Machine learning-based preoperative analytics for the prediction of anastomotic leakage in colorectal surgery: a swiss pilot study.

BACKGROUND: Anastomotic leakage (AL), a severe complication following colorectal surgery, arises from defects at the anastomosis site. This study evaluates the feasibility of predicting AL using machine learning (ML) algorithms based on preoperative data. METHODS: We retrospectively analyzed data including 21 predictors from patients undergoing colorectal surgery with bowel anastomosis at four Swiss hospitals. Several ML algorithms were applied for binary classification into AL or non-AL groups, utilizing a five-fold cross-validation strategy with a 90% training and 10% validation split. Additionally, a holdout test set from an external hospital was employed to assess the models' robustness in external validation. RESULTS: Among 1244 patients, 112 (9.0%) suffered from AL. The Random Forest model showed an AUC-ROC of 0.78 (SD: ± 0.01) on the internal test set, which significantly decreased to 0.60 (SD: ± 0.05) on the external holdout test set comprising 198 patients, including 7 (3.5%) with AL. Conversely, the Logistic Regression model demonstrated more consistent AUC-ROC values of 0.69 (SD: ± 0.01) on the internal set and 0.61 (SD: ± 0.05) on the external set. Accuracy measures for Random Forest were 0.82 (SD: ± 0.04) internally and 0.87 (SD: ± 0.08) externally, while Logistic Regression achieved accuracies of 0.81 (SD: ± 0.10) and 0.88 (SD: ± 0.15). F1 Scores for Random Forest moved from 0.58 (SD: ± 0.03) internally to 0.51 (SD: ± 0.03) externally, with Logistic Regression maintaining more stable scores of 0.53 (SD: ± 0.04) and 0.51 (SD: ± 0.02). CONCLUSION: In this pilot study, we evaluated ML-based prediction models for AL post-colorectal surgery and identified ten patient-related risk factors associated with AL. Highlighting the need for multicenter data, external validation, and larger sample sizes, our findings emphasize the potential of ML in enhancing surgical outcomes and inform future development of a web-based application for broader clinical use.

Development and validation of a predictive model of the hospital cost associated with bariatric surgery.

Hospitals are facing difficulties in predicting, evaluating, and managing cost-affecting parameters in patient treatments. Inaccurate cost prediction leads to a deficit in operational revenue. This study aims to determine the ability of Machine Learning (ML) algorithms to predict the cost of care in bariatric and metabolic surgery and develop a predictive tool for improved cost analysis. 602 patients who underwent bariatric and metabolic surgery at Wetzikon hospital from 2013 to 2019 were included in the study. Multiple variables including patient factors, surgical factors, and post-operative complications were tested using a number of predictive modeling strategies. The study was registered under Req 2022-00659 and approved by an institutional review board. The cost was defined as the sum of all costs incurred during the hospital stay, expressed in CHF (Swiss Francs). The data was preprocessed and split into a training set (80%) and a test set (20%) to build and validate models. The final model was selected based on the mean absolute percentage error (MAPE). The Random Forest model was found to be the most accurate in predicting the overall cost of bariatric surgery with a mean absolute percentage error of 12.7. The study provides evidence that the Random Forest model could be used by hospitals to help with financial calculations and cost-efficient operation. However, further research is needed to improve its accuracy. This study serves as a proof of principle for an efficient ML-based prediction tool to be tested on multi-center data in future phases of the study.

Gastrointestinal Stromal Tumor (GIST): A Remarkable Case Report and Literature Review.

Gastrointestinal stromal tumor (GIST) makes up less than 1% of all gastrointestinal tumors, but it is the most common mesenchymal tumor of the digestive system. It is commonly found in the stomach and the small intestine and rarely seen in the colon and the esophagus. Additionally, sigmoid GIST is quite rare since colorectal GIST often occurs in the rectum. A total of 21 patients (including the study case) were looked at for this study, of which 14 (66.6%) were males and seven (33.3%) were females. We focused on GIST and conducted an online search and systematic analysis of all case presentations.

Corrigendum: The development of machine learning in bariatric surgery.

[This corrects the article DOI: 10.3389/fsurg.2023.1102711.].

The development of machine learning in bariatric surgery.

