Development and validation of a nomogram for predicting the risk of pressure injury in adult patients undergoing abdominal surgery - Xue Feng; Meng Wang; Ya Zhang; Qian Liu; Mingyang Guo; Hongyin Liang (Elsevier, 2022)
Objectives: This study aimed to develop a nomogram for predicting the risk of pressure injury (PI) in adult patients undergoing abdominal surgery and validate its effectiveness among these patients. Methods: This study retrospectively included 11,247 adult patients, who underwent abdominal surgery and postoperative supervision in ICU, in a tertiary care hospital in western China between January 2017 and December 2020. All datasets were extracted from the patient's medical records and randomly divided into the training cohort (8,997) and the validation cohort (2,250) by 8:2. The univariable logistic regression was used to select potentially relevant features. Then, multivariable logistic regression was also conducted and utilized to establish the nomogram. The nomogram was compared with the Braden scale for predicting PI in the validation cohort through the area under the curve (AUC) of the receiver operator characteristic (ROC) curve, Hosmer-Lemeshow (H-L) test, and decision curve analysis (DCA). Results: 873 (7.8%) patients suffered PIs. Logistic regression analysis showed that time of operation, weight, type of operation, albumin, and Braden scale score were independent risk factors for PI. A nomogram integrating five selected characteristics was constructed. The AUC of the ROC curve for the nomogram was 0.831, with a specificity of 85.2% and sensitivity of 63.7%. The AUC of the ROC curve for the Braden scale was 0.567, with a specificity of only 33.0%. The P-values of the H-L test were 0.45 (nomogram) and 0.22 (Braden scale), both indicating good calibration. The DCA also displayed that the nomogram had better predictive validity. Conclusion: Compared with the Braden scale, the nomogram showed a better predictive performance. This nomogram is informative and has the potential to better guide caregivers for risk stratification and prevention of PI, although it requires further validation.