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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
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2.

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
Dátum:2019
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
folyóiratcikk
acute pancreatitis
comorbidities
mortality
severity
length of hospitalization
complications
prediction
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
OTKA
K116634
OTKA
K120335
OTKA
GINOP-2.3.2-15-2016-00048
GINOP
EFOP-3.6.2-16-2017-00006
EFOP
Internet cím:Intézményi repozitóriumban (DEA) tárolt változat
DOI
Borító:

3.

001-es BibID:BIBFORM094178
035-os BibID:(WOS)000727779500019 (Scopus)85106978919
Első szerző:Szakó Lajos
Cím:Early occurrence of pseudocysts in acute pancreatitis - A multicenter international cohort analysis of 2275 cases / Lajos Szakó, Noémi Gede, Alex Váradi, Benedek Tinusz, Nóra Vörhendi, Dóra Mosztbacher, Áron Vincze, Tamás Takács, László Czakó, Ferenc Izbéki, László Gajdán, Veronika Dunás-Varga, József Hamvas, Mária Papp, Krisztina Eszter Fehér, Márta Varga, Artautas Mickevicius, Imola Török, Klementina Ocskay, Márk Félix Juhász, Szilárd Váncsa, Nándor Faluhelyi, Orsolya Farkas, Attila Miseta, András Vereczkei, Alexandra Mikó, Péter Jenő Hegyi, Andrea Szentesi, Andrea Párniczky, Bálint Erőss, Péter Hegyi
Dátum:2021
ISSN:1424-3903
Megjegyzések:BACKGROUND Pseudocysts being the most frequent local complications of acute pancreatitis (AP) have substantial effect on the disease course, hospitalization and quality of life of the patient. Our study aimed to understand the effects of pre existing (OLD-P) and newly developed (NEW-P) pseudocysts on AP. METHODS Data were extracted from the Acute Pancreatitis Registry organized by the Hungarian Pancreatic Study Group (HPSG). 2275 of 2461 patients had uploaded information concerning pancreatic morphology assessed by imaging technique. Patients were divided into "no pseudocyst" (NO-P) group, "old pseudocyst" (OLD-P) group, or "newly developed pseudocyst" (NEW-P) groups. RESULTS The median time of new pseudocyst development was nine days from hospital admission and eleven days from the beginning of the abdominal pain. More NEW-P cases were severe (15.9% vs 4.7% in the NO-P group p<0.001), with longer length of hospitalization (LoH) (median: 14 days versus 8 days, p<0.001), and were associated with several changed laboratory parameters. OLD-P was associated with male gender (72.2% vs. 56.1%, p=0.0014), alcoholic etiology (35.2% vs. 19.8% in the NO-P group), longer hospitalization (median: 10 days, p<0.001), a previous episode of AP (p<0.001), pre-existing diagnosis of chronic pancreatitis (CP) (p<0.001), current smoking (p<0.001), and increased alcohol consumption (unit/week) (p=0.014). CONCLUSION Most of the new pseudocysts develop within two weeks. Newly developing pseudocysts are associated with a more severe disease course and increased length of hospitalization. Pre-existing pseudocysts are associated with higher alcohol consumption and smoking. Because CP is more frequently associated with a pre-existing pseudocyst, these patients need closer attention after AP.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Pancreatology. - 21 : 6 (2021), p. 1161-1172. -
További szerzők:Gede Noémi Váradi Alex (1991-) (biológus) Tinusz Benedek Vörhendi Nóra Mosztbacher Dóra Vincze Áron Takács Tamás (Szeged) Czakó László Izbéki Ferenc Gajdán László Dunás-Varga Veronika Hamvas József Papp Mária (1975-) (belgyógyász, gasztroenterológus) Fehér Krisztina Eszter Varga Márta Mickevicius, Artautas Török Imola Ocskay Klementina Juhász Márk Félix Váncsa Szilárd Faluhelyi Nándor Farkas Orsolya Miseta Attila Vereczkei András Mikó Alexandra Hegyi Péter Jr. (belgyógyász) Szentesi Andrea Párniczky Andrea (gyermekgyógyász) Erőss Bálint Hegyi Péter Jenő (belgyógyász)
Internet cím:Intézményi repozitóriumban (DEA) tárolt változat
DOI
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4.

