Developing a COPD Mortality Prediction Rule for Primary Care


The study, conducted in Spain, sought to determine the factors that created a higher risk of death from acute exacerbations of chronic obstructive pulmonary disease (COPD) in primary care.

Information gathered from patients with acute exacerbations of chronic obstructive pulmonary disease (COPD) in several provinces of Spain led researchers to create a prediction rule to assess and categorize patients by risk of short-term mortality. The study was published in the European Journal of General Practice.

The aim of the study was to create a COPD assessment for primary care that can be done without the need of complex instruments. The authors noted the lack of any existing predictive model for use in primary care before their work, which limited the ability for general practitioners to treat acute exacerbations of COPD (AECOPD) in primary care.

Most cases of COPD are handled within primary care, and the authors said early detection and treatment of AECOPD is critical to mitigate negative long-term outcomes.

To generate their model, researchers created a cohort study that drew data from 148 health centers in the Spanish provinces of Zamora, Soria, Valladolid, Burgos, and Salamanca between December 2013 and November 2014. Patients examined were already diagnosed with AECOPD and aged 40 or over.

Researchers included 1054 patients from with 1696 qualifying exacerbations; 84% of patients were male, with a mean age of 76 years. During the follow-up period, 17 patients died within 30 days of their last primary care visit, most from AECOPD.

Based on exacerbations in the last 12 months, researchers developed a clinical prediction rule was including age and heart rate, displaying an area under the receiver operating characteristic curve of 0.792 (95% CI, 0.692–0.891) to stratify patients into 3 risk categories, low, medium, and high.

Each risk category is accompanied by recommended actions. Low-risk patients could utilize more casual primary care. Medium risk patients should be observed closely by doctors, who must factor in additional variables if it is decided to treat patients in primary care. High-risk patients need heightened monitoring and could be referred to treatment in a hospital.

While some predictive models had been published prior to the authors’ effort, the authors argued these could not ascertain primary care variables in patients experiencing AECOPD at the same level of comprehensiveness as their own model.

The study noted some limitations. The sample size was smaller than required, and so ran the risk of the mode being overfitted, skewing good predictive performance to those surveyed and potentially bad performance to new subjects. The authors also acknowledged a “large proportion of missing data.”

Furthermore, concerns about minor sensitivity and high specificity in COPD diagnoses from electronic health records led the authors to suggest these diagnoses may potentially be used to study risk factors, but not in prevalence studies.

In addition, women represented only 16% of those studied, and 2 deaths of female patients were observed during the study, possibly reducing the application of the rule’s predictive performance in women. The small percentage was explained as being due to women with COPD in Spain representing between 22% to 29% of total instances of COPD.

Despite any limitations, the authors claimed that their model is the first to be able to predict the short-term risk of death in primary care settings due to AECOPD. “Although it is a rare event, it can be accurately predicted from knowing the exacerbations suffered in the last 12 months, age, and heart rate,” they noted.

However, their findings still need external validation and further research, they said.


Alameda, C., Matía, Á. C., & Casado, V. (2021). Predictors for mortality due to acute exacerbation of COPD in primary care: Derivation of a clinical prediction rule in a multicentre cohort study. Eur J Gen Pract. Published online August 6, 2021. doi:10.1080/13814788.2021.1959547

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