Rana A. Nablawi, Lama S. Alghamdi, Adnan E. Alshaikh
et al.
BackgroundChronic kidney disease (CKD) is a severe health condition that involves a decline in kidney function, leading to high mortality rates in Saudi Arabia and globally. It often coexists with chronic non-communicable conditions such as hypertension and diabetes. As CKD progresses, patients experience psychological distress, anxiety, and depression, which can negatively impact their health and quality of life. This can lead to reduced treatment adherence, increased mortality, and poor quality of life.ObjectiveThis study sought to assess the prevalence of depression among CKD patients, investigate how quality of life (QoL) and depression vary across CKD stages, and examine the relationship between depression and QoL at different disease stages. This study was conducted at a tertiary care center in Jeddah, Saudi Arabia.MethodsThis cross-sectional research, conducted in Jeddah, Saudi Arabia, from February to May 2024, included 95 CKD patients who met the CKD diagnostic criteria as confirmed by a nephrologist. Pregnant women, dialysis patients, and patients under the age of 18 were excluded from the research. Patients’ contact information was gathered from electronic medical records at King Abdulaziz University Hospital (KAUH), and consent was sought over the phone. Depression was assessed in non-dialysis CKD patients using the Patient Health Questionnaire (PHQ-9), and health-related quality of life (HRQoL) was assessed using the 12-Item Short-Form Health Survey (SF-12) score. Demographic information, previous medical comorbidities, and estimated glomerular filtration rate (eGFR) were also considered. The 2012 Kidney Disease: Improving Global Outcomes (KDIGO) CKD classification was used to classify patients into stages. The research sought to give a full evaluation of patients’ mental and physical health.ResultsA total of 95 patients were included in this study, with a predominance of male gender (58.9%) and those who were aged 60 years and above (50.5%). Most patients were non-smokers (78.9%), and 45.3% were classified as non-obese patients. Comorbidities were widespread among these patients, especially hypertension (82.1%) and diabetes (74.7%). Regarding severity level measured by PHQ-9, the median score was 12.0, 28.4% of the patients were classified as having moderate depression, and the correlation between depression and physical activity (PCS12) and mental health (MCS12) was significantly negative. Multiple linear regression analysis showed that depression was significantly associated with lower physical and mental capacity scores, alongside older age and female gender.ConclusionThis study emphasized the substantial impact of depressive symptoms among obese patients, highlighting the interplay between mental health and chronic physical conditions. Our findings suggest that specific risk factors such as fatigue, chronic illness, including hypertension, and prior mental health history are associated with increased vulnerability to depression. These insights underscore the importance of integrating routine mental health screening and individualized intervention strategies into patient care, particularly for those with comorbid conditions. Future research is needed to further explore the causal relationships and to inform more effective, targeted public health.
Tomoaki Miyazaki, Kei Matsumoto, Shugo Aoki
et al.
Abstract Background Gordonia spp. is a rare infectious disease that has been reported in only 18 cases to date as a cause of peritoneal dialysis-related peritonitis. This is the first report of peritonitis associated with peritoneal dialysis caused by Gordonia otitidis and is a valuable case in which long-term intravenous vancomycin administration was successful. Case presentation A 48-year-old female started peritoneal dialysis at the age of 47 years owing to end-stage renal failure caused by chronic glomerulonephritis. She was hospitalized for peritonitis 3 months after the start of dialysis. We administered cefazolin and ceftazidime intravenously and detected Gordonia otitidis in the drainage fluid after long-term culture for approximately 6 days. Therefore, we switched to vancomycin and treated the patient intravenously for a total of 6 weeks while checking blood levels and trough values in the drainage fluid. The patient had an increase in the number of draining cells for 3 weeks after the start of treatment, but the number of draining cells improved after that, and no relapse was observed 6 months after the end of treatment, suggesting that the treatment was successful. Conclusions When encountering peritoneal dialysis-associated peritonitis for the Gordonia genus, long-term intravenous administration of vancomycin should be considered as one of the treatments.
Sri Varsha Mulakala, G. Neeharika, P. Vinay Kumar
et al.
The recent increase in morbidity is primarily due to chronic diseases including Diabetes, Heart disease, Lung cancer, and brain tumours. The results for patients can be improved, and the financial burden on the healthcare system can be lessened, through the early detection and prevention of certain disorders. In this study, we built a machine-learning model for predicting the existence of numerous diseases utilising datasets from various sources, including Kaggle, Dataworld, and the UCI repository, that are relevant to each of the diseases we intended to predict. Following the acquisition of the datasets, we used feature engineering to extract pertinent features from the information, after which the model was trained on a training set and improved using a validation set. A test set was then used to assess the correctness of the final model. We provide an easy-to-use interface where users may enter the parameters for the selected ailment. Once the right model has been run, it will indicate whether the user has a certain ailment and offer suggestions for how to treat or prevent it.
INTRODUCTION Many pediatric urology conditions affect putatively normal tissues or appear too commonly to be based solely on specific DNA mutations. Understanding epigenetic mechanisms in pediatric urology, therefore, has many implications that can impact cell and tissue responses to settings, such as environmental and hormonal influences on urethral development, uropathogenic infections, obstructive stimuli, all of which originate externally or extracellularly. Indeed, the cell's response to external stimuli is often mediated epigenetically. In this commentary, we highlight work on the critical role that epigenetic machinery, such as DNA methyltransferases (DNMTs), Enhancer of Zeste Polycomb Repressive Complex 2 Subunit (EZH2), and others play in regulating gene expression and cellular functions in three urological contexts. DESIGN Animal and cellular constructs were used to model clinical pediatric uropathology. The hypertrophy, trabeculation, and fibrosis of the chronically obstructed bladder was explored using smooth muscle cell models employing disorganised vs. normal extracellular matrix (ECM), as well as a new animal model of chronic obstructive bladder disease (COBD) which retains its pathologic features even after bladder de-obstruction. Cell models from human and murine hypospadias or genital tubercles (GT) were used to illustrate developmental responses and epigenetic dependency of key developmental genes. Finally, using bladder urothelial and organoid culture systems, we examined activity of epigenetic machinery in response to non uropathogenic vs. uropathogenic E.coli (UPEC). DNMT and EZH2 expression and function were interrogated in these model systems. RESULTS Disordered ECM exerted a principal mitogenic and epigenetic role for on bladder smooth muscle both in vitro and in CODB in vivo. Key genes, e.g., BDNF and KCNB2 were under epigenetic regulation in actively evolving obstruction and COBD, though each condition showed distinct epigenetic responses. In models of hypospadias, estrogen strongly dysregulated WNT and Hox expression, which was normalized by epigenetic inhibition. Finally, DNA methylation machinery in the urothelium showed specific activation when challenged by uropathogenic E.coli. Similarly, UPEC induces hypermethylation and downregulation of the growth suppressor p16INK4A. Moreover, host cells exposed to UPEC produced secreted factors inducing epigenetic responses transmissible from one affected cell to another without ongoing bacterial presence. DISCUSSION Microenvironmental influences altered epigenetic activity in the three described urologic contexts. Considering that many obstructed bladders continue to display abnormal architecture and dysfunction despite relief of obstruction similar to after resection of posterior valves or BPH, the epigenetic mechanisms described highlight novel approaches for understanding the underlying smooth muscle myopathy of this crucial clinical problem. Similarly, there is evidence for an epigenetic basis of xenoestrogen on development of hypospadias, and UTI-induced pan-urothelial alteration of epigenetic marks and propensity for subsequent (recurrent) UTI. The impact of mechanical, hormonal, infