Rationale of a Cross Sectional Analytic Study on Determinants of Recurrent Preeclampsia at University Clinics of Kinshasa (Democratic Republic of Congo) and at Victor Dupouy Hospital Center (France)

Research Background: Pre-eclampsia is one of main causes of materno-foetal mortality and morbidity worldwide, with a prevalence of 3% - 7%. Although considered a primiparous condition, it can nevertheless recur. Several factors appear to be associated with risk of recurrence of pre-eclampsia, such as the term of delivery of previous pregnancy, severity of disease, the existence of co-morbidities and the inter-genital space. Purpose: The aim of our study will be to analyse and identify in a population of pregnant women with a history of preeclampsia risk factors associated with occurrence of recurrent preeclampsia at University clinics of Kinshasa (Democratic Republic of Congo) and at Victor Dupouy Hospital Center (France). Methods: In this study, pregnant women with an history of preeclampsia who will give birth between November 2018 and October 2024 at University Clinics of Kinshasa (UCK) and Victor Dupouy Hospital Center (VDHC) will be included. This will be a cross-sectional analytical study, data from previous and subsequent pregnancies will be studied. Expected Result: The prevalence of recurrent preeclampsia in the study population will be determined. And we will highlight the factors that will determine the recurrence of preeclampsia by analysing the risk factors. Conclusion: Knowledge of the factors associated with recurrent preeclampsia could be an excellent tool for predicting and preventing the disease.

Recurrent Transient Ischemic Attacks Revealing Cerebral Amyloid Angiopathy: A Comprehensive Case

This case report investigates the manifestation of cerebral amyloid angiopathy (CAA) through recurrent Transient Ischemic Attacks (TIAs) in an 82-year-old patient. Despite initial diagnostic complexities, cerebral angiography-MRI revealed features indicative of CAA. Symptomatic treatment resulted in improvement, but the patient later developed a fatal hematoma. The discussion navigates the intricate therapeutic landscape of repetitive TIAs in the elderly with cardiovascular risk factors, emphasizing the pivotal role of cerebral MRI and meticulous bleeding risk management. The conclusion stresses the importance of incorporating SWI sequences, specifically when suspecting a cardioembolic TIA, as a diagnostic measure to explore and exclude CAA in the differential diagnosis. This case report provides valuable insights into these challenges, highlighting the need to consider CAA in relevant cases.

Recurrent neural network decoding of rotated surface codes based on distributed strategy

Quantum error correction is a crucial technology for realizing quantum computers.These computers achieve faulttolerant quantum computing by detecting and correcting errors using decoding algorithms.Quantum error correction using neural network-based machine learning methods is a promising approach that is adapted to physical systems without the need to build noise models.In this paper,we use a distributed decoding strategy,which effectively alleviates the problem of exponential growth of the training set required for neural networks as the code distance of quantum error-correcting codes increases.Our decoding algorithm is based on renormalization group decoding and recurrent neural network decoder.The recurrent neural network is trained through the ResNet architecture to improve its decoding accuracy.Then we test the decoding performance of our distributed strategy decoder,recurrent neural network decoder,and the classic minimum weight perfect matching(MWPM)decoder for rotated surface codes with different code distances under the circuit noise model,the thresholds of these three decoders are about 0.0052,0.0051,and 0.0049,respectively.Our results demonstrate that the distributed strategy decoder outperforms the other two decoders,achieving approximately a 5%improvement in decoding efficiency compared to the MWPM decoder and approximately a 2%improvement compared to the recurrent neural network decoder.

