UNASSIGNED: Activin A is a key regulator in liver regeneration, but data evaluating its role in humans after hepatic surgery are limited. In this study we explore the predictive role of circulating activin A, its antagonist follistatin-like 3 (FSTL-3), and their ratio for posthepatectomy liver failure (PHLF) and monitor their levels after surgery, to evaluate their role in human liver regeneration.
UNASSIGNED: Activin A and FSTL-3 levels were assessed in 59 patients undergoing liver surgery. Using receiver operating characteristic analysis, we evaluated the predictive potential of activin A, FSTL-3, and their ratio.
UNASSIGNED: While perioperative dynamics of activin A and FSTL3 were significantly affected by hepatic resection (activin A P = .045, FSTL-3 P = .005), their functionally relevant ratio did not significantly change (P = .528). Neither activin A nor FSTL-3 alone but only their ratio exhibited a significant predictive potential for PHLF (area under the curve: 0.789, P = .038). Patients with low preoperative activin A/FSTL-3 ratio were found to more frequently suffer from PHLF (0.017) and morbidity (0.005).
UNASSIGNED: Activin A/FSTL-3 ratio predicts PHLF and morbidity. Its significance in preoperative patient assessment needs to be further validated in larger, independent cohorts.

BACKGROUND: Liver stiffness (LS) measurement with two-dimensional shear wave elastography (2D-SWE) correlates with the degree of liver fibrosis and thus indirectly reflects liver function reserve. The size of the spleen increases due to tissue proliferation, fibrosis, and portal vein congestion, which can indirectly reflect the situation of liver fibrosis/cirrhosis. It was reported that the size of the spleen was related to posthepatectomy liver failure (PHLF). So far, there has been no study combining 2D-SWE measurements of LS with spleen size to predict PHLF. This prospective study aimed to investigate the utility of 2D-SWE assessing LS and spleen area (SPA) for the prediction of PHLF in hepatocellular carcinoma (HCC) patients and to develop a risk prediction model.
OBJECTIVE: To investigate the utility of 2D-SWE assessing LS and SPA for the prediction of PHLF in HCC patients and to develop a risk prediction model.
METHODS: This was a multicenter observational study prospectively analyzing patients who underwent hepatectomy from October 2020 to March 2022. Within 1 wk before partial hepatectomy, ultrasound examination was performed to measure LS and SPA, and blood was drawn to evaluate the patient\'s liver function and other conditions. Least absolute shrinkage and selection operator logistic regression and multivariate logistic regression analysis was applied to identify independent predictors of PHLF and develop a nomogram. Nomogram performance was validated further. The diagnostic performance of the nomogram was evaluated with receiver operating characteristic curve compared with the conventional models, including the model for end-stage liver disease (MELD) score and the albumin-bilirubin (ALBI) score.
RESULTS: A total of 562 HCC patients undergoing hepatectomy (500 in the training cohort and 62 in the validation cohort) were enrolled in this study. The independent predictors of PHLF were LS, SPA, range of resection, blood loss, international normalized ratio, and total bilirubin. Better diagnostic performance of the nomogram was obtained in the training [area under receiver operating characteristic curve (AUC): 0.833; 95% confidence interval (95%CI): 0.792-0.873; sensitivity: 83.1%; specificity: 73.5%] and validation (AUC: 0.802; 95%CI: 0.684-0.920; sensitivity: 95.5%; specificity: 52.5%) cohorts compared with the MELD score and the ALBI score.
CONCLUSIONS: This PHLF nomogram, mainly based on LS by 2D-SWE and SPA, was useful in predicting PHLF in HCC patients and presented better than MELD score and ALBI score.

UNASSIGNED: Posthepatectomy liver failure (PHLF) is a serious complication associated with high mortality rates. Machine learning (ML) has rapidly developed and may outperform traditional models in predicting PHLF in patients who have undergone hepatectomy. This study aimed to predict PHLF using ML and compare its performance with that of traditional scoring systems.
UNASSIGNED: The clinicopathological data of 334 patients who underwent liver resection were retrospectively collected. The Pycaret library, a simple, open-source machine learning library, was used to compare multiple classification models for PHLF prediction. The predictive performance of 15 ML algorithms was compared using the mean area under the receiver operating characteristic curve (AUROC) and accuracy, and the best-fit model was selected among 15 ML algorithms. Next, the predictive performance of the selected ML-PHLF model was compared with that of routine scoring systems, the albumin-bilirubin score (ALBI) and the fibrosis-4 (FIB-4) index, using AUROC.
UNASSIGNED: The best model was extreme gradient boosting (accuracy:93.1%; AUROC:0.863) among the 15 ML algorithms. As compared with ALBI and FIB-4, the ML PHLF model had higher AUROC for predicting PHLF.
UNASSIGNED: The novel ML model for predicting PHLF outperformed routine scoring systems.

