RESUMO
Objective: To compare the application effects of tissue-selecting therapy stapler (TST), procedure for prolapse and hemorrhoids (PPH), and Ruiyun procedure for hemorrhoids (RPH) in the treatment of mixed hemorrhoids, specifically focusing on primary outcomes such as recovery time, pain levels, and quality of life. Methods: Based on the presence of mixed hemorrhoids,120 patients were admitted to the general surgery department of the hospital from January 2019 to December 2022 were selected and randomly divided into three groups, with 40 cases in each group. The parameters like VAS, ARP, SAP, and HF-QoL scores were chosen to comprehensively assess pain, anal function, and overall quality of life. Group A was treated with TST, group B was treated with PPH, and group C was treated with RPH. The parameters related to surgical treatment and rehabilitation, pain levels [Visual Analog Scale (VAS)] at different times, preoperative and postoperative anal dynamic function [anal rest pressure (ARP), squeeze anal pressure (SAP), and duration of contraction], anal function and quality of life were compared among the three groups. The incidence rates of complications that occurred within 1 month after surgery and postoperative recurrence rate were calculated. Results: There were significant differences in intraoperative blood loss, surgical time, length of hospital stay, and wound healing time among the three groups (TST, PPH, and RPH) (P < .05). There were statistically significant differences in VAS scores among the three groups (TST, PPH, and RPH) on the 1st and 2nd day after surgery (P < .05). The scores increased in sequence from group C, group A to group B. There was no statistically significant difference among the three groups (TST, PPH, and RPH) in terms of ARP, SAP, and duration of contraction before and after treatment, and Wexner scores at different time points after surgery (P > .05). There were statistically significant differences in HF-QoL scores among the three groups (TST, PPH, and RPH) at 1 month and 3 months after surgery (P < .05). One month after surgery, the HF-QoL score of group C was lower than those of groups A and B (P < .05). Three months after surgery, the HF-QoL scores increased in sequence from group C, group A to group B (P < .05). There were statistically significant differences in the incidence rates of urinary retention and anal stenosis among the three groups (TST, PPH, and RPH) (P < .05). The incidence rates of urinary retention and anal stenosis in group B were much higher than those in group B, group A and group C (P < .05). Conclusion: RPH not only shows superiority in treating mixed hemorrhoids in terms of intraoperative blood loss, surgical time, postoperative pain, and quality of life, but also holds promise for enhancing clinical practices with potentially shorter hospital stays and improved patient outcomes.
RESUMO
Due to the wide range of time scales involved in the ordinary differential equations (ODEs) describing chemical reaction kinetics, multidimensional numerical simulation of chemical reactive flows using detailed combustion mechanisms is computationally expensive. To confront this issue, this article presents an economic data-driven tabulation algorithm for fast combustion chemistry integration. It uses the recurrent neural networks (RNNs) to construct the tabulation from a series of current and past states to the next state, which takes full advantage of RNN in handling long-term dependencies of time series data. The training data are first generated from direct numerical integrations to form an initial state space, which is divided into several subregions by the K-means algorithm. The centroid of each cluster is also determined at the same time. Next, an Elman RNN is constructed in each of these subregions to approximate the expensive direct integration, in which the integration routine obtained from the centroid is regarded as the basis for a storing and retrieving solution to ODEs. Finally, the alpha-shape metrics with principal component analysis (PCA) are used to generate a set of reduced-order geometric constraints that characterize the applicable range of these RNN approximations. For online implementation, geometric constraints are frequently verified to determine which RNN network to be used to approximate the integration routine. The advantage of the proposed algorithm is to use a set of RNNs to replace the expensive direct integration, which allows to reduce both the memory consumption and computational cost. Numerical simulations of a H2/CO-air combustion process are performed to demonstrate the effectiveness of the proposed algorithm compared to the existing ODE solver.
