Lactate trajectories and risk assessment of acute kidney injury and in-hospital death in mechanically ventilated sepsis patients_West China Medical Journal

Authors：

ZHAN Ke , WEI Yuxuan , LI Hongqian , QI Ling , YANG Ting , TANG Yuhan , WANG Qiaoyu , TIAN Shulin ,  WU Weihua

Department of Nephrology, the Affiliated Hospital of Southwest Medical University / Sichuan Provincial Clinical Research Center for Kidney Disease, Luzhou, Sichuan 646000, P. R. China;

Corresponding?author：

WU Weihua, Email: 12390369@qq.com

Keywords：

Sepsis; lactate; Medical Information Mart for Intensive Care Ⅳ; acute kidney injury

DOI：

10.7507/1002-0179.202506198

Video：

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Objective To retrospectively analyze the clinical characteristics of different lactate trajectories in sepsis patients receiving mechanical ventilation (MV) and to investigate their associations with acute kidney injury (AKI) and in-hospital death risk, aiming to provide references for early renal protection in critically ill sepsis patients. Methods Data from sepsis patients receiving MV were extracted from the Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) database. The daily mean lactate values over the first 10 days were calculated. The latent class trajectory model (LCTM) was used to identify lactate trajectories over time and group the patients accordingly. AKI was the primary outcome measure, while in-hospital death was the secondary outcome measure. Logistic regression and Cox regression analyses were used to explore the associations between different lactate trajectories and these outcomes. Kaplan-Meier curves were drawn to compare in-hospital death risks among different lactate trajectory groups. Results A total of 2 062 MV-treated sepsis patients were included. After LCTM analysis, 1 396 patients were classified into the low lactate trajectory group, 451 into the moderate lactate trajectory group, and 215 into the high lactate trajectory group. After adjusting for confounding factors, the high lactate trajectory group was associated with an increased risk of AKI and in-hospital death (P<0.05). Conclusions In sepsis patients receiving MV, those with high lactate trajectories have a higher risk of AKI. Lactate trajectory changes can serve as an early assessment indicator for AKI and mortality risk in critically ill sepsis patients.

Citation： ZHAN Ke, WEI Yuxuan, LI Hongqian, QI Ling, YANG Ting, TANG Yuhan, WANG Qiaoyu, TIAN Shulin, WU Weihua. Lactate trajectories and risk assessment of acute kidney injury and in-hospital death in mechanically ventilated sepsis patients. West China Medical Journal, 2025, 40(7): 1067-1072. doi: 10.7507/1002-0179.202506198 Copy

