Predictors of micro-costing components in liver transplantation

OBJECTIVES: Although liver transplantation procedures are common and highly expensive, their cost structure is still poorly understood. This study aimed to develop models of micro-costs among patients undergoing liver transplantation procedures while comparing the role of individual clinical predictors using tree regression models. METHODS: We prospectively collected micro-cost data from patients undergoing liver transplantation in a tertiary academic center. Data collection was conducted using an Intranet registry integrated into the institution’s database for the storing of financial and clinical data for transplantation cases. RESULTS: A total of 278 patients were included and accounted for 300 procedures. When evaluating specific costs for the operating room, intensive care unit and ward, we found that in all of the sectors but the ward, human resources were responsible for the highest costs. High cost supplies were important drivers for the operating room, whereas drugs were among the top four drivers for all sectors. When evaluating the predictors of total cost, a MELD score greater than 30 was the most important predictor of high cost, followed by a Donor Risk Index greater than 1.8. CONCLUSION: By focusing on the highest cost drivers and predictors, hospitals can initiate programs to reduce cost while maintaining high quality care standards

Uterine transplantation: a systematic review

Up to 15% of the reproductive population is infertile, and 3 to 5% of these cases are caused by uterine dysfunction. This abnormality generally leads women to consider surrogacy or adoption. Uterine transplantation, although still experimental, may be an option in these cases. This systematic review will outline the recommendations, surgical aspects, immunosuppressive drugs and reproductive aspects related to experimental uterine transplantation in women

Predictors of micro-costing components in liver transplantation

OBJECTIVES: Although liver transplantation procedures are common and highly expensive, their cost structure is still poorly understood. This study aimed to develop models of micro-costs among patients undergoing liver transplantation procedures while comparing the role of individual clinical predictors using tree regression models. METHODS: We prospectively collected micro-cost data from patients undergoing liver transplantation in a tertiary academic center. Data collection was conducted using an Intranet registry integrated into the institution’s database for the storing of financial and clinical data for transplantation cases. RESULTS: A total of 278 patients were included and accounted for 300 procedures. When evaluating specific costs for the operating room, intensive care unit and ward, we found that in all of the sectors but the ward, human resources were responsible for the highest costs. High cost supplies were important drivers for the operating room, whereas drugs were among the top four drivers for all sectors. When evaluating the predictors of total cost, a MELD score greater than 30 was the most important predictor of high cost, followed by a Donor Risk Index greater than 1.8. CONCLUSION: By focusing on the highest cost drivers and predictors, hospitals can initiate programs to reduce cost while maintaining high quality care standards

Higher MELD score increases the overall cost on the waiting list for liver transplantation: a micro-costing analysis based study

ABSTRACT BACKGROUND: The pre-transplant period is complex and includes lots of procedures. The severity of liver disease predisposes to a high number of hospitalizations and high costs procedures. Economic evaluation studies are important tools to handle costs on the waiting list for liver transplantation. OBJECTIVE: The objective of the present study was to evaluate the total cost of the patient on the waiting list for liver transplantation and the main resources related to higher costs. METHODS: A cost study in a cohort of 482 patients registered on waiting list for liver transplantation was carried out. In 24 months follow-up, we evaluated all costs of materials, medicines, consultations, procedures, hospital admissions, laboratorial tests and image exams, hemocomponents replacements, and nutrition. The total amount of each resource or component used was aggregated and multiplied by the unitary cost, and thus individual cost for each patient was obtained. RESULTS: The total expenditure of the 482 patients was US$6,064,986.51. Outpatient and impatient costs correspond to 32.4$ 1,965,045.52) and 67.6% (US$4,099,940.99) respectively. Main cost drivers in outpatient were: medicines (44.31$ 16,686.74 ± 16,105.02) and the less expensive were those with MELD below 17 (US$ 5,703.22 ± 9,318.68). CONCLUSION: Total costs on the waiting list for liver transplantation increased according to the patient’s severity. Individually, hospitalizations, hemocomponents reposition and hepatocellular carcinoma treatment were the main cost drivers to the patient on the waiting list. The longer the waiting time, the higher the total cost on list, causing greater impact on health systems