Recorded recurrent deep reinforcement learning guidance laws for intercepting endoatmospheric maneuvering missiles

This work proposes a recorded recurrent twin delayed deep deterministic(RRTD3)policy gradient algorithm to solve the challenge of constructing guidance laws for intercepting endoatmospheric maneuvering missiles with uncertainties and observation noise.The attack-defense engagement scenario is modeled as a partially observable Markov decision process(POMDP).Given the benefits of recurrent neural networks(RNNs)in processing sequence information,an RNN layer is incorporated into the agent’s policy network to alleviate the bottleneck of traditional deep reinforcement learning methods while dealing with POMDPs.The measurements from the interceptor’s seeker during each guidance cycle are combined into one sequence as the input to the policy network since the detection frequency of an interceptor is usually higher than its guidance frequency.During training,the hidden states of the RNN layer in the policy network are recorded to overcome the partially observable problem that this RNN layer causes inside the agent.The training curves show that the proposed RRTD3 successfully enhances data efficiency,training speed,and training stability.The test results confirm the advantages of the RRTD3-based guidance laws over some conventional guidance laws.

Secrecy Outage Probability Minimization in Wireless-Powered Communications Using an Improved Biogeography-Based Optimization-Inspired Recurrent Neural Network

This paper focuses on wireless-powered communication systems,which are increasingly relevant in the Internet of Things(IoT)due to their ability to extend the operational lifetime of devices with limited energy.The main contribution of the paper is a novel approach to minimize the secrecy outage probability(SOP)in these systems.Minimizing SOP is crucial for maintaining the confidentiality and integrity of data,especially in situations where the transmission of sensitive data is critical.Our proposed method harnesses the power of an improved biogeography-based optimization(IBBO)to effectively train a recurrent neural network(RNN).The proposed IBBO introduces an innovative migration model.The core advantage of IBBO lies in its adeptness at maintaining equilibrium between exploration and exploitation.This is accomplished by integrating tactics such as advancing towards a random habitat,adopting the crossover operator from genetic algorithms(GA),and utilizing the global best(Gbest)operator from particle swarm optimization(PSO)into the IBBO framework.The IBBO demonstrates its efficacy by enabling the RNN to optimize the system parameters,resulting in significant outage probability reduction.Through comprehensive simulations,we showcase the superiority of the IBBO-RNN over existing approaches,highlighting its capability to achieve remarkable gains in SOP minimization.This paper compares nine methods for predicting outage probability in wireless-powered communications.The IBBO-RNN achieved the highest accuracy rate of 98.92%,showing a significant performance improvement.In contrast,the standard RNN recorded lower accuracy rates of 91.27%.The IBBO-RNN maintains lower SOP values across the entire signal-to-noise ratio(SNR)spectrum tested,suggesting that the method is highly effective at optimizing system parameters for improved secrecy even at lower SNRs.

Mapping Network-Coordinated Stacked Gated Recurrent Units for Turbulence Prediction

Accurately predicting fluid forces acting on the sur-face of a structure is crucial in engineering design.However,this task becomes particularly challenging in turbulent flow,due to the complex and irregular changes in the flow field.In this study,we propose a novel deep learning method,named mapping net-work-coordinated stacked gated recurrent units(MSU),for pre-dicting pressure on a circular cylinder from velocity data.Specifi-cally,our coordinated learning strategy is designed to extract the most critical velocity point for prediction,a process that has not been explored before.In our experiments,MSU extracts one point from a velocity field containing 121 points and utilizes this point to accurately predict 100 pressure points on the cylinder.This method significantly reduces the workload of data measure-ment in practical engineering applications.Our experimental results demonstrate that MSU predictions are highly similar to the real turbulent data in both spatio-temporal and individual aspects.Furthermore,the comparison results show that MSU predicts more precise results,even outperforming models that use all velocity field points.Compared with state-of-the-art methods,MSU has an average improvement of more than 45%in various indicators such as root mean square error(RMSE).Through comprehensive and authoritative physical verification,we estab-lished that MSU’s prediction results closely align with pressure field data obtained in real turbulence fields.This confirmation underscores the considerable potential of MSU for practical applications in real engineering scenarios.The code is available at https://github.com/zhangzm0128/MSU.

