In this retrospective cohort study of ARDS patients complicated with sepsis in the ICU, we validated the presence of elevated lactate levels in septic patients with ARDS. Importantly, this is the first study to document the value of GBTM-based serial blood lactate evaluations to significantly improve the diagnostic capacity of traditional critical care evaluation systems compared to previously described lactate approaches. Interestingly, we used the MFPI algorithm to demonstrate that GBTM lactate groups yield superior performance in identifying high-risk patients than initial lactate groups for both short- and long-term outcomes.
Sepsis/multiple organ failure is well-established as a common cause of mortality in ARDS patients, and improvement in clinical outcomes may depend more on the management of sepsis/multiple organ failure than on oxygenation measures alone [20]. It is widely acknowledged that blood lactate level is a useful marker of the severity of sepsis or multiple organ failure, with higher levels predictive of higher mortality [9]. The peak lactate level has been initially applied in various blood lactate evaluation systems [8]. However, it should be borne in mind that tissue hypoperfusion and hypoxia may be present with elevated lactate levels before routine hemodynamic measurements change [30]. Therefore, initial measurements of lactate levels in the ICU are valuable for early identification. Mikkelsen et al. found that the initial serum lactate was associated with mortality independent of clinically apparent organ dysfunction and shock in patients admitted to the emergency department with severe sepsis [10]. Early initial lactate-guided therapy can significantly reduce ICU mortality [11]. Overwhelming evidence substantiates that initial blood lactate levels ranging from 2.0 to 4.0 mmol/L are associated with poor outcomes [9, 10, 12, 13]. The initial lactate is simple to calculate and readily available in all institutions. However, a single measurement of the lactate concentration can be challenging to interpret, especially in patients with ARDS, since it reflects a balance between lactate production and elimination. In this study, we divided the initial lactate into three groups with 2.0 mmol/L and 4.0 mmol/L as cut-off values for comparison with the GBTM lactate groups. The high initial lactate group exhibited lower mortality rates than the corresponding GBTM-based lactate group. The initial lactate groups exhibited lower survival during survival curve analysis than the GBTM lactate groups (Supplemental Fig. 4). More importantly, we specifically compared GBTM lactate groups with the initial lactate groups using the MFPI algorithm. Both high (group 3) and low (group 2) initial lactate groups did not correspond well to relative high-risk and low-risk clinical outcomes on the pre-specified continuous age, eGFR, SOFA score, and APACHE II score, nor could it obtain the high-risk interval with statistical significance. Taken together, our findings substantiate that GBTM lactate groups are more advantageous than the initial lactate groups.
Since continuous blood lactate levels assessment may provide more information than individual values, serial blood lactate measurements have been proposed [31]. Subsequently, the concepts of hyperlactatemia duration [15], lactate clearance [17], and lactate AUC [16] have been recommended. In our study, GBTM-based lactate groups could roughly cover patients with high initial blood lactate, peak lactate level and lactate AUC values (Supplemental Fig. 2B), with group 3 more tightly associated with the three parameters than group 2 or 1. Accordingly, the GBTM groups could account for findings in the above four lactate evaluation systems. Findings in GBTM lactate groups were not driven by individual parameters such as initial lactate, peak lactate value, lactate AUC, etc., but by a combination of these. In addition, GBTM lactate groups exhibited significantly enhanced diagnostic performance of the established model of SOFA score/APACHE II score with the addition of initial lactate. Meanwhile, the AUC, NRI and IDI obtained by adding GBTM lactate groups were the largest compared with established models where lactate AUC, lactate clearance and the peak lactate values were added, suggesting better diagnostic efficacy.
Several limitations and shortcomings were present in this study. Given its retrospective design, our study may have been subject to systematic errors and biases with missing values for serial lactate measurements. Nevertheless, the random forest data interpolation method based on machine learning [27], known to outperform all other data interpolation methods [32], was used to handle the missing data. Moreover, as an observational study, we could not establish a causal relationship between lactate groups and clinical outcomes and exclude the impact of potential confounders. Indeed, we could not include these potential confounders during multivariate analysis due to the lack of data. Given the strong association between lactate groups and short- or long-term outcomes and the consistency of trends for continuous indicators during MFPI, it is highly unlikely that these factors can affect the conclusions of this study. Due to a lack of information (Such as bilateral infiltration on chest roentgenogram), we could not use the Berlin definition [33] to define patients with ARDS. Moreover, due to the study's retrospective nature, we could not determine the causal relationship between ARDS and sepsis. Given that the sample size in the study was small, our findings may have been biased in favor of effect size inflation, and the statistical ability may be insufficient to detect the correct number of tracks when using GBTM. Hence, future GBTM-based interventional studies with larger sample sizes are required to validate our findings.