical record (EMR)-enabled programmes. Methods A prospective controlled before and after study of adult inpatients admitted with HF and two concurrent control conditions (acute myocardial infarction (AMI) and pneumonia (PNA)) was performed between 1 December 2008 and 1 December 2010 at a large urban public teaching hospital. An EMR-based software platform stratified all patients admitted with HF on a daily basis by their 30-day readmission risk using a published electronic predictive model. Patients at highest risk received an intensive set of evidence-based interventions designed to reduce readmission using existing resources. The main outcome measure was readmission for any cause and to any hospital within 30 days of discharge. Results There were 834 HF admissions in the pre-intervention period and 913 in the post-intervention period. The unadjusted readmission rate declined from 26.2% in the pre-intervention period to 21.2% in the post-intervention period (p=0.01), a decline that persisted in adjusted analyses (adjusted OR (AOR)=0.73; 95% CI 0.58 to 0.93, p=0.01). In contrast, there was no significant change in the unadjusted and adjusted readmission rates for PNA and AMI over the same period. There were 45 fewer readmissions with 913 patients enrolled and 228 patients receiving intervention, resulting in a number needed to treat (NNT) ratio of 20. Conclusions An EMR-enabled strategy that targeted scarce care transition resources to high-risk HF patients significantly reduced the risk-adjusted odds of readmission.