Összesen 3 találat.


001-es BibID:BIBFORM090160
035-os BibID:(cikkazonosító)1367 (WOS)000626774100081 (Scopus)85099483306
Első szerző:Hegyi Péter Jr. (belgyógyász)
Cím:Evidence for diagnosis of early chronic pancreatitis after three episodes of acute pancreatitis : a cross-sectional multicentre international study with experimental animal model / Péter J. Hegyi, Alexandra Soós, Emese Tóth, Attila Ébert, Viktória Venglovecz, Katalin Márta, Péter Mátrai, Alexandra Mikó, Judit Bajor, Patrícia Sarlós, Áron Vincze, Adrienn Halász, Ferenc Izbéki, Zoltán Szepes, László Czakó, György Kovács, Mária Papp, Zsolt Dubravcsik, Márta Varga, József Hamvas, Balázs C. Németh, Melania Macarie, Ali Tüzüm Ince, Elena A. Dubtsova, Mariya A. Kirynkova, Igor E. Khatkov, Tanya Bideeva, Artautas Mickevicius, Elena Ramírez-Maldonado, Ville Sallinen, Bálint Erős, Dániel Pécsi, Andrea Szentesi, Andrea Párniczky, László Tiszlavicz, Péter Hegyi
Megjegyzések:Abstract Chronic pancreatitis (CP) is an end-stage disease with no specific therapy; therefore, an early diagnosis is of crucial importance. In this study, data from 1315 and 318 patients were analysed from acute pancreatitis (AP) and CP registries, respectively. The population from the AP registry was divided into AP (n = 983), recurrent AP (RAP, n = 270) and CP (n = 62) groups. The prevalence of CP in combination with AP, RAP2, RAP3, RAP4 and RAP5 + was 0%, 1%, 16%, 50% and 47%, respectively, suggesting that three or more episodes of AP is a strong risk factor for CP. Laboratory, imaging and clinical biomarkers highlighted that patients with RAP3 + do not show a significant difference between RAPs and CP. Data from CP registries showed 98% of patients had at least one AP and the average number of episodes was four. We mimicked the human RAPs in a mouse model and found that three or more episodes of AP cause early chronic-like morphological changes in the pancreas. We concluded that three or more attacks of AP with no morphological changes to the pancreas could be considered as early CP (ECP).The new diagnostic criteria for ECP allow the majority of CP patients to be diagnosed earlier. They can be used in hospitals with no additional costs in healthcare.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
Megjelenés:Scientific Reports. - 11 : 1 (2021), p. 1-14. -
További szerzők:Soós Alexandra Tóth Emese Ébert Attila Venglovecz Viktória Márta Katalin Mátrai Péter Mikó Alexandra Bajor Judit Sarlós Patrícia Vincze Áron Halász Adrienn Izbéki Ferenc Szepes Zoltán Czakó László Kovács György (1982-) (belgyógyász, gasztroenterológus) Papp Mária (1975-) (belgyógyász, gasztroenterológus) Dubravcsik Zsolt (belgyógyász, gasztroenterológus) Varga Márta Hamvas József Németh Balázs Csaba Macarie, Melania Ince, Ali Tüzün Dubtsova, Elena A. Kirynkova, Mariya A. Khatkov, Igor E. Bideeva, Tanya Mickevicius, Artautas Ramírez-Maldonado, Elena Sallinen, Ville Erős Bálint Pécsi Dániel Szentesi Andrea Párniczky Andrea (gyermekgyógyász) Tiszlavicz László Hegyi Péter Jenő (belgyógyász)
Internet cím:DOI
Intézményi repozitóriumban (DEA) tárolt változat


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
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 ( 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
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


001-es BibID:BIBFORM076218
035-os BibID:(cikkazonosító)1776 (WoS)000463100200001 (Scopus)85068267109
Első szerző:Szakács Zsolt
Cím:Aging and Comorbidities in Acute Pancreatitis II. : a Cohort-analysis of 1203 Prospectively Collected Cases / Zsolt Szakács, Noémi Gede, Dániel Pécsi, Ferenc Izbéki, Mária Papp, György Kovács, Eszter Fehér, Dalma Dobszai, Balázs Kui, Katalin Márta, Klára Kónya, Imre Szabó, Imola Török, László Gajdán, Tamás Takács, Patrícia Sarlós, Szilárd Gódi, Márta Varga, József Hamvas, Áron Vincze, Andrea Szentesi, Andrea Párniczky, Peter Hegyi
Megjegyzések:Introduction: Our meta-analysis indicated that aging influences the outcomes of acute pancreatitis (AP), however, a potential role for comorbidities was implicated, as well. Here we aimed to determine how age and comorbidities modify the outcomes in AP in a cohort-analysis of Hungarian AP cases. Materials and methods: Data of patients diagnosed with AP by the revised Atlanta criteria were extracted from the Hungarian National Pancreas Registry. Outcomes of interest were mortality, severity, length of hospitalization, local, and systemic complications of AP. Comorbidities were measured by means of Charlson Comorbidity Index (CCI) covering pre-existing chronic conditions. Non-parametric univariate and multivariate statistics were used in statistical analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Results: A total of 1203 patients from 18 centers were included. Median age at admission was 58 y (range: 18-95 y), median CCI was 2 (range: 0-10). Only severe comorbidities (CCI?3) predicted mortality (OR=4.48; CI: 1.57-12.80). Although severe comorbidities predicted AP severity (OR=2.10, CI: 1.08-4.09), middle (35-64 years) and old age (?65 years) were strong predictors with borderline significance, as well (OR=7.40, CI: 0.99-55.31 and OR=6.92, CI: 0.91-52.70, respectively). Similarly, middle and old age predicted a length of hospitalization ?9 days. Interestingly, the middle-aged (35-64 years) were three times more likely to develop pancreatic necrosis than young adults (OR=3.21, CI: 1.26-8.19), whereas the old-aged (?65 years) were almost nine times more likely to develop systemic complications than young adults (OR=8.93, CI: 1.20-66.80), though having severe comorbidities (CCI?3) was a predisposing factor, as well. Conclusion: Both aging and comorbidities modify the outcomes of AP. Comorbidities seem to be decisive regarding mortality and severity, however, age is a strong predictor of the latter, as well. The middle-aged are the most likely to develop local complications, whereas those having severe comorbidities are vulnerable to developing systemic complications. Studies validating the implementation of CCI-based predictive scores are awaited.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
acute pancreatitis
length of hospitalization
Charlson Comorbidity Index
Megjelenés:Frontiers in Physiology. - 2019 (2019). -
További szerzők:Gede Noémi Pécsi Dániel Izbéki Ferenc Papp Mária (1975-) (belgyógyász, gasztroenterológus) Kovács György (1982-) (belgyógyász, gasztroenterológus) Fehér Eszter Dobszai Dalma Kui Balázs Márta Katalin Kónya Klára Szabó Imre Török Imola Gajdán László Takács Tamás (Szeged) Sarlós Patrícia Gódi Szilárd Varga Márta Hamvas József Vincze Áron Szentesi Andrea Párniczky Andrea (gyermekgyógyász) Hegyi Péter Jenő (belgyógyász)
Pályázati támogatás:KH125678
Internet cím:Intézményi repozitóriumban (DEA) tárolt változat
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