Time Dynamics of Symptom Progression in Patients with Acute Pancreatitis: A Dynamic Time Warping Analysis

Rui Han¹Xiaoyu Deng²Hebing Liu³Yujie Duan¹Kexin Huang¹Qinghuan Kong¹Yuhang Pu¹Yongliang Jiao¹Haiqi Yang¹Yong Jia^1*Zhaohua Cheng^4*

• ¹School of Nursing, Jilin University, Changchun, China
• ²University of Cambridge Department of Psychology, Cambridge, United Kingdom
• ³Northeast Normal University College of Humanities and Sciences, Changchun, China
• ⁴The Second Hospital of Jilin University, Changchun, China

ABSTRACT Background: Acute pancreatitis (AP) morbidity has been increasing in recent years. Patients with AP exhibit highly variable symptom patterns over time, posting challenges to traditional analytical methods. Dynamic Time Warping (DTW) effectively aligns temporal sequences of different rhythms, offering a novel approach to model these complex dynamics. Objective: This study employs DTW technology to systematically analyse the individualised developmental trajectories of symptom clusters in patients with AP, delving into the heterogeneous characteristics during the process of time series changes. Methods: In a longitudinal study of 155 patients with AP, 32 symptoms were assessed using the Memorial Symptom Assessment Scale at hospitalization and 1, 3, 6, 9, and 12 months post-discharge. DTW was used to analyse temporal dynamics, generating individual symptom distance matrices. At the group level, these matrices are integrated using Distatis analysis, followed by hierarchical clustering to identify symptom clusters and network analysis to determine central symptoms. Results: Each patient had unique symptom manifestations and dynamic change patterns. Six major symptom clusters were identified: emotional disorder cluster, appetite disorder cluster, multi-system physical discomfort cluster, localised physiological perception abnormality cluster, functional decline cluster, and abdominal discomfort cluster. Centrality analysis revealed that the appetite domain exhibited high centrality, suggesting that its variation may influence multiple aspects of patient experience. Conclusion: DTW provides a novel and effective approach for analysing the temporal trajectories of symptoms both within and across individuals. The research results provide methodological support and empirical evidence for individualised symptom management, early intervention, and predictive model construction of AP progression.