Desarrollo y validación de un nomograma para predecir el edema pulmonar neurogénico en la hemorragia intracerebral...

The pathophysiological mechanism of neurogenic pulmonary edema (NPE) is still unclear, and the condition is severe with a high mortality rate. Identifying the risk factors for NPE is of great significance. Therefore, this study aims to explore the risk factors of hypertensive intracerebral hemorrhage (HICH) complicated with NPE and construct a risk prediction model based on this.

We retrospectively collected baseline admission data from 274 patients with hypertensive intracerebral hemorrhage (HICH) admitted to Suzhou Hospital of Integrated Traditional Chinese and Western Medicine from March 2023 to March 2025. All candidate predictors were obtained from the first clinical assessment within 6 h after admission (first available values), including vital signs, GCS score, arterial blood gas parameters (PaO2/FiO2 and lactate), BNP, and hematoma volume measured on the initial CT scan. Patients were classified into NPE and non-NPE groups according to the occurrence of new-onset NPE during hospitalization. Apply the Least Absolute Shrinkage and Selection Operator (LASSO) method and multivariate logistic regression to determine independent risk factors. These risk factors are used to construct a nomogram for predicting the risk of NPE occurrence. Additionally, 152 patients with HICH from January 2022 to March 2023 were collected as an internal temporal validation cohort. Compared through consistency index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and DCA.

The cerebral hemorrhage volume, heart rate, GCS score, arterial partial pressure of oxygen/fraction of inspired oxygen (PaO2/FiO2), Lactic (LAC) and B-type natriuretic peptide (BNP) are independent influencing factors of HICH complicated with NPE (P < 0.05). Establish and validate a risk prediction model for HICH concurrent NPE based on the above six risk factors. The C-index of the training cohort and validation cohort are 0.980 (95% CI: 0.966-0.994) and 0.976 (95% CI: 0.952-1.000), respectively. The calibration curve of the nomogram shows good consistency with the ideal curve. The ROC curves showed that the AUC of NPE risk in the training cohort and validation cohort patients were 0.985 (95% CI: 0.973-0.997) and 0.975 (0.955-0.996), respectively; The DCA shows that HICH patients have a higher net benefit in predicting the risk of NPE based on this model.

The nomogram has good predictive performance and applicability for predicting NPE in HICH. This can be used to screen for the risk of NPE occurrence in this population.