Long-Duration Neoadjuvant Therapy with FOLFIRINOX Yields Favorable Outcomes for Patients Who Undergo Surgery for Pancreatic Cancer.

BACKGROUND: In 2023 alone, it's estimated that over 64,000 patients will be diagnosed with PDAC and more than 50,000 patients will die of the disease. Current guidelines recommend neoadjuvant therapy for patients with borderline resectable and locally advanced PDAC, and data is emerging on its role in resectable disease. Neoadjuvant chemotherapy may increase the number of patients able to receive complete chemotherapy regimens, increase the rate of microscopically tumor-free resection (R0) margin, and aide in identifying unfavorable tumor biology. To date, this is the largest study to examine surgical outcomes after long-duration neoadjuvant chemotherapy for PDAC. METHODS: Retrospective analysis of single-institution data. RESULTS: The routine use of long-duration therapy in our study (median cycles: FOLFIRINOX = 10; gemcitabine-based = 7) is unique. The majority (85%) of patients received FOLFIRINOX without radiation therapy; the R0 resection rate was 76%. Median OS was 41 months and did not differ significantly among patients with resectable, borderline-resectable, or locally advanced disease. CONCLUSIONS: This study demonstrates that in patients who undergo surgical resection after receipt of long-duration neoadjuvant FOLFIRINOX therapy alone, survival outcomes are similar regardless of pretreatment resectability status and that favorable surgical outcomes can be attained.

The autophagy protein RUBCNL/PACER represses RIPK1 kinase-dependent apoptosis and necroptosis.

Mesenchymal stem cells (MSCs) are used in cell therapy; nonetheless, their application is limited by their poor survival after transplantation in a proinflammatory microenvironment. Macroautophagy/autophagy activation in MSCs constitutes a stress adaptation pathway, promoting cellular homeostasis. Our proteomics data indicate that RUBCNL/PACER (RUN and cysteine rich domain containing beclin 1 interacting protein like), a positive regulator of autophagy, is also involved in cell death. Hence, we screened MSC survival upon various cell death stimuli under loss or gain of function of RUBCNL. MSCs were protected from TNF (tumor necrosis factor)-induced regulated cell death when RUBCNL was expressed. TNF promotes inflammation by inducing RIPK1 kinase-dependent apoptosis or necroptosis. We determine that MSCs succumb to RIPK1 kinase-dependent apoptosis upon TNF sensing and necroptosis when caspases are inactivated. We show that RUBCNL is a negative regulator of both RIPK1-dependent apoptosis and necroptosis. Furthermore, RUBCNL mutants that lose the ability to regulate autophagy, retain their function in negatively regulating cell death. We also found that RUBCNL forms a complex with RIPK1, which disassembles in response to TNF. In line with this finding, RUBCNL expression limits assembly of RIPK1-TNFRSF1A/TNFR1 complex I, suggesting that complex formation between RUBCNL and RIPK1 represses TNF signaling. These results provide new insights into the crosstalk between the RIPK1-mediated cell death and autophagy machineries and suggest that RUBCNL, due to its functional duality in autophagy and apoptosis/necroptosis, could be targeted to improve the therapeutic efficacy of MSCs. Abbreviations: BAF: bafilomycin A1; CASP3: caspase 3; Caspases: cysteine-aspartic proteases; cCASP3: cleaved CASP3; CQ: chloroquine; CHX: cycloheximide; cPARP: cleaved poly (ADP-ribose) polymerase; DEPs: differential expressed proteins; ETO: etoposide; MEF: mouse embryonic fibroblast; MLKL: mixed lineage kinase domain-like; MSC: mesenchymal stem cell; MTORC1: mechanistic target of rapamycin kinase complex 1; Nec1s: necrostatin 1s; NFKB/NF-kB: nuclear factor of kappa light polypeptide gene enhancer in B cells; PLA: proximity ligation assay; RCD: regulated cell death; RIPK1: receptor (TNFRSF)-interacting serine-threonine kinase 1; RIPK3: receptor-interacting serine-threonine kinase 3; RUBCNL/PACER: RUN and cysteine rich domain containing beclin 1 interacting protein like; siCtrl: small interfering RNA nonsense; siRNA: small interfering RNA; TdT: terminal deoxynucleotidyl transferase; Tm: tunicamycin; TNF: tumor necrosis factor; TNFRSF1A/TNFR1: tumor necrosis factor receptor superfamily, member 1a.

