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001-es BibID:	BIBFORM101294
035-os BibID:	(cikkazonosító)e842 (wos)000804849400001
Első szerző:	Kui Balázs
Cím:	EASY-APP : an artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis / Kui Balázs, Pintér József, Molontay Roland, Nagy Marcell, Farkas Nelli, Gede Noémi, Vincze Áron, Bajor Judit, Gódi Szilárd, Czimmer József, Szabó Imre, Illés Anita, Sarlós Patrícia, Hágendorn Roland, Pár Gabriella, Papp Mária, Vitális Zsuzsanna, Kovács György, Fehér Eszter, Földi Ildikó, Izbéki Ferenc, Gajdán László, Fejes Roland, Németh Balázs Csaba, Török Imola, Farkas Hunor, Artautas Mickevicius, Ville Sallinen, Shamil Galeev, Elena Ramirez Maldonado, Párniczky Andrea, Erőss Bálint, Hegyi Péter Jenő, Márta Katalin, Váncsa Szilárd, Sutton Robert, Enrique de-Madaria, Elizabeth Pando, Piero Alberti, Maria José Gómez-Jurado, Alina Tantau, Szentesi Andrea, Hegyi Péter, Hungarian Pancreatic Study Group
Dátum:	2022
ISSN:	2001-1326
Megjegyzések:	Background: Acute pancreatitis (AP) is a potentially severe or even fatal inflammation of the pancreas. Early identification of patients, who are at high risk for developing a severe course of the disease is crucial for preventing organ failure and death. Most of the former predictive scores require many parameters or at least 24 hours to predict the severity, so the early therapeutic window is missing. Methods: The early achievable severity index (EASY) is a registered multicentre, multinational, prospective, observational study (ISRCTN10525246). Clinical parameters were collected from 15 countries and 28 medical centres via eCRF. The predictions were made using machine learning models including Decision Tree, Random Forest, Logistic Regression, SVM, CatBoost, and XGBoost. For the modeling, we used the scikit-learn, xgboost, and catboost Python packages. We have evaluated our models using 4-fold cross-validation and the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and accuracy metrics have been calculated on the union of the test sets of the cross-validation. The most important factors and their contribution to the prediction were identified using a modern tool of explainable artificial intelligence, called SHapley Additive exPlanations (SHAP). Using the XGBoost machine learning algorithm for prediction, the SHAP values for the explanation, and the bootstrapping method for the estimation of confidence we have developed a web application in the Streamlit Python-based framework. Results: The prediction model is based on the international cohort of 1184 patients and a validation cohort of 3543 patients. The best performing model has been an XGBoost classifier with an average AUC score of 0.81 and accuracy of 89.1% and the model is improving with experience. The six most influential features are the respiratory rate, body temperature, abdominal muscular reflex, gender, age, and glucose level. Finally, a free and easy-to-use web application was developed (http://easy-app.org/). Conclusions: The EASY prediction score is a practical tool for identifying patients at high risk for severe acute pancreatitis within hours of hospital admission. The easy-to-use web application is available for clinicians and contributes to the improvement of the model.
