Analysis of the risk factors for secondary hemorrhage after abdominal surgery

Introduction

This study aimed to conduct a clinical review and analysis to recommend options for the prevention and treatment of postoperative hemorrhage.

Patients and Methods

A total of 138 patients who experienced postoperative hemorrhage after abdominal surgery in the period between January 2015 and December 2020 at the Sir Run Run Shaw Hospital, affiliated to Zhejiang University School of Medicine, participated in this study. They were divided into a group with primary bleeding only and a secondary bleeding group. Univariate and multivariate statistical analyses were performed, followed by plotting of cumulative hazard and survival curves for the two groups.

Results

The main factors of interest found to be associated with secondary hemorrhage were duration of the operation, the time of the first bleeding incident, intervention time, performance of combined organ resection, use of surgical intervention, occurrence of abdominal infection, admission to the intensive care unit (ICU), postoperative length of stay, and total hospitalization expenses. Among these, a long operative duration (>5 h) and an extended intervention time (>5 h) were identified as independent predictors of risk of secondary hemorrhage.

Conclusions

Secondary hemorrhage after abdominal surgery is mainly associated with subjective human factors, and it is an important cause of poor prognosis and even death. Proper reductions in operation time and implementation of a quick response to bleeding are the key factors in tackling bleeding. Further reduction in the rates of postoperative hemorrhage and mortality will require a concerted effort by surgeons in terms of both intraoperative surgical techniques and postoperative management.

Development and validation of a machine learning-based predictive model for secondary post-tonsillectomy hemorrhage

Background

The main obstacle to a patient's recovery following a tonsillectomy is complications, and bleeding is the most frequent culprit. Predicting post-tonsillectomy hemorrhage (PTH) allows for accurate identification of high-risk populations and the implementation of protective measures. Our study aimed to investigate how well machine learning models predict the risk of PTH.

Methods

Data were obtained from 520 patients who underwent a tonsillectomy at The 940th Hospital of Joint Logistics Support Force of Chinese People's Liberation Army. The age range of the patients was 2-57 years, and 364 (70%) were male. The prediction models were developed using five machine learning models: decision tree, support vector machine (SVM), extreme gradient boosting (XGBoost), random forest, and logistic regression. The performance of the models was evaluated using the area under the receiver operating characteristic curve (AUC). Shapley additive explanation (SHAP) was used to interpret the results of the best-performing model.

Results

The frequency of PTH was 11.54% among the 520 patients, with 10.71% in the training group and 13.46% in the validation set. Age, BMI, season, smoking, blood type, INR, combined secretory otitis media, combined adenoidectomy, surgical wound, and use of glucocorticoids were selected by mutual information (MI) method. The XGBoost model had best AUC (0.812) and Brier score (0.152). Decision curve analysis (DCA) showed that the model had a high clinical utility. The SHAP method revealed the top 10 variables of MI according to the importance ranking, and the average of the age was recognized as the most important predictor variable.

Conclusion

This study built a PTH risk prediction model using machine learning. The XGBoost model is a tool with potential to facilitate population management strategies for PTH.

[Risk factor analysis of secondary post-tonsillectomy hemorrhage in children]

Objective: To analyze the risk factors of secondary post-tonsillectomy hemorrhage (PTH) in children, and to provide a theoretical basis for reducing complications after tonsillectomy. Method: A retrospective analysis of 354 children underwent tonsillectomy was performed, among which 42 secondary hemorrhage cases were divided into bleeding group, and other 312 cases were divided into non-bleeding group. To analyze the risk factors of secondary PTH and to discusses the pathogenesis of the hemorrhage, statistical analysis was conducted among eight clinical data including gender, age, reason of surgery, degree of tonsil embedding, surgery approach, surgeon' s skill level, intra-operative hemorrhagic volume, and postoperative absence of upper respiratory tract infection. Result: Univariant analysis showed that there was no statistical difference of gender, reason for operation, surgeon' s skill level, intra-operative hemorrhagic volume and postoperative upper respiratory tract infection different between bleeding group and non-bleeding group, while there was significant statistical difference of age, degree of tonsillar embedding, and surgery approach. Further multivariate logistic regression analysis of the three relevant factors showed that there was a significant correlation between the degree of tonsillar embedding and the surgery approach and the hemorrhage. Conclusion: Hemorrhage after tonsillectomy is a common and potentially fatal complication, with risk factors of the degree of tonsillar embedding, and the surgery approach. .

Flufenamic acid inhibits secondary hemorrhage and BSCB disruption after spinal cord injury

Acute spinal cord injury (SCI) induces secondary hemorrhage and initial blood-spinal cord barrier (BSCB) disruption. The transient receptor potential melastatin 4 (Trpm4) together with sulfonylurea receptor 1 (Sur1) forms the Sur1-Trpm4 channel complex. The up-regulation of Sur1-Trpm4 after injury plays a crucial role in secondary hemorrhage, which is the most destructive mechanism in secondary injuries of the central nervous system (CNS). The matrix metalloprotease (MMP)-mediated disruption of the BSCB leads to an inflammatory response, neurotoxin production and neuronal cell apoptosis. Thus, preventing secondary hemorrhage and BSCB disruption should be an important goal of therapeutic interventions in SCI.

Methods: Using a moderate contusion injury model at T10 of the spinal cord, flufenamic acid (FFA) was injected intraperitoneally 1 h after SCI and then continuously once per day for one week.

Results: Trpm4 expression is highly up-regulated in capillaries 1 d after SCI. Treatment with flufenamic acid (FFA) inhibited Trpm4 expression, secondary hemorrhage, and capillary fragmentation and promoted angiogenesis. In addition, FFA significantly inhibited the expression of MMP-2 and MMP-9 at 1 d after SCI and significantly attenuated BSCB disruption at 1 d and 3 d after injury. Furthermore, we found that FFA decreased the hemorrhage- and BSCB disruption-induced activation of microglia/macrophages and was associated with smaller lesions, decreased cavity formation, better myelin preservation and less reactive gliosis. Finally, FFA protected motor neurons and improved locomotor functions after SCI.

Conclusion: This study indicates that FFA improves functional recovery, in part, due to the following reasons: (1) it inhibits the expression of Trpm4 to reduce the secondary hemorrhage; and (2) it inhibits the expression of MMP-2 and MMP-9 to block BSCB disruption. Thus, the results of our study suggest that FFA may represent a potential therapeutic agent for promoting functional recovery.