BACKGROUND: Posthepatectomy liver failure (PHLF) is one of the most important causes of death following liver resection. Heparin, an established anticoagulant, can protect liver function through a number of mechanisms, and thus, prevent liver failure.
OBJECTIVE: To look at the safety and efficacy of heparin in preventing hepatic dysfunction after hepatectomy.
METHODS: The data was extracted from Multiparameter Intelligent Monitoring in Intensive Care III (MIMIC-III) v1. 4 pinpointed patients who had undergone hepatectomy for liver cancer, subdividing them into two cohorts: Those who were injected with heparin and those who were not. The statistical evaluations used were unpaired t-tests, Mann-Whitney U tests, chi-square tests, and Fisher\'s exact tests to assess the effect of heparin administration on PHLF, duration of intensive care unit (ICU) stay, need for mechanical ventilation, use of continuous renal replacement therapy (CRRT), incidence of hypoxemia, development of acute kidney injury, and ICU mortality. Logistic regression was utilized to analyze the factors related to PHLF, with propensity score matching (PSM) aiming to balance the preoperative disparities between the two groups.
RESULTS: In this study, 1388 patients who underwent liver cancer hepatectomy were analyzed. PSM yielded 213 matched pairs from the heparin-treated and control groups. Initial univariate analyses indicated that heparin potentially reduces the risk of PHLF in both matched and unmatched samples. Further analysis in the matched cohorts confirmed a significant association, with heparin reducing the risk of PHLF (odds ratio: 0.518; 95% confidence interval: 0.295-0.910; P = 0.022). Additionally, heparin treatment correlated with improved short-term postoperative outcomes such as reduced ICU stay durations, diminished requirements for respiratory support and CRRT, and lower incidences of hypoxemia and ICU mortality.
CONCLUSIONS: Liver failure is an important hazard following hepatic surgery. During ICU care heparin administration has been proved to decrease the occurrence of hepatectomy induced liver failure. This indicates that heparin may provide a hopeful option for controlling PHLF.

OBJECTIVE: To evaluate the predictive ability of combining Technetium-99m-galactosyl human serum albumin (99mTc‑GSA) single-photon emission computed tomography (SPECT)/computed tomography (CT) volume and plasma clearance rate of indocyanine green (ICGK) for posthepatectomy liver failure (PHLF).
METHODS: Fifty patients who underwent 99mTc-GSA scintigraphy as a preoperative examination for segmentectomy or more from July 2021 to June 2023 were evaluated prospectively. Patients were divided into two groups according to the presence or absence of posthepatectomy liver failure (PHLF). Total functional liver volume (t-FLV) and remnant FLV (r-FLV) were measured from 99mTc-GSA SPECT/CT image. Future liver remnant ICGK (ICGK-F) was calculated by ICGK and remnant liver volume from CT. Area under the curve (AUC) of ICGK-F, r-FLV, r-FLV/t-FLV, ICGK × r-FLV, ICGK × r-FLV/t-FLV was calculated to evaluate predictive ability of each parameter for PHLF.
RESULTS: PHLF was occurred in 7 patients. AUC of ICGK × r-FLV was significantly higher than that of ICGK-F (0.99; 95% confidence interval [CI]: 0.96-1 vs 0.82; 95%CI: 0.64-0.96; p = 0.036). There was no significant difference between the AUC of r-FLV, r-FLV/t-FLV, ICGK × r-FLV/t-FLV and that of ICGK-F, respectively.
CONCLUSIONS: The combination of 99mTc‑GSA SPECT/CT volume and ICGK can predict PHLF more accurately than ICGK-F.

