• Patient Prefer Adher · Jan 2024

    Predictive Value of Troponin I, Creatinine Kinase Isoenzyme and the New Japanese Severity Score in Severe Acute Pancreatitis.

    • Xiaoxing Wei, Shengteng Guo, and Qinghua Wang.
    • School of Nursing (School of Gerontology), Binzhou Medical University, Binzhou, Shandong, People's Republic of China.
    • Patient Prefer Adher. 2024 Jan 1; 18: 113111401131-1140.

    PurposeTo evaluate troponin I, creatine kinase isoenzyme, and the new Japanese Severity Score(JSS) for predicting Severe Acute Pancreatitis-Associated myocardial Injury(SACI).Patients And MethodsThis retrospective study included 136 patients with Severe Acute Pancreatitis, hospitalized in grade-III hospital from June 1, 2015, to October 31, 2022; selected using convenience sampling method and divided into SACI occurrence (n =34) and SACI non-occurrence (n =102) groups. New JSS evaluated predictive value of each SACI index. Binary logistic regression model compared risk factors and constructed a prediction model. Area under receiver operating characteristic curve (AUC) and Hosmer-Lemeshow goodness of fit test evaluated model's prediction efficiency and calibration ability.ResultsThe incidence of SACI was 25%. Univariate analysis found that troponin I and creatine kinase isoenzyme were significantly different (P < 0.05) and independent risk factors for SACI. The new JSS, troponin I, and creatine kinase isoenzyme were included in the prediction model. The prediction model had a good calibration ability, and its predicted value and the actual observed value were not significantly different (Hosmer-Lemeshow χ2 = 5.408, P = 0.368). AUC of the model was 0.803 (95% CI: 0.689-0.918), and the optimal threshold of the prediction model was 0.318 with the maximum Youden index (0.488). The AUC for internal validation was 0.788 (95% CI: 0.657-0.876), and external validation was 0.761 (95% CI: 0.622-0.832).ConclusionTroponin I and creatine kinase isoenzymes combined with the new JSS have a high predictive value for SACI, improving the early prediction and treatment of at-risk patients.© 2024 Wei et al.

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