Notes

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Donor-derived cell-free DNA (dd-cfDNA) is a potential noninvasive molecular marker of graft rejection after kidney transplant, whose diagnostic accuracy remains controversial.

We performed a systematic review and meta-analysis to evaluate the diagnostic accuracy of dd-cfDNA. Relevant literature was searched from online databases, and the data on the diagnostic accuracy of discriminating main rejection episodes (MRE) and antibody-mediated rejection (AMR) were merged, respectively.

Nine studies were included in the meta-analysis, of which 6 were focused on the diagnostic accuracy of dd-cfDNA for MRE, whose pooled sensitivity, specificity, area under the receiver operating characteristics curve (AUC), diagnostic odds ratio(DOR), overall positive likelihood ratio (PLR), and negative likelihood ratio (NLR) with 95% confidence intervals were 0.70(0.57-0.81), 0.78(0.70-0.84), 0.81(0.77-0.84), 8.18(5.11-13.09), 3.15(2.47-4.02), 0.39(0.27-0.55), respectively. 5 tests were focused on discriminating AMR, whose pooled indicators were 0.84(0.75-0.90), 0.80(0.74-0.84), 0.89(0.86-0.91), 20.48(10.76-38.99), 4.13(3.21-5.33), 0.20(0.12-0.33), respectively.

Donor-derived cell-free DNA can be a helpful marker for the diagnosis of antibody-mediated rejection among those recipients suspected of renal dysfunction. Its diagnostic accuracy on the main rejection episodes remains uncertain, which requires further prospective, large-scale, multicenter, and common population research.
Donor-derived cell-free DNA can be a helpful marker for the diagnosis of antibody-mediated rejection among those recipients suspected of renal dysfunction. Its diagnostic accuracy on the main rejection episodes remains uncertain, which requires further prospective, large-scale, multicenter, and common population research.
Patients' loss to follow-up (LFU) has significant impacts on outcomes and is a barrier to improving care, especially in adolescent and young adult (AYA) renal transplant recipients. There is limited information regarding the relationship between transfer of care from pediatric to adult transplant centers, age and LFU among AYA renal transplant recipients.

We studied 16 386 individuals aged 10-29 who received kidney transplants between 1/1/2005 - 12/31/2015 using the Scientific Registry of Transplant Recipients. The primary outcome was LFU, which was defined as >1 year without follow-up in a transplant clinic/program. Death or graft failure within a year of the last follow-up was not classified as LFU. We performed a retrospective cohort study describing LFU using Pearson's chi-square tests. Multivariable logistic regression was used to estimate the change in likelihood of LFU associated with recipient characteristics and institution transfer.

22.26% (N=3647) of our study population met criteria for LFU.11.17% (N=1830) transferred institutions during the study period. LFU occurred in 50.18% of recipients who transferred institutions. LFU peaked at age 20, with 7.4% of 20-year-olds being LFU. The odds of LFU among renal transplant recipients who transferred institutions was 3.36 times greater (95% confidence interval 3.1, 3.6) than the odds of LFU among those who did not transfer institutions.

LFU is a critical problem facing AYA renal transplant recipients, and institution transfer is a significant risk factor for LFU. Additional studies investigating the interplay between age, institution transfer, and LFU in the AYA population are still needed.
LFU is a critical problem facing AYA renal transplant recipients, and institution transfer is a significant risk factor for LFU. Additional studies investigating the interplay between age, institution transfer, and LFU in the AYA population are still needed.
Fast-track anesthesia in liver transplantation (LT) has been discussed over the past few decades; however, factors associated with immediate extubation after LT surgery are not well defined. This study aimed to identify predictive factors and examine impacts of immediate extubation on post-LT outcomes.

A total of 279 LT patients between January 2014 and May 2017 were included. Primary outcome was immediate extubation after LT. Other post-operation outcomes included reintubation, ICU stay and cost, pulmonary complications within 90 days, and 90-day graft survival. Logistic regression was performed to identify factors that were predictive for immediate extubation. check details A matched control was used to study immediate extubation effect on the other post-operation outcomes.

Of these 279 patients, 80 (28.7%) underwent immediate extubation. Patients with anhepatic time >75min and with total intraoperative blood transfusion ≥12units were less likely to be immediately extubated (odds ratio [OR]=0.48; 95% confidence interval [CI]=0.26-0.89, P=0.02; OR=0.11; 95%CI=0.05-0.21, P<0.001). The multivariable analysis showed immediate extubation significantly decreased the risk of pulmonary complications (OR=0.34, 95%CI=0.15-0.77, P=0.01). According to a matched case-control model (immediate group [n=72], delayed group [n=72]), the immediate group had a significantly lower rate of pulmonary complications (11.1% vs 27.8%, P=0.012). ICU stay and cost were relatively lower in the immediate group (2 vs 3 days, P=0.082, $5700 vs $7710, P=0.11). Reintubation rates (2.8% vs 2.8%, P>0.9) and 90-day graft survival rates (95.8% vs 98.6%, P=0.31) were similar.

Immediate extubation post-LT in appropriate patients is safe and may improve patient outcomes and resource allocation.
Immediate extubation post-LT in appropriate patients is safe and may improve patient outcomes and resource allocation.
Approximately 3.7% of patients experience adverse events in health care facilities, many of which are preventable. Patient safety requires effective training and an interprofessional culture of safety, but few studies compare the safety skills of different hospital professions. We sought to assess skills in safety hazards identification among staff from different health care disciplines with a pilot study.

An exercise with a simulated room of an inpatient ward with a patient mannequin in a hospital bed with 34-intentionally planted safety hazards was set up. Health care staff members from various professions walked around the room and independently documented observed safety hazards. Identified hazards were separated based on staff disciplines, grouped into 5 categories (patient, medications, equipment, environment, care processes), and analyzed using analysis of variance. Because participants identified more hazards than the 34 intentionally planted hazards, these were analyzed separately.

The study included 111 staff nurses (n = 68), nursing students (n = 5), medical students (n = 3), physicians (n = 11), social workers (n = 5), pharmacists (n = 6), certified nursing assistants (n = 9), and psychologists (n = 4).
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