National practice patterns in the use of endoscopic ultrasound biopsy for resectable Pancreatic Neuroendocrine Tumors: Insights into the role of DOTATATE PET/CT in diagnosis.

INTRODUCTION: Pancreatic neuroendocrine tumors (PNETs) are typically diagnosed using endoscopic ultrasound-guided (EUS) biopsy, which can be associated with complications. Since 2016, DOTATATE PET/CT has emerged as an effective tool to localize and stage PNETs. METHODS: Patients with PNETs who underwent R0 resections were identified from the 2004-2019 National Cancer Database PUF. Joinpoint regression and multivariable logistic regression were used to analyze trends in the use of biopsy. RESULTS: Of 16,746 R0 resected PNET patients, 44 â€‹% underwent diagnostic biopsy. Joinpoint regression showed a significant increase in the use of biopsy from 2004 to 2019 (APC 1.80, p â€‹< â€‹0.001). A higher percentage of patients diagnosed after DOTATATE approval underwent biopsy compared to those diagnosed before (48 â€‹% vs. 42 â€‹%, p â€‹< â€‹0.001). Adjusted analysis showed diagnosis after 2016 was associated with increased odds of biopsy (OR â€‹= â€‹1.67, p â€‹< â€‹0.001). CONCLUSIONS: Despite technologic advancement with DOTATATE PET/CT, there has been a significant increase in the proportion of resectable PNETs undergoing preoperative biopsy.

A machine learning approach for predicting textbook outcome after cytoreductive surgery and hyperthermic intraperitoneal chemotherapy.

INTRODUCTION: Peritoneal carcinomatosis is considered a late-stage manifestation of neoplastic diseases. Cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC) can be an effective treatment for these patients. However, the procedure is associated with significant morbidity. Our aim was to develop a machine learning model to predict the probability of achieving textbook outcome (TO) after CRS-HIPEC using only preoperatively known variables. METHODS: Adult patients with peritoneal carcinomatosis and who underwent CRS-HIPEC were included from a large, single-center, prospectively maintained dataset (2001-2020). TO was defined as a hospital length of stay ≤14 days and no postoperative adverse events including any complications, reoperation, readmission, and mortality within 90 days. Four models (logistic regression, neural network, random forest, and XGBoost) were trained, validated, and a user-friendly risk calculator was then developed. RESULTS: A total of 1954 CRS-HIPEC procedures for peritoneal carcinomatosis were included. Overall, 13% (n = 258) achieved TO following CRS-HIPEC procedure. XGBoost and logistic regression had the highest area under the curve (AUC) (0.76) after model optimization, followed by random forest (AUC 0.75) and neural network (AUC 0.74). The top preoperative variables associated with achieving a TO were lower peritoneal cancer index scores, not undergoing proctectomy, splenectomy, or partial colectomy and being asymptomatic from peritoneal metastases prior to surgery. CONCLUSION: This is a data-driven study to predict the probability of achieving TO after CRS-HIPEC. The proposed pipeline has the potential to not only identify patients for whom surgery is not associated with prohibitive risk, but also aid surgeons in communicating this risk to patients.

Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery: a systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) approaches have become increasingly popular in predicting surgical outcomes. However, it is unknown whether they are superior to traditional statistical methods such as logistic regression (LR). This study aimed to perform a systematic review and meta-analysis to compare the performance of ML vs LR models in predicting postoperative outcomes for patients undergoing gastrointestinal (GI) surgery. METHODS: A systematic search of Embase, MEDLINE, Cochrane, Web of Science, and Google Scholar was performed through December 2022. The primary outcome was the discriminatory performance of ML vs LR models as measured by the area under the receiver operating characteristic curve (AUC). A meta-analysis was then performed using a random effects model. RESULTS: A total of 62 LR models and 143 ML models were included across 38 studies. On average, the best-performing ML models had a significantly higher AUC than the LR models (ΔAUC, 0.07; 95% CI, 0.04-0.09; P < .001). Similarly, on average, the best-performing ML models had a significantly higher logit (AUC) than the LR models (Δlogit [AUC], 0.41; 95% CI, 0.23-0.58; P < .001). Approximately half of studies (44%) were found to have a low risk of bias. Upon a subset analysis of only low-risk studies, the difference in logit (AUC) remained significant (ML vs LR, Δlogit [AUC], 0.40; 95% CI, 0.14-0.66; P = .009). CONCLUSION: We found a significant improvement in discriminatory ability when using ML over LR algorithms in predicting postoperative outcomes for patients undergoing GI surgery. Subsequent efforts should establish standardized protocols for both developing and reporting studies using ML models and explore the practical implementation of these models.