1.	Marik PE, Bellomo R. Stress hyperglycemia: AN essential survival response!. Crit Care, 2013, 17(2): 305.
2.	Nolt B, Tu F, Wang X, et al. Lactate and Immunosuppression in Sepsis. Shock, 2018, 49(2): 120-125.
3.	Li X, Yang Y, Zhang B, et al. Lactate metabolism in human health and disease. Signal Transduct Target Ther, 2022, 7(1): 305.
4.	Bou Chebl R, El Khuri C, Shami A, et al. Serum lactate is an independent predictor of hospital mortality in critically ill patients in the emergency department: a retrospective study. Scand J Trauma Resusc Emerg Med, 2017, 25(1): 69.
5.	Johnson AEW, Bulgarelli L, Shen L, et al. MIMIC-IV, a freely accessible electronic health record dataset. Sci Data, 2023, 10(1): 1.
6.	Sun DQ, Zheng CF, Lu FB, et al. Serum lactate level accurately predicts mortality in critically ill patients with cirrhosis with acute kidney injury. Eur J Gastroenterol Hepatol, 2018, 30(11): 1361-1367.
7.	Nasu T, Ueda K, Kawashima S, et al. Prediction of early acute kidney injury after trauma using prehospital systolic blood pressure and lactate levels: a prospective validation study. Injury, 2022, 53(1): 81-85.
8.	龔春蕾, 蔣遠霞, 唐艷, 等. 血乳酸升高是膿毒癥相關性急性腎損傷發生及死亡的獨立危險因素. 中華危重病急救醫學, 2022, 34(7): 714-720.
9.	Choi S, You J, Kim YJ, et al. High intraoperative serum lactate level is associated with acute kidney injury after brain tumor resection. J Neurosurg Anesthesiol, 2025, 37(1): 55-63.
10.	Jones BL, Nagin DS. A note on a Stata plugin for estimating group-based trajectory models. Sociol Methods Res, 2013, 42: 608-613.
11.	Chebl RB, Tamim H, Dagher GA, et al. Serum lactate as an independent predictor of in-hospital mortality in intensive care patients. J Intensive Care Med, 2020, 35(11): 1257-1264.
12.	Mirza SS, Wolters FJ, Swanson SA, et al. 10-year trajectories of depressive symptoms and risk of dementia: a population-based study. Lancet Psychiatry, 2016, 3(7): 628-635.
13.	Proust-Lima C, Letenneur L, Jacqmin-Gadda H. A nonlinear latent class model for joint analysis of multivariate longitudinal data and a binary outcome. Stat Med, 2007, 26(10): 2229-2245.
14.	Summary of Recommendation Statements. Kidney Int Suppl (2011), 2012, 2(1): 8-12.
15.	Huang S, Li X, Chen B, et al. Association between serum sodium trajectory and mortality in patients with acute kidney injury: a retrospective cohort study. BMC Nephrol, 2024, 25(1): 152.
16.	余雪勤. 二分類變量缺失數據處理方法的比較研究. 統計學與應用, 2023, 12(5): 1376-1384.
17.	Yue S, Li S, Huang X, et al. Machine learning for the prediction of acute kidney injury in patients with sepsis. J Transl Med, 2022, 20(1): 215.
18.	Vincent JL, Quintairos E Silva A, Couto L Jr, et al. The value of blood lactate kinetics in critically ill patients: a systematic review. Crit Care, 2016, 20(1): 257.
19.	Wei Y, Zhuang J, Li J, et al. Lactate trajectories and outcomes in patients with sepsis in the intensive care unit: group-based trajectory modeling. Front Public Health, 2025, 13: 1610220.
20.	Nichol A, Bailey M, Egi M, et al. Dynamic lactate indices as predictors of outcome in critically ill patients. Crit Care, 2011, 15(5): R242.
21.	Sakr Y, Dubois MJ, De Backer D, et al. Persistent microcirculatory alterations are associated with organ failure and death in patients with septic shock. Crit Care Med, 2004, 32(9): 1825-1831.
22.	Mesquida J, Espinal C, Gruartmoner G, et al. Prognostic implications of tissue oxygen saturation in human septic shock. Intensive Care Med, 2012, 38(4): 592-597.
23.	陶麗麗, 楊其霖, 陳維校. 入重癥監護室時血乳酸水平對膿毒癥患者急性腎損傷發生的預測價值. 實用臨床醫藥雜志, 2021, 25(14): 41-44, 53.
24.	Villar J, Short JH, Lighthall G. Lactate predicts both short- and long-term mortality in patients with and without sepsis. Infect Dis (Auckl), 2019, 12: 1178633719862776.
25.	Corradi F, Brusasco C, Paparo F, et al. Renal doppler resistive index as a marker of oxygen supply and demand mismatch in postoperative cardiac surgery patients. Biomed Res Int, 2015: 763940.
26.	Sun N, Zheng S, Rosin DL, et al. Development of a photoacoustic microscopy technique to assess peritubular capillary function and oxygen metabolism in the mouse kidney. Kidney Int, 2021, 100(3): 613-620.
27.	Kuwabara S, Goggins E, Okusa MD. The pathophysiology of sepsis-associated AKI. Clin J Am Soc Nephrol, 2022, 17(7): 1050-1069.
28.	Samuvel DJ, Sundararaj KP, Nareika A, et al. Lactate boosts TLR4 signaling and NF-kappaB pathway-mediated gene transcription in macrophages via monocarboxylate transporters and MD-2 up-regulation. J Immunol, 2009, 182(4): 2476-2484.
29.	高雪, 徐翎鈺, 管陳, 等. 血清乳酸脫氫酶水平與住院患者急性腎損傷的相關性研究及預后風險評估. 臨床醫學進展, 2024, 14(4): 952-962.
30.	Toro J, Manrique-Caballero CL, Gómez H. Metabolic reprogramming and host tolerance: a novel concept to understand sepsis-associated AKI. J Clin Med, 2021, 10(18): 4184.
31.	Smith JA, Stallons LJ, Schnellmann RG. Renal cortical hexokinase and pentose phosphate pathway activation through the EGFR/Akt signaling pathway in endotoxin-induced acute kidney injury. Am J Physiol Renal Physiol, 2014, 307(4): F435-F444.
32.	Waltz P, Carchman E, Gomez H, et al. Sepsis results in an altered renal metabolic and osmolyte profile. J Surg Res, 2016, 202(1): 8-12.
33.	An S, Yao Y, Hu H, et al. PDHA1 hyperacetylation-mediated lactate overproduction promotes sepsis-induced acute kidney injury via Fis1 lactylation. Cell Death Dis, 2023, 14(7): 457.
34.	Molema G, Zijlstra JG, van Meurs M, et al. Renal microvascular endothelial cell responses in sepsis-induced acute kidney injury. Nat Rev Nephrol, 2022, 18(2): 95-112.
35.	Wu L, Tiwari MM, Messer KJ, et al. Peritubular capillary dysfunction and renal tubular epithelial cell stress following lipopolysaccharide administration in mice. Am J Physiol Renal Physiol, 2007, 292(1): F261-F268.