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk severity prediction acute pancreatitis artificial intelligence
Megjelenés:	Clinical and Translational Medicine. - 12 : 6 (2022), p. 1-13. -
További szerzők:	Pintér József (1930-) (urológus) Molontay Roland Nagy Marcell Farkas Nelli Gede Noémi Vincze Áron Bajor Judit Gódi Szilárd Czimmer József Szabó Imre Illés Anita Sarlós Patrícia Hágendorn Roland Pár Gabriella Papp Mária (1975-) (belgyógyász, gasztroenterológus) Vitális Zsuzsanna (1963-) (belgyógyász, gasztroenterológus) Kovács György (1982-) (belgyógyász, gasztroenterológus) Fehér Eszter Földi Ildikó (1981-) (orvos) Izbéki Ferenc Gajdán László Fejes Roland Németh Balázs Csaba Török Imola Farkas Hunor Mickevicius, Artautas Sallinen, Ville Galeev, Shamil Ramírez-Maldonado, Elena Párniczky Andrea (gyermekgyógyász) Erőss Bálint Hegyi Péter Jenő (belgyógyász) Márta Katalin Váncsa Szilárd Sutton, Robert de-Madaria, Enrique Pando, Elizabeth Alberti, Piero Gómez-Jurado, Maria José Tantau, Alina Szentesi Andrea Hegyi Péter (pszichológus) Hungarian Pancreatic Study Group
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat DOI
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001-es BibID:	BIBFORM100014
035-os BibID:	(cikkazonosító)e050821 (WoS)000739490700018 (Scopus)85122762723
Első szerző:	Ocskay Klementina
Cím:	Recurrent acute pancreatitis prevention by the elimination of alcohol and cigarette smoking (REAPPEAR) : protocol of a randomised controlled trial and a cohort study / Klementina Ocskay, Márk Félix Juhász, Nelli Farkas, Noémi Zádori, Lajos Szakó, Zsolt Szakács, Andrea Szentesi, Bálint Erőss, Emőke Miklós, Antal Zemplényi, Béla Birkás, Árpád Csathó, István Hartung, Tamás Nagy, László Czopf, Ferenc Izbéki, László Gajdán, Mária Papp, László Czakó, Dóra Illés, Marco V. Marino, Antonello Mirabella, Ewa Małecka-Panas, Hubert Zatorski, Yaroslav Susak, Kristina Opalchuk, Gabriele Capurso, Laura Apadula, Cristian Gheorghe, Ionut Adrian Saizu, Ole H. Petersen, Enrique de-Madaria, Jonas Rosendahl, Andrea Párniczky, Péter Hegyi, Hungarian Pancreatic Study Group
Dátum:	2022
ISSN:	2044-6055
Megjegyzések:	Background/objectives Acute recurrent pancreatitis (ARP) due to alcohol and/or tobacco abuse is a preventable disease which lowers quality of life and can lead to chronic pancreatitis. The REAPPEAR study aims to investigate whether a combined patient education and cessation programme for smoking and alcohol prevents ARP. Methods and analysis The REAPPEAR study consists of an international multicentre randomised controlled trial (REAPPEAR-T) testing the efficacy of a cessation programme on alcohol and smoking and a prospective cohort study (REAPPEAR-C) assessing the effects of change in alcohol consumption and smoking (irrespective of intervention). Daily smoker patients hospitalised with alcohol-induced acute pancreatitis (AP) will be enrolled. All patients will receive a standard intervention priorly to encourage alcohol and smoking cessation. Participants will be subjected to laboratory testing, measurement of blood pressure and body mass index and will provide blood, hair and urine samples for later biomarker analysis. Addiction, motivation to change, socioeconomic status and quality of life will be evaluated with questionnaires. In the trial, patients will be randomised either to the cessation programme with 3-monthly visits or to the control group with annual visits. Participants of the cessation programme will receive a brief intervention at every visit with direct feedback on their alcohol consumption based on laboratory results. The primary endpoint will be the composite of 2-year all-cause recurrence rate of AP and/ or 2-year all-cause mortality. The cost-effectiveness of the cessation programme will be evaluated. An estimated 182 participants will be enrolled per group to the REAPPEAR-T with further enrolment to the cohort. Ethics and dissemination The study was approved by the Scientific and Research Ethics Committee of the Hungarian Medical Research Council (40394-10/2020/ EÜIG), all local ethical approvals are in place. Results will be disseminated at conferences and in peer-reviewed journals. Trial registration number NCT04647097