Increased retinal venule diameter as a prognostic indicator for recurrent cerebrovascular events:a prospective observational study

Microvasculature of the retina is considered an alternative marker of cerebral vascular risk in healthy populations.However,the ability of retinal vasculature changes,specifically focusing on retinal vessel diameter,to predict the recurrence of cerebrovascular events in patients with ischemic stroke has not been determined comprehensively.While previous studies have shown a link between retinal vessel diameter and recurrent cerebrovascular events,they have not incorporated this information into a predictive model.Therefore,this study aimed to investigate the relationship between retinal vessel diameter and subsequent cerebrovascular events in patients with acute ischemic stroke.Additionally,we sought to establish a predictive model by combining retinal veessel diameter with traditional risk factors.We performed a prospective observational study of 141 patients with acute ischemic stroke who were admitted to the First Affiliated Hospital of Jinan University.All of these patients underwent digital retinal imaging within 72 hours of admission and were followed up for 3 years.We found that,after adjusting for related risk factors,patients with acute ischemic stroke with mean arteriolar diameter within 0.5-1.0 disc diameters of the disc margin(MAD_(0.5-1.0DD))of≥74.14μm and mean venular diameter within 0.5-1.0 disc diameters of the disc margin(MVD_(0.5-1.0DD))of≥83.91μm tended to experience recurrent cerebrovascular events.We established three multivariate Cox proportional hazard regression models:model 1 included traditional risk factors,model 2 added MAD_(0.5-1.0DD)to model 1,and model 3 added MVD0.5-1.0DD to model 1.Model 3 had the greatest potential to predict subsequent cerebrovascular events,followed by model 2,and finally model 1.These findings indicate that combining retinal venular or arteriolar diameter with traditional risk factors could improve the prediction of recurrent cerebrovascular events in patients with acute ischemic stroke,and that retinal imaging could be a useful and non-invasive method for identifying high-risk patients who require closer monitoring and more aggressive management.

Embryo Transfer Strategies for Women with Recurrent Implantation Failure During the Frozen-thawed Embryo Transfer Cycles:Sequential Embryo Transfer or Double-blastocyst Transfer?

Objective Both sequential embryo transfer(SeET)and double-blastocyst transfer(DBT)can serve as embryo transfer strategies for women with recurrent implantation failure(RIF).This study aims to compare the effects of SeET and DBT on pregnancy outcomes.Methods Totally,261 frozen-thawed embryo transfer cycles of 243 RIF women were included in this multicenter retrospective analysis.According to different embryo quality and transfer strategies,they were divided into four groups:group A,good-quality SeET(GQ-SeET,n=38 cycles);group B,poor-quality or mixed-quality SeET(PQ/MQ-SeET,n=31 cycles);group C,good-quality DBT(GQ-DBT,n=121 cycles);and group D,poor-quality or mixed-quality DBT(PQ/MQ-DBT,n=71 cycles).The main outcome,clinical pregnancy rate,was compared,and the generalized estimating equation(GEE)model was used to correct potential confounders that might impact pregnancy outcomes.Results GQ-DBT achieved a significantly higher clinical pregnancy rate(aOR 2.588,95%CI 1.267–5.284,P=0.009)and live birth rate(aOR 3.082,95%CI 1.482–6.412,P=0.003)than PQ/MQ-DBT.Similarly,the clinical pregnancy rate was significantly higher in GQ-SeET than in PQ/MQ-SeET(aOR 4.047,95%CI 1.218–13.450,P=0.023).The pregnancy outcomes of GQ-SeET were not significantly different from those of GQ-DBT,and the same results were found between PQ/MQ-SeET and PQ/MQ-DBT.Conclusion SeET relative to DBT did not seem to improve pregnancy outcomes for RIF patients if the embryo quality was comparable between the two groups.Better clinical pregnancy outcomes could be obtained by transferring good-quality embryos,no matter whether in SeET or DBT.Embryo quality plays a more important role in pregnancy outcomes for RIF patients.