暂无摘要。

BACKGROUND: Posthepatectomy liver failure (PHLF), complications of portal hypertension, and disease recurrence determine the outcome for hepatocellular carcinoma (HCC) patients undergoing liver resection. This study aimed to evaluate the von Willebrand factor antigen (vWF-Ag) as a non-invasive test for clinically significant portal hypertension (CSPH) and a predictive biomarker for time to recurrence (TTR) and overall survival (OS).
METHODS: The study recruited 72 HCC patients with detailed preoperative workup from a prospective trial (NCT02118545) and followed for complications, TTR, and OS. Additionally, 163 compensated patients with resectable HCC were recruited to evaluate vWF-Ag cutoffs for ruling out or ruling in CSPH. Finally, vWF-Ag cutoffs were prospectively evaluated in an external validation cohort of 34 HCC patients undergoing liver resection.
RESULTS: In receiver operating characteristic (ROC) analyses, vWF-Ag (area under the curve [AUC], 0.828) was similarly predictive of PHLF as indocyanine green clearance (disappearance rate: AUC, 0.880; retention rate: AUC, 0.894), whereas computation of future liver remnant was inferior (AUC, 0.756). Cox-regression showed an association of vWF-Ag with TTR (per 10%: hazard ratio [HR], 1.056; 95% confidence interval [CI] 1.017-1.097) and OS (per 10%: HR, 1.067; 95% CI 1.022-1.113). In the analyses, VWF-Ag yielded an AUC of 0.824 for diagnosing CSPH, with a vWF-Ag of 182% or lower ruling out and higher than 291% ruling in CSPH. Therefore, a highest-risk group (> 291%, 9.7% of patients) with a 57.1% incidence of PHLF was identified, whereas no patient with a vWF-Ag of 182% or lower (52.7%) experienced PHLF. The predictive value of vWF-Ag for PHLF and OS was externally validated.
CONCLUSIONS: For patients with resectable HCC, VWF-Ag allows for simplified preoperative risk stratification. Patients with vWF-Ag levels higher than 291% might be considered for alternative treatments, whereas vWF-Ag levels of 182% or lower identify patients best suited for surgery.

Significant advances in surgical techniques and relevant medium- and long-term outcomes over the past two decades have led to a substantial expansion in the indications for major liver resections. To support these outstanding results and to reduce perioperative complications, anesthesiologists must address and master key perioperative issues (preoperative assessment, proactive intraoperative anesthesia strategies, and implementation of the Enhanced Recovery After Surgery approach). Intensive care unit monitoring immediately following liver surgery remains a subject of active and often unresolved debate. Among postoperative complications, posthepatectomy liver failure (PHLF) occurs in different grades of severity (A-C) and frequency (9%-30%), and it is the main cause of 90-d postoperative mortality. PHLF, recently redefined with pragmatic clinical criteria and perioperative scores, can be predicted, prevented, or anticipated. This review highlights: (1) The systemic consequences of surgical manipulations anesthesiologists must respond to or prevent, to positively impact PHLF (a proactive approach); and (2) the maximal intensive treatment of PHLF, including artificial options, mainly based, so far, on Acute Liver Failure treatment(s), to buy time waiting for the recovery of the native liver or, when appropriate and in very selected cases, toward liver transplant. Such a clinical context requires a strong commitment to surgeons, anesthesiologists, and intensivists to work together, for a fruitful collaboration in a mandatory clinical continuum.

BACKGROUND: Previous research has demonstrated the impact of postoperative phosphate levels on liver regeneration and outcomes after liver resection surgeries, a potential predictor for regenerative success and liver failure. However, little is known about the association between low preoperative serum phosphate levels and outcomes in liver resections.
METHODS: We performed a retrospective analysis of liver resections performed at our institution. Patients were categorized based on preoperative phosphate levels (low versus normal). Our primary outcome measure was posthepatectomy liver failure.
RESULTS: A total of 265 cases met the study criteria. 71 patients (26.7%) had low preoperative phosphate levels. The incidence of posthepatectomy liver failure was higher in the low preoperative phosphate group (19.2% versus 12.4%). However, after propensity score matching, rates of posthepatectomy liver failure were similar between low and normal preoperative phosphate cohorts (13% versus 14%, P = 0.83).
CONCLUSIONS: Low preoperative phosphate levels were not associated with worse postoperative outcomes in this study. Further studies are warranted to investigate this association and its relevance as a clinical prognostic factor for postoperative liver failure.

UNASSIGNED: Liver surgery is an essential component of hepatocellular carcinoma (HCC) treatment. Advances in surgical techniques and perioperative care have improved outcomes and have helped to expand surgical indications. However, liver fibrosis and cirrhosis still remain major problems for liver surgery due to the relevant impact on liver regeneration of the future liver remnant (FLR) after surgery. Especially in patients with clinically significant portal hypertension due to liver cirrhosis, surgery is limited. Despite recent efforts in developing predictive models, estimating the postoperative hepatic function remains difficult.
UNASSIGNED: In this review, we focus on the role of surgery in the treatment of HCC in structurally altered livers. The importance of assessing FLR with techniques such as contrast-enhanced CT, e.g., with the help of artificial intelligence is highlighted. Moreover, strategies for increasing the FLR with approaches like portal vein embolization and liver vein deprivation prior to surgery are discussed. Patient selection, minimally invasive liver surgery including robotic techniques, and perioperative concepts like the Enhanced Recovery After Surgery (ERAS) guidelines are identified as crucial parts of avoiding posthepatectomy liver failure.
UNASSIGNED: The need for ongoing research to optimize patient selection criteria and perioperative care and to develop innovative biomarkers for outcome prediction is emphasized.