In this study, we implemented multivariate Cox regression to identify the independent risk factors associated with the hospital mortality of sepsis-related acute respiratory failure, and nine predictors including mechanical ventilation, immunosuppressive disease, Klebsiella pneumoniae, Acinetobacter baumannii, abdominal cavity infection, PO2 < 60 mmHg, neutrophils, white blood cell count, and systolic blood pressure were integrated into a prediction nomogram presented as a visualization model. Besides, the model had good performance in predictive value. To the best of our knowledge, this study is the first prediction model to determine mortality risk in sepsis patients with acute respiratory failure based on the MIMIC-IV database. Moreover, the model may be a clinically useful tool for predicting the short-term prognosis of such patients.
The lung is the most easily involved organ in severe infection. In sepsis, acute respiratory failure was the common sepsis-related organ injury (4, 7, 13) and led to significant mortality, which was even as high as 34% − 45% (14). For this reason, this study directly focuses on clinical characteristics relevant to the modifiable mortality in sepsis-associated acute respiratory failure. With increasing recognition that current approaches to the management of sepsis do not eliminate severe outcomes of sepsis patients due to complicated disease processes (1, 2) and that this complexity is also confounding the prognosis of sepsis patients with acute respiratory failure (7), the prognostic risk model may offer one potential approach. Although targeting sepsis has had some success (15, 16), this study provides the first prognostic model for sepsis-related acute respiratory failure to complement such a prediction system. Specifically, our findings suggest that prognostic predictors focusing on the lung, as presented by our data-driven analysis of mortality risk, especially mechanical ventilation, Klebsiella pneumoniae, Acinetobacter baumannii infection, and PO2 < 60 mmHg, may identify septic individuals most likely to die from factors associated with acute respiratory failure. Moreover, these findings on respiratory-related predictors are consistent with the following studies. Some reported that acute respiratory failure, a leading cause of ICU admission, often needed mechanical ventilation as a life-supporting intervention, but which could lead to excess mortality (5, 17). Some studies on respiratory infection showed that Klebsiella pneumonia substantially contributed to the mortality of nosocomial and ventilator-associated pneumonia in the ICU (18, 19), and that compared with non-Acinetobacter baumannii, sepsis patients with Acinetobacter baumannii pulmonary infection had a higher mortality rate (20). Besides, Acinetobacter baumannii was also one of the most common pathogens to cause hospital-acquired pneumonia, especially in the ICU (21), indicating that it may be a common and important mortality-related biomarker. Most importantly, according to the fact that Acinetobacter baumannii accounted for the largest weight in our model, the predictive value of Acinetobacter baumannii infection was applicable to sepsis patients with acute respiratory failure, and as the most important predictor to hospital mortality of such patients. In addition, PO2 < 60 mmHg as an important predictor of poor outcome was supported by an autopsy study, which showed that dead patients with severe acute respiratory distress syndrome were more likely to refractory hypoxemia (22). Therefore, focusing on clinically respiratory-related characteristics may be a priority for predicting the prognosis in sepsis patients with acute respiratory failure.
We also analyzed non-pulmonary risk factors and found significant results in this study. Although sepsis was derived from infection, severe sepsis was often accompanied by other organ impairment and even evolved into multiple organ dysfunction syndromes, the mortality of which was extremely high (2, 4). Therefore, the mortality of sepsis is clinically relevant to disease progression, comorbidity in particular. Interestingly, among comorbid diseases, only immunosuppressive disease was an independent predictor for hospital mortality of sepsis-related acute respiratory failure in this study. It has been confirmed that immunity damage is the main pathophysiological manifestation of the occurrence and progression of sepsis and aggravates the inflammatory cascade reaction (23, 24). Consistently, our finding on comorbid immunosuppression also highlights the important role of immunity in the short-term prognosis of sepsis patients. Based on the fact that the inflammatory response induced by infection is the promoter of sepsis (2, 24), we assume that inflammation-related markers may reflect the prognosis of sepsis. Our findings that white blood cell count and neutrophils from laboratory tests were independent prognostic biomarkers support this assumption. These biomarkers are common and necessary in clinical practice and can effectively reflect the response and severity of bacterial infection (25).
