Abstract Rationale To develop simplified nomograms for predicting likelihood of severe pulmonary hypertension (PH) in patients with chronic obstructive pulmonary disease (COPD) and survival in COPD-PH. Methods A total of 179 COPD patients (128 without severe PH, and 51 with severe PH) were analyzed. Variables including demographic data and clinical examination were collected. Multivariable logistic regression analysis was used to screen statistically significant PH variables for establishing a nomogram model. Multivariate Cox hazards analysis identified the predictors of death or lung transplantation, which to construct a nomogram. Results Peripheral capillary oxygen saturation at peak (Peak SpO2), peak oxygen consumption per kilogram (peak VO2/kg), peak heart rate (peak HR) and pulmonary arterial systolic pressure (PASP) were related factors of severe PH based on multivariate logistic regression and were used to develop a nomogram. The C-index of the training and validation cohort was 0.906 (95% CI:0.85-0.96) and 0.93 (95%CI: 0.85-1.00). Predictors included in the survival nomogram model were age, diffusing capacity for carbon monoxide of predicted (DLCO % predicted) and minute ventilation/carbon dioxide output slope (VE/VCO2 slope). The model was constructed for the prediction of 1, 2 and 3-year survival. The C-index of the nomogram of the training and validation cohort was 0.80(95% CI:0.71-0.89) and 0.69(95% CI:0.52-0.86). Decision curve analysis (DCA) showed the nomogram model provided good net benefits. Conclusions The nomogram models based on clinical variables of noninvasive testing offers an individualized tool to predict severe PH in patients with COPD and survival in COPD-PH patients. This abstract is funded by: This study was supported by the Natural Science Foundation of Shanghai 2024 Science and Technology Innovation Action Plan24ZR1460100 and the Department Support Fund of Shanghai Pulmonary Hospital.
Guo et al. (Fri,) studied this question.