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001-es BibID:BIBFORM090166
Első szerző:Hágendorn Roland
Cím:Disturbance of consciousness deteriorates the severity of acute pancreatitis. An international multicentre cohort analyses of 1220 prospectively collected patients / R. Hagendorn, Á. Vincze, F. Izbeki, L. Gajdan, S. Godi, A. Illes, P. Sarlos, N. Farkas, B. Erős, V. Lillik, D. Illes, P. Varjú, K. Marta, I. Török, M. Papp, Z. Vitalis, B. Bod, J. Hamvas, Z. Szepes, T. Takacs, L. Czakó, A. Szentesi, A. Parniczky, P. Hegyi, A. Miko
Dátum:2020
ISSN:1424-3903
Megjegyzések:Purpose: Disturbance of consciousness (DOC) may develop in acute pancreatitis (AP). In clinical practice, it is known that DOC may worsen the patient's condition, but we have no exact data on how DOC affects the outcome of AP. Materials and methods: From the Hungarian Pancreatic Study Groups' AP registry, 1220 cases contained the exact data on DOC. Patients were separated to Non-DOC and DOC, whereas DOC was further divided into non-alcohol related DOC (Non-ALC DOC) and ALC-DOC groups. Statistical analysis was performed by SPSS 24 Software Package. Results: From the 1220 patients, 47 (3.85%) developed DOC, 23 (48.9%) cases were ALC DOC vs. 24 (51.1%) Non-ALC DOC. The incidence of severe AP was higher in the DOC compared to the Non-DOC group (19.15% vs. 5.29%, p<0.001). The mortality was higher in the DOC vs. Non-DOC group (14.89% vs. 1.71%, p<0.001). Length of hospitalization (LOH) was longer in the DOC vs. non-DOC group (Me:11; IQR:8-17 days vs. Me:9; IQR:6-13 days, p?0.049). Patients with ALC DOC developed more frequently moderately-severe AP vs. Non-ALC DOC (43.48% vs. 12.5%), while the incidence of severe AP was significantly higher in Non-ALC vs. ALC DOC group (33.33% vs. 4.35%) (p<0.001). LOH showed tendency to be longer in Non-ALC DOC compared to ALC DOC respectively (Me:13; IQR:7-20 days vs. Me:9.5; IQR:8-15.5 days, p?0.119). Conclusions: DOC during AP is associated with a higher rate of moderate and severe AP and increases the risk of mortality; therefore, the DOC should be closely monitored and prevented in AP.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idézhető absztrakt
folyóiratcikk
Megjelenés:Pancreatology. - 20 (2020), p. S25. -
További szerzők:Vincze Áron Izbéki Ferenc Gajdán László Gódi Szilárd Illés Árpád (1959-) (belgyógyász, haematológus, onkológus) Sarlós Péter Farkas Nelli Erős Bálint Lillik Veronika Illés Dóra Varjú Péter Márta Katalin Török I. Papp Mária (1975-) (belgyógyász, gasztroenterológus) Vitális Zsuzsanna (1963-) (belgyógyász, gasztroenterológus) Bod Barnabás Hamvas József Szepes Zoltán Takács T. Czakó László Szentesi Andrea Párniczky Andrea (gyermekgyógyász) Hegyi Péter Jenő (belgyógyász) Mikó Alexandra
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2.

001-es BibID:BIBFORM085501
Első szerző:Hágendorn Roland
Cím:Development of disturbance of consciousness is associated with increased severity in acute pancreatitis / Roland Hágendorn, Áron Vincze, Ferenc Izbéki, László Gajdán, Szilárd Gódi, Anita Illés, Patrícia Sarlós, Nelli Farkas, Bálint Erőss, Veronika Lillik, Dóra Illés, Péter Varjú, Katalin Márta, Imola Török, Mária Papp, Zsuzsanna Vitális, Barnabás Bod, József Hamvas, Zoltán Szepes, Tamás Takács, László Czakó, Zsolt Márton, Andrea Szentesi, Andrea Párniczky, Péter Hegyi, Alexandra Mikó
Dátum:2020
ISSN:1424-3903
Megjegyzések:Background Disturbance of consciousness (DOC) may develop in acute pancreatitis (AP). In clinical practice, it is known that DOC may worsen the patient's condition, but we have no exact data on how DOC affects the outcome of AP. Methods From the Hungarian Pancreatic Study Groups' AP registry, 1220 prospectively collected cases were analysed, which contained exact data on DOC, included patients with confusion, delirium, convulsion, and alcohol withdrawal, answering a post hoc defined research question. Patients were separated to Non-DOC and DOC, whereas DOC was further divided into non-alcohol related DOC (Non-ALC DOC) and ALC DOC groups. For statistical analysis, independent sample t-test, Mann-Whitney, Chi-squared, or Fisher exact test were used. Results From the 1220 patients, 47 (3.9%) developed DOC, 23 (48.9%) cases were ALC DOC vs. 24 (51.1%) Non-ALC DOC. Analysis between the DOC and Non-DOC groups showed a higher incidence of severe AP (19.2% vs. 5.3%, p<0.001), higher mortality (14.9% vs. 1.7%, p<0.001), and a longer length of hospitalization (LOH) (Me=11; IQR: 8-17 days vs. Me=9; IQR: 6-13 days, p=0.049) respectively. Patients with ALC DOC developed more frequently moderate AP vs. Non-ALC DOC (43.5% vs. 12.5%), while the incidence of severe AP was higher in Non-ALC vs. ALC DOC group (33.3% vs. 4.4%) (p<0.001). LOH showed a tendency to be longer in Non-ALC DOC compared to ALC DOC, respectively (Me:13; IQR:7-20 days vs. Me:9.5; IQR:8-15.5 days, p=0.119). Conclusion DOC during AP is associated with a higher rate of moderate and severe AP and increases the risk of mortality.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
disturbance of consciousness
acute pancreatitis
alcohol
delirium
mortality
Megjelenés:Pancreatology. - 20 : 5 (2020), p. 806-812. -
További szerzők:Vincze Áron Izbéki Ferenc Gajdán László Gódi Szilárd Illés Anita Sarlós Patrícia Farkas Nelli Erőss Bálint Lillik Veronika Illés Dóra Varjú Péter Márta Katalin Török Imola Papp Mária (1975-) (belgyógyász, gasztroenterológus) Vitális Zsuzsanna (1963-) (belgyógyász, gasztroenterológus) Bod Barnabás Hamvas József Szepes Zoltán Takács Tamás (Szeged) Czakó László Márton Zsolt Szentesi Andrea Párniczky Andrea (gyermekgyógyász) Hegyi Péter Jenő (belgyógyász) Mikó Alexandra
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3.

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
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DOI
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