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032). However, IVF/24hr did not correlate with length of hospital stay (PCC 0.08, p=0.174). On multivariate analysis, only organ failure at admission was an independent predictor of persistent organ failure (OR 16.1, p<0.001). Persistent organ failure and local complications were found to be the only independent predictors in-hospital mortality (OR 27.6, p<0.001 and OR 16.95, p=0.001 respectively). There was no difference in clinical outcomes in African Americans compared to other races.

More aggressive early IVF therapy in a predominantly mild acute pancreatitis cohort, was not associated with improvement in persistent organ failure, length of hospital stay, or in-hospital mortality.

More aggressive early IVF therapy in a predominantly mild acute pancreatitis cohort, was not associated with improvement in persistent organ failure, length of hospital stay, or in-hospital mortality.

The aim of this study was to describe the clinical characteristics and management of gastric outlet obstruction following acute pancreatitis(AP).

Gastric outlet obstruction (GOO) is not uncommon in acute pancreatitis (AP) and can occur throughout the course. However, the clinical features and related treatment of GOO is rarely reported.

A retrospective review of AP patients with a diagnosis of GOO from March 2017 to June 2020 was performed. The diagnosis and management of GOO, as well as the demographic characteristics and clinical outcomes of the study patients, were collected and analyzed.

Over the three years, there were 60 AP patients developed GOO, constituting an incidence of 5.7%. Thirty-three patients (55.0%, 33/60) developed GOO in the first 4 weeks and 27 patients (45.0%, 27/60) after 4 weeks from onset. Pancreatic necrosis compression (60.6%; 20/33), gastric outlet gastrointestinal edema (27.3%, 9/33) are the main causes of early-onset GOO (≤4 weeks), while wall-off necrosis (92.6%, 25/27) is the leading cause in the late phase (>4 weeks). The management of GOO incorporates both supportive and specific treatment like gastric decompression, gastric juice reinfusion, percutaneous catheter drainage, etc. The mortality of AP patients with GOO (≤4 weeks) was 21.2% and none patients who developed GOO (>4 weeks) died.

GOO, as a gastrointestinal complication developed in AP patients, has two peak incidences in the duration of AP and needs to be paid more attention to.

GOO, as a gastrointestinal complication developed in AP patients, has two peak incidences in the duration of AP and needs to be paid more attention to.Recently, convolutional neural networks (CNNs)-based facial landmark detection methods have achieved great success. However, most of existing CNN-based facial landmark detection methods have not attempted to activate multiple correlated facial parts and learn different semantic features from them that they can not accurately model the relationships among the local details and can not fully explore more discriminative and fine semantic features, thus they suffer from partial occlusions and large pose variations. To address these problems, we propose a cross-order cross-semantic deep network (CCDN) to boost the semantic features learning for robust facial landmark detection. Specifically, a cross-order two-squeeze multi-excitation (CTM) module is proposed to introduce the cross-order channel correlations for more discriminative representations learning and multiple attention-specific part activation. Moreover, a novel cross-order cross-semantic (COCS) regularizer is designed to drive the network to learn cross-order cross-semantic features from different activation for facial landmark detection. Diphenyleneiodonium It is interesting to show that by integrating the CTM module and COCS regularizer, the proposed CCDN can effectively activate and learn more fine and complementary cross-order cross-semantic features to improve the accuracy of facial landmark detection under extremely challenging scenarios. Experimental results on challenging benchmark datasets demonstrate the superiority of our CCDN over state-of-the-art facial landmark detection methods.

Nonsquamous penile cancers comprise 5% of penile malignancies, though their clinicopathologic features and prognostic significance remain unknown. We used a national cancer registry to detail clinical characteristics and compare cancer-specific mortality (CSM) of nonsquamous cancers with squamous cell carcinoma (SCC).

The Surveillance, Epidemiology, and End Results (SEER) database (1975-2016) was queried to identify adults with nonsquamous penile cancer and penile SCC. Multivariable Fine and Gray competing-risks regression, propensity score matching, and cumulative incidence plots were used.

666 men with nonsquamous penile cancer and 5,894 men with penile SCC were identified. The most commonly represented nonsquamous histological subtypes were Kaposi sarcoma (n = 183, 27.5%), melanoma (n = 74, 11.1%), basal cell carcinoma (n = 65, 9.8%), and extramammary Paget disease (n = 42, 6.3%). Cumulative incidence plots revealed a 10-year CSM rate of 32.6% in the nonsquamous penile cancer group and 25.6% in the ms, likely due to improved control of systemic HIV in patients with Kaposi sarcoma. However, men with penile melanoma continue to experience a higher rate of CSM.

The most common nonsquamous penile cancers are Kaposi sarcoma, melanoma, and basal cell carcinoma. Overall, CSM is higher in nonsquamous penile cancers as compared to stage-matched SCC. Outcomes are similar in modern patients, likely due to improved control of systemic HIV in patients with Kaposi sarcoma. However, men with penile melanoma continue to experience a higher rate of CSM.

Clinical trials are pillars of modern clinical evidence generation. However, the clinical trial enterprise can be inefficient, and trials often fail before their planned endpoint is reached. We sought to estimate how often urologic oncology trials fail, why trials fail, and associations with trial failure.

We queried phase 2/3 urologic clinical trial data from ClinicalTrials.gov registered between 2007 and 2019, with status marked as active, completed, or terminated. We extracted relevant trial data, including anticipated and actual accrual, from trial records and ClinicalTrials.gov archives. We manually coded reasons given in the "why stopped" free text field for trial failure into categories (poor accrual, interim results, toxicity/adverse events, study agent unavailable, canceled by the sponsor, inadequate budget, logistics, trial no longer needed, principal investigator left, no reason given, or other). We considered trials terminated for safety or efficacy to be completed trials. Trials marked as terminated for other reasons were considered failed trials.