Development of a Nomogram to Predict 28-Day Mortality of Patients With Sepsis-Induced Coagulopathy: An Analysis of the MIMIC-III Database

Abstract

Background: Sepsis-induced coagulopathy (SIC) is a common cause for inducing poor prognosis of critically ill patients in intensive care unit (ICU). However, currently there are no tools specifically designed for assessing short-term mortality in SIC patients. This study aimed to develop a practical nomogram to predict the risk of 28-day mortality in SIC patients.Methods: In this retrospective cohort study, we extracted patients from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Sepsis was defined based on Sepsis 3.0 criteria and SIC based on Toshiaki Iba's criteria. Kaplan–Meier curves were plotted to compare the short survival time between SIC and non-SIC patients. Afterward, only SIC cohort was randomly divided into training or validation set. We employed univariate logistic regression and stepwise multivariate analysis to select predictive features. The proposed nomogram was developed based on multivariate logistic regression model, and the discrimination and calibration were verified by internal validation. We then compared model discrimination with other traditional severity scores and machine learning models.Results: 9432 sepsis patients in MIMIC III were enrolled, in which 3280 (34.8%) patients were diagnosed as SIC during the first ICU admission. SIC was independently associated with the 7- and 28-day mortality of ICU patients. K–M curve indicated a significant difference in 7-day (Log-Rank: P < 0.001 and P = 0.017) and 28-day survival (Log-Rank: P < 0.001 and P < 0.001) between SIC and non-SIC groups whether the propensity score match (PSM) was balanced or not. For nomogram development, a total of thirteen variables of 3,280 SIC patients were enrolled. When predicted the risk of 28-day mortality, the nomogram performed a good discrimination in training and validation sets (AUROC: 0.78 and 0.81). The AUROC values were 0.80, 0.81, 0.71, 0.70, 0.74, and 0.60 for random forest, support vector machine, sequential organ failure assessment (SOFA) score, logistic organ dysfunction score (LODS), simplified acute physiology II score (SAPS II) and SIC score, respectively, in validation set. And the nomogram calibration slope was 0.91, the Brier value was 0.15. As presented by the decision curve analyses, the nomogram always obtained more net benefit when compared with other severity scores.Conclusions: SIC is independently related to the short-term mortality of ICU patients. The nomogram achieved an optimal prediction of 28-day mortality in SIC patient, which can lead to a better prognostics assessment. However, the discriminative ability of the nomogram requires validation in external cohorts to further improve generalizability.

Development of a nomogram for predicting 90-day mortality in patients with sepsis- associated liver injury: a clinical study of the MIMIC-IV database

“…Blood lactate, an indicator of tissue perfusion, is often used to provide feedback on survival in patients with sepsis 39,40 , and some high-quality studies on the effect of lactate on mortality in SALI patients have been identi ed only in children 41,42 ; this is the rst report in adult SALI patients. Some of the other variables, such as TBIL, albumin, RDW and APTT, which are frequently used in research to predict sepsis and sepsis-associated injury 14,17,18,43,44 , are rarely mentioned in studies of sepsis-associated liver injury, especially in adult reports 15 . Our ndings suggest that all of these variables independently predict mortality from sepsis-associated liver injury.…”

“…Professor Fragaki stated that the ALBI score is more appropriate for the identi cation and prognostic evaluation of early-onset liver dysfunction in a recent study 50 ; therefore, we chose the ALBI score to assess liver function in this article. The SOFA score, LODS score and SAPS II score are widely used in mortality risk analysis and prognosis assessment of patients with sepsis 17,44,51,52 . It is rare to use a model to predict both sepsis and liver injury at the same time, except in the few reports where the level of evidence is not high 15 .…”

Effects of β-blockers therapy on the 28-day and 3-year survival rates of end-stage renal disease patients with cardiovascular disease: a retrospective cohort study

“…All the data in this retrospective cohort study were obtained from the MIMIC III database ( 16 ). The MIMIC III database contains the information of 46,520 patients admitted to various ICUs of the Beth Israel Deaconess Medical Center (BIDMC) in Boston from 2001 to 2012, and includes data on patients’ demographics, vital signs, laboratory tests, fluid balance, and survival status.…”

Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients

“…Over the years, researchers have focused on different granularity of time range for in-hospital mortality prediction such as 6-hour mortality in ICU patients [22], 8 to 24-hour, 1-day and 2-day mortality in NICU patients [23], 24-hour mortality in acute myocardial infarction patients [24], 7-day mortality in acute heart failure patients [25], 28-day mortality in sepsisinduced coagulopathy patients [26], 90-Day survival in acutely ill patients [27], and so on.…”