Literature Review of Criteria for Defining Recipient-Site Infection after Oral Oncologic Surgery with Simultaneous Reconstruction

Establishing a role for the oral microbiome in infectious complications following major oral cavity cancer surgery

Surgery forms the backbone of treatment for most locoregional or advanced oral cavity squamous cell carcinoma. Unfortunately, infectious complications (including orocutaneous fistulas) are common following such extensive surgery and can afflict over half of patients. These complications can lead to delays in adjuvant treatment, prolonged hospitalization, reconstructive failure, and decreased quality of life. The frequency and morbidity associated with infectious complications has led to the search for pre-disposing risk factors; and, several have been identified, including both patient (e.g. diabetes) and surgical (e.g. operative time) factors. However, these findings are inconsistently reproduced, and risk factor modification has had a limited impact on rates of infectious complications. This is striking given that the likely contaminant-the oral microbiome-is a well-studied microbial reservoir. Because many oral cavity cancer surgeries involve violation of oral mucosa and the spillage of the oral microbiome into normally sterile areas (e.g. the neck), variance in oral microbiome composition and function could underly differences in infectious complications. The goal of this perspective is to highlight 1) this knowledge gap and 2) opportunities for studies in this domain. The implication of this line of thought is that the identification of oral microbial dysbiosis in patients undergoing surgery for oral cavity cancer could lead to targeted pre-operative therapeutic interventions, decreased infectious complications, and improved patient outcomes.

Precision in Prevention: Tailoring Single-Use Negative Pressure Wound Therapy Utilization Through Artificial Intelligence-Based Surgical Site Complications Risk and Cost Modeling

Background: Surgical site complications (SSCs) are common, yet preventable hospital-acquired conditions. Single-use negative pressure wound therapy (sNPWT) has been shown to be effective in reducing rates of these complications. In the era of value-based care, strategic allocation of sNPWT is needed to optimize both clinical and financial outcomes. Materials and Methods: We conducted a retrospective analysis using data from the Premier Healthcare Database (2017-2021) for 10 representative open procedures in orthopedic, abdominal, cardiovascular, cesarean delivery, and breast surgery. After separating data into training and validation sets, various machine learning algorithms were used to develop pre-operative SSC risk prediction models. Model performance was assessed using standard metrics and predictors of SSCs were identified through feature importance evaluation. Highest-performing models were used to simulate the cost-effectiveness of sNPWT at both the patient and population level. Results: The prediction models demonstrated good performance, with an average area under the curve of 76%. Prominent predictors across subspecialities included age, obesity, and the level of procedure urgency. Prediction models enabled a simulation analysis to assess the population-level cost-effectiveness of sNPWT, incorporating patient and surgery-specific factors, along with the established efficacy of sNPWT for each surgical procedure. The simulation models uncovered significant variability in sNPWT's cost-effectiveness across different procedural categories. Conclusions: This study demonstrates that machine learning models can effectively predict a patient's risk of SSC and guide strategic utilization of sNPWT. This data-driven approach allows for optimization of clinical and financial outcomes by strategically allocating sNPWT based on personalized risk assessments.

Barbed suture in oral cavity reconstruction: preliminary results

The purpose of this study is to evaluate the efficacy and safety of unidirectional barbed suture (V-Loc) compared to a standard monofilament stitch (Vicryl) in suturing of a free flap to local tissue after head and neck surgery for squamous cell carcinoma of the oral cavity. Complication rates, operative closure time, length of hospitalisation and costs were evaluated. The study cohort (group A) of 20 consecutive patients reconstructed using barbed stitches for suturing was prospectively compared to a control cohort (group B) of 20 consecutive patients reconstructed using conventional vicryl stitches. All patients were affected by squamous cell carcinoma of the tongue and underwent different types of glossectomy and reconstruction with free flaps. This analysis demonstrates the efficacy of the barbed suture compared with a standard monofilament stitch in terms of lower complication rate (15% group A, 30% group B), intra-operative closure times (486 minutes group A, 517 minutes group B), and length of hospitalisation (average length of hospitalisation 14.60 days group A, 16.85 days group B). These factors coupled with the use of a lower number of stitches compared with the standard stitches may compensate the increased cost of the barbed suture. In conclusion, this study demonstrates that the use of unidirectional barbed stitches for suturing of a free flap to the recipient site reduces the complication rate, principally in terms of dehiscence and fistula incidence, and reduces intra-operative time and length of hospitalisation. Based on these results and on the literature, the use of unidirectional barbed stitches can be considered as a safe and efficient alternative to conventional stitches for suturing of free flaps to local tissue.

Artificial neural network approach to predict surgical site infection after free-flap reconstruction in patients receiving surgery for head and neck cancer

Background

The aim of this study was to develop an effective surgical site infection (SSI) prediction model in patients receiving free-flap reconstruction after surgery for head and neck cancer using artificial neural network (ANN), and to compare its predictive power with that of conventional logistic regression (LR).

Materials and methods

There were 1,836 patients with 1,854 free-flap reconstructions and 438 postoperative SSIs in the dataset for analysis. They were randomly assigned tin ratio of 7:3 into a training set and a test set. Based on comprehensive characteristics of patients and diseases in the absence or presence of operative data, prediction of SSI was performed at two time points (pre-operatively and post-operatively) with a feed-forward ANN and the LR models. In addition to the calculated accuracy, sensitivity, and specificity, the predictive performance of ANN and LR were assessed based on area under the curve (AUC) measures of receiver operator characteristic curves and Brier score.

Results

ANN had a significantly higher AUC (0.892) of post-operative prediction and AUC (0.808) of pre-operative prediction than LR (both P<0.0001). In addition, there was significant higher AUC of post-operative prediction than pre-operative prediction by ANN (p<0.0001). With the highest AUC and the lowest Brier score (0.090), the post-operative prediction by ANN had the highest overall predictive performance.

Conclusion

The post-operative prediction by ANN had the highest overall performance in predicting SSI after free-flap reconstruction in patients receiving surgery for head and neck cancer.