Stefan Patauner

ORCID: 0000-0001-7592-0934
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About
Contact & Profiles
Research Areas
  • Hepatocellular Carcinoma Treatment and Prognosis
  • Liver Disease Diagnosis and Treatment
  • Cholangiocarcinoma and Gallbladder Cancer Studies
  • COVID-19 and healthcare impacts
  • Cardiac, Anesthesia and Surgical Outcomes
  • Liver Disease and Transplantation
  • Trauma and Emergency Care Studies
  • Pancreatic and Hepatic Oncology Research
  • Liver physiology and pathology
  • Intestinal and Peritoneal Adhesions
  • Pancreatitis Pathology and Treatment
  • Gallbladder and Bile Duct Disorders
  • Colorectal Cancer Screening and Detection
  • Radiomics and Machine Learning in Medical Imaging
  • Colorectal Cancer Treatments and Studies
  • Radiation Dose and Imaging
  • Respiratory Support and Mechanisms
  • Advanced X-ray and CT Imaging
  • Nutrition and Health in Aging
  • Healthcare cost, quality, practices
  • Advances in Oncology and Radiotherapy
  • Surgical site infection prevention
  • Medical Imaging and Pathology Studies
  • Global Cancer Incidence and Screening
  • Bariatric Surgery and Outcomes

Ospedale di Bolzano
2014-2024

Laboratoire des Sciences de l'Ingénieur, de l'Informatique et de l'Imagerie
2020-2022

University of Birmingham
2020-2021

Institut de Virologie
2021

NIHR Birmingham Biomedical Research Centre
2021

Yorkshire Cancer Research
2021

Urology Foundation
2021

Association for Cancer Surgery
2021

AstraZeneca (Brazil)
2020

Stryker (United Kingdom)
2020

Background: We aimed to assess the ability of comprehensive complication index (CCI) and Clavien-Dindo (CDC) scale predict excessive length hospital stay (e-LOS) in patients undergoing liver resection for hepatocellular carcinoma. Methods: Patients were identified from an Italian multi-institutional database randomly selected be included either a derivation or validation set. Multivariate logistic regression models ROC curve analysis including CCI CDC as predictors e-LOS fitted compare...

10.3390/cancers12123868 article EN Cancers 2020-12-21

Clear indications on how to select retreatments for recurrent hepatocellular carcinoma (HCC) are still lacking.To create a machine learning predictive model of survival after HCC recurrence allocate patients their best potential treatment.Real-life data were obtained from an Italian registry between January 2008 and December 2019 median (IQR) follow-up 27 (12-51) months. External validation was made derived by another cohort Japanese cohort. Patients who experienced first surgical approach...

10.1001/jamasurg.2022.6697 article EN JAMA Surgery 2022-12-28

10.1016/j.hpb.2023.06.004 article EN HPB 2023-06-13

10.1016/j.ejso.2014.08.308 article EN European Journal of Surgical Oncology 2014-10-15

10.1016/j.ejso.2016.06.267 article EN European Journal of Surgical Oncology 2016-08-25
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