{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T16:33:10Z","timestamp":1770222790518,"version":"3.49.0"},"reference-count":24,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2019,7,14]],"date-time":"2019-07-14T00:00:00Z","timestamp":1563062400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical Endocrinology"],"published-print":{"date-parts":[[2019,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>Although surgical resection is the primary treatment method for pheochromocytoma, it carries a high risk of morbidity, especially cardiovascular\u2010related morbidity. There are no models for predicting cardiovascular morbidity after pheochromocytoma surgery. Thus, we developed and validated a model for the preoperative prediction of cardiovascular morbidity after pheochromocytoma surgery.<\/jats:p><\/jats:sec><jats:sec><jats:title>Design<\/jats:title><jats:p>The development cohort consisted of 262 patients who underwent unilateral laparoscopic or open pheochromocytoma surgery at our centre between 1 January 2007 and 31 December 2016. Patient's clinicopathologic data were recorded. The LASSO regression was used for data dimension reduction and feature selection; then, multivariable logistic regression analysis was used to develop the prediction model. An independent cohort consisting of 112 consecutive patients from 1 January 2017 and 31 December 2018 was used for validation. The performance of this prediction model was assessed with respect to discrimination, calibration and clinical usefulness.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The predictors in this prediction model included body mass index, history of coronary heart disease, tumour size, intraoperative hemodynamic instability and use of crystal\/colloid fluids preoperatively. In the validation cohort, the model showed good discrimination with an AUROC of 0.869 (95% CI, 0.797, 0.940) and good calibration (unreliability test, <jats:italic>P<\/jats:italic>\u00a0=\u00a0.852). Decision curve analysis demonstrated that the model was also clinically useful.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This study presented a good nomogram that could facilitate the preoperative individualized prediction of cardiovascular morbidity after pheochromocytoma surgery, which may help improve perioperative strategy and good treatment outcomes.<\/jats:p><\/jats:sec>","DOI":"10.1111\/cen.14057","type":"journal-article","created":{"date-parts":[[2019,7,6]],"date-time":"2019-07-06T14:33:22Z","timestamp":1562423602000},"page":"490-497","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Development and validation of a predictive model for predicting cardiovascular morbidity in patients after pheochromocytoma surgery"],"prefix":"10.1111","volume":"91","author":[{"given":"Song","family":"Bai","sequence":"first","affiliation":[{"name":"Department of Urology Shengjing Hospital of 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