Development and validation of a RASS-related nomogram to predict the in-hospital mortality of neurocritical patients: a retrospective analysis based on the MIMIC-IV clinical database

Abstract

Background

Richmond agitation-sedation scale (RASS) is a simple and widely used tool for evaluating sedation and agitation in adult ICU patients. Early deep sedation has been shown to be an important independent predictor of death, however, studies on the role of RASS in the prognostic assessment of neurocritical patients are lacking. The purpose of this study was to investigate the relationship between RASS and in-hospital mortality in neurocritical patients, and to develop and validate an effective predictive model based on this.

Methods

This was a retrospective study of neurocritical patients from a large clinical database. A total of 2651 patients were collected, including general demographic characteristics, past medical history, biochemical test data and physical examination within 24 h of admission, and related medical records. Univariate and multivariate logistic regression analyses were used to screen out significant variables. Finally, 11 significant predictors were included into the logistic regression to establish the nomogram.

Results

The area under the curve (AUC) of the nomogram was 0.9087(0.8950–0.9224) and the corrected c index was 0.9043, which gave the model better discriminatory ability compared with critical care related scales, such as SOFA and SAPSII scores. Besides, tools including calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were used to verify that the model had good discrimination, calibration, and clinical applicability.

Conclusions

RASS score was an independent prognostic predictor of in-hospital death in neurocritical patients, and patients who are deeply sedated have a worse prognosis. RASS-related nomogram could be applied to predict the prognosis of neurocritical patients and to take effective intervention measures in early stage.

Keywords:

• RASS
• nomogram
• in-hospital mortality
• neurocritical patients
• MIMIC-IV clinical database

Transparency

Declaration of funding

There are no financial or other relationships to disclose for this project.

Declaration of financial/other relationships

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contributions

All authors made significant contributions to this study, including the conception of the article, design, and execution of the project. Shenyan Gu and Yuqin Wang were responsible for drafting or critically revising the intellectual content of the paper, Xin Tong and Jiahui Gu were involved in the data statistics and analysis, and Kaifu Ke and Yuanyuan Zhang were involved in the critical review of the manuscript and approved the final version of the manuscript submitted for publication. All authors had access to and analyzed and interpreted the data and are responsible for the accuracy and completeness of the work.

Acknowledgements

No assistance in the preparation of this article is to be declared.

Data availability statement

All available data were obtained from MIMIC-IV database, which can be found below: https://doi.org/10.13026/a3wn-hq05. Further inquiries can be directed to the corresponding author.