Lymph Node Involvement and Not the Histophatologic Subtype Is Correlated with Outcome After Resection of Adenocarcinoma of the Ampulla of Vater

Background Intestinal and pancreaticobiliary types of Vater`s ampulla adenocarcinoma have been considered as having different biologic behavior and prognosis. The aim of the present study was to determine the best immunohistochemical panel for tumor classification and to analyze the survival of patients having these histological types of adenocarcinoma. Method Ninety-seven resected ampullary adenocarcinomas were histologically classified, and the prognosis factors were analyzed. The expression of MUC1, MUC2, MUC5AC, MUC6, CK7, CK17, CK20, CD10, and CDX2 was evaluated by using immunohistochemistry. Results Forty-three Vater`s ampulla carcinomas were histologically classified as intestinal type, 47 as pancreaticobiliary, and seven as other types. The intestinal type had a significantly higher expression of MUC2 (74.4% vs. 23.4%), CK20 (76.7% vs. 29.8%), CDX2 (86% vs. 21.3%), and CD10 (81.4% vs. 51.1%), while MUC1 (53.5% vs. 82.9%) and CK7 (79.1% vs. 95.7%) were higher in pancreatobiliary adenocarcinomas. The most accurate markers for immunohistochemical classification were CDX2, MUC1, and MUC2. Survival was significantly affected by pancreaticobiliary type (p=0.021), but only lymph node metastasis, lymphatic invasion, and stage were independent risk factors for survival in a multivariate analysis. Conclusion The immunohistochemical expression of CDX2, MUC1, and MUC2 allows a reproducible classification of ampullary carcinomas. Although carcinomas of the intestinal type showed better survival in the univariate analysis, neither histological classification nor immunohistochemistry were independent predictors of poor prognosis

Early detection of acute kidney injury in the perioperative period of liver transplant with neutrophil gelatinase-associated lipocalin.

BACKGROUND:Acute kidney injury (AKI) is a common complication in patients undergoing liver transplant (LT) and is associated with high morbidity and mortality. We aim to evaluate the pattern of urine and plasma neutrophil gelatinase-associated lipocalin (NGAL) elevation during the perioperative period of LT and to assess it as a prognostic marker for AKI progression, need for dialysis and mortality. METHODS:We assessed NGAL levels before induction of anesthesia, after portal reperfusion and at 6, 18, 24, and 48 h after surgery. Patients were monitored daily during the first week after LT. RESULTS:Of 100 enrolled patients undergoing liver transplant, 59 developed severe AKI based on the KDIGO serum creatinine (sCr) criterion; 34 were dialysed, and 21 died within 60 days after LT. Applying a cut-off value of 136 ng/ml, UNGAL values 6 h after surgery was a good predictor of AKI development within 7 days after surgery, having a positive predictive value (PPV) of 80% with an AUC of 0.76 (95% CI 0.67-0.86). PNGAL at 18 h after LT was also a good predictor of AKI in the first week, having a PPV of 81% and AUC of 0.74 (95% CI 0.60-0.88). Based on PNGAL and UNGAL cut-off criteria levels, time to AKI diagnosis was 28 and 23 h earlier than by sCr, respectively. The best times to assess the need for dialysis were 18 h after LT by PNGAL and 06 h after LT by UNGAL. CONCLUSION:In conclusion, the plasma and urine NGAL elevation pattern in the perioperative period of the liver transplant can predict AKI diagnosis earlier. UNGAL was an early independent predictor of AKI development and need for dialysis. Further studies are needed to assess whether the clinical use of biomarkers can improve patient outcomes. TRIAL REGISTRATION:Registered at Clinical Trials ( clinicaltrials.gov ) in March 24th, 2014 by title "Acute Kidney Injury Biomarkers: Diagnosis and Application in Pre-operative Period of Liver Transplantation (AKIB)" and identifier NCT02095431, retrospectively registered