Objective
To create a model for prediction of success of uterine‐preserving procedures in women with placenta accreta spectrum (PAS).
Methods
PAS‐ID is a multicenter study that included 11 centers from 9 countries. Women with PAS, who were managed between January 1, 2010 and December 31, 2019, were retrospectively included. Data were split into model development and validation cohorts, and a prediction model was created using logistic regression. Main outcome was success of uterine preservation.
Results
Out of 797 women with PAS, 587 were eligible. Uterus‐preserving procedures were successful in 469 patients (79.9%). Number of previous cesarean sections (CS) was inversely associated with management success (adjusted odds ratio [aOR] 0.02, 95% confidence interval [CI] 0.001–3.63 with five previous CS). Other variables were complete placental invasion (aOR 0.14, 95% CI 0.05–0.43), type of CS incision (aOR 0.04, 95% CI 0.01–0.25 for classical incision), compression sutures (aOR 2.48, 95% CI 1.00–6.16), accreta type (aOR 3.76, 95% CI 1.13–12.53), incising away from placenta (aOR 5.09, 95% CI 1.52–16.97), and uterine resection (aOR 102.57, 95% CI 3.97–2652.74).
Conclusion
The present study provides a prediction model for success of uterine preservation, which may assist preoperative and intraoperative decisions, and promote incorporation of uterine preservation procedures in comprehensive PAS protocols.
Impaired wound healing is one of the most critical complications associated with diabetes mellitus. Infections and foot ulcers are major causes of morbidity for diabetic patients. The current treatment of diabetic foot ulcers, commonly used antibiotics, is associated with the development of bacterial resistance. Hence, novel and more effective natural therapeutic antibacterial agents are urgently needed and should be developed against the pathogenic bacteria inhabiting diabetic wounds. Therefore, the current study aimed to investigate the impact of fig latex on pathogenic bacteria and its ability to promote the healing process of diabetic wounds. The pathogenic bacteria were isolated from patients with diabetic foot ulcers admitted to Assiut University Hospital. Fig latex was collected from trees in the Assiut region, and its chemical composition was analyzed using GC‒MS. The antibacterial efficacy of fig latex was assessed on the isolated bacteria. An in vivo study to investigate the effect of fig latex on diabetic wound healing was performed using three mouse groups: nondiabetic control mice, diabetic mice and diabetic mice treated with fig latex. The influence of fig latex on the expression levels of β-defensin-1, PECAM-1, CCL2 and ZO-1 and collagen formation was investigated. The GC‒MS analysis demonstrated the presence of triterpenoids, comprising more than 90% of the total latex content. Furthermore, using a streptozotocin-induced diabetic mouse model, topical treatment of diabetic wound tissues with fig latex was shown to accelerate and improve wound closure by increasing the expression levels of β-defensin-1, collagen, and PECAM-1 compared to untreated diabetic wounds. Additionally, fig latex decreased the expression levels of ZO-1 and CCL2.
Indoor object detection is a fundamental activity for the development of applications of mobility-assistive technology for visually impaired people (VIP). The challenge of seeing interior objects in a real indoor environment is a challenging one since there are numerous complicated issues that need to be taken into consideration, such as the complexity of the background, occlusions, and viewpoint shifts. Electronic travel aids that are composed of the necessary sensors may assist VIPs with their navigation. The sensors have the ability to detect any obstacles, regardless of whether they are static or dynamic, and offer information on the context of an interior scene. The characteristics of an interior scene are not very clear and are subject to a great deal of variation. Recent years have seen the emergence of methods for dealing with issues of this kind, some of which include the use of neural networks, probabilistic methods, and fuzzy logic. This study describes a method for detecting indoor objects using a rotational ultrasonic array and neutrosophic logic. A neutrosophic set has been seen as the next evolution of the fuzzy set because of its indeterminate membership value, which is absent from conventional fuzzy sets. The suggested method is constructed to reflect the position of the walls (obstacle distance) and to direct the VIP to move freely (ahead, to the right, or to the left) depending on the degree of truthiness, the degree of indeterminacy, and the degree of falsity for the reflected distance. The results of the experiments show that the suggested indoor object detecting system has good performance, as its accuracy rate (a mean average precision) is 97.2 ± 1%.
Diabetic wound infection is the major risk caused by bacteria. Not all bacteria detected in the diabetic wound considered as infection. The main criteria to term and considering the infection is not only to find these bacteria have the ability to colonize the wound [1], but also detect an immune response as a reaction to this bacteria wound
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