Effects of data smoothing and recurrent neural network(RNN)algorithms for real-time forecasting of tunnel boring machine(TBM)performance

Tunnel boring machines(TBMs)have been widely utilised in tunnel construction due to their high efficiency and reliability.Accurately predicting TBM performance can improve project time management,cost control,and risk management.This study aims to use deep learning to develop real-time models for predicting the penetration rate(PR).The models are built using data from the Changsha metro project,and their performances are evaluated using unseen data from the Zhengzhou Metro project.In one-step forecast,the predicted penetration rate follows the trend of the measured penetration rate in both training and testing.The autoregressive integrated moving average(ARIMA)model is compared with the recurrent neural network(RNN)model.The results show that univariate models,which only consider historical penetration rate itself,perform better than multivariate models that take into account multiple geological and operational parameters(GEO and OP).Next,an RNN variant combining time series of penetration rate with the last-step geological and operational parameters is developed,and it performs better than other models.A sensitivity analysis shows that the penetration rate is the most important parameter,while other parameters have a smaller impact on time series forecasting.It is also found that smoothed data are easier to predict with high accuracy.Nevertheless,over-simplified data can lose real characteristics in time series.In conclusion,the RNN variant can accurately predict the next-step penetration rate,and data smoothing is crucial in time series forecasting.This study provides practical guidance for TBM performance forecasting in practical engineering.

A gated recurrent unit model to predict Poisson’s ratio using deep learning

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

Aerial target threat assessment based on gated recurrent unit and self-attention mechanism

Aerial threat assessment is a crucial link in modern air combat, whose result counts a great deal for commanders to make decisions. With the consideration that the existing threat assessment methods have difficulties in dealing with high dimensional time series target data, a threat assessment method based on self-attention mechanism and gated recurrent unit(SAGRU) is proposed. Firstly, a threat feature system including air combat situations and capability features is established. Moreover, a data augmentation process based on fractional Fourier transform(FRFT) is applied to extract more valuable information from time series situation features. Furthermore, aiming to capture key characteristics of battlefield evolution, a bidirectional GRU and SA mechanisms are designed for enhanced features.Subsequently, after the concatenation of the processed air combat situation and capability features, the target threat level will be predicted by fully connected neural layers and the softmax classifier. Finally, in order to validate this model, an air combat dataset generated by a combat simulation system is introduced for model training and testing. The comparison experiments show the proposed model has structural rationality and can perform threat assessment faster and more accurately than the other existing models based on deep learning.

Lymphovenous anastomosis and complex decongestive therapy for severe deformed lymphedema with recurrent infection:A case report

BACKGROUND Lower extremity lymphedema is a common complication following treatment for gynecological malignancies.Its incidence rate can reach up to 70%,affecting~20 million people worldwide.However,specialized treatment centers are scarce,and there is a lack of consensus on treatment approaches.Furthermore,there are even fewer reports on the systematic and effective treatment of severe lymphedema with malformations.Effective management of this condition remains a significant challenge for clinicians.CASE SUMMARY A 40-year-old woman developed bilateral leg swelling 6 years after receiving treatment for endometrial cancer.Since August 2018,she experienced>30 episodes of lymphangitis.Upon presentation,she exhibited bilateral leg swelling and deformation,with four large swellings in the posterior thigh that impeded movement,and pain in the limbs.Skin manifestations included lichenoid lesions and features of deep sclerosis.Radionuclide lymphoscintigraphy confirmed the diagnosis of lower limb lymphedema.After 6 mo of complex decongestive therapy(CDT)and three lymphaticovenous anastomosis(LVA)treatments,the patient lost 49 kg in weight.She also experienced a maximum circumference reduction of 35.2 cm in the left lower limb and 37.5 cm in the right lower limb.The leg pain disappeared,her swelling significantly decreased,and she regained the ability to walk,cycle,and run normally.CONCLUSION The combined application of CDT and LVA therapy demonstrates significant positive effects in the treatment of severe,deformed stage III lymphedema.

