ArticleERJ open research2025
Accuracy of early warning scores for predicting clinical worsening in COPD patients.
Article in ERJ open research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Development and evaluation of a clinical prediction model for in-hospital mortality in patients with acute exacerbation of chronic obstructive pulmonary disease.Journal of thoracic disease · 2026Article
- Evaluating the real-world utility of four physiological scores for prehospital interventions in resource-limited EMS systems: a population-based study of 15,720 cases.BMC health services research · 2026Article
- A Modified Delphi Process to Develop Consensus Definitions of Time-Dependent Care by Paramedic Services Systems.Prehospital and disaster medicine · 2025Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: COPD, a condition whose acute exacerbations (AECOPD) are commonly faced by the emergency medical services (EMSs), could modify the performance of early warning scores (EWSs). Our objectives were to assess the 2-day mortality predictive performance of five EWSs in patients with baseline COPD managed by an EMS with unselected acute diseases and to compare the EWS performance between those with AECOPD and those without. Methods: This was a prospective observational study of adults (age >18 years) with a previous COPD diagnosis who were admitted to and transferred to the emergency department by the EMSs due to an unselected acute disease, whether AECOPD or other according to the emergency medical team. Demographics, vital signs for the five EWSs (National Early Warning Score 2 (NEWS2), quick Sequential (Sepsis-related) Organ Failure Assessment (qSOFA), quick COVID-19 Severity Index (qCSI), CURB-65 score for pneumonia severity and BAP-65 score for AECOPD) calculations and outcomes (hospital and intensive care unit (ICU) admission and 2-day mortality) were collected. Results: A total of 1703 patients with COPD were selected: 524 with AECOPD and 1179 without. NEWS2 presented the highest predictive capacity for the global, AECOPD and non-AECOPD cohorts: area under the curve 0.880 (95% CI 0.84-0.91), 0.775 (95% CI 0.68-0.86) and 0.913 (95% CI 0.86-0.96), respectively. Conclusions: NEWS2 was the best predictive model for COPD, presenting excellent performance for the global and non-AECOPD cohorts but a decreased performance for the AECOPD cohort. Therefore, NEWS2 may aid in EMS decision making through appropriate risk assessment, but its use in COPD patients with AECOPD should be handled with care due to decreased performance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.