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	BMJ Open. - 12 : 1 (2022), p. 1-9. -
További szerzők:	Juhász Márk Félix Farkas Nelli Zádori Noémi Szakó Lajos Szakács Zsolt Szentesi Andrea Erőss Bálint Miklós Emőke Zemplényi Antal Birkás Béla Csathó Árpád Hartung István Nagy Tamás (1977-) (vegyész, orvosi laboratóriumi analitikus) Czopf László Izbéki Ferenc Gajdán László Papp Mária (1975-) (belgyógyász, gasztroenterológus) Czakó László Illés Dóra Marino, Marco Vito Mirabella, Antonello Małecka-Panas, Ewa Zatorski, Hubert Susak, Yaroslav Mykhailovych Opalchuk, Kristina Capurso, Gabriele Apadula, Laura Gheorghe, Cristian Saizu, Ionut Adrian Petersen, Ole H. de-Madaria, Enrique Rosendahl, Jonas Párniczky Andrea (gyermekgyógyász) Hegyi Péter Jenő (belgyógyász) Hungarian Pancreatic Study Group
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001-es BibID:	BIBFORM082674
Első szerző:	Zádori Noémi
Cím:	EarLy elimination of fatty acids iN hypertriglyceridemia-induced acuTe pancreatitis (ELEFANT trial) : protocol of an open-label, multicenter, adaptive randomized clinical trial / Noémi Zádori, Noémi Gede, Judit Antal, Andrea Szentesi, Hussain Alizadeh, Áron Vincze, Ferenc Izbéki, Mária Papp, László Czakó, Márta Varga, Enrique de-Madaria, Ole H. Petersen, Vijay P. Singh, Julia Mayerle, Nándor Faluhelyi, Attila Miseta, István Reiber, Péter Hegyi
Dátum:	2020
ISSN:	1424-3903
Megjegyzések:	Introduction: Acute pancreatitis (AP) is a life-threatening inflammatory disease, with no specific pharmacologi- cal treatment. However, concerning some etiologies, early specific intervention (such as ERCP in biliary AP) has proven to be remarkably beneficial. Hypertriglyceridemia (HTG) induces severe pancreatic damage by several direct (cellular damage) and indirect (deterioration of microcirculation) mechanisms. Published data suggest that early removal of triglycerides (TGs) and toxic free fatty acids (FFAs) may be advantageous; however, high-quality evidence is still missing in the literature. Methods: /Design: ELEFANT is a randomized controlled, multicenter, international trial testing the concept that early elimination of TGs and FFAs from the blood is beneficial in HTG-AP. The study will be performed with the adaptive "drop-the-loser" design, which supports the possibility of dropping the inferior treatment arm, based on the results of the interim analysis. Patients with HTG-AP defined by TG level over 11.3 mmol/l (1000 mg/dL) are randomized into three groups: (A) patients who undergo plasmapheresis and receive aggressive fluid resuscita- tion; (B) patients who receive insulin and heparin treatment with aggressive fluid resuscitation; and (C) patients with aggressive fluid resuscitation. Please note that all intervention must be started within 48 h from the onset of abdominal pain. Exclusion criteria are designed logically to decrease the possibility of any distorting effects of other diseases. The composite primary endpoint will include both severity and mortality.
Tárgyszavak:	Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk Acute pancreatitis Hypertriglyceridemia Plasmapheresis Free fatty acids Heparin Insulin Randomized clinical trial
Megjelenés:	Pancreatology. - 20 : 3 (2020), p. 369-376. -
További szerzők:	Gede Noémi Antal Judit Szentesi Andrea Alizadeh, Hussain Vincze Áron Izbéki Ferenc Papp Mária (1975-) (belgyógyász, gasztroenterológus) Czakó László Varga Márta de-Madaria, Enrique Petersen, Ole H. Singh, Vijay P. Mayerle, Julia Faluhelyi Nándor Miseta Attila Reiber István Hegyi Péter (pszichológus)
Pályázati támogatás:	GINOP-2.3.2-15-2016-00048 GINOP KH-125678 Egyéb EFOP-3.6.2-16-2017-00006 EFOP LP2014-10/2014 Egyéb
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