Recurrent herpes infection showing a new facial phenotype:A case report

BACKGROUND Facial herpes is a common form of the herpes simplex virus-1 infection and usually presents as vesicles near the mouth,nose,and periocular sites.In contrast,we observed a new facial symptom of herpes on the entire face without vesicles.CASE SUMMARY A 33-year-old woman with a history of varicella infection and shingles since an early age presented with sarcoidosis of the entire face and neuralgia without oral lesions.The patient was prescribed antiviral treatment with valacyclovir and acyclovir cream.One day after drug administration,facial skin lesions and neurological pain improved.Herpes simplex without oral blisters can easily be misdiagnosed as pimples upon visual examination in an outpatient clinic.CONCLUSION As acute herpes simplex is accompanied by neuralgia,prompt diagnosis and prescription are necessary,considering the pathological history and health conditions.

Radiofrequency ablation combined with transcatheter arterial chemoembolization for recurrent liver cancer

BACKGROUND The recurrence rate of liver cancer after surgery is high.Radiofrequency ablation(RFA)combined with transcatheter arterial chemoembolization(TACE)is an effective treatment for liver cancer;however,its efficacy in recurrent liver cancer remains unclear.AIM To investigate the clinical effect of TACE combined with RFA in the treatment of recurrent liver cancer.METHODS Ninety patients with recurrent liver cancer were divided into 2 groups according to treatment plan:Control(RFA alone);and experimental[TACE combined with RFA(TACE+RFA)].The incidence of increased alanine aminotransferase levels,complications,and other indices were compared between the two groups before and after the procedures.RESULTS One month after the procedures,the short-term efficacy rate and Karnofsky Performance Status scores of the experimental group were significantly higher than those of the control group(P<0.05).Alpha-fetoprotein(AFP)and total bilirubin levels were lower than those in the control group(P<0.05);The overall response rate was 82.22%and 66.67%in the experimental and control groups,respectively;The disease control rate was 93.33%and 82.22%in the experimental and control groups,respectively,the differences are statistically significant(P<0.05).And there were no statistical differences in complications between the two groups(P>0.05).CONCLUSION TACE+RFA was effective for the treatment of recurrent liver cancer and significantly reduced AFP levels and improved various indices of liver function.

Diagnosis and management of benign recurrent intrahepatic cholestasis and psychosocial stressors in an adolescent:A case report

BACKGROUND Benign recurrent intrahepatic cholestasis(BRIC)is a rare autosomal recessive disorder,characterized by episodes of intense pruritus,elevated serum levels of alkaline phosphatase and bilirubin,and near-normal-glutamyl transferase.These episodes may persist for weeks to months before spontaneously resolving,with patients typically remaining asymptomatic between occurrences.Diagnosis entails the evaluation of clinical symptoms and targeted genetic testing.Although BRIC is recognized as a benign genetic disorder,the triggers,particularly psychosocial factors,remain poorly understood.CASE SUMMARY An 18-year-old Chinese man presented with recurrent jaundice and pruritus after a cold,which was exacerbated by self-medication involving vitamin B and paracetamol.Clinical and laboratory evaluations revealed elevated levels of bilirubin and liver enzymes,in the absence of viral or autoimmune liver disease.Imaging excluded biliary and pancreatic abnormalities,and liver biopsy demonstrated centrilobular cholestasis,culminating in a BRIC diagnosis confirmed by the identification of a novel ATP8B1 gene mutation.Psychological assessment of the patient unveiled stress attributable to academic and familial pressures,regarded as potential triggers for BRIC.Initial relief was observed with ursodeoxycholic acid and cetirizine,followed by an adjustment of the treatment regimen in response to elevated liver enzymes.The patient's condition significantly improved following a stress-related episode,thanks to a comprehensive management approach that included psychosocial support and medical treatment.CONCLUSION Our research highlights genetic and psychosocial influences on BRIC,emphasizing integrated diagnostic and management strategies.