Robotic-assisted endoluminal gastric leiomyoma resection: a novel surgical technique for benign gastroesophageal junction tumors.

Gastric leiomyomas are rare, benign smooth muscle tumors that arise from the muscularis propria and can be found in any part of the stomach. The American College of Gastroenterologists recommends resection only for symptomatic leiomyomas, which can often present with bleeding, abdominal pain, or dyspepsia. Notably, symptomatic leiomyomas that arise at the gastroesophageal (GE) junction, especially those that are large, pose unique challenges. Specifically, total gastrectomy with esophagojejunostomy is often necessary, which can be associated with a compromised quality of life and possible complications such as anastomotic stricture or reflux esophagitis. In this context, we present the case of a young, male patient with a large symptomatic leiomyoma at the GE junction who was offered a robotic-assisted endoluminal leiomyoma resection. By placing endoluminal trocars and utilizing the Da Vinci® robot, we were able to carefully excise the tumor without perforating the stomach or causing GE junction stenosis. This allowed the patient to preserve his stomach and avoid a high-risk anastomosis. Another notable highlight of the case included the use of the endoscope as both a bougie and a source of insufflation. The patient had an uncomplicated postoperative course and a rapid recovery, highlighting the feasibility of this approach for patients with benign GE junction tumors.

A Novel Machine Learning Approach to Predict Textbook Outcome in Colectomy.

