This study was conducted to determine the characteristics of patients transferred to the ICU using a multicenter cohort. In this study, 41.1% of the patients selected for RRT were transferred to the ICU. Patients who were younger; female; had a higher SOFA or MEWS score; or did not have solid tumors, hematologic malignancies, or chronic lung disease were more likely to be admitted to the ICU after RRT activation. In addition, patients admitted to the ICU had an in-hospital mortality rate of 34.3%. Factors associated with patient mortality included older age, high SOFA or NEWS scores, high inflammatory markers, solid tumors, hematologic malignancies, chronic lung disease, and no history of diabetes mellitus (DM), cardiovascular disease, or transplantation. Univariate analysis of in-hospital mortality showed that ICU admission may be a risk factor; but multivariate analysis did not.
In our study, the ICU group had a higher rate of activation due to respiratory distress, sepsis, cardiac arrest, and various types of shock (Table 2). These findings are consistent with those of several previous studies 13–16 and support the notion that ICU patients experience multiple physiological instabilities 17. In addition, the ICU group underwent more frequent interventions such as central line insertion, intubation, and vasopressor administration compared to the GW group. These procedures are critical in managing conditions such as shock or respiratory failure, which are common reasons for initiating interventions in the ICU setting 9,13,18,19. Follow-up care is less complicated when interventions are implemented quickly 15,20. A meta-analysis published in 2015 showed an overall reduction in in-hospital mortality after RRS (RR 0.87, 95%CI 0.81–0.95, P < 0.001) 6. There is also evidence that RRT is associated with improved outcomes 21,22. Therefore, early intervention with RRT may be important to optimize patient management and outcomes.
In several other studies, approximately 20–40% of patients with activated RRT were transferred to the ICU 7–11, results which are similar to those of our study. Our previous study showed that factors influencing ICU admission included high disease severity, as indicated by high SOFA and NEWS scores 12. In the multivariate analysis performed in this study, in addition to factors indicating disease severity, younger age, no malignancy, and no history of chronic lung disease were identified as influencing factors. In some studies, older patients were admitted to the ICU with worse outcomes, such as 1-year mortality 23–25. Our results also showed that advanced age was a cause of increased in-hospital mortality, which could be attributed to the decision to transfer younger patients with a higher chance of survival to the ICU for critical care. In addition, patients with a history of cancer have a higher mortality rate 26; when patients with malignancies are admitted to the ICU, their mortality rate is approximately 40%, which is even higher in the case of hematological malignancies 27,28. In a meta-analysis conducted by Huapaya et al. 29, the in-hospital mortality of patients with various types of interstitial lung disease (ILD) was 52%. In addition, Brown et al. 30 showed that patients with ILD or chronic obstructive pulmonary disease (COPD) have a longer ICU stay than cancer patients. As these factors, like age, are associated with in-hospital mortality, these prognostically relevant factors have been shown to influence the decision to admit patients to the ICU.
The factors associated with in-hospital mortality were not significantly different from those reported in our previous single-center study 12. In this study, the risk factors for in-hospital mortality were older age, higher SOFA, NEWS2, lactate level, CRP level, WBC count, history of solid tumors, hematologic malignancy, and chronic lung disease. History of solid tumors, hematologic malignancies, and chronic lung disease are indicators of poor outcome 23–30. In a study conducted in 2018, to build a mortality prediction model for patients with RRT calls, systolic blood pressure (SBP), time from admission to RRT call, and RR were suggested as factors predicting mortality 20, which showed results consistent with our analysis. However, in our study, a low MEWS score was found to be a factor in the two death-related outcomes. MEWS has already been widely used as an early warning score and it is useful in predicting in-hospital outcomes 31,32. A meta-analysis published by Suwanpasu et al. 33 showed that the MEWS threshold of 4 or more had resasonable accuracy for predicting in-hospital death. In addition, the mean MEWS score of deceased patients was 3.5–4.5 34,35. In contrast, our results showed a mean MEWS score of 4.4 ± 2.2, with the ICU group having a higher mean of 5.0 ± 2.4. This suggests that patients in our study were more critically ill at the time of assessment compared to general predictions. In light of these findings, our study underscores the complexity of predicting mortality in hospitalized patients and highlights the need for a multifaceted approach that considers both traditional risk factors and specific patient characteristics, including MEWS scores, to accurately assess and manage in-hospital mortality risk.
This study has several limitations. First, our analysis was limited to evaluating the causes at the time of RRT activation, without considering additional complications or diagnoses that occurred after the patient was transferred to the ICU. Second, the inclusion criteria were limited to patients evaluated for RRT, excluding those who were admitted directly to the ICU or were unavailable, which may have introduced selection bias. Third, although there were variations among centers in patient demographics, RRT activation criteria, and timing of interventions, this multicenter retrospective cohort study utilized a large patient database. This provides a broad perspective of most RRT-activated patients, although it may not fully capture the nuances of individual center practices and patient populations.