International journal of surgery (London, England) · 2025
Association of albumin trajectories and cumulative exposure with in-hospital mortality in acute pancreatitis: a retrospective cohort study.
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Zou Yaoyu, Kuang Maobin, Xiong Shixuan, Xu Xin, Li Xueyang, Ding Ling, He Cong, Li Nianshuang, Ke Huajing, Huang Xin, Lei Yupeng, Xiong Huifang, He Wenhua, Luo Lingyu, Xia Liang, Lu Nonghua, Wan Jianhua, Zhu Yin
Аннотация
BACKGROUND: Hypoalbuminemia is common in acute pancreatitis (AP) and associated with poor outcomes, but its cumulative and dynamic impacts are not well characterized.
METHODS: This study included 3,214 AP patients (2005-2023). Cumulative albumin exposure (CumALB) was calculated over the first 7 days using the trapezoidal method. Latent class mixed modeling (LCMM) identified distinct albumin trajectories. Multivariable logistic regression and restricted cubic splines (RCS) assessed associations between CumALB and in-hospital mortality. Kaplan-Meier curves compared survival across trajectories. A simplified nomogram was developed using predictors selected via Boruta and LASSO algorithms, with performance assessed by AUC, calibration, and decision curves. Validation was conducted in three cohorts: the MIMIC-IV database ( n = 514), the eICU-CRD database ( n = 211), and the local cohort from 2024 ( n = 880).
RESULTS: Patients in the lowest CumALB tertile had significantly higher mortality (11.0%) than those in the highest tertile (1.3%, P < 0.001). Each 1-SD increase in CumALB reduced mortality risk by 42% (adjusted OR = 0.58, 95% CI: 0.44-0.76, P < 0.001), with RCS confirming a linear inverse relationship. CumALB outperformed single-day albumin in mortality prediction. LCMM identified four trajectories; low-stable (LS-T1) had highest mortality (17.7%), whereas low-increasing (LI-T4) had lower mortality (8.6%). Compared with LS-T1, high-stable (HS-T2) and LI-T4 groups had reduced risks (adjusted OR = 0.16 and 0.49, respectively; P < 0.05). The CumALB-based nomogram achieved an AUC of 0.836 in the training set (70%) and 0.864 in the internal test set (30%), outperforming APACHE II (AUC = 0.76), SIRS (AUC = 0.72), Ranson (AUC = 0.72), and BISAP (AUC = 0.80). Validation was conducted using three independent cohorts: the MIMIC-IV cohort (AUC = 0.631), the eICU-CRD cohort (AUC = 0.681), and the local cohort from 2024 (AUC = 0.844). Sensitivity analyses further confirmed the robustness of these results.
CONCLUSION: CumALB may provide a useful measure of the cumulative burden of hypoalbuminemia in patients with acute pancreatitis, and albumin trajectories could help capture its dynamic changes. The CumALB-based predictive model demonstrated good performance in predicting mortality risk, potentially assisting clinicians in early risk stratification and clinical decision-making for high-risk patients within heterogeneous populations. However, prospective validation is warranted before clinical implementation.
METHODS: This study included 3,214 AP patients (2005-2023). Cumulative albumin exposure (CumALB) was calculated over the first 7 days using the trapezoidal method. Latent class mixed modeling (LCMM) identified distinct albumin trajectories. Multivariable logistic regression and restricted cubic splines (RCS) assessed associations between CumALB and in-hospital mortality. Kaplan-Meier curves compared survival across trajectories. A simplified nomogram was developed using predictors selected via Boruta and LASSO algorithms, with performance assessed by AUC, calibration, and decision curves. Validation was conducted in three cohorts: the MIMIC-IV database ( n = 514), the eICU-CRD database ( n = 211), and the local cohort from 2024 ( n = 880).
RESULTS: Patients in the lowest CumALB tertile had significantly higher mortality (11.0%) than those in the highest tertile (1.3%, P < 0.001). Each 1-SD increase in CumALB reduced mortality risk by 42% (adjusted OR = 0.58, 95% CI: 0.44-0.76, P < 0.001), with RCS confirming a linear inverse relationship. CumALB outperformed single-day albumin in mortality prediction. LCMM identified four trajectories; low-stable (LS-T1) had highest mortality (17.7%), whereas low-increasing (LI-T4) had lower mortality (8.6%). Compared with LS-T1, high-stable (HS-T2) and LI-T4 groups had reduced risks (adjusted OR = 0.16 and 0.49, respectively; P < 0.05). The CumALB-based nomogram achieved an AUC of 0.836 in the training set (70%) and 0.864 in the internal test set (30%), outperforming APACHE II (AUC = 0.76), SIRS (AUC = 0.72), Ranson (AUC = 0.72), and BISAP (AUC = 0.80). Validation was conducted using three independent cohorts: the MIMIC-IV cohort (AUC = 0.631), the eICU-CRD cohort (AUC = 0.681), and the local cohort from 2024 (AUC = 0.844). Sensitivity analyses further confirmed the robustness of these results.
CONCLUSION: CumALB may provide a useful measure of the cumulative burden of hypoalbuminemia in patients with acute pancreatitis, and albumin trajectories could help capture its dynamic changes. The CumALB-based predictive model demonstrated good performance in predicting mortality risk, potentially assisting clinicians in early risk stratification and clinical decision-making for high-risk patients within heterogeneous populations. However, prospective validation is warranted before clinical implementation.