BACKGROUND: Several calculators exist to predict risk of postoperative complications. However, in low-risk procedures such as colectomy, a tool to determine the probability of achieving the ideal outcome could better aid clinical decision-making, especially for high-risk patients. A textbook outcome is a composite measure that serves as a surrogate for the ideal surgical outcome. OBJECTIVE: To identify the most important factors for predicting textbook outcomes in patients with nonmetastatic colon cancer undergoing colectomy and to create a textbook outcome decision support tool using machine learning algorithms. DESIGN: This was a retrospective analysis study. SETTINGS: Data were collected from the American College of Surgeons National Surgical Quality Improvement Program database. PATIENTS: Adult patients undergoing elective colectomy for nonmetastatic colon cancer (2014-2020) were included. MAIN OUTCOME MEASURES: Textbook outcome was the main outcome, defined as no mortality, no 30-day readmission, no postoperative complications, no 30-day reinterventions, and a hospital length of stay of ≤5 days. Four models (logistic regression, decision tree, random forest, and eXtreme Gradient Boosting) were trained and validated. Ultimately, a web-based calculator was developed as proof of concept for clinical application. RESULTS: A total of 20,498 patients who underwent colectomy for nonmetastatic colon cancer were included. Overall, textbook outcome was achieved in 66% of patients. Textbook outcome was more frequently achieved after robotic colectomy (77%), followed by laparoscopic colectomy (68%) and open colectomy (39%, p < 0.001). eXtreme Gradient Boosting was the best performing model (area under the curve = 0.72). The top 5 preoperative variables to predict textbook outcome were surgical approach, patient age, preoperative hematocrit, preoperative oral antibiotic bowel preparation, and patient sex. LIMITATIONS: This study was limited by its retrospective nature of the analysis. CONCLUSIONS: Using textbook outcome as the preferred outcome may be a useful tool in relatively low-risk procedures such as colectomy, and the proposed web-based calculator may aid surgeons in preoperative evaluation and counseling, especially for high-risk patients. See Video Abstract . UN NUEVO ENFOQUE DE APRENDIZAJE AUTOMTICO PARA PREDECIR EL RESULTADO DE LOS LIBROS DE TEXTO EN COLECTOMA: ANTECEDENTES:Existen varias calculadoras para predecir el riesgo de complicaciones posoperatorias. Sin embargo, en procedimientos de bajo riesgo como la colectomía, una herramienta para determinar la probabilidad de lograr el resultado ideal podría ayudar mejor a la toma de decisiones clínicas, especialmente para pacientes de alto riesgo. Un resultado de libro de texto es una medida compuesta que sirve como sustituto del resultado quirúrgico ideal.OBJETIVO:Identificar los factores más importantes para predecir el resultado de los libros de texto en pacientes con cáncer de colon no metastásico sometidos a colectomía y crear una herramienta de apoyo a la toma de decisiones sobre los resultados de los libros de texto utilizando algoritmos de aprendizaje automático.DISEÑO:Este fue un estudio de análisis retrospectivo.AJUSTES:Los datos se obtuvieron de la base de datos del Programa Nacional de Mejora de la Calidad del Colegio Americano de Cirujanos.PACIENTES:Se incluyeron pacientes adultos sometidos a colectomía electiva por cáncer de colon no metastásico (2014-2020).MEDIDAS PRINCIPALES DE RESULTADO:El resultado de los libros de texto fue el resultado principal, definido como ausencia de mortalidad, reingreso a los 30 días, complicaciones posoperatorias, reintervenciones a los 30 días y una estancia hospitalaria ≤5 días. Se entrenaron y validaron cuatro modelos (regresión logística, árbol de decisión, bosque aleatorio y XGBoost). Finalmente, se desarrolló una calculadora basada en la web como prueba de concepto para su aplicación clínica.RESULTADOS:Se incluyeron un total de 20.498 pacientes sometidos a colectomía por cáncer de colon no metastásico. En general, el resultado de los libros de texto se logró en el 66% de los pacientes. Los resultados de los libros de texto se lograron con mayor frecuencia después de la colectomía robótica (77%), seguida de la colectomía laparoscópica (68%) y la colectomía abierta (39%) (p<0,001). XGBoost fue el modelo con mejor rendimiento (AUC=0,72). Los cinco principales variables preoperatorias para predecir el resultado en los libros de texto fueron el abordaje quirúrgico, la edad del paciente, el hematocrito preoperatorio, la preparación intestinal con antibióticos orales preoperatorios y el sexo femenino.LIMITACIONES:Este estudio estuvo limitado por la naturaleza retrospectiva del análisis.CONCLUSIONES:El uso de los resultados de los libros de texto como resultado preferido puede ser una herramienta útil en procedimientos de riesgo relativamente bajo, como la colectomía, y la calculadora basada en la web propuesta puede ayudar a los cirujanos en la evaluación y el asesoramiento preoperatorios, especialmente para pacientes de alto riesgo. (Traducción-Yesenia Rojas-Khalil ).

Inadequate Lymph Node Yield: An Inadequate Indication for Adjuvant Chemotherapy in Stage II Colon Cancer.

Background: Optimal therapy for stage II colon cancer remains unclear, and national guidelines recommend "consideration" of adjuvant chemotherapy (ACT) in the presence of high-risk features, including inadequate lymph node yield (LNY, <12 nodes). This study aims to determine whether the survival benefit of ACT in stage II disease varies based on the adequacy of LNY. Methods: We used the National Cancer Database (NCDB) to identify adults who underwent resection for a single primary T3 or T4 colon cancer between 2006 and 2018. Multivariable logistic regression tested for associations between ACT and prespecified demographic and clinical characteristics, including the adequacy of LNY. We used Cox proportional hazards models to assess overall survival and restricted cubic splines to estimate the optimal LNY threshold to dichotomize patients based on overall survival. Results: Unadjusted 5- and 10-year survival rates were 84% and 75%, respectively, among patients who received ACT and 70% and 50% among patients who did not (log-rank P < 0.01). Inadequate LNY was independently associated with both receipt of ACT (odds ratios, 1.50; P < 0.01) and decreased overall survival [hazard ratio (HR), 1.56; P < 0.01]. ACT was independently associated with improved survival (HR, 0.67; P < 0.01); this effect size did not change based on the adequacy of LNY (interaction P = 0.41). Results were robust to re-analysis with our cohort-optimized threshold of 18 lymph nodes. Conclusions: Consistent with contemporary guidelines, patients with inadequate LNY are more likely to receive ACT. LNY adequacy is an independent prognostic factor but, in isolation, should not dictate whether patients receive ACT.