1. Marik PE, Bellomo R. Stress hyperglycemia: AN essential survival response!. Crit Care, 2013, 17(2): 305.
2. Nolt B, Tu F, Wang X, et al. Lactate and Immunosuppression in Sepsis. Shock, 2018, 49(2): 120-125.
3. Li X, Yang Y, Zhang B, et al. Lactate metabolism in human health and disease. Signal Transduct Target Ther, 2022, 7(1): 305.
4. Bou Chebl R, El Khuri C, Shami A, et al. Serum lactate is an independent predictor of hospital mortality in critically ill patients in the emergency department: a retrospective study. Scand J Trauma Resusc Emerg Med, 2017, 25(1): 69.
5. Johnson AEW, Bulgarelli L, Shen L, et al. MIMIC-IV, a freely accessible electronic health record dataset. Sci Data, 2023, 10(1): 1.
6. Sun DQ, Zheng CF, Lu FB, et al. Serum lactate level accurately predicts mortality in critically ill patients with cirrhosis with acute kidney injury. Eur J Gastroenterol Hepatol, 2018, 30(11): 1361-1367.
7. Nasu T, Ueda K, Kawashima S, et al. Prediction of early acute kidney injury after trauma using prehospital systolic blood pressure and lactate levels: a prospective validation study. Injury, 2022, 53(1): 81-85.
8. 龔春蕾, 蔣遠霞, 唐艷, 等. 血乳酸升高是膿毒癥相關性急性腎損傷發生及死亡的獨立危險因素. 中華危重病急救醫學, 2022, 34(7): 714-720.
9. Choi S, You J, Kim YJ, et al. High intraoperative serum lactate level is associated with acute kidney injury after brain tumor resection. J Neurosurg Anesthesiol, 2025, 37(1): 55-63.
10. Jones BL, Nagin DS. A note on a Stata plugin for estimating group-based trajectory models. Sociol Methods Res, 2013, 42: 608-613.
11. Chebl RB, Tamim H, Dagher GA, et al. Serum lactate as an independent predictor of in-hospital mortality in intensive care patients. J Intensive Care Med, 2020, 35(11): 1257-1264.
12. Mirza SS, Wolters FJ, Swanson SA, et al. 10-year trajectories of depressive symptoms and risk of dementia: a population-based study. Lancet Psychiatry, 2016, 3(7): 628-635.
13. Proust-Lima C, Letenneur L, Jacqmin-Gadda H. A nonlinear latent class model for joint analysis of multivariate longitudinal data and a binary outcome. Stat Med, 2007, 26(10): 2229-2245.
14. Summary of Recommendation Statements. Kidney Int Suppl (2011), 2012, 2(1): 8-12.
15. Huang S, Li X, Chen B, et al. Association between serum sodium trajectory and mortality in patients with acute kidney injury: a retrospective cohort study. BMC Nephrol, 2024, 25(1): 152.
16. 余雪勤. 二分類變量缺失數據處理方法的比較研究. 統計學與應用, 2023, 12(5): 1376-1384.
17. Yue S, Li S, Huang X, et al. Machine learning for the prediction of acute kidney injury in patients with sepsis. J Transl Med, 2022, 20(1): 215.
18. Vincent JL, Quintairos E Silva A, Couto L Jr, et al. The value of blood lactate kinetics in critically ill patients: a systematic review. Crit Care, 2016, 20(1): 257.
19. Wei Y, Zhuang J, Li J, et al. Lactate trajectories and outcomes in patients with sepsis in the intensive care unit: group-based trajectory modeling. Front Public Health, 2025, 13: 1610220.