Background: Machine learning (ML), is an approach to data analysis that makes the process of analytical model building automatic. The significance of ML stems from its potential to evaluate big data and achieve quicker and more accurate outcomes. ML has recently witnessed increased adoption in the medical domain. Bariatric surgery, otherwise referred to as weight loss surgery, reflects the series of procedures performed on people demonstrating obesity. This systematic scoping review aims to explore the development of ML in bariatric surgery. Methods: The study used the Preferred Reporting Items for Systematic and Meta-analyses for Scoping Review (PRISMA-ScR). A comprehensive literature search was performed of several databases including PubMed, Cochrane, and IEEE, and search engines namely Google Scholar. Eligible studies included journals published from 2016 to the current date. The PRESS checklist was used to evaluate the consistency demonstrated during the process. Results: A total of seventeen articles qualified for inclusion in the study. Out of the included studies, sixteen concentrated on the role of ML algorithms in prediction, while one addressed ML's diagnostic capacity. Most articles (n = 15) were journal publications, whereas the rest (n = 2) were papers from conference proceedings. Most included reports were from the United States (n = 6). Most studies addressed neural networks, with convolutional neural networks as the most prevalent. Also, the data type used in most articles (n = 13) was derived from hospital databases, with very few articles (n = 4) collecting original data via observation. Conclusions: This study indicates that ML has numerous benefits in bariatric surgery, however its current application is limited. The evidence suggests that bariatric surgeons can benefit from ML algorithms since they will facilitate the prediction and evaluation of patient outcomes. Also, ML approaches to enhance work processes by making data categorization and analysis easier. However, further large multicenter studies are required to validate results internally and externally as well as explore and address limitations of ML application in bariatric surgery.

Developing and validating a multivariable prediction model for predicting the cost of colon surgery.

Hospitals are burdened with predicting, calculating, and managing various cost-affecting parameters regarding patients and their treatments. Accuracy in cost prediction is further affected when a patient suffers from other health issues that hinder the traditional prognosis. This can lead to an unavoidable deficit in the final revenue of medical centers. This study aims to determine whether machine learning (ML) algorithms can predict cost factors based on patients undergoing colon surgery. For the forecasting, multiple predictors will be taken into the model to provide a tool that can be helpful for hospitals to manage their costs, ultimately leading to operating more cost-efficiently. This proof of principle will lay the groundwork for an efficient ML-based prediction tool based on multicenter data from a range of international centers in the subsequent phases of the study. With a mean absolute percentage error result of 18%-25.6%, our model's prediction showed decent results in forecasting the costs regarding various diagnosed factors and surgical approaches. There is an urgent need for further studies on predicting cost factors, especially for cases with anastomotic leakage, to minimize unnecessary hospital costs.

Cost and Quality Comparison of Hernia Surgery in Stationary, Day-Patient and Outpatient Care.

BACKGROUND: Medical progress is increasingly enabling more and more stationary treatment to be provided in the outpatient sector. This development should be welcomed, as healthcare costs have been rising for years. The design of efficient processes and a needs-based infrastructure enable further savings. According to international recommendations (EHS/IEHS), outpatient treatment of unilateral inguinal hernias is recommended. METHOD: Data from patients in GZO Hospital Wetzikon/Zurich between 2019 and 2021 for unilateral inguinal hernia repair was included in this study (n = 234). Any over- or under-coverage correlated with one of the three treatment groups: stationary, partially stationary and patients treated in outpatients clinic. Complications and 30-day readmissions were also monitored. RESULTS: Final revenue for all patients is -95.36 CHF. For stationary treatments, the mean shifts down to -575.01 CHF, for partially stationary treatments the mean shifts up to -24.73 CHF, and for patients in outpatient clinic final revenue is 793.12 CHF. This result is also consistent with the operation times, which are lowest in the outpatient clinic with a mean of 36 min, significantly longer in the partially stationary setting with 58 min, and longest in the stationary setting with 76 min. The same applies to the anesthesia times and the relevant care times by the nurses as the most important cost factors in addition to the supply and allocation costs. CONCLUSIONS: We show that cost-effective elective unilateral inguinal hernia care in the outpatient clinic with profit (mean 793.12 CHF) is possible. Stationary unilateral hernia care (mean -575.01 CHF) is loss-making. Crucial factors for cost efficiency are optimized processes in the operating room (anesthesia, surgical technique and quality, operating time), as well as optimized care processes with minimal preoperative services and care times for the patient. However, at the same time, these optimizations pose a challenge to surgical and anesthesiology training and structures with high levels of preoperative and Postoperative services and pay-as-you-go costs. The complication rate is 0.91% lower than in a comparable study. The readmission within 30 days post-operation results with a positive deviation of -3.53% (stationary) and with a negative deviation of +2.29% (outpatient clinic) compared to a comparative study.

