Related Experiment Video
Updated: Jan 20, 2026

Author Spotlight: Oral Candida Diagnosis to Advance Clinical Treatment Regimen for pSS Patients
Published on: March 1, 2024
Predictive factors for COPD exacerbations and mortality in patients with overlap syndrome
Philippe Jaoude1,2, Ali A El-Solh1,2,3
1The Veterans Affairs Western New York Healthcare System, Buffalo, New York.
Introduction:
Patients with chronic obstructive pulmonary disease (COPD) and obstructive sleep apnoea (OSA)-overlap syndrome-have a substantially greater risk of morbidity and mortality, compared to those with either COPD or OSA alone.
Objectives:
The aim of this retrospective study was to identify clinical modifiable factors associated with COPD exacerbations and all-cause mortality in patients with overlap syndrome.
Methods:
The electronic records of patients with simultaneous COPD and OSA who had a documented acute exacerbation of COPD during a 42-month period were evaluated for reviewed. A control group of overlap syndrome patients without exacerbations was matched 1:1 for age and body mass index. Vital status and cause of death were assessed through the population death registry.
Results:
Out of 225 eligible cases, 92 patients had at least one episode of COPD exacerbation. There was no significant association between severity of airflow limitation and apnoea hypopnea index (P = .31). After adjusting for confounding variables, patients who had at least one COPD exacerbation were more likely to be active smokers (P = .01), have poorer lung function (P = .001) and less likely to adhere to continuous positive airway pressure (CPAP) use (P = .03). All-cause mortality was also correlated with low forced expiratory volume in 1 second (P = .006), CPAP use (P = .007), and burden of comorbidities (P < .001).
Conclusion:
Lung function and CPAP use were independent predictors of COPD exacerbations and all-cause mortality in a cohort of patients with overlap syndrome. These factors should be taken into account when considering the management and prognosis of these patients.
More Related Videos
05:16Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
Published on: June 10, 2025
08:52Modeling Osteosarcoma Using Li-Fraumeni Syndrome Patient-derived Induced Pluripotent Stem Cells
Published on: June 13, 2018
Related Concept Videos
Factors Affecting Protein-Drug Binding: Patient-Related Factors
Age stands as a key determinant in protein-drug binding. Neonates, characterized by low albumin content, experience heightened concentrations of unbound drugs such as phenytoin and...
COPD: Pathogenesis and Clinical Features
The primary cause for the onset of COPD is cigarette smoking and exposure to air pollution. These hazardous factors initiate a chain reaction within the lungs, resulting in chronic inflammation, damage to the airways, and a...
COPD: Management Using Bronchodilators and Corticosteroids
¹H NMR: Interpreting Distorted and Overlapping Signals
As Δν decreases and the signals move closer, the doublets appear increasingly distorted. The intensities of the inner lines increase at the cost of those of the outer lines as the signals are...
Predicting Molecular Geometry
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.