Populational change of CD4^(+)CD25^(+)Treg cells is responsible for the synergistic effect of the combination of RAMP2 with baicalin in treating recurrent spontaneous abortion mouse models

Background: The absence of a safe and effective therapy for recurrent spontaneous abortion due to a maternofetal failure in immunological tolerance remains an intractable clinical obstacle for surgeons. Recently, traditional Chinese medicine has become a feasible alternative for certain diseases, including recurrent spontaneous abortion. However, because of the complex composition of the traditional Chinese medicine formula, its action mechanism remains unclear. Methods: We selected two isolated active ingredients (RAMP and baicalin) from the traditional Chinese medicine formula and used an abortion-prone CBA/J × DBA/2 model to simulate human RSA and compared the changes in fetal resorption rate, Treg cell percentage, and relevant cytokines before and after combination therapy. In addition, The mechanisms were preliminarily discussed using in vitro differentiation models. Results: In CBA/J × DBA/2 abortion-prone mice, the combination therapy resulted in a lower embryo resorption rate compared to that obtained with individual delivery of either RAMP or baicalin, thereby playing an embryo-protective role through the increase in Treg cells for the maintenance of maternal-fetal immune tolerance. In in vitro primary cell differentiation experiments, the concentration of Treg cells significantly increased from 11% to 17.9% after the combination therapy compared to that of the single administration group. Conclusion: the synergistic effects of RAMP and baicalin were responsible for Treg differentiation. The present study provides a solid basis for improving the applicability of traditional Chinese herbs in the treatment of recurrent spontaneous abortion.

Study on Ecological Change Remote Sensing Monitoring Method Based on Elman Dynamic Recurrent Neural Network

In this paper, Hailin City of Heilongjiang Province, China is taken as the research area. As an important city in Heilongjiang Province, China, the sustainable development of its ecological environment is related to the opening up, economic prosperity and social stability of Northeast China. In this paper, the remote sensing ecological index (RSEI) of Hailin City in recent 20 years was calculated by using Landsat 5/8/9 series satellite images, and the temporal and spatial changes of the ecological environment in Hailin City were further analyzed and the influencing factors were discussed. From 2003 to 2023, the mean value of RSEI in Hailin City decreased and increased, and the ecological environment decreased slightly as a whole. RSEI declined most significantly from 2003 to 2008, and it increased from 2008 to 2013, decreased from 2013 to 2018, and increased from 2018 to 2023 again, with higher RSEI value in the south and lower RSEI value in the northwest. It is suggested to appropriately increase vegetation coverage in the northwest to improve ecological quality. As a result, the predicted value of Elman dynamic recurrent neural network model is consistent with the change trend of the mean value, and the prediction error converges quickly, which can accurately predict the ecological environment quality in the future study area.

A HybridManufacturing ProcessMonitoringMethod Using Stacked Gated Recurrent Unit and Random Forest

This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations.Since real-time production process monitoring is critical in today’s smart manufacturing.The more robust the monitoring model,the more reliable a process is to be under control.In the past,many researchers have developed real-time monitoring methods to detect process shifts early.However,thesemethods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties.In this paper,a robust monitoring model combining Gated Recurrent Unit(GRU)and Random Forest(RF)with Real-Time Contrast(RTC)called GRU-RF-RTC was proposed to detect process shifts rapidly.The effectiveness of the proposed GRU-RF-RTC model is first evaluated using multivariate normal and nonnormal distribution datasets.Then,to prove the applicability of the proposed model in a realmanufacturing setting,the model was evaluated using real-world normal and non-normal problems.The results demonstrate that the proposed GRU-RF-RTC outperforms other methods in detecting process shifts quickly with the lowest average out-of-control run length(ARL1)in all synthesis and real-world problems under normal and non-normal cases.The experiment results on real-world problems highlight the significance of the proposed GRU-RF-RTC model in modern manufacturing process monitoring applications.The result reveals that the proposed method improves the shift detection capability by 42.14%in normal and 43.64%in gamma distribution problems.