The development of machine learning in lung surgery: A narrative review.

Background: Machine learning reflects an artificial intelligence that allows applications to improve their accuracy to predict outcomes, eliminating the need to conduct explicit programming on them. The medical field has increased its focus on establishing tools for integrating machine learning algorithms in laboratory and clinical settings. Despite their importance, their incorporation is minimal in the medical sector yet. The primary goal of this study is to review the development of machine learning in the field of thoracic surgery, especially lung surgery. Methods: This article used the Preferred Reporting Items for Systematic and Meta-analyses (PRISMA). The sources used to gather data are the PubMed, Cochrane, and CINAHL databases and the Google Scholar search engine. Results: The study included 19 articles, where ten concentrated on the application of machine learning in especially lung surgery, six focused on the benefits and limitations of machine learning algorithms in lung surgery, and three provided an overview of the future of machine learning in lung surgery. Conclusion: The outcome of this study indicates that the field of lung surgery has attempted to integrate machine learning algorithms. However, the implementation rate is low, owing to the newness of the concept and the various challenges it encompasses. Also, this study reveals the absence of sufficient literature discussing the application of machine learning in lung surgery. The necessity for future research on the topic area remains evident.

The Effects of Anastomotic Leaks on the Net Revenue from Colon Surgery.

Background: Complications in colon surgery can have severe health consequences, while at the same time, they are associated with increased costs. An anastomotic leak (AL) is associated with significantly increased costs compared to cases without. The aim of our analysis was to evaluate, which individual processes and patient-unrelated factors influencing the treatment process of colon surgery are responsible for the financial burden in patients with AL. Methods: Data from 263 patients who underwent colon surgery in Wetzikon hospital between January 2018 and December 2020 and was analyzed. In these 263 cases, 12 anastomotic leaks occurred and were compared with 36 cases without AL using a Propensity Score Matching (PSM). The covariates for the PSM have been Age, Sex, and Type of Surgery (t value: −3.26, p-value: 0.001). Results: A total of 48 surgeries were broken down in terms of costs and profitability. This reflected a mean deficit of −37,527 CHF per case (range from −130.05 to +755 CHF) for patients with AL, whereas a mean profit of 1590 CHF per case (range from −24.37 to +12.65 CHF) for those without AL (p < 0.001). Thus, the difference in profit showed a factor of 24.6 with an overall significant negative outcome for the occurrence of AL. The main cost contributing factors were the length of hospital stay (~p < 0.05) and length of intensive care (p < 0.05), whereas neither surgical operation time and anesthesia time nor surgical access, insurance status, indication or type of operation had a significant influence on the net revenue. Conclusion: AL after colon surgery leads to a significant deficit regarding the net revenue. Regarding process optimization, our analysis identified several sectors of non-patient-related, yet cost-influencing variables that should be addressed in future evaluations and optimization of the colon surgery treatment processes.

Suprapubic Cholecystectomy Improves Cosmetic Outcome Compared to Classic Cholecystectomy.

Currently, cholecystectomy is performed laparoscopically. While the conventional approach (CA) with four access ports persists, other methods seek to reduce trauma or to optimize cosmetic results. In this study, the safety and cosmetic outcome of a suprapubic approach (SA) were evaluated. Between 2015 and 2016, patients undergoing elective cholecystectomy either by CA or by a suprapubic approach (SA) at our institution were included. The cosmetic outcome, postoperative morbidity, operative time and length of stay were evaluated. Pictures of the site of intervention were taken 6−12 months postoperatively and rated on a scale from 1 (unsatisfying aesthetic result) to 5 (excellent aesthetic result). Five "non-medical" and five "medical" raters as well as one board-certified plastic surgeon performed the ratings. A total of 70 patients were included (n = 28 SA, n = 42 CA). The two groups did not differ in baseline characteristics (age, gender, BMI). The SA group showed a significantly better aesthetic outcome compared to the CA group 4.8 (4.8−4.9) vs. 4.2 (3.8−4.4), (p > 0.001). Medical raters: 4.0 (3.8−4.2) vs. 4.8 (4.6−5.0), (p < 0.001); non-medical raters: 4.2 (3.8−4.6) vs. 5.0 (4.8−5.0), (p < 0.001); plastic surgeon: 4.0 (4.0−4.0) vs. 5.0 (5.0−5.0), (p < 0.001). Fair interrater consistency was demonstrated with an ICC of 0.47 (95% CI = 0.38−0.57). No significant difference in the complication rate (1 (3.5%) in SA vs. 6 (14%) in CA, (p = 0.3)), or the operating time 66 (50−86) vs. 70 (65−82) min, (p = 0.3), were observed. Patients stayed for a median of three (3−3) days in the SA group and 3 (3−4) days in the CA group (p = 0.08). This study demonstrated that the suprapubic approach is an appropriate alternative to conventional laparoscopic cholecystectomy, presenting a better cosmetic outcome with a similar complication rate.

