A nomogram for predicting rectovaginal fistula after low anterior resection for rectal cancer

A Nomogram Model to Predict Deep Vein Thrombosis Risk After Surgery in Patients with Hip Fractures

Aims

This study aimed to establish a nomogram model for predicting the probability of postoperative deep vein thrombosis (DVT) risk in patients with hip fractures.

Methods

504 patients were randomly assigned to the training set and validation set, and then divided into a DVT group and a non-DVT group. The study analysed the risk factors for DVT using univariate and multivariate analyses. Based on these parameters, a nomogram model was constructed and validated. The predicting performance of nomogram was evaluated by discrimination, calibration, and clinical usefulness.

Results

The predictors contained in the nomogram model included age, surgical approach, 1-day postoperative D-dimer value and admission ultrasound diagnosis of the lower limb vein. Furthermore, the area under the ROC curve (AUC) for the specific DVT risk-stratification nomogram model (0.815; 95% CI 0.746-0.884) was significantly higher than the current model (Caprini) (0.659; 95% CI 0.572-0.746, P < 0.05). According to the calibration plots, the prediction and actual observation were in good agreement. In the range of threshold probabilities of 0.2-0.8, the predictive performance of the model on DVT risk could be maximized.

Conclusions

The current predictive model could serve as a reliable tool to quantify the possibility of postoperative DVT in hip fractures patients.

Rectovaginal fistula after low anterior resection: Prevention and management

Rectovaginal fistula after low anterior resection for rectal malignancy is one of the most challenging postoperative complications because it is difficult to treat and may complicate plans of adjuvant therapy. This problematic complication could lead to multiple operations, stoma formation, sexual dysfunction, fecal incontinence and psychosocial ramifications. This review comprehensively covers an overview of its incidence, risk factors, presentation and evaluation, management (ranging from conservative measures, endoscopic treatment and local tissue repair to radical resection and redo anastomosis) and treatment outcomes of rectovaginal fistula after low anterior resection. Notably, these therapeutic options and outcomes are influenced by several factors, including the size and location of the fistula, tumor clearance, cancer staging, quality of colorectal anastomosis and surrounding tissue, presence of diverting stoma, previous attempted repair, and the surgeon’s experience. Also, strategies to prevent rectovaginal fistula after low anterior resection are presented with illustrations. Finally, a decision-making algorithm for managing this complication is proposed.

A nomogram model to predict the venous thromboembolism risk after surgery in patients with gynecological tumors

OBJECTIVE

Venous thromboembolism (VTE) is a common post-surgical complication of gynecological malignant tumors that has serious implications on the prognosis and quality-of-life of patients. However, there exists only a few recognized specific evaluation models for the occurrence of VTE after gynecological malignant tumor surgery. We aimed to establish a nomogram model that could predict the probability of post-surgical VTE in patients with gynecological malignancies.

METHODS

We collected the clinical information of 673 patients who underwent surgery for gynecological malignant tumor in our hospital between January 2014 and May 2020. To reduce bias from confounding factors between groups, a 1:1 ratio propensity score matching (PSM) method was performed; meanwhile, univariate and multivariate analyses were applied to analyze the risk factors of VTE after surgeries. A nomogram prediction model was accordingly established and internally validated.

RESULTS

The predictors contained in the nomogram model included age, D-dimer value, body mass index (BMI), and surgical approach. The C-index of the model was 0.721 (95% confidence interval: 0.644-0.797), with good discrimination and calibration effect. The internally verified C-index value was 0.916. Decision curve analysis confirmed that the nomogram model was clinically useful when the incidence of thrombosis in patients was 10-75%.

CONCLUSIONS

Considering the risk factors of VTE after surgery for gynecological malignant tumor, a high-performance nomogram model was established and then validated to provide individual risk assessment and guide treatment decisions.