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Background <p>Individualized management of early fluid therapy in acute pancreatitis (AP) remains challenging. Traditional studies primarily focus on static fluid balance, overlooking the heterogeneity of dynamic trajectories.</p> Methods <p>Based on a single-center retrospective cohort, 3,142 AP patients admitted within 72&#xa0;h of onset were included. Daily fluid therapy-to-body weight ratio (FWR) and CumFWR (trapezoidal AUC) were calculated. Latent Class Growth Modeling (LCGM) identified dynamic FWR trajectories within 72&#xa0;h. Multivariate Cox regression analyzed the relationship between FWR and in-hospital mortality risk. Three-dimensional fitted surface plot analysis evaluated interactions between CumFWR and hematocrit.</p> Results <p>LCGM successfully identified five distinct dynamic fluid therapy trajectories within 72&#xa0;h, showing significant clinical differences: Low Stable Group (LSG1, n = 229, 7.3%), Low-Moderate Sustained Group (LMSG2, n = 340, 10.8%), Moderate Stable Group (MSG3, n = 2073, 66.0%), Moderate-High Fluctuating Group (MHFG4, n = 231, 7.4%), and High Sustained Group (HSG5, n = 269, 8.6%). Multivariate Cox regression revealed significantly increased in-hospital mortality risk compared to MSG3 for both MHFG4 (adjusted HR = 2.08, 95%CI 1.15–3.78) and HSG5 (adjusted HR = 2.91, 95%CI 1.77–4.79). Furthermore, each 1 standard deviation increase in CumFWR was associated with a 47% increased mortality risk (HR = 1.47, 95%CI 1.26–1.72). Three-dimensional fitted surface plot demonstrated high mortality risk between high CumFWR and abnormal hematocrit (low/high HCT), particularly prominent in the HSG5 group (<i>p</i> &lt; 0.001).</p> Conclusion <p>This study reveals five distinct dynamic trajectory patterns of early fluid therapy in AP. High-load sustained or fluctuating therapy significantly increases mortality risk. Dynamic monitoring of HCT (within a 35–44% safety window) and therapy trajectories offers a potential strategy to optimize fluid management.</p>

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Early fluid therapy trajectories in acute pancreatitis: a retrospective cohort study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月5日

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  • Jianhua Wan,
  • Shixuan Xiong,
  • Yaoyu Zou,
  • Maobin Kuang,
  • Huajing Ke,
  • Wenhua He,
  • Yin Zhu,
  • Nonghua Lu,
  • Liang Xia

摘要

Background

Individualized management of early fluid therapy in acute pancreatitis (AP) remains challenging. Traditional studies primarily focus on static fluid balance, overlooking the heterogeneity of dynamic trajectories.

Methods

Based on a single-center retrospective cohort, 3,142 AP patients admitted within 72 h of onset were included. Daily fluid therapy-to-body weight ratio (FWR) and CumFWR (trapezoidal AUC) were calculated. Latent Class Growth Modeling (LCGM) identified dynamic FWR trajectories within 72 h. Multivariate Cox regression analyzed the relationship between FWR and in-hospital mortality risk. Three-dimensional fitted surface plot analysis evaluated interactions between CumFWR and hematocrit.

Results

LCGM successfully identified five distinct dynamic fluid therapy trajectories within 72 h, showing significant clinical differences: Low Stable Group (LSG1, n = 229, 7.3%), Low-Moderate Sustained Group (LMSG2, n = 340, 10.8%), Moderate Stable Group (MSG3, n = 2073, 66.0%), Moderate-High Fluctuating Group (MHFG4, n = 231, 7.4%), and High Sustained Group (HSG5, n = 269, 8.6%). Multivariate Cox regression revealed significantly increased in-hospital mortality risk compared to MSG3 for both MHFG4 (adjusted HR = 2.08, 95%CI 1.15–3.78) and HSG5 (adjusted HR = 2.91, 95%CI 1.77–4.79). Furthermore, each 1 standard deviation increase in CumFWR was associated with a 47% increased mortality risk (HR = 1.47, 95%CI 1.26–1.72). Three-dimensional fitted surface plot demonstrated high mortality risk between high CumFWR and abnormal hematocrit (low/high HCT), particularly prominent in the HSG5 group (p < 0.001).

Conclusion

This study reveals five distinct dynamic trajectory patterns of early fluid therapy in AP. High-load sustained or fluctuating therapy significantly increases mortality risk. Dynamic monitoring of HCT (within a 35–44% safety window) and therapy trajectories offers a potential strategy to optimize fluid management.