ArticleJournal of healthcare engineering2021
Sentiment Analysis for Necessary Preview of 30-Day Mortality in Sepsis Patients and the Control Strategies.
Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Clinical sentiment analysis of ICU notes: a dataset and a comparison of lexicon and clinical language model methods.BMC medical informatics and decision making · 2026Article
- Relationship between the sentiment of nursing notes and one-year mortality of elderly sepsis patients.PloS one · 2025Article
- Article
- A prediction model with measured sentiment scores for the risk of in-hospital mortality in acute pancreatitis: a retrospective cohort study.Annals of translational medicine · 2022Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study was to preview the risk of 30-day mortality in sepsis patients using sentiment analysis. The clinical data of patients and nursing notes were collected from the Medical Information Mart for Intensive Care (MIMIC-III) database. The factors influencing 30-day mortality were analyzed using the Cox regression model. And, the prognostic index (PI) was estimated. The receiver operating characteristic (ROC) curve was used to determine the PI cut-off point and assess the prediction ability of the model. In total, 1844 of 3560 patients were eligible for the study, with a 30-day mortality of 37.58%. Multivariate Cox analysis showed that sentiment polarity scores, sentiment subjectivity scores, simplified acute physiology score (SAPS)-II, age, and intensive care unit (ICU) types were all associated with the risk of 30-day mortality (
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Registered trials
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