Two is better than one: the double diffusion technique in classifying heart failure.

BACKGROUND

Heart failure (HF) is a chronic condition in which the heart does not pump enough blood to meet the body's demands. Diffusing capacity of the lung for nitric oxide () and carbon monoxide () may be used to classify patients with HF, as and are lung function measurements that reflect pulmonary gas exchange. Our objectives were to determine 1) if added to testing predicts HF better than alone and 2) whether the binary classification of HF is better when z-scores are combined with z-scores than using z-scores alone.

METHODS

This was a retrospective secondary data analysis in 140 New York Heart Association Class II HF patients (ejection fraction <40%) and 50 patients without HF. z-scores for , and + were created from reference equations from three articles. The model with the lowest Bayesian Information Criterion was the best predictive model. Binary HF classification was evaluated with the Matthews Correlation Coefficient (MCC).

RESULTS

The top two of 12 models were combined z-score models. The highest MCC (0.51) was from combined z-score models. At most, only 32% of the variance in the odds of having HF was explained by combined z-scores.

CONCLUSIONS

Combined z-scores explained 32% of the variation in the likelihood of an individual having HF, which was higher than models using or z-scores alone. Combined z-score models had a moderate ability to classify patients with HF. We recommend using the NO-CO double diffusion technique to assess gas exchange impairment in those suspected of HF.