Certification Training and Liver Transplant Experience Improves Liver Procurement Outcomes: The Dutch Approach.

BACKGROUND: This study investigates the impact of certification training and liver transplant experience on procurement outcomes of deceased donor liver procurement in the Netherlands. METHODS: Three groups (trainee, certified, and master) were formed, with further subdivision based on liver transplant experience. Three key outcomes-surgical injury, graft discard after injury, and donor hepatectomy duration-were analyzed. RESULTS: There were no significant differences in surgical graft injury in the three groups (trainee, 16.9%; certified, 14.8%; master, 18.2%; P  = 0.357; 2011 to 2018). The only predictor for surgical graft injury was donation after circulatory death (odds ratio [OR], 1.49; 95% confidence interval [CI], 1.10-2.02). Of the three groups, the master group had the highest discard rate after surgical injury (trainee, 0%; certified, 1.3%; master, 2.8%; P  = 0.013). Master group without liver transplant experience (OR, 3.16; 95% CI, 1.21-8.27) and male donor sex (OR, 3.58; 95% CI, 1.32-9.73) were independent risk factors for discarding livers after surgical injury. Independent predictors for shorter hepatectomy durations included donors older than 50 years (coefficient [Coeff], -7.04; 95% CI, -8.03 to -3.29; P  < 0.001), and master group (Coeff, -9.84; 95% CI, -14.37 to -5.31; P  < 0.001) and certified group with liver transplant experience (Coeff, -6.54; 95% CI, -10.83 to -2.26; P  = 0.003). On the other hand, master group without liver transplant experience (Coeff, 5.00; 95% CI, 1.03-8.96; P  = 0.014) and donation after circulatory death (Coeff, 10.81; 95% CI, 8.32-13.3; P  < 0.001) were associated with longer hepatectomy durations. CONCLUSIONS: Training and certification in abdominal organ procurement surgery were associated with a reduced discard rate for surgical injured livers and shorter hepatectomy times. The contrast between master group with and without liver transplant experience underscores the need for specialized training in this field.

Quality assessment of donor liver procurement surgery using an unadjusted CUSUM prediction model. A practical nationwide evaluation.

BACKGROUND: The aim of this study was to analyze the value of the unadjusted CUSUM graph of liver surgical injury and discard rates in organ procurement in the Netherlands. METHODS: Unadjusted CUSUM graphs were plotted for surgical injury (C event) and discard rate (C2 event) from procured livers accepted for transplantation for each local procurement team compared with the total national cohort. The average incidence for each outcome was used as benchmark based on procurement quality forms (Sep 2010-Oct 2018). The data from the five Dutch procuring teams were blind-coded. RESULTS: The C and C2 event rate were 17% and 1.9%, respectively (n = 1265). A total of 12 CUSUM charts were plotted for the national cohort and the five local teams. National CUSUM charts showed an overlapping "alarm signal." This overlapping signal for both C and C2, albeit a different time period, was only found in one local team. The other CUSUM alarm signal went off for two separate local teams, but only for C events or C2 events respectively, and at different points in time. The other remaining CUSUM charts showed no alarm signaling. CONCLUSION: The unadjusted CUSUM chart is a simple and effective monitoring tool in following performance quality of organ procurement for liver transplantation. Both national and local recorded CUSUMs are useful to see the implication of national and local effects on organ procurement injury. Both procurement injury and organ discard are equally important in this analysis and need to be separately CUSUM charted.

Improved Mortality Prediction in Dialysis Patients Using Specific Clinical and Laboratory Data.

BACKGROUND: Risk prediction models can be used to inform patients undergoing renal replacement therapy about their survival chances. Easily available predictors such as registry data are most convenient, but their predictive value may be limited. We aimed to improve a simple prediction model based on registry data by incrementally adding sets of clinical and laboratory variables. METHODS: Our data set includes 1,835 Dutch patients from the Netherlands Cooperative Study on the Adequacy of Dialysis. The potential survival predictors were categorized on availability. The first category includes easily available clinical data. The second set includes laboratory values like albumin. The most laborious category contains glomerular filtration rate (GFR) and Kt/V. Missing values were substituted using multiple imputation. Within 1,225 patients, we recalibrated the registry model and subsequently added parameter sets using multivariate Cox regression analyses with backward selection. On the other 610 patients, calibration and discrimination (C-index, integrated discrimination improvement (IDI) index and net reclassification improvement (NRI) index) were assessed for all models. RESULTS: The recalibrated registry model showed adequate calibration and discrimination (C-index=0.724). Adding easily available parameters resulted in a model with 10 predictors, with similar calibration and improved discrimination (C-index=0.784). The IDI and NRI indices confirmed this, especially for short-term survival. Adding laboratory values resulted in an alternative model with similar discrimination (C-index=0.788), and only the NRI index showed minor improvement. Adding GFR and Kt/V as candidate predictors did not result in a different model. CONCLUSION: A simple model based on registry data was enhanced by adding easily available clinical parameters.

Patient survival after the diagnosis of cancer in renal transplant recipients: a nested case-control study.

INTRODUCTION: Malignancy is a well-known complication after renal transplantation. We studied the influence of cancer on patient survival in the Dutch renal transplant population in a nested case-controlled analysis. METHODS: Between March 1966 and May 2008, 15,227 renal transplantations in 12,805 recipients were registered in the Netherlands Organ Transplant Registry database. Total follow-up was 89,651 person years. We performed an analysis of patient and graft survival both from the day of transplantation and the diagnosis of cancer in recipients with invasive cancer. Recipients without invasive cancer, matched for gender, age, and year of transplantation, served as a control group. For the survival analysis after the diagnosis of cancer, the matched control group consisted of patients with a functioning graft at the moment the index patient was diagnosed with cancer. RESULTS: Cancer had been registered in 908 (7.1%) patients, 630 (69%) of them died with functioning kidney, 510 (81%) because of their malignancy (at 8.2 years after transplantation, median). The median patient survival after transplantation was 11.9 vs. 16.8 years in the study and control group, respectively (P<0.001). The median patient and graft survival after the diagnosis of cancer was 2.1 vs. 8.3 (P<0.001) and 25 vs. 22.4 (P<0.001) years in the study and control group, respectively. CONCLUSION: Mortality because of cancer is observed at a significantly later time after transplantation compared with mortality because of the other main lethal complications. It significantly affects life expectancy and carries a poor prognosis with a limited survival after diagnosis.