Development and validation of a predictive nomogram for preoperative deep vein thrombosis (DVT) in isolated calcaneal fracture

Abstract

The fact that most of the patients with preoperative DVTs after calcaneal fractures are asymptomatic brought challenges to the early intervention, and periodic imaging examinations aggravated the financial burden of the patients in preoperative detumescence period. This study aimed to use routine clinical data, obtained from the database of Surgical Site Infection in Orthopaedic Surgery (SSIOS), to construct and validate a nomogram for predicting preoperative DVT risk in patients with isolated calcaneal fracture. The nomogram was established base on 7 predictors independently related to preoperative DVT. The performance of the model was tested by concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA), and the results were furtherly verified internally and externally. 952 patients were enrolled in this study, of which 711 were used as the training set. The AUC of the nomogram was 0.870 in the training set and 0.905 in the validation set. After internal verification, the modified C-index was 0.846. Calibration curve and decision curve analysis both performed well in the training set and validation set. In short, we constructed a nomogram for predicting preoperative DVT risk in patients with isolated calcaneal fracture and verified its accuracy and clinical practicability.

Development and validation of a predictive nomogram for subsequent contralateral hip fracture in elderly patients within 2 years after hip fracture surgery

“…The exclusion criteria were: hip fractures due to diseases such as joint tuberculosis and tumors; multiple fractures or multiple traumas; patients with previous hip arthroplasty or internal fixation of the hip; ipsilateral hip refracture (periprosthetic fracture) within 2 years; patients with blood system disorders or other disorders affecting blood tests; incomplete follow-up information owing to patient death (The death may be due to factors such as advanced age and severe complications, which may affect the expected outcome), etc. According to the requirements for developing a clinical prediction model, the sample size should be at least 10 times the number of variables ( 19 , 20 ). In our study there were 38 variables, thus the sample size should be at least 380, and therefore our sample size is adequate.…”

Construction and validation of a predictive model for lower extremity deep vein thrombosis after total knee arthroplasty

“…The lack of specific symptoms in the early stage of DVT after total knee arthroplasty [ 8 ] makes it difficult to accurately predict the risk of DVT by traditional laboratory indicators, [ 9 ] and there is less evidence of relevant predictive models. Nomogram have been used in many fields, not only for the prediction of post-fracture lower extremity DVT, [ 10 ] but also for the prediction of post-fracture pneumonia [ 11 ] and post-fracture delirium, [ 12 ] etc, and all of them have achieved good prediction results. The aim of the present study was to investigate the independent risk factors for lower extremity DVT after total knee arthroplasty and to establish a nomogram prediction model accordingly.…”

Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures

“…[ 11 ] The occurrence of postoperative incision infection may affect the treatment outcome and increase the cost of treatment for patients. Nomograms have been used in many fields to predict not only postoperative lower limb deep vein thrombosis, [ 12 ] but also postoperative pneumonia and postoperative delirium after fracture, [ 13 , 14 ] and it has achieved good prediction results. This study aimed to investigate the independent risk factors for postoperative incisional infection after ankle fracture and to develop a nomogram prediction model accordingly.…”