Medicina
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Review
Current Updates on Involvement of Artificial Intelligence and Machine Learning in Semen Analysis.
Background and Objectives: Infertility rates and the number of couples undergoing reproductive care have both increased substantially during the last few decades. Semen analysis is a crucial step in both the diagnosis and the treatment of male infertility. The accuracy of semen analysis results remains quite poor despite years of practice and advancements. ⋯ Conclusions: AI and machine learning are becoming increasingly popular in biomedical applications. The examination and selection of sperm by andrologists and embryologists may benefit greatly from using these algorithms. Furthermore, when bigger and more reliable datasets become accessible for training, these algorithms may improve over time.
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Background and Objectives: This study aimed to assess the value of a novel prognostic model, based on clinical variables, comorbidities, and demographic characteristics, to predict long-term prognosis in patients who received mechanical ventilation (MV) for over 14 days and who underwent a tracheostomy during the first 14 days of MV. Materials and Methods: Data were obtained from 278 patients (66.2% male; median age: 71 years) who underwent a tracheostomy within the first 14 days of MV from February 2011 to February 2021. Factors predicting 1-year mortality after the initiation of MV were identified by binary logistic regression analysis. ⋯ Based on the maximum Youden index, the cut-off value for predicting mortality was set at ≥2, with a sensitivity of 67.4% and a specificity of 76.3%. Conclusions: The tracheostomy-ProVent score is a good predictive tool for estimating 1-year mortality in tracheostomized patients undergoing MV for >14 days. This comprehensive model integrates clinical variables and comorbidities, enhancing the precision of long-term prognosis in these patients.
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Background and Objectives: Augmented reality head-mounted display (AR-HMD) is a novel technology that provides surgeons with a real-time CT-guided 3-dimensional recapitulation of a patient's spinal anatomy. In this case series, we explore the use of AR-HMD alongside more traditional robotic assistance in surgical spine trauma cases to determine their effect on operative costs and perioperative outcomes. Materials and Methods: We retrospectively reviewed trauma patients who underwent pedicle screw placement surgery guided by AR-HMD or robotic-assisted platforms at an academic tertiary care center between 1 January 2021 and 31 December 2022. ⋯ No significant difference was found between the two cohorts in any outcome metrics. Conclusions: Although the need to address urgent spinal conditions poses a significant challenge to the implementation of innovative technologies in spine surgery, this study represents an initial effort to show that AR-HMD can yield comparable outcomes to traditional robotic surgical techniques. Moreover, it highlights the potential for AR-HMD to be readily integrated into Level 1 trauma centers without requiring extensive modifications or adjustments.
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Background and Objectives: Skull base reconstruction is a crucial step during transsphenoidal surgery. Sphenoid mucosa is a mucosal membrane located in the sphenoid sinus. Preservation and lateral shifting of sphenoid mucosa as sphenoid mucosal flap (SMF) during the transsphenoidal exposure of the sella may be important for later closure. ⋯ Total or partial SMF resulted in fewer local complications (p = 0.012), such as fat graft necrosis, bone graft necrosis, sinusitis or fungal infection, in contrast to no SMF implementation. Conclusions: SMF seems to be an effective technique for skull base reconstruction after transsphenoidal surgery, as it can reduce the usage of avascular grafts such as fat along with the incidence of local complications, such as fat graft necrosis, bone graft necrosis, sinusitis and fungal infection, or it may improve the sinonasal quality of life by maintaining favorable wound healing through vascular flap and promote the normalization of the sphenoid sinus posterior wall. Further clinical studies evaluating sphenoid mucosal flap preservation and application in combination with other techniques, particularly for higher-grade CSF leaks, are required.
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Background and Objectives: Postoperative bleeding is a significant cause of morbidity and mortality following liver resection. Therefore, it is crucial to minimize bleeding during liver resection and effectively manage it when it occurs. Arista® AH (Becton, Dickinson and Company, Franklin Lakes, NJ, USA) is a microporous polysaccharide hemosphere (MPH), a new plant-derived polysaccharide powder hemostat that can be applied to the entire surgical field. ⋯ Within the subgroup of major resections in non-cirrhotic patients, the Arista® AH group demonstrated significantly better outcomes compared to the control group, showed lower EBL, reduced need for blood transfusions, decreased volume of drain fluid collected within 48 h, earlier removal of drains, and shorter hospital stays. In contrast, for the other subgroups such as minor resection (both non-cirrhotic and cirrhotic) and major resection with cirrhosis, the differences between the Arista® AH and control groups in various parameters like EBL, blood transfusion rates, drain fluid volume, time to drain removal, and duration of hospital stay were not statistically significant. Conclusions: Arista® AH significantly improved intraoperative blood management and postoperative recovery in patients undergoing liver resection, particularly in non-cirrhotic patients who underwent major resection.