20. Nichol A, Bailey M, Egi M, et al. Dynamic lactate indices as predictors of outcome in critically ill patients. Crit Care, 2011, 15(5): R242.
21. Sakr Y, Dubois MJ, De Backer D, et al. Persistent microcirculatory alterations are associated with organ failure and death in patients with septic shock. Crit Care Med, 2004, 32(9): 1825-1831.
22. Mesquida J, Espinal C, Gruartmoner G, et al. Prognostic implications of tissue oxygen saturation in human septic shock. Intensive Care Med, 2012, 38(4): 592-597.
23. 陶麗麗, 楊其霖, 陳維校. 入重癥監護室時血乳酸水平對膿毒癥患者急性腎損傷發生的預測價值. 實用臨床醫藥雜志, 2021, 25(14): 41-44, 53.
24. Villar J, Short JH, Lighthall G. Lactate predicts both short- and long-term mortality in patients with and without sepsis. Infect Dis (Auckl), 2019, 12: 1178633719862776.
25. Corradi F, Brusasco C, Paparo F, et al. Renal doppler resistive index as a marker of oxygen supply and demand mismatch in postoperative cardiac surgery patients. Biomed Res Int, 2015: 763940.
26. Sun N, Zheng S, Rosin DL, et al. Development of a photoacoustic microscopy technique to assess peritubular capillary function and oxygen metabolism in the mouse kidney. Kidney Int, 2021, 100(3): 613-620.
27. Kuwabara S, Goggins E, Okusa MD. The pathophysiology of sepsis-associated AKI. Clin J Am Soc Nephrol, 2022, 17(7): 1050-1069.
28. Samuvel DJ, Sundararaj KP, Nareika A, et al. Lactate boosts TLR4 signaling and NF-kappaB pathway-mediated gene transcription in macrophages via monocarboxylate transporters and MD-2 up-regulation. J Immunol, 2009, 182(4): 2476-2484.
29. 高雪, 徐翎鈺, 管陳, 等. 血清乳酸脫氫酶水平與住院患者急性腎損傷的相關性研究及預后風險評估. 臨床醫學進展, 2024, 14(4): 952-962.
30. Toro J, Manrique-Caballero CL, Gómez H. Metabolic reprogramming and host tolerance: a novel concept to understand sepsis-associated AKI. J Clin Med, 2021, 10(18): 4184.
31. Smith JA, Stallons LJ, Schnellmann RG. Renal cortical hexokinase and pentose phosphate pathway activation through the EGFR/Akt signaling pathway in endotoxin-induced acute kidney injury. Am J Physiol Renal Physiol, 2014, 307(4): F435-F444.
32. Waltz P, Carchman E, Gomez H, et al. Sepsis results in an altered renal metabolic and osmolyte profile. J Surg Res, 2016, 202(1): 8-12.
33. An S, Yao Y, Hu H, et al. PDHA1 hyperacetylation-mediated lactate overproduction promotes sepsis-induced acute kidney injury via Fis1 lactylation. Cell Death Dis, 2023, 14(7): 457.
34. Molema G, Zijlstra JG, van Meurs M, et al. Renal microvascular endothelial cell responses in sepsis-induced acute kidney injury. Nat Rev Nephrol, 2022, 18(2): 95-112.
35. Wu L, Tiwari MM, Messer KJ, et al. Peritubular capillary dysfunction and renal tubular epithelial cell stress following lipopolysaccharide administration in mice. Am J Physiol Renal Physiol, 2007, 292(1): F261-F268.

West China Medical Journal

Lactate trajectories and risk assessment of acute kidney injury and in-hospital death in mechanically ventilated sepsis patients

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