The Development of Artificial Intelligence in Hernia Surgery: A Scoping Review.

Background: Artificial intelligence simulates human intelligence in machines that have undergone programming to make them think like human beings and imitate their activities. Artificial intelligence has dominated the medical sector to perform various patient diagnosis activities and improve communication between professionals and patients. The main goal of this study is to perform a scoping review to evaluate the development of artificial intelligence in all forms of hernia surgery except the diaphragm and upside-down hernia. Methods: The study used the Preferred Reporting Items for Systematic and Meta-analyses for Scoping Review (PRISMA-ScR) to guide the structuring of the manuscript and fulfill all the requirements of every subheading. The sources used to gather data are the PubMed, Cochrane, and EMBASE databases, IEEE and Google and Google Scholar search engines. AMSTAR tool is the most appropriate for assessing the methodological quality of the included studies. Results: The study exclusively included twenty articles, whereby seven focused on artificial intelligence in inguinal hernia surgery, six focused on abdominal hernia surgery, five on incisional hernia surgery, and two on AI in medical imaging and robotics in hernia surgery. Conclusion: The outcomes of this study reveal a significant literature gap on artificial intelligence in hernia surgery. The results also indicate that studies focus on inguinal hernia surgery more than any other types of hernia surgery since the articles addressing the topic are more. The study implies that more research is necessary for the field to develop and enjoy the benefits associated with AI. Thus, this situation will allow the integration of AI in activities like medical imaging and surgeon training.

Advancements of Artificial Intelligence in Liver-Associated Diseases and Surgery.

Background and Objectives: The advancement of artificial intelligence (AI) based technologies in medicine is progressing rapidly, but the majority of its real-world applications has not been implemented. The establishment of an accurate diagnosis with treatment has now transitioned into an artificial intelligence era, which has continued to provide an amplified understanding of liver cancer as a disease and helped to proceed better with the method of procurement. This article focuses on reviewing the AI in liver-associated diseases and surgical procedures, highlighting its development, use, and related counterparts. Materials and Methods: We searched for articles regarding AI in liver-related ailments and surgery, using the keywords (mentioned below) on PubMed, Google Scholar, Scopus, MEDLINE, and Cochrane Library. Choosing only the common studies suggested by these libraries, we segregated the matter based on disease. Finally, we compiled the essence of these articles under the various sub-headings. Results: After thorough review of articles, it was observed that there was a surge in the occurrence of liver-related surgeries, diagnoses, and treatments. Parallelly, advanced computer technologies governed by AI continue to prove their efficacy in the accurate screening, analysis, prediction, treatment, and recuperation of liver-related cases. Conclusions: The continual developments and high-order precision of AI is expanding its roots in all directions of applications. Despite being novel and lacking research, AI has shown its intrinsic worth for procedures in liver surgery while providing enhanced healing opportunities and personalized treatment for liver surgery patients.

The Development of Healthcare Jobs in the COVID-Pandemic-A New Economic Market.

Background: The COVID-19 pandemic commenced in China and has caused the death of numerous people globally. Despite the adverse effects, the outbreak has created room for job opportunities in healthcare, particularly the pharmaceutical domain. The main goal of this study is to examine how the current pandemic has triggered job creation in the healthcare domain and created a new economic market. Methods: The study used the Preferred Reporting Items for Systematic and Meta-analyses for Scoping Review (PRISMA-ScR) to structure the manuscript and the subheadings to use. The source used to gather data is the PubMed database. Results: The study exclusively included fourteen articles, five of which focused on the pharmaceutical sector, three focused on vaccine sales, three on vaccination centers, and three on testing centers. Conclusion: The COVID-19 pandemic has created job opportunities in the healthcare sector. Most jobs are in the pharmaceutical sector, vaccination, and testing centers. However, more comprehensive research on the topic is necessary to gather conclusive outcomes on whether these jobs will be relevant after the pandemic.

