Impact of Continuous Renal Replacement Therapy as Treatment for Sepsis-Associated Acute Kidney Injury on Lactate Levels and the Risk of 28-Day Mortality in Intensive Care Units

Results

Patient characteristics

Among the 717 S-AKI patients, 157 received CRRT. Table 1 lists the baseline characteristics of the two CRRT groups including demographics, vital signs, laboratory-result comorbidities, and SOFA scores. These characteristics demonstrate that CRRT was associated with significant differences in age, race, RDW, NA, MG, PHOS, CR, and UO, liver disease status, ventilator and vasopressor use, SOFA score, and 28-day mortality.

The longitudinal lactate data of 3661 observations were displayed using trajectory functions and plotted using interaction figures. Figure 2 indicates the linear trajectory record of lactate and log(lactate) for each patient over the 28-day analysis period. The figure shows that most observations were concentrated within the first 5 days after patient admission. Lactate levels of patients ranged from 0.5 to 20, with log(lactate) ranging from − 0.4 to 1.3. Cox regression was performed to analyze the relationship between CRRT and 28-day survival, with CRRT being adjusted for by age, race, RDW, NA, MG, PHOS, CR, and UO, liver disease status, ventilator and vasopressor use, and SOFA score. The Schoenfeld residuals test (Fig. 3) was used to determine the independence of residuals and the time to test for the proportional-hazards hypothesis in the Cox model. The results in Fig. 3 revealed that CRRT was not a time-dependent variable and therefore could be analyzed directly using Cox regression. CRRT was also found to not be related to 28-day survival in S-AKI patients after adjusting multiple variables.

Linear mixed-effect models, on the other hand, indicated the association between CRRT and log(lactate). Among the independent variables, CRRT and lactate observation time were statistically correlated with log(lactate) in longitudinal status. The result of the JM demonstrated that after combining the longitudinal submodel of lactate and the survival model of CRRT, CRRT was still not related to the 28-day survival of S-AKI patients. After adjusting the survival submodel, the correlation between CRRT use and elevation of log(lactate) was statistically significant. The parameter estimation of CRRT and log(lactate) indicated that using CRRT increased log(lactate) by 0.041 in S-AKI patients. The JM also instigated a fixed association between lactate level changes and the event result, producing an exp value of (1.755) = 5.78, indicating that an increase of one unit of log(lactate) will increase the risk of 28-day mortality 5.78-fold (Table 2).

Discussion

Our survival submodel indicates that CRRT use has no effect on the 28-day mortality of S-AKI patients in critical care. S-AKI patient often have weaker glomerular filtration functions, which can increase the probability of adverse symptoms such as electrolyte/acidolysis imbalance and also impair metabolism¹⁷. Therefore, preventing further aggravation through eliminating metabolic toxins to prevent further aggravation is necessary. CRRT is currently one of the main treatment methods¹⁸. This intervention focuses on replacing kidney function, removing toxic substances such as CR, or improving the fluid-electrolyte imbalance that allows for future treatments since patients are in a stable condition^18–20. Although CRRT is still the most common treatment for S-AKI, studies have indicated that renal replacement therapy cannot improve its survival^8,21. Whether to apply high-intensity CRRT to S-AKI patients remains controversial. Some studies have indicated that the use of high-dose renal replacement therapy does not improve the overall survival of patients or the recovery of renal function^21,22. The efficacy of CRRT on the prognosis of S-AKI can therefore not be confirmed.

The analysis of longitudinal submodel indicated that the use of CRRT is associated with increases in lactate levels within 28 days, while the joint modeling of longitudinal and survival data indicated that lactate level changes were associated with mortality and that log(lactate) is a risk factor for 28-day mortality in S-AKI patients. Many studies have confirmed lactate as a powerful biomarker for sepsis with renal damage and can accurately predict mortality^23–25. Reducing lactate is therefore a vital procedure for improving the likelihood of patient survival. However, although CRRT is the most popular treatment in patients with sepsis and AKI, there is still a possibility that it cannot reduce acidosis, resulting in the continued elevation of lactate levels after CRRT is performed²⁶. Potential explanations include how in clinical practice, since it is generally believed that if lactate fluctuates to a lower range, there will be no negative impact on the prognosis of patients. Therefore, these lower lactate levels may not receive adequate attention. Additionally, lactate levels may be affected by the buffer used in CRRT²⁷. For example, when using lactate-based fluids, sepsis patients failed to completely metabolize lactate²⁸, potentially leading to increased lactate levels, eventually developing into metabolic acidosis hyperlactatemia. Finally, when sepsis patients with AKI have more serious infections, vascular permeability is increased and the responses to vasopressors are poor. Although CRRT can temporarily remove toxins and other substances from the body, circulatory ischemia and hypoxia still cannot be improved, and lactate will also continuously increase²⁹. Our research found that across all ranges of lactate levels, the risk of death increased 5.78-fold for every unit increase in log(lactate). When using CRRT to treat patients with sepsis and AKI, we should therefore pay more attention to changes in patient lactate levels.

This study had some limitations. Some factors during the use of CRRT will impact survival, such as filter coagulation, the conversion of patients to intermittent hemodialysis after hemodynamic stability is reached, and the death of patients during treatment. The limited database means we could not analyze these impacts retrospectively. Additionally, the single-center nature of the database reduces the generalizability of our results, which must therefore be tested in further research.

Conclusion

CRRT is not an effective treatment for S-AKI patients in the critical-care unit, and has a tendency to increase lactate levels, which is a significant risk factor for the prognosis. Other treatments that focus on controlling lactate levels should receive more attention in critical care.

Declarations

Ethics approval and Consent to participate

The study was an analysis of a third-party anonymized publicly available database with pre-existing institutional review board (IRB) approval.

Consent for publication 

Not applicable

Availability of supporting data 

The data were available on the MIMIC-III website at https://mimic.physionet.org/

Competing interests

The authors declare that they have no competing interests.

Funding

This work was supported by the National Natural Science Foundation of China (No. 82072232; 81871585), the Natural Science Foundation of Guangdong Province (No. 2018A030313058), Technology and Innovation Commission of Guangzhou Science, China (No.201804010308).

Authors’ contributions

LZ created the study protocol, performed the statistical analyses and wrote the first manuscript draft. ZW conceived the study and critically revised the manuscript. FX assisted with the study design and performed data collection. YR assisted with data collection and manuscript editing. DH confirmed the data and assisted with the statistical analyses. CL assisted with study coordination and helped draft the manuscript. JL assisted with manuscript revision and data confirmation. HY contributed to data interpretation and manuscript revision. All authors read and approved the final manuscript.

Acknowledgment

None

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Tables

Table.1 Baseline characteristics between CRRT Unreceived /Received Group

Table.1 Baseline characteristics between CRRT Unreceived /Received Group(continued)

^*P-value is less than 0.05

Table.2 Result of effects between two submodels and the Joint Model

Cox: Cox Proportional Hazards Model; LME: Linear Mixed Effect Model; JM: Joint Model

LME submodel independents includes: CRRT use, time of lactate level, CRRT*Time, NLR, SOFA Group and age.

Cox submodel was adjusted by: Age, ethnicity, RDW, NA, MG, PHOS, CR, UO, liver disease status, ventilator use, vasopressor use, and SOFA score.