JMIR Publications

ABSTRACT

Background:

Septic shock (SS) is a syndrome with high mortality. Early forewarning and diagnosis of SS, which is critical in reducing mortality, is still challenging in clinical management.

Objective:

We propose a simple, fast risk-stratified forewarning model for SS to help physicians recognition in time. Moreover, further insights can be gained from the application of the model to improve our understanding of SS.

Methods:

The 5125 sepsis patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database were divided into training, validation, and test sets. In addition, 2180 sepsis patients from the eICU Collaborative Research Database (eICU) were used as an external validation set. We developed a simplified risk-stratified early forewarning model for SS based on the weight of evidence and logistic regression, which was compared with multi-feature complex models, and clinical characteristics among risk groups were evaluated.

Results:

Using only vital signs and rapid arterial blood gas test features according to feature importance, an SS risk predictor (SORP) was constructed, with an AUC of 0.9458 in the test set, which is only slightly lower than the optimal multi-feature complex model (0.9651). A median forewarning time of 13 hours was calculated for SS patients. Four distinct risk groups (high, medium, low, and ultralow) were identified by SORP 6 hours before onset, and the incidence rates of SS in the four risk groups in the postonset interval were 88.6%, 34.5%, 2.5%, and 0.3%, respectively. The severity increased significantly with increasing risk in both clinical features and survival. Clustering analysis demonstrated the high similarity of pathophysiological characteristics between the high-risk patients without SS diagnosis (NS_HR) and the SS patients, while a significantly worse overall survival was shown in NS_HR. In further exploring the characteristics of the treatment and comorbidities of the NS_HR group, these patients demonstrated a significantly higher incidence of mean blood pressure (MBP) <65 mmHg, significantly lower vasopressor use and infused volume, and more severe renal dysfunction. The above findings were further validated by multicenter eICU data.

Conclusions:

SORP demonstrated accurate forewarning and a reliable risk stratification capability. Whether high-risk patients are diagnosed with SS, they have similar pathophysiologic phenotypes and high mortality. NS_HR patients, overlooked by the Sepsis-3 definition, may provide further insight into the pathophysiological processes of SS onset and help to complement its diagnosis and precise management. The importance of precise fluid resuscitation management in SS patients with renal dysfunction is further highlighted. The model is available online at: http://www.informatics.icu/SORP.