# Development and validation of nomogram for predicting neurogenic pulmonary edema in hypertensive intracerebral hemorrhage

**Authors:** Yajuan Xu, Yinxian Shi

PMC · DOI: 10.3389/fcvm.2026.1726478 · 2026-02-03

## TL;DR

This study develops a predictive model to identify patients with hypertensive intracerebral hemorrhage at risk of neurogenic pulmonary edema using clinical factors.

## Contribution

A novel nomogram is developed and validated for predicting neurogenic pulmonary edema in hypertensive intracerebral hemorrhage patients.

## Key findings

- Cerebral hemorrhage volume, heart rate, GCS score, PaO2/FiO2, lactate, and BNP are independent risk factors for NPE in HICH.
- The nomogram achieved high predictive accuracy with C-indexes of 0.980 and 0.976 in training and validation cohorts.
- Calibration and ROC analyses confirmed the model's strong performance and clinical utility.

## Abstract

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.

## Full-text entities

- **Genes:** NPPB (natriuretic peptide B) [NCBI Gene 4879] {aka BNP, Iso-ANP}, CRP (C-reactive protein) [NCBI Gene 1401] {aka PTX1}, LCT (lactase) [NCBI Gene 3938] {aka LAC, LPH, LPH1}
- **Diseases:** ventilator (MESH:D053717), neurological disorders (MESH:D009461), ARDS (MESH:D012128), bradycardia (MESH:D001919), sympathetic nervous system disorders (MESH:D001342), respiratory deterioration (MESH:D012131), cerebral edema (MESH:D001929), multiple organ failure (MESH:D009102), alveolar hemorrhage (MESH:D006470), infiltrates (MESH:D017254), tachycardia (MESH:D013610), cerebral vascular malformations (MESH:D054079), functional failure (MESH:D058186), acute stroke (MESH:D020521), pneumonia (MESH:D011014), renal failure (MESH:D051437), dyspnea (MESH:D004417), diabetes (MESH:D003920), lung diseases (MESH:D008171), valvular abnormalities (MESH:D006349), cyanosis (MESH:D003490), malignant tumors (MESH:D009369), cardiac arrest (MESH:D006323), Cardiogenic pulmonary edema (MESH:D011654), central nervous system injury (MESH:D002493), edema (MESH:D004487), lung injury (MESH:D055370), cerebral vascular abnormalities (MESH:D002532), volume overload (MESH:D019190), hyperlipidemia (MESH:D006949), Hematoma (MESH:D006406), cardiogenic (MESH:D013575), critically ill (MESH:D016638), HICH (MESH:D020299), blood flow disorders (MESH:D054318), Coma (MESH:D003128), gastrointestinal bleeding (MESH:D006471), sepsis (MESH:D018805), cardiovascular failure (MESH:D006333), wheezing (MESH:D012135), aspiration (MESH:D011015), primary diseases of the heart, lungs, and kidneys (MESH:D007674), moyamoya disease (MESH:D009072), cardiac dysfunction (MESH:D006331), associated (MESH:D018886), brainstem damage (MESH:D020295), infection (MESH:D007239), coagulation dysfunction (MESH:D001778), pulmonary vascular (MESH:D057772), tachypnea (MESH:D059246), pulmonary congestion (MESH:D001261), hypertension (MESH:D006973), acute brain injury (MESH:D001930), hematological disorders (MESH:D006402), consciousness impairment (MESH:D003244), neurological damage (MESH:D020196), subarachnoid hemorrhage (MESH:D013345), cerebral hemorrhage (MESH:D002543), barotrauma (MESH:D001469)
- **Chemicals:** H2O (MESH:D014867), lactate (MESH:D019344), adrenaline (MESH:D004837), oxygen (MESH:D010100), carbon dioxide (MESH:D002245), catecholamine (MESH:D002395), furosemide (MESH:D005665), HCO3- (MESH:D001639), LAC (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

6 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12909559/full.md

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Source: https://tomesphere.com/paper/PMC12909559