Diabetes-Related Mechanisms of Action Involved in the Therapeutic Effect of Croton Species: A Systematic Review.

Over the years, ethnopharmacological and phytochemical investigations have been conducted to understand the potential effects of the Croton genus on several diseases. It has been revealed that these terpenoid-rich species traditionally used to treat gastrointestinal diseases, heal wounds, and relieve pain have a wide range of therapeutic effects; however, those used to treat diabetes, as well as their action mechanisms, have not been reviewed so far. Therefore, the main objective of this review was to compile all Croton species that have shown pharmacological effects against diabetes and describe their action mechanisms. Through a search of the literature, 17 species with hypoglycemic, antihyperglycemic, antilipidemic, antihypertensive, antioxidant, and anti-inflammatory effects were found. Among the mechanisms by which they exerted these effects were the inhibition of α-glucosidases, the promotion of insulin secretion, and the increase in glucose uptake. Interestingly, it was found that some of them may have antihyperglycemic properties, although there were no ethnopharmacological reports that support their traditional use. Moreover, others only presented studies on their hypoglycemic effect in fasting, so further works are encouraged to describe the mechanisms involved in lowering fasting blood glucose levels, such as hepatic glucose production, especially for C. cajucara, C. cuneatus, C. gratissimus var. gratissimus, C. guatemalensis, and C. membranaceus. It is expected that this review contributes to the plant science knowledge of the genus, and it can be used in future references on the identification and development of new molecules/phytomedicines that help in the treatment of diabetes.

Last glacial hydroclimate variability in the Yucatán Peninsula not just driven by ITCZ shifts.

We reconstructed hydroclimate variability in the Yucatán Peninsula (YP) based on stalagmite oxygen and carbon isotope records from a well-studied cave system located in the northeastern YP, a region strongly influenced by Caribbean climate dynamics. The new stalagmite isotopic records span the time interval between 43 and 26.6 ka BP, extending a previously published record from the same cave system covering the interval between 26.5 and 23.2 ka BP. Stalagmite stable isotope records show dominant decadal and multidecadal variability, and weaker variability on millennial timescales. These records suggest significant precipitation declines in the broader Caribbean region during Heinrich events 4 and 3 of ice-rafted discharge into the North Atlantic, in agreement with the antiphase pattern of precipitation variability across the equator suggested by previous studies. On millennial timescales, the stalagmite isotope records do not show the distinctive saw-tooth pattern of climate variability observed in Greenland during Dansgaard-Oeschger (DO) events, but a pattern similar to North Atlantic sea surface temperature (SST) variability. We propose that shifts in the mean position of the Intertropical Convergence Zone (ITCZ), per se, are not the dominant driver of last glacial hydroclimate variability in the YP on millennial timescales but instead that North Atlantic SSTs played a dominant role. Our results support a negative climate feedback mechanism whereby large low latitude precipitation deficits resulting from AMOC slowdown would lead to elevated salinity in the Caribbean and ultimately help reactivate AMOC and Caribbean precipitation. However, because of the unique drivers of future climate in the region, predicted twenty-first century YP precipitation reductions are unlikely to be modulated by this negative feedback mechanism.

Sofosbuvir plus glecaprevir/pibrentasvir as salvage therapy after liver transplantation in NS5A inhibitor-experienced patients. A case series.

BACKGROUND: Treatment of chronic hepatitis C virus (HCV) infection with direct-acting antivirals achieves a sustained virologic response rate higher than 95%. However, virologic failure remains a clinical challenge, and data on retreatment are limited, especially in special populations such as liver transplant (LT) recipients. OBJECTIVES: This study evaluated the sofosbuvir plus glecaprevir-pibrentasvir (GLE/PIB) regimen in LT recipients who had failed to a nonstructural protein 5A (NS5A) inhibitor-based regimen. MATERIAL AND METHODS: Retrospective study of 111 liver transplant recipients between January 2018 and December 2020; 18 patients presented with HCV recurrent infection after LT, out of whom three had a history of at least one NS5A inhibitor-based regimen. Salvage therapy with sofosbuvir plus GLE/PIB was started for 12 weeks; baseline characteristics and outcomes were recorded. RESULTS: All three patients (100%) achieved an undetectable HCV viral load 12 weeks after treatment completion. No serious adverse events were observed. CONCLUSION: In our series, sofosbuvir plus GLE/PIB for 12 weeks is an effective and safe salvage therapy after LT in patients previously treated with NS5A inhibitors.

