Discussion
anaemia, death, inflammation, RDW, infection, CHD, atherosclerosis, tissue damage
ANAEMIA, INFLAMMATION, LYSIS, INFECTION, CORONARY ATHEROSCLEROSIS, INFLAMMATION OR INFECTION, ATHEROSCLEROSIS
This was the first study to assess the relationship between the composite inflammation indicators and mortality in ICU patients with CHD. Most inflammation indicators in our study were significantly associated with ICU mortality in the retrospective MIMIC IV database of ICU patients with CHD. Demonstrating the significant promise of these inflammation indicators for mortality risk management in ICU patients with CHD.The basic mechanism of CHD is abnormal lipid metabolism leading to coronary atherosclerosis (Neutrophils, the most abundant subtype of leukocytes in the blood, are critical in mediating inflammation. Neutrophils cause smooth muscle cell lysis and death, which has been shown to cause tissue damage and inflammation in advanced stages of atherosclerosis (In our study, RDW was the prognostic independent factor with the most pronounced correlation among the inflammatory indicators studied above. It has been shown that RDW affects the poor prognosis of CHD patients, but the underlying causes remain unclear. Although anaemia is a known risk factor for mortality, we adjusted for haemoglobin in Model 3 and, therefore, still consider RDW to be a risk factor for mortality separate from anaemia. We hypothesized two main causes for the higher risk mortality of CHD patients with high RDW: (a) RDW is associated with a variety of inflammatory markers, e.g., interleukin-6 (Our novel predictive model provides an accurate risk assessment and helps ICU physicians identify which ICU patients with CHD are at high mortality risk. And allows ICU healthcare teams to improve the prognosis of high mortality risk patients through more frequent monitoring, more urgent interventions, and stricter medication management at the early stage. In addition, earlier identification of high mortality risk patients can facilitate more informed discussions about the patient’s condition and prognosis between ICU physicians and the patient’s families. Overall, our model has a potentially important role in mortality risk management of ICU patients with CHD, helping to improve the accuracy of clinical decision-making and the quality of healthcare. However, the validity and feasibility of the model have only been confirmed in the datasets. Despite the strong clinical utility of the nomogram, further validation and adjustment is needed in the actual ICU clinical setting.Some limitations of our study should be noted. First, this was a retrospective study in which retrospective bias is unavoidable, and thus more rigorous prospective studies would be required in the future. Second, previously mentioned traditional inflammatory indicators of IL-6 and CRP are important in mortality risk of CHD. We tried to extract them but due to the limitations of MIMIC IV, the percentage of missing values for CRP was about 98% and no record of IL-6 was retrieved. Further studies are still needed to prove whether they will have an impact on our results. Third, our study data were from the database of the United States and were overwhelmingly of White race, so applicability to ICU patients from other countries or other races requires further validation. Fourth, despite we adjusted for virous potential confounders, there may still be some important factors that were missed, and these may have a non-negligible impact on our inflammatory indicators. For example, neutrophil counts are usually elevated when there is an active infection or inflammation in the patient’s body, while lymphocyte counts may be decreased, thus affecting our inflammatory indicators. However, due to MIMIC’s limitations, it is hard to definitively determine the patient’s infection condition. Fifth, although our novel model demonstrated promising predictive performance in the internal and external validation cohort form MIMIC IV and EICU, however scalability to other hospitals remains an issue as the model’s performance in the external validation cohort is weaker than the internal validation cohort. Therefore, we also need a larger external validation cohort to validate the performance of our model. Despite these limitations, our study shows that the new model we constructed is remarkably promising and deserves further exploration in future clinical work and research.