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

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 (D_LNO) and carbon monoxide (D_LCO) may be used to classify patients with HF, as D_LNO and D_LCO are lung function measurements that reflect pulmonary gas exchange. Our objectives were to determine 1) if D_LNO added to D_LCO testing predicts HF better than D_LCO alone and 2) whether the binary classification of HF is better when D_LNO z-scores are combined with D_LCO z-scores than using D_LCO z-scores alone.

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 D_LNO, D_LCO and D_LNO+D_LCO 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).

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.

Combined z-scores explained 32% of the variation in the likelihood of an individual having HF, which was higher than models using D_LNO or D_LCO 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.