Analysis of the Degree of Psychological Distress of Elderly Patients with Recurrent Trigeminal Neuralgia and Its Influencing Factors

Objective:To analyze the degree of psychological distress among elderly patients with recurrent trigeminal neuralgia and its influencing factors.Methods:A single-center cross-sectional study was conducted on 126 elderly patients with recurrent trigeminal neuralgia who visited the Pain Department of our hospital from March 2022 to April 2024.Logistic regression analysis was employed to evaluate the factors influencing psychological distress,based on general patient data,the Distress Thermometer(DT),the Perceived Social Support from Family Scale(PSS-Fa),and the Pitsburgh Sleep Quality Index(PSQI).Results:Among the 126 elderly patients with recurrent trigeminal neuralgia,those with a DT score≥4(72 patients,57.14%)were more prevalent than those with a DT score<4(54 patients,42.86%).The average DT score for all patients was 4.35±1.72.Patients in the DT score≥4 group were older than those in the DT score<4 group(t=4.207,P=0.000),had lower PSS-Fa scores(t=5.925,P=0.000),and had higher PSQI scores(t=17.858,P=0.000).There were no statistically significant differences in gender,marital status,residence area,education level,disease type,or pain location(all P>0.05).Older age and poor sleep quality were identified as independent risk factors for psychological distress in elderly patients with recurrent trigeminal neuralgia(OR=1.258,OR=1.713,both P<0.05),while higher levels of family support were identified as a protective factor(OR=0.581,P=0.025).Conclusion:Elderly patients with recurrent trigeminal neuralgia experience psychological distress,and the degree of severity depends on age,quality of sleep,and level of family support.

Investigation of risk factors in the development of recurrent urethral stricture after internal urethrotomy

BACKGROUND Urethral stricture is a condition that often develops with trauma and results in narrowing of the urethral lumen.Although endoscopic methods are mostly used in its treatment,it has high recurrence rates.Therefore,open urethroplasty is recommended after unsuccessful endoscopic treatments.AIM To investigate the risk factors associated with urethral stricture recurrence.METHODS The data of male patients who underwent internal urethrotomy for urethral stricture between January 2017 and January 2023 were retrospectively analyzed.Demographic data,comorbidities,preoperative haemogram,and biochemical values obtained from peripheral blood and operative data were recorded.Patients were divided into two groups in terms of recurrence development;recurrence and non-recurrence.Initially recorded data were compared between the two groups.RESULTS A total of 303 patients were included in the study.The mean age of the patients was 66.6±13.6 years.The mean duration of recurrence development was 9.63±9.84(min-max:1-39)months in the recurrence group.Recurrence did not occur in non-recurrence group throughout the follow-up period with an average time of 44.15±24.07(min-max:12-84)months.In the comparison of both groups,the presence of diabetes mellitus(DM),hypertension(HT),and multiple comorbidi-ties were significantly higher in the recurrence(+)group(P=0.038,P=0.012,P=0.013).Blood group,postoperative use of non-steroidal anti-inflammatory drugs,preoperative cystostomy,cause of stricture,iatrogenic cause of stricture,location and length of stricture,indwelling urinary cathater size and day of catheter removal did not differ between the two groups.No statistically significant difference was observed between the two groups in terms of age,uroflowmetric maximum flow rate value,hemo-gram parameters,aspartate aminotransferase(AST),alanine aminotransferase(ALT),fasting blood sugar,creati-nine,glomerular filtration rate,neutrophil-lymphocyte ratio,platelet-lymphocyte ratio,lymphocyte-monocyte ratio,monocyte-lymphocyte ratio and AST/ALT ratios.CONCLUSION In patients with urethral stricture recurrence,only the frequency of DM and HT was high,while inflammation marker levels and stricture-related parameters were similar between the groups.