BackgroundsIn this study, we evaluated the factors associated with a pathologic complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) for esophageal squamous cell carcinoma (ESCC).MethodsPre-nCRT parameters in ESCC patients treated between 1999 and 2006 were analyzed to identify predictors of pCR. All patients received 5-fluorouracil/cisplatin-based chemotherapy and external beam radiation followed by scheduled esophagectomy. Variables were analyzed using univariate and multivariate analyses with pCR as the dependent variable. Estimated pCR rate was calculated with a regression model.ResultsFifty-nine (20.9%) of 282 patients achieved pCR. Univariate analysis identified four patient factors (age, smoking status, drinking history and hypertension), one pre-nCRT parameter (tumor length) as significant predictors of pCR (all P <0.05). On multivariate analysis, tumor length ≤3 cm (favorable, odds ratio (OR): 4.85, P = 0.001), patient age >55 years (favorable, OR: 1.95, P = 0.035), and being a non-smoker (favorable, OR: 3.6, P = 0.003) were independent predictors of pCR. The estimated pCR rates based on a logistic regression including those three predictors were 71%, 35 to approximately 58%, 19 to approximately 38%, and 12% for patients with 3, 2, 1 and 0 predictors, respectively.ConclusionAge, smoking habit and tumor length were important pCR predictors. These factors may be used to predict outcomes for ESCC patients receiving nCRT, to develop risk-adapted treatment strategies, and to select patients who could participate in trials on new therapies.

III (Therapeutic).

Background: Postoperative free flap monitoring is a critical part of reconstructive microsurgery. Postoperative clinical assessments rely heavily on specialty-trained staff. Therefore, in regions with limited specialist availability, the feasibility of performing microsurgery is restricted. This study aimed to apply artificial intelligence in postoperative free flap monitoring and validate the ability of machine learning in predicting and differentiating types of postoperative free flap circulation. Methods: Postoperative data from 176 patients who received free flap surgery were prospectively collected, including free flap photographs and clinical evaluation measures. Flap circulation outcome variables included normal, arterial insufficiency, and venous insufficiency. The Synthetic Minority Oversampling Technique plus Tomek Links (SMOTE-Tomek) was applied for data balance. Data were divided into 80%:20% for model training and validation. Shapley Additive Explanations were used for prediction interpretations of the model. Results: Of 805 total included flaps, 555 (69%) were normal, 97 (12%) had arterial insufficiency, and 153 (19%) had venous insufficiency. The most effective prediction model was developed based on random forest, with an accuracy of 98.4%. Temperature and color differences between the flap and the surrounding skin were the most significant contributing factors to predict a vascular compromised flap. Conclusions: This study demonstrated the reliability of a machine-learning model in differentiating various types of postoperative flap circulation. This novel technique may reduce the burden of free flap monitoring and encourage the broader use of reconstructive microsurgery in regions with a limited number of staff specialists.

BackgroundDepression is common among patients with head and neck cancer, thereby affecting their survival rate. However, whether close monitoring of depression affects the survival outcomes of these patients is unknown. Therefore, this study aimed to determine whether depression treatment continuity after the diagnosis of cancer affects the survival of these patients.MethodsA total of 55,069 patients diagnosed with head and neck cancer in the Cancer Registration System database in Taiwan were enrolled. This cohort was followed from January 1, 2007 to December 31, 2017. Furthermore, the patients were divided into four groups, namely, “no depression,” “pre-cancer only,” “post-cancer only,” and “both before and after cancer,” on the basis of the diagnosis of depression and the duration of the follow-up period in the psychiatric clinic. Further, the Cox proportional hazard model was applied to estimate the hazard of death for the four groups.ResultsA total of 6,345 (11.52%) patients were diagnosed with depression in this cohort. The “pre-cancer only” group had a lower overall survival (HR = 1.18; 95% CI = 1.11–1.25) compared with the “no depression” group. Moreover, the “post-cancer only” group had better overall survival (HR = 0.88; 95% CI = 0.83–0.94) compared with the “no depression” group, especially in advanced-stage patients. Patients who were diagnosed with depression before cancer and had continuous depression treatments after the cancer diagnosis had better overall survival (HR = 0.78; 95% CI = 0.71–0.86) compared with patients who had treatment interruptions.ConclusionPatients with pre-cancer depression had poorer survival outcomes, especially those who did not receive psychiatric clinic visits after their cancer diagnosis. Nonetheless, in patients with advanced-stage cancer, depression treatment may improve overall survival.

