Publications by authors named "B Ergun"

Article Synopsis
  • Glycemic variability (GV) is a common issue in critically ill patients, and this study explored its impact on 28-day mortality through a multicenter analysis involving 578 patients across five ICUs in Turkey.
  • The study tracked several glycemic parameters within the first 24 hours, finding significant differences in CV (coefficient of variation), SD (standard deviation), and MGD (maximal-minimal glucose difference) between survivors and non-survivors, with higher levels linked to increased mortality risk.
  • Results indicated that CV is an independent risk factor for mortality, with a strong correlation with MGD, suggesting that monitoring these glycemic metrics could be critical for predicting patient outcomes in intensive care settings.
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() is a tumor suppressor gene involved in DNA repair and cell cycle regulation. Pathogenic or likely pathogenic (P/LP) variants in are associated with increased cancer risk. Conversely, recent large cohort studies have identified certain variants that, despite being classified as P/LP by in silico analysis, are considered low risk.

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Although the representation of women in palliative care has improved in recent years, gender inequality still exists in editorial leadership. This study aimed to characterize gender distribution in leadership positions on the editorial boards of palliative care journals. This cross-sectional study analyzed the gender composition of editorial boards for palliative care journals indexed in the Web of Science (WoS) and the factors that affect this composition.

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Cost-effective, noninvasive screening methods for preclinical Alzheimer's disease (AD) and other neurocognitive disorders remain an unmet need. The olfactory neural circuits develop AD pathological changes prior to symptom onset. To probe these vulnerable circuits, we developed the digital remote AROMHA Brain Health Test (ABHT), an at-home odor identification, discrimination, memory, and intensity assessment.

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There is no study that comprehensively evaluates data on the readability and quality of "palliative care" information provided by artificial intelligence (AI) chatbots ChatGPT®, Bard®, Gemini®, Copilot®, Perplexity®. Our study is an observational and cross-sectional original research study. In our study, AI chatbots ChatGPT®, Bard®, Gemini®, Copilot®, and Perplexity® were asked to present the answers of the 100 questions most frequently asked by patients about palliative care.

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