Abstract:

Objective

To investigate risk factors of early survival of sepsis patients and develop a Cox risk prediction model.

Methods

Data of 226 septic patients who were admitted to the ICU of the Affiliated Hospital of Nanjing University of Chinese Medicine from January 2018 to December 2021 were retrospectively analyzed.According to their early survival (28 days) outcomes， patients were divided into a survival group (n=183) and a death group (n=43).Univariate and multivariate Cox regression was used to explore independent risk factors of early survival of sepsis patients.A random forest algorithm was used to screen predictive variables and a nomogram was constructed.A calibration curve， a Brier score and a continuous rank probability score (CRPS) curve were constructed to evaluate the distinction and calibration of the nomogram.A clinical decision curve was drawn to evaluate the clinical applicability of the nomogram.

Results

Multivariate Cox regression showed that age ［hazard ratio (HR) = 1.032，95% confidence interval (CI) (1.004， 1.062)， P = 0.025］ and sequential organ failure assessment (SOFA) score ［HR = 1.165， 95%CI (1.017， 1.335)， P = 0.027］ were independent risk factors of early survival of sepsis patients.Six predictive variables (age， SOFA score， brian natriuretic peptide， lactatic acid， activated partial thromboplastin time and D-Dimer) were screened by the random forest algorithm and a nomogram was constructed.The calibration curve showed that the nomogram had a good fitting degree.The Brier score and CRPS curve showed that the total Brier score was less than 0.20 and the total CRPS was less than 0.15.The clinical decision curve showed that the prediction model had good clinical applicability.

Conclusion

The Cox risk model for early survival of sepsis patients has good clinical predictive ability and applicability.

Key words: Sepsis, Risk factor, Early survival, Clinical prediction model, Nomogram