No abstract

Arterial and venous insufficiency are two major causes of chronic wounds with different etiology, pathophysiology, and clinical manifestations. With recent advancements in clinical examination, clinicians are able to obtain an accurate diagnosis of the underlying disease, which plays an important role in the treatment planning and management of patients. Arterial ulcers are mainly caused by peripheral artery diseases (PADs), which are traditionally examined by physical examination and non-invasive arterial Doppler studies. However, advanced imaging modalities, such as computed tomography angiography (CTA) and indocyanine green (ICG) angiography, have become important studies as part of a comprehensive diagnostic process. On the other hand, chronic wounds caused by venous insufficiency are mainly evaluated by duplex ultrasonography and venography. Several scoring systems, including Clinical–Etiology–Anatomy–Pathophysiology (CEAP) classification, the Venous Clinical Severity Score (VCSS), the Venous Disability Score, and the Venous Segmental Disease Score (VSDS) are useful in defining disease progression. In this review, we provide a comprehensive overlook of the most widely used and available clinical examinations for arterial and venous insufficiency wounds.

Background: Free flap monitoring is essential for postmicrosurgical management and outcomes but traditionally relies on human observers; the process is subjective and qualitative and imposes a heavy burden on staffing. To scientifically monitor and quantify the condition of free flaps in a clinical scenario, we developed and validated a successful clinical transitional deep learning (DL) model integrated application. Material and Methods: Patients from a single microsurgical intensive care unit between 1 April 2021 and 31 March 2022, were retrospectively analyzed for DL model development, validation, clinical transition, and quantification of free flap monitoring. An iOS application that predicted the probability of flap congestion based on computer vision was developed. The application calculated probability distribution that indicates the flap congestion risks. Accuracy, discrimination, and calibration tests were assessed for model performance evaluations. Results: From a total of 1761 photographs of 642 patients, 122 patients were included during the clinical application period. Development (photographs =328), external validation (photographs =512), and clinical application (photographs =921) cohorts were assigned to corresponding time periods. The performance measurements of the DL model indicate a 92.2% training and a 92.3% validation accuracy. The discrimination (area under the receiver operating characteristic curve) was 0.99 (95% CI: 0.98–1.0) during internal validation and 0.98 (95% CI: 0.97–0.99) under external validation. Among clinical application periods, the application demonstrates 95.3% accuracy, 95.2% sensitivity, and 95.3% specificity. The probabilities of flap congestion were significantly higher in the congested group than in the normal group (78.3 (17.1)% versus 13.2 (18.1)%; 0.8%; 95% CI, P<0.001). Conclusion: The DL integrated smartphone application can accurately reflect and quantify flap condition; it is a convenient, accurate, and economical device that can improve patient safety and management and assist in monitoring flap physiology.

An innovative immunosuppressant with a minimally invasive delivery system has emerged in the biomedical field. The application of biodegradable and biocompatible polymer forms, such as hydrogels, scaffolds, microspheres, and nanoparticles, in transplant recipients to control the release of immunosuppressants can minimize the risk of developing unfavorable conditions. In this review, we summarized several studies that have used implantable immunosuppressant delivery to release therapeutic agents to prolong allograft survival. We also compared their applications, efficacy, efficiency, and safety/side effects with conventional therapeutic-agent administration. Finally, challenges and the future prospective were discussed. Collectively, this review will help relevant readers understand the different approaches to prevent transplant rejection in a new era of therapeutic agent delivery.