Effects of Intensive Blood Glucose Control on Surgical Site Infection for Liver Transplant Recipients: A Randomized Controlled Trial

Oliveira, Ramon Antônio; Tanner, Judith; Mancero, Jorge Marcelo Padilla; Poveda, Vanessa de Brito

doi:10.1016/j.transproceed.2022.10.062

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…Oliveira et al reported the effects of intensive blood glucose control (IBGC) on surgical site infection (SSI) for LT recipients. 53 The IBGC target was 80 to 130 mg/dL, and the standard blood glucose control (SBGC) target was below 180 mg/ dL. The protocol was initiated after LT recipients' admission to the ICU.…”

Section: Postoperative Managementmentioning

confidence: 99%

Abdominal Organ Transplantation: Noteworthy Literature in 2023

Katayama,

Maffucci,

Domanski

et al. 2024

Semin Cardiothorac Vasc Anesth

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This review highlights noteworthy literature published in 2023 and pertinent to anesthesiologists and critical care physicians caring for patients undergoing abdominal organ transplantation. We feature 9 studies from 593 peer-reviewed papers on pancreatic transplantation, 3 from 194 on intestinal transplantation, and 28 from over 4513 on kidney transplantation. The liver transplantation section includes a special focus on 20 studies from 5666 clinical trial publications. We explore a broad range of topics, including donor management, perioperative recipient management, and innovative pharmacologic and mechanical interventions tested for the improvement of patient and graft outcomes and survival.

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Section: Postoperative Managementmentioning

confidence: 99%

Abdominal Organ Transplantation: Noteworthy Literature in 2023

Katayama,

Maffucci,

Domanski

et al. 2024

Semin Cardiothorac Vasc Anesth

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“…Just recently, diabetes mellitus (DM) has emerged as a previously underestimated complication following LT, which can primarily be attributed to the interference of postoperative immunosuppressive therapy with the patient's glucose metabolism, leading to high blood sugar levels and the development of DM. DM after LT can increase the risk of infection, wound healing complications, and cardiovascular disease, all of which ultimately reduce the patient's quality of life and survival rate [11][12][13][14]. It is important to acknowledge that the risk of developing DM after LT is dependent on several factors, including the type and dose of immunosuppressive drugs, age, family history, and preexisting medical conditions [15].…”

Section: Introductionmentioning

confidence: 99%

Prediction of New-Onset Diabetes Mellitus within 12 Months after Liver Transplantation—A Machine Learning Approach

Loosen

Krieg

Chaudhari

et al. 2023

JCM

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Background: Liver transplantation (LT) is a routine therapeutic approach for patients with acute liver failure, end-stage liver disease and/or early-stage liver cancer. While 5-year survival rates have increased to over 80%, long-term outcomes are critically influenced by extrahepatic sequelae of LT and immunosuppressive therapy, including diabetes mellitus (DM). In this study, we used machine learning (ML) to predict the probability of new-onset DM following LT. Methods: A cohort of 216 LT patients was identified from the Disease Analyzer (DA) database (IQVIA) between 2005 and 2020. Three ML models comprising random forest (RF), logistic regression (LR), and eXtreme Gradient Boosting (XGBoost) were tested as predictors of new-onset DM within 12 months after LT. Results: 18 out of 216 LT patients (8.3%) were diagnosed with DM within 12 months after the index date. The performance of the RF model in predicting the development of DM was the highest (accuracy = 79.5%, AUC 77.5%). It correctly identified 75.0% of the DM patients and 80.0% of the non-DM patients in the testing dataset. In terms of predictive variables, patients’ age, frequency and time of proton pump inhibitor prescription as well as prescriptions of analgesics, immunosuppressants, vitamin D, and two antibiotic drugs (broad spectrum penicillins, fluocinolone) were identified. Conclusions: Pending external validation, our data suggest that ML models can be used to predict the occurrence of new-onset DM following LT. Such tools could help to identify LT patients at risk of unfavorable outcomes and to implement respective clinical strategies of prevention.

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Effects of Intensive Blood Glucose Control on Surgical Site Infection for Liver Transplant Recipients: A Randomized Controlled Trial

Cited by 2 publications

References 26 publications

Abdominal Organ Transplantation: Noteworthy Literature in 2023

Abdominal Organ Transplantation: Noteworthy Literature in 2023

Prediction of New-Onset Diabetes Mellitus within 12 Months after Liver Transplantation—A Machine Learning Approach

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