Thyroglossal Duct Cyst, a Case Report and Literature Review.

A thyroglossal duct cyst (TGDC) is one of the most commonly encountered congenital anomalies of the neck. However, it is difficult to diagnose as differentiating it from other cysts like brachial cysts, lymphangiomas, epidermoid cysts, dermoid cysts, and hydatid cysts, is challenging. In this paper, we systematically reviewed the literature of 47 patients-25 males (53.1%) and 21 females (44.7%)-about their TGDC to assess the clinical picture, therapy, and prognosis of the disease. Most of the patients were children under the age of ten (63.8%). All patients had a history of a painless swelling in the anterior midline of the neck that moved in response to deglutition and tongue protrusion, thus interfering with their daily activity. Post-resection recurrence was unusual, with only 3 of 47 patients (6.4%) experiencing recurrence.

Prognostic Value of Immunohistochemical Markers for Locally Advanced Rectal Cancer.

The aim of this study is to reveal the potential roles of apoptosis markers (Bcl2 and p53), proliferation markers (Ki-67 and CyclD1), and the neuroendocrine marker Chromogranin A as markers for the radioresistance of rectal cancer. Statistically significant differences were found in the expression of p53, Ki-67, and Chromogranin A in groups of patients with and without a favorable prognosis after radiotherapy. The survival analysis revealed that the marker of neuroendocrine differentiation, Chromogranin A, also demonstrated a high prognostic significance, indicating a poor prognosis. Markers of proliferation and apoptosis had no prognostic value for patients who received preoperative radiotherapy. Higher Chromogranin A values were predictors of poor prognosis. The results obtained from studying the Chromogranin A expression suggest that the secretion of biologically active substances by neuroendocrine cells causes an increase in tumor aggressiveness.

The Increasing Investment of Real Estate in the Health System-A Comparison between the USA and Europe.

BACKGROUND: This study aimed to compare property development and increasing investment in real estate by the healthcare system organizations in the USA and Europe. Real estate investments have upsurged in healthcare due to the multiple benefits to patients and medical practitioners. METHODS: The approach of acquiring data was through secondary sources and online questionnaires. The researchers applied inclusion and exclusion criteria by exclusively including the articles published after 2014 to ensure the validity and reliability of the information. RESULTS: A total of 53.33% of the articles reviewed focused on the United States, while 46.67% concentrated on Europe. The development of real estate in healthcare is essential in both regions due to the challenges faced with the current infrastructure. Study Limitation: Currently, there are very few studies concentrating on the research topic. CONCLUSIONS: The USA and Europe should focus on increasing real estate investments in healthcare by focusing on hospitals and trusts, rehabilitation centers, and nursing homes.

The Development of Telemedicine and eHealth in Surgery during the SARS-CoV-2 Pandemic.

SARS-CoV-2 has hampered healthcare systems worldwide, but some countries have found new opportunities and methods to combat it. In this study, we focused on the rapid growth of telemedicine during the pandemic around the world. We conducted a systematic literature review of all the articles published up to the present year, 2021, by following the requirements of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. The data extracted comprised eHealth and telemedicine in surgery globally, and independently in Europe, the United States, and Switzerland. This review explicitly included fifty-nine studies. Out of all the articles included, none of them found that telemedicine causes poor outcomes in patients. Telemedicine has created a new path in the world of healthcare, revolutionizing how healthcare is delivered to patients and developing alternative methods for clinicians.

Analysis of Factors Relevant to Revenue Improvement in Ventral Hernia Repair, Their Influence on Surgical Training, and Development of Predictive Models: An Economic Evaluation.

