Key result
A novel nomogram incorporating age, admission heart rate, extent of resection, laterality, and percent maximum ventilation volume predicted new-onset postoperative atrial fibrillation following pulmonary resection with an AUC of 0.811.
Why the study?
New-onset postoperative atrial fibrillation (NOPAF) following pulmonary resection is a common clinical concern, prompting the need for an intuitive risk-prediction nomogram to guide protective treatments.
Can a nomogram based on clinical and surgical variables accurately predict new-onset postoperative atrial fibrillation in patients undergoing pulmonary resection?
Cohort (n=3,583)
No
Can a nomogram based on clinical and surgical variables accurately predict new-onset postoperative atrial fibrillation in patients undergoing pulmonary resection?
Effect estimate: AUC 0.811 (95% CI 0.758-0.864)
A novel 5-variable nomogram demonstrated good discrimination (AUC 0.811) for predicting new-onset postoperative atrial fibrillation after pulmonary resection, which may help guide targeted prophylactic strategies.
Nomogram may aid NOPAF risk stratification after pulmonary resection; leaves open need for external validation before clinical use.
Background: The new-onset postoperative atrial fibrillation (NOPAF) following pulmonary resection is a common clinical concern. The aim of this study was to construct a nomogram to intuitively predict the risk of NOPAF and offer protective treatments. Methods: Patients who underwent pulmonary resection between January 2018 and December 2020 were consecutively enrolled. Forward stepwise multivariable logistic regression analyses were used to screen independent predictors, and a derived nomogram model was built. The model performance was evaluated in terms of calibration, discrimination and clinical utility and validated with bootstrap resampling. Results: A total of 3583 patients who met the research criteria were recruited for this study. The incidence of NOPAF was 1.507% (54/3583). A nomogram, composed of five independent predictors, namely age, admission heart rate, extent of resection, laterality, percent maximum ventilation volume per minute (%MVV), was constructed. The concordance index (C-index) was 0.811. The nomogram showed substantial discriminative ability, with an area under the receiver operating characteristic curve of 0.811 (95% CI 0.758-0.864). Moreover, the model shows prominent calibration performance and higher net clinical benefits. Conclusion: We developed a novel nomogram that can predict the risk of NOPAF following pulmonary resection, which may assist clinicians predict the individual probability of NOPAF and perform available prophylaxis. By using bootstrap resampling for validation, the optimal discrimination and calibration were demonstrated, indicating that the nomogram may have clinical practicality.
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Zhang et al. (2023) conducted a cohort in Pulmonary malignancies or benign lesions requiring pulmonary resection (n=3,583). Risk factors for NOPAF (age, admission heart rate, extent of resection, laterality, %MVV) vs. Patients without NOPAF was evaluated on Discriminative ability of the nomogram for predicting new-onset postoperative atrial fibrillation (AUC) (AUC 0.811, 95% CI 0.758-0.864). A novel nomogram incorporating age, admission heart rate, extent of resection, laterality, and percent maximum ventilation volume predicted new-onset postoperative atrial fibrillation following pulmonary resection with an AUC of 0.811.
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