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Background <p>Low cardiac output syndrome (LCOS) after pericardiectomy is the leading cause of postoperative death in patients with constrictive pericarditis. This study aimed to construct a predictive model, enabling accurate assessment of the risk of postoperative LCOS.</p> Methods <p>We retrospectively collected the data of patients with constrictive pericarditis who underwent pericardiectomy in four hospitals. These patients were divided into the training cohort, the validation cohort and the testing cohort for model construction, internal and external validation, respectively. A nomogram was developed by multivariate logistic regression. Model discrimination was assessed via ROC curve.</p> Results <p>From November 2012 to April 2024, 166 patients in one hospital were included and randomly divided into the training (117 cases) and validation (49 cases) cohorts with the ratio of 7:3. Independent risk factors of postoperative LCOS included age, the classification of cardiac function (CF), central venous pressure (CVP) and D-dimer (DD), while left ventricular ejection fraction (LVEF) was the protective factor. A new model named after these factors (ACCED) was constructed based on the training cohort. The AUC of ACCED model predicting postoperative LCOS was 0.923 in the training cohort, with AUC of 0.881 in the validation cohort. The testing cohort enrolled 94 patients in one hospital from May 2024 to April 2025 and three other hospitals from May 2015 to April 2025, with the AUC of 0.956 in predicting postoperative LCOS.</p> Conclusion <p>The ACCED model could provide preliminary prediction of postoperative LCOS risk in the patients with constrictive pericarditis receiving pericardiectomy.</p>

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A simple nomogram for predicting postoperative low cardiac output syndrome in constrictive pericarditis

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  • 发表日期：

    2026年6月21日

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  • Likui Fang,
  • Jinming Xu,
  • Bo Ye,
  • Hong Jiang,
  • Jian Hu,
  • Fangming Zhong

摘要

Background

Low cardiac output syndrome (LCOS) after pericardiectomy is the leading cause of postoperative death in patients with constrictive pericarditis. This study aimed to construct a predictive model, enabling accurate assessment of the risk of postoperative LCOS.

Methods

We retrospectively collected the data of patients with constrictive pericarditis who underwent pericardiectomy in four hospitals. These patients were divided into the training cohort, the validation cohort and the testing cohort for model construction, internal and external validation, respectively. A nomogram was developed by multivariate logistic regression. Model discrimination was assessed via ROC curve.

Results

From November 2012 to April 2024, 166 patients in one hospital were included and randomly divided into the training (117 cases) and validation (49 cases) cohorts with the ratio of 7:3. Independent risk factors of postoperative LCOS included age, the classification of cardiac function (CF), central venous pressure (CVP) and D-dimer (DD), while left ventricular ejection fraction (LVEF) was the protective factor. A new model named after these factors (ACCED) was constructed based on the training cohort. The AUC of ACCED model predicting postoperative LCOS was 0.923 in the training cohort, with AUC of 0.881 in the validation cohort. The testing cohort enrolled 94 patients in one hospital from May 2024 to April 2025 and three other hospitals from May 2015 to April 2025, with the AUC of 0.956 in predicting postoperative LCOS.

Conclusion

The ACCED model could provide preliminary prediction of postoperative LCOS risk in the patients with constrictive pericarditis receiving pericardiectomy.