BACKGROUND: Ventral hernia repairs (VHR) are frequent but loss- making. This study aims to identify epidemiological and procedure related factors in VHR and their influence on surgical training. METHODS: Data from 86 consecutive patients who underwent VHR in 2019 was collected. Moreover, 66 primary ventral hernias and 20 incisional hernias were repaired in open procedures. Linear regression models were made. RESULTS: Primary VHR procedures showed a mean deficit of -378.17 CHF per case. Incisional hernia repair procedures resulted in a deficit of -1442.50 CHF per case. The two hernia groups were heterogeneous. For the primary VHR procedures, the surgery time (ß = 0.564, p < 0.001) had the greatest influence, followed by the costs of the mesh (ß = -0.215, p < 0.001). The epidemiological factors gender (ß = 0.143, p < 0.01) and body mass index (BMI) (ß = -0.087, p = 0.074) were also influential. For incisional hernia procedures a surgeon's experience had the most significant influence (ß = 0.942, p < 0.001), and the second largest influence was the price of the mesh (ß = -0.500, p < 0.001). The epidemiological factor BMI (ß = -0.590, p < 0.001), gender (ß = -0.113, p = 0.055) and age (ß = -0.026, p < 0.050) also had a significant influence. CONCLUSION: Our analysis shows a way of improving financial results in the field of ventral hernia repair. Costs can be visualized and reduced to optimize revenue enhancement in surgical departments. In our analysis primary ventral hernias are an appropriate training operation, in which the experience of the surgeon has no significant impact on costs. In primary VHR procedures, revenue enhancement is limited when using an expensive mesh. However, the treatment of incisional hernias is recommended by specialists. The financial burden is significantly higher with less experience. Therefore, these operations are not suitable for surgical training. The re-operation rate decreases with increasing experience of the surgeon. This directly affects the Patient Related Outcome (PROM) and quality of treatment. Therefore, high-quality training must be enforced. Since financial pressure on hospitals is increasing further, it is crucial to investigate cost influencing factors. The majority of Swiss public hospitals will no longer be able to operate ventral hernias profitably without new concepts. In addition to purchasing management, new construction projects, and mergers, improving the results of individual departments is a key factor in maintaining the profitability of hospitals in the future regarding hernia repair without losing the scope of teaching procedures.

Analysis of Factors Relevant to Revenue Enhancement in Hernia Interventions (SwissDRG G09).

BACKGROUND: Since diagnosis-related groups (SwissDRG) were established in Switzerland in 2012, small and medium-size hospitals have encountered increasing financial troubles. Even though hernia repair operations are frequent, most hospitals fail to cover their costs with these procedures. Previous studies have focused mainly on analyzing costs and the contributing factors but less on variables that can be positively influenced. Therefore, this study aims to identify the relevant and influenceable factors for revenue growth in hernia repair surgery. METHODS: Data from all patients who underwent the SwissDRG G09 surgery for a hernia in 2019 were analyzed. The contribution margin (CM4), as well as any over- or under-coverage, was correlated to case-specific costs. RESULTS: A total of 168 patients received hernia repair surgery with the SwissDRG code G09. The average revenue/loss generated by one procedure was CHF -623.84. Procedures covered by the General Health Insurance (OKP) generated a loss of CHF -830.70 on average, whereas procedures covered by private insurance companies (VVG) generated revenue of CHF +1100 on average. Significant factors impacting the profitability of hernia repair operations were teaching during surgery (p < 0.005), the surgical operating time (p < 0.001), the total anesthesia time (p < 0.001), the number of surgeons present (p = 0.022), the insurance state of patients (p < 0.001), and the type of surgery (p < 0.01 for Lichtenstein's procedure). CONCLUSIONS: This study reveals that hernia repair surgery performed under cost coverage by OKP is generally unprofitable. Our results further imply that the most important and influenceable factors for revenue enhancement are the quality and process optimization of the surgical department. To compensate for this deficit, hospitals should aim to increase the percentage of patients with private health insurance coverage in their procedures. Since outpatient surgery does not provide a valid alternative due to the low reimbursement by insurance companies, the cost efficiency of inpatient hernia repair needs to be increased by process optimization of the surgical department; for instance, by providing specialized hernia teams performing with shorter operation times and high quality.

Advantages of negative pressure wound therapy with instillation of super oxidized solution and dwell time in diabetic foot syndrome: a rare case report.

Negative pressure wound therapy (NPWT) with instillation therapy (V.A.C. Vera-Flow™) and dwell time (NPWTi-d) is an innovative method for complex wound healing. NPWTi-d combines vacuum-aided drainage of wounds with the precise distribution of topical cleansing solution over the wounds. Furthermore, super oxidized solutions have illustrated their ability to potentiate wound healing and decrease bacterial contamination. Furthermore, aided with this method, infected wounds can be disinfected. If surgical debridement or removal of the infected site is not possible or desired. Therefore, in the case of a 66-year-old patient with diabetic foot syndrome (DFS) with severe infection, our approach was to couple NPWTi-d with instillation and dwelling of super oxidized solution to bolster benefits. This is the first case report using NPWTi-d with instillation of super oxidized solution in DFS in Switzerland. This case indicates that this approach is beneficial in the treatment of complex and critically infected wounds in DFS.