001-es BibID:BIBFORM082672
035-os BibID:(cikkazonosító)1202 (WoS)000487293600001 (Scopus)85072974153
Első szerző:Szentesi Andrea
Cím:Multiple Hits in Acute Pancreatitis : Components of Metabolic Syndrome Synergize Each Other's Deteriorating Effects / Andrea Szentesi, Andrea Párniczky, Áron Vincze, Judit Bajor, Szilárd Gódi, Patricia Sarlós, Noémi Gede, Ferenc Izbéki, Adrienn Halász, Katalin Márta, Dalma Dobszai, Imola Török, Hunor Farkas, Mária Papp, Márta Varga, József Hamvas, János Novák, Artautas Mickevicius, Elena Ramirez Maldonado, Ville Sallinen, Dóra Illés, Balázs Kui, Bálint Erőss, László Czakó, Tamás Takács, Péter Jr. Hegyi, Hungarian Pancreatic Study Group
Dátum:2019
ISSN:1664-042X
Megjegyzések:Introduction: The incidence of acute pancreatitis (AP) and the prevalence of metabolic syndrome (MetS) are growing worldwide. Several studies have confirmed that obesity (OB), hyperlipidemia (HL), or diabetes mellitus (DM) can increase severity, mortality, and complications in AP. However, there is no comprehensive information on the independent or joint effect of MetS components on the outcome of AP. Our aims were (1) to understand whether the components of MetS have an independent effect on the outcome of AP and (2) to examine the joint effect of their combinations. Methods: From 2012 to 2017, 1435 AP cases from 28 centers were included in the prospective AP Registry. Patient groups were formed retrospectively based on the presence of OB, HL, DM, and hypertension (HT). The primary endpoints were mortality, severity, complications of AP, and length of hospital stay. Odds ratio (OR) with 95% confidence intervals (CIs) were calculated. Results: 1257 patients (55.7 ? 17.0 years) were included in the analysis. The presence of OB was an independent predictive factor for renal failure [OR: 2.98 (CI: 1.33?6.66)] and obese patients spent a longer time in hospital compared to non-obese patients (12.1 vs. 10.4 days, p = 0.008). HT increased the risk of severe AP [OR: 3.41 (CI: 1.39?8.37)], renal failure [OR: 7.46 (CI: 1.61?34.49)], and the length of hospitalization (11.8 vs. 10.5 days, p = 0.020). HL increased the risk of local complications [OR: 1.51 (CI: 1.10?2.07)], renal failure [OR: 6.4 (CI: 1.93?21.17)], and the incidence of newly diagnosed DM [OR: 2.55 (CI: 1.26?5.19)]. No relation was found between the presence of DM and the outcome of AP. 906 cases (mean age ? SD: 56.9 ? 16.7 years) had data on all four components of MetS available. The presence of two, three, or four MetS factors increased the incidence of an unfavorable outcome compared to patients with no MetS factors. Conclusion: OB, HT, and HL are independent risk factors for a number of complications. HT is an independent risk factor for severity as well. Components of MetS strongly synergize each other's detrimental effect. It is important to search for and follow up on the components of MetS in AP.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
acute pancreatitis
metabolic syndrome
obesity
diabetes mellitus
hypertension
hyperlipidemia severity
mortality
Megjelenés:Frontiers in Physiology. - 10 (2019), p. 1-13. -
További szerzők:Párniczky Andrea (gyermekgyógyász) Vincze Áron Bajor Judit Gódi Szilárd Sarlós Patrícia Gede Noémi Izbéki Ferenc Halász Adrienn Márta Katalin Dobszai Dalma Török Imola Farkas Hunor Papp Mária (1975-) (belgyógyász, gasztroenterológus) Varga Márta Hamvas József Novák János Mickevicius, Artautas Maldonado, Elena Ramirez Sallinen, Ville Illés Dóra Kui Balázs Erőss Bálint Czakó László Takács Tamás (Szeged) Hegyi Péter Jr. (belgyógyász) Hungarian Pancreatic Study Group
Pályázati támogatás:KH125678
Egyéb
K116634
Egyéb
K120335
Egyéb
K128222
Egyéb
GINOP 2.3.2-15-2016-00048
GINOP
EFOP-3.6.2-16-2017-00006
EFOP
LP2014-10/2014
Egyéb
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
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5.

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
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
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