Publications by authors named "M S Benk"

Background: Clinical prediction models are needed to accurately predict the prognosis of patients with gastric cancer who have received neoadjuvant therapy and to determine the best treatment strategies. The aim of this study is to determine the role of two prognostic factors, the neoadjuvant rectal (NAR) score and the downstaging depth score (DDS), in predicting survival in patients with gastric cancer who received neoadjuvant therapy and underwent curative gastrectomy.

Methods: We reviewed the medical records of 129 patients who had been diagnosed with primary gastric cancer and underwent radical gastrectomy after receiving neoadjuvant therapy.

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Background: Acute appendicitis is the most common cause of surgical emergencies. It can be difficult to distinguish cases of acute appendicitis that should be managed by laparoscopic appendectomy (LA) from those that should be managed by open surgery. This study aimed to prevent the inappropriate choice of technique and associated complications by identifying potential risk factors for conversion from laparoscopic to open appendectomy (OA) at the time of initial surgical assessment.

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The clinical significance of the albumin-bilirubin (ALBI) grade in patients with pancreatic head cancer (PHC) undergoing surgery is unknown. Preoperative ALBI grade is believed to be influenced by tumor burden. This study aimed to develop and validate the ALBI grade as a preoperative prognostic model for predicting the survival of patients with PHC.

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Introduction: Seroma development after mastectomy is a common complication. Continued seroma causes increased outpatient visits, repeated aspirations, infection, delayed healing, delayed adjuvant therapy, and increased cost. Various treatments are being attempted to prevent and reduce seroma development.

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Background: Work stress places a heavy economic and disease burden on society. Recent technological advances include digital health interventions for helping employees prevent and manage their stress at work effectively. Although such digital solutions come with an array of ethical risks, especially if they involve biomedical big data, the incorporation of employees' values in their design and deployment has been widely overlooked.

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