Publications by authors named "Albina Zubayraeva"

Background: Mid-rectal cancer treatment traditionally involves conventional laparoscopic-assisted resection (CLAR). This study aimed to assess the clinical and therapeutic advantages of Natural Orifice Specimen Extraction Surgery (NOSES) over CLAR.

Aims: To compare the clinical outcomes, intraoperative metrics, postoperative recovery, complications, and long-term prognosis between NOSES and CLAR groups.

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Objectives: Radical surgery for sigmoid colon cancer is commonly performed with complete mesocolic excision (CME) and apical lymph node dissection, reached by central vascular ligation (CVL) of the inferior mesenteric artery (IMA) and associated extended left colon resection. However, IMA branches can be ligated selectively according to tumor location with D3 lymph node dissection (LND), economic segmental colon resection and tumorspecific mesocolon excision (TSME) if IMA is skeletonized. This study aimed to compare left hemicolectomy with CME and CVL and segmental colon resection with selective vascular ligation (SVL) and D3 LND.

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Article Synopsis
  • The study developed an AI-based predictive length of stay (LOS) score specifically for patients with advanced high-grade serous ovarian cancer following surgery, aiming to improve hospital care efficiency.
  • Machine learning techniques, including artificial neural networks, were applied alongside logistic regression to predict LOS outcomes, yielding high accuracy rates between 70-98% for different prediction scenarios.
  • The research identified key factors influencing LOS, such as surgical complexity and postoperative complications, and showcased a user-friendly interface for clinicians to access these insights, ultimately aiding in the analysis of factors prolonging hospital stays.
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Achieving complete surgical cytoreduction in advanced stage high grade serous ovarian cancer (HGSOC) patients warrants an availability of Critical Care Unit (CCU) beds. Machine Learning (ML) could be helpful in monitoring CCU admissions to improve standards of care. We aimed to improve the accuracy of predicting CCU admission in HGSOC patients by ML algorithms and developed an ML-based predictive score.

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Subtotal and extended left colectomies with ileocecal junction preservation represent preferable alternatives in cases of massive involvement of the colon in the pathological process. However, these approaches might be challenging in terms of reconstructive steps. Antiperistaltic cecorectal anastomosis is one of the possible techniques.

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