ANTECEDENTES: El tratamiento del virus de la hepatitis C (VHC) crónica con antivirales de acción directa logra tasas de respuesta virológica sostenida superiores a 95 %. Sin embargo, el manejo del fracaso virológico sigue siendo un desafío clínico y la evidencia sobre el retratamiento es limitada, especialmente en poblaciones como los receptores de trasplante hepático (TH). OBJETIVO: Este estudio evaluó el régimen de sofosbuvir más glecaprevir/pibrentasvir (GLE/PIB) en receptores de TH en quienes falló el régimen basado en inhibidores de la proteína no estructural 5A (NS5A). MATERIAL Y MÉTODOS: Estudio retrospectivo de 111 pacientes trasplantados entre enero de 2018 y diciembre de 2020; 18 pacientes presentaron infección recurrente por VHC posterior al TH, tres de ellos tuvieron antecedentes de al menos un régimen basado en inhibidores de NS5A. Se inició terapia de rescate con sofosbuvir más GLE/PIB durante 12 semanas posterior al TH; se registraron las características basales de los pacientes y sus desenlaces. RESULTADOS: En los tres pacientes se logró obtener una carga viral indetectable de VHC a las 12 semanas de finalizar el tratamiento. No se observaron eventos adversos graves. CONCLUSIÓN: En nuestra serie, sofosbuvir más GLE/PIB durante 12 semanas demostró ser una terapia de rescate efectiva y segura posterior al TH en pacientes previamente tratados con inhibidores de NS5A.

A Machine Learning Approach to Predict Postoperative Pancreatic Fistula After Pancreaticoduodenectomy Using Only Preoperatively Known Data.

BACKGROUND: Clinically-relevant postoperative pancreatic fistula (CR-POPF) following pancreaticoduodenectomy (PD) is a major postoperative complication and the primary determinant of surgical outcomes. However, the majority of current risk calculators utilize intraoperative and postoperative variables, limiting their utility in the preoperative setting. Therefore, we aimed to develop a user-friendly risk calculator to predict CR-POPF following PD using state-of-the-art machine learning (ML) algorithms and only preoperatively known variables. METHODS: Adult patients undergoing elective PD for non-metastatic pancreatic cancer were identified from the ACS-NSQIP targeted pancreatectomy dataset (2014-2019). The primary endpoint was development of CR-POPF (grade B or C). Secondary endpoints included discharge to facility, 30-day mortality, and a composite of overall and significant complications. Four models (logistic regression, neural network, random forest, and XGBoost) were trained, validated and a user-friendly risk calculator was then developed. RESULTS: Of the 8666 patients who underwent elective PD, 13% (n = 1160) developed CR-POPF. XGBoost was the best performing model (AUC = 0.72), and the top five preoperative variables associated with CR-POPF were non-adenocarcinoma histology, lack of neoadjuvant chemotherapy, pancreatic duct size less than 3 mm, higher BMI, and higher preoperative serum creatinine. Model performance for 30-day mortality, discharge to a facility, and overall and significant complications ranged from AUC 0.62-0.78. CONCLUSIONS: In this study, we developed and validated an ML model using only preoperatively known variables to predict CR-POPF following PD. The risk calculator can be used in the preoperative setting to inform clinical decision-making and patient counseling.

