Background: C-reactive protein level (CRP) and white blood cell count (WBC) have been variably used in clinical trials on acute pancreatitis (AP). We assessed their potential role. Methods: First, we investigated studies which have used CRP or WBC, to describe their current role in trials on AP. Second, we extracted the data of 1435 episodes of AP from our registry. CRP and WBC on admission, within 24 h from the onset of pain and their highest values were analyzed. Descriptive statistical tools as Kruskal-Wallis, Mann-Whitney U, Levene's F tests, Receiver Operating Characteristic (ROC) curve analysis and AUC (Area Under the Curve) with 95% confidence interval (CI) were performed. Results: Our literature review showed extreme variability of CRP used as an inclusion criterion or as a primary outcome or both in past and current trials on AP. In our cohort, CRP levels on admission poorly predicted mortality and severe cases of AP; AUC: 0.669 (CI:0.569-0.770); AUC:0.681 (CI: 0.601-0.761), respectively. CRP levels measured within 24 h from the onset of pain failed to predict mortality or severity; AUC: 0.741 (CI:0.627-0.854); AUC:0.690 (CI:0.586-0.793), respectively. The highest CRP during hospitalization had equally poor predictive accuracy for mortality and severity AUC:0.656 (CI:0.544-0.768); AUC:0.705 (CI:0.640-0.769) respectively. CRP within 24 h from the onset of pain used as an inclusion criterion markedly increased the combined event rate of mortality and severe AP (13% for CRP > 25 mg/l and 28% for CRP > 200 mg/l). Conclusion: CRP within 24 h from the onset of pain as an inclusion criterion elevates event rates and reduces the number of patients required in trials on AP.

Akuutti haimatulehdus on tavallinen sairaus kirurgian päivystyksessä akuutti vatsa -potilailla. Haimatulehduksen etiologian määrittämisellä on tärkeä rooli toisaalta mahdollisesti tarvittavien hoitotoimenpiteiden valitsemisessa, mutta ennen kaikkea uusiutumisen estossa. Yleisimmät etiologiset tekijät akuutin pankreatiitin taustalla ovat alkoholin liiallinen käyttö sekä sappikivitauti. Harvinaisempia aiheuttajia ovat haiman tai haimatiehyen mekaaninen ärsytys toimenpiteen seurauksena, hypertriglyseridemia, autoimmuunitulehdus sekä tietyt lääkeaineet. Osassa tapauksista aiheuttajaa ei löydetä ja nämä jäävät ns. idiopaattisiksi. Teimme retrospektiivisen katsauksen Helsingin Yliopistolliseen sairaalaan kuuluvassa Meilahden sairaalassa vuosina 2016-2018 hoidetuista akuuttiin pankreatiittiin sairastuneista potilaista. Tarkoituksenamme oli selvittää akuutin haimatulehduksen tämänhetkinen ilmaantuvuus sekä mahdolliset muutokset haimatulehdusten etiologiajakaumassa. Lisäksi arvioimme tarkasteltavina olleiden suureiden mahdollista osuutta altistavina tekijöinä akuuttiin haimatulehdukseen sairastumiselle. Arvioitavia suureita olivat potilaiden ikä, sukupuoli, tupakointihistoria, alkoholinkäyttö, BMI sekä veren hyytymistä estävän lääkityksen käyttö. Tarkistimme myös potilaiden elossaolotiedot sekä selvitimme ilmenneet haimasyöpätapaukset akuuttiin pankreatiittiin sairastaneilla potilailla. Akuutin pankreatiitin insidenssi oli matalampi kuin aiemmissa suomalaisissa tutkimuksissa. Alkoholipankreatiittien osuus oli vähentynyt, mutta oli edelleen korkeampi kuin muissa Pohjoismaissa. Sappipankreatiittien osuus oli noussut. Idiopaattisiksi jääneissä ja alkoholin aiheuttamissa tapauksissa tupakointi esittäytyi merkittävänä riskitekijänä. Idiopaattisissa tapauksissa myös antikoagulanttien käyttö oli mahdollinen haimatulehduksen riskitekijä. Obesiteetti vaikutti olevan merkittävä riskitekijä sekä idiopaattiselle että sappikivitaudin aiheuttamalle pankreatiitille.

Background Acute pancreatitis (AP) is a potentially severe or even fatal inflammation of the pancreas. Early identification of patients 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 h to predict the severity; therefore, the early therapeutic window is often missed. Methods The early achievable severity index (EASY) is a multicentre, multinational, prospective and observational study (ISRCTN10525246). The predictions were made using machine learning models. We used the scikit-learn, xgboost and catboost Python packages for modelling. We evaluated our models using fourfold cross-validation, and the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and accuracy metrics were calculated on the union of the test sets of the cross-validation. The most critical factors and their contribution to the prediction were identified using a modern tool of explainable artificial intelligence called SHapley Additive exPlanations (SHAP). Results The prediction model was based on an international cohort of 1184 patients and a validation cohort of 3543 patients. The best performing model was an XGBoost classifier with an average AUC score of 0.81 +/- 0.033 and an accuracy of 89.1%, and the model improved with experience. The six most influential features were the respiratory rate, body temperature, abdominal muscular reflex, gender, age and glucose level. Using the XGBoost machine learning algorithm for prediction, the SHAP values for the explanation and the bootstrapping method to estimate confidence, we developed a free and easy-to-use web application in the Streamlit Python-based framework (http://easy-app.org/). Conclusions The EASY prediction score is a practical tool for identifying patients at high risk for severe AP within hours of hospital admission. The web application is available for clinicians and contributes to the improvement of the model.

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.