ArticleFrontiers in medicine2025
Carbon dioxide combining power as a predictor of unplanned ICU transfer in hospital wards: a retrospective cohort study.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Predictive performance of an extended NEWS model for acute deterioration in general ward inpatients: a retrospective observational study.Journal of Korean biological nursing science · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Unplanned intensive care unit (ICU) transfers are associated with high mortality. Conventional early warning scores like modified Early Warning Score (MEWS) show limited predictive ability. Carbon dioxide combining power (CO2CP), a routine acid-base parameter, may enable earlier detection of clinical deterioration. Objective: To evaluate CO2CP as a predictor of mortality in unplanned ICU transfers and assess its additive value to traditional scoring systems. Methods: This single-center retrospective study analyzed 101 adults with unplanned ICU transfers (Feb 2024-Jun 2025). CO2CP levels within 8 h pre-transfer, MEWS, and APACHE II scores were collected. Primary outcome was ICU mortality. Analyses included ROC curves, survival analysis, multivariable logistic regression, decision curve analysis, and correlation assessment. Results: The area under the ROC curve (AUC) for CO2CP was 0.722 (95% CI: 0.615-0.829), higher than that of MEWS (AUC = 0.528, Conclusion: Carbon dioxide combining power may serve as an independent predictor of mortality risk in unplanned ICU transfers. Its integration with MEWS may enhance early risk stratification in general wards, though these findings require validation in larger prospective studies.
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