Although we also found that systolic blood pressure, an important hemodynamic index, independently affected the mortality of sepsis patients with acute respiratory failure, it was difficult to specifically identify the mortality risk if only based on clinical symptoms and signs. In this case, adding clinical biomarkers with the predictive value may help to solve this dilemma. However, infection site is also an important part of infection-related mortality in sepsis. Despite the impact of infection site on hospital mortality in sepsis patients cannot be defined based on a review (26), our finding showed that abdominal cavity infection was a mortality risk factor in sepsis patients with acute respiratory failure. This finding clearly supports the infection-related mortality theory. But surprisingly, a prior study reported that infection sites of pulmonary and other sources, but not abdominal, were predictive of outcome in sepsis patients with acute lung injury but not in those without acute lung injury (27). These seemingly contradictory results may be related to patient population, sample size, and other confounding factors. These different studies do not affect our understanding of the importance of infection site in sepsis, especially in sepsis-related acute respiratory failure, even though this heterogeneity may be confounding their clinical extension.
SAPS II was commonly a system score for the severity of critical illness and clinically a useful tool for predicting the short-term prognosis in sepsis (12, 28). But whether it applies to sepsis-associated acute respiratory failure remains unclear. Therefore, we developed a novel prognostic prediction model and compared its predictive performance with SAPS II in this study. Our finding suggests that SAPS II in discriminating sepsis-related acute respiratory failure patients under the risk of hospital mortality was not as good as previously reported. However, this finding was consistent with a study, which reported that SAPS II and SOFA scores had not significantly predictive value in sepsis mortality (29). In addition, this study also showed that the prediction model possessed the superior discrimination than SAPS II in the mortality risk. It compared with the previously developed model for predicting the mortality of patients with skin and soft tissue infections(ROC AUC of 0.84), our model still shows better discrimination(30). It follows that targeting a predictive model based on a combination of independent risk factors may be a preferred option for evaluating the short-term prognosis of sepsis patients with acute respiratory failure in the ICU.
There are some limitations to this study. First, this study has inherent shortcomings of the retrospective cohort study, although the MIMIC-IV database is currently the latest version of 0.4, including brand-new datasets from 2008 to 2019. Besides, the complexity of clinical data suggests that there may be unadjusted potential confounding factors hidden in this study. Second, one challenge of clinical research on sepsis is that there is no specific diagnostic method, it still relies on a rule-out definition, which may lead to relatively low sensitivity for the diagnosis of sepsis. Therefore, the model based on Sepsis-3 also faces the above challenge and can be used only in sepsis-related acute respiratory failure diagnosed by the exclusion method. Third, when evaluating the survival of such patients, we cannot absolutely rely on the model, combine specific clinical support conditions, such as FiO2, whether to use vasoactive drugs, etc. The model is only used as an aid to the evaluation. Finally, the external performance of the model may need to be further evaluated due to the lack of a prospective cohort to validate the model.
This study provides a novel prediction model for hospital mortality in ICU patients with sepsis and acute respiratory failure, based on the MIMIC-IV database. In the cohort, mechanical ventilation, immunosuppressive disease, Klebsiella pneumoniae, Acinetobacter baumannii infection, abdominal cavity infection, PO2 < 60 mmHg, neutrophils, white blood cell count, and systolic blood pressure were independently associated with the mortality of sepsis patients with acute respiratory failure. Besides, Acinetobacter baumannii infection was reported as the most significant prognostic biomarker. Therefore, the model will be specifically beneficial for improving the short-term prognosis of sepsis patients with acute respiratory failure once preventive measures targeted to the mortality-related risk factors are implemented.