Sofosbuvir más glecaprevir/pibrentasvir como terapia de rescate postrasplante hepático en pacientes con exposición previa a inhibidores de NS5A. Serie de casos / Sofosbuvir plus glecaprevir/pibrentasvir as salvage therapy after liver transplantation in NS5A inhibitor-experienced patients. A case series

Resumen Antecedentes: El tratamiento de la infección crónica por el virus de la hepatitis C (VHC) con antivirales de acción directa logra tasas de respuesta virológica sostenida superiores a 95 %. Sin embargo, el manejo del fracaso virológico sigue siendo un desafío clínico y la evidencia sobre el retratamiento es limitada, especialmente en poblaciones como los receptores de trasplante hepático (TH). Objetivo: Este estudio evaluó el régimen de sofosbuvir más glecaprevir/pibrentasvir (GLE/PIB) en receptores de TH en quienes falló el régimen basado en inhibidores de la proteína no estructural 5A (NS5A). Material y métodos: Estudio retrospectivo de 111 pacientes trasplantados entre enero de 2018 y diciembre de 2020; 18 pacientes presentaron infección recurrente por VHC posterior al TH, tres de ellos tuvieron antecedentes de al menos un régimen basado en inhibidores de NS5A. Se inició terapia de rescate con sofosbuvir más GLE/PIB durante 12 semanas posterior al TH; se registraron las características basales de los pacientes y sus desenlaces. Resultados: En los tres pacientes se logró obtener una carga viral indetectable de VHC a las 12 semanas de finalizar el tratamiento. No se observaron eventos adversos graves. Conclusión: En nuestra serie, sofosbuvir más GLE/PIB durante 12 semanas demostró ser una terapia de rescate efectiva y segura posterior al TH en pacientes previamente tratados con inhibidores de NS5A.

Abstract Background: Treatment of chronic hepatitis C virus (HCV) infection with direct-acting antivirals achieves a sustained virologic response rates higher than 95%. However, virologic failure remains a clinical challenge, and data on retreatment are limited, especially in special populations such as liver transplant (LT) recipients. Objective: This study evaluated the sofosbuvir plus glecaprevir-pibrentasvir (GLE/PIB) regimen in LT recipients who had failed to a nonstructural protein 5A (NS5A) inhibitor-based regimen. Material and methods: Retrospective study of 111 liver transplant recipients between January 2018 and December 2020; 18 patients presented with HCV recurrent infection after LT, out of whom three had a history of at least one NS5A inhibitor-based regimen. Salvage therapy with sofosbuvir plus GLE/PIB was started for 12 weeks; baseline characteristics and outcomes were recorded. Results: All three patients (100%) achieved an undetectable HCV viral load 12 weeks after treatment completion. No serious adverse events were observed. Conclusion: In our series, sofosbuvir plus GLE/PIB for 12 weeks is an effective and safe salvage therapy after LT in patients previously treated with NS5A inhibitors.

Development and Validation of Prediction Models and Risk Calculators for Posthepatectomy Liver Failure and Postoperative Complications Using a Diverse International Cohort of Major Hepatectomies.

OBJECTIVE: The study aim was to develop and validate models to predict clinically significant posthepatectomy liver failure (PHLF) and serious complications [a Comprehensive Complication Index (CCI)>40] using preoperative and intraoperative variables. BACKGROUND: PHLF is a serious complication after major hepatectomy but does not comprehensively capture a patient's postoperative course. Adding the CCI as an additional metric can account for complications unrelated to liver function. METHODS: The cohort included adult patients who underwent major hepatectomies at 12 international centers (2010-2020). After splitting the data into training and validation sets (70:30), models for PHLF and a CCI>40 were fit using logistic regression with a lasso penalty on the training cohort. The models were then evaluated on the validation data set. RESULTS: Among 2192 patients, 185 (8.4%) had clinically significant PHLF and 160 (7.3%) had a CCI>40. The PHLF model had an area under the curve (AUC) of 0.80, calibration slope of 0.95, and calibration-in-the-large of -0.09, while the CCI model had an AUC of 0.76, calibration slope of 0.88, and calibration-in-the-large of 0.02. When the models were provided only preoperative variables to predict PHLF and a CCI>40, this resulted in similar AUCs of 0.78 and 0.71, respectively. Both models were used to build 2 risk calculators with the option to include or exclude intraoperative variables ( PHLF Risk Calculator; CCI>40 Risk Calculator ). CONCLUSIONS: Using an international cohort of major hepatectomy patients, we used preoperative and intraoperative variables to develop and internally validate multivariable models to predict clinically significant PHLF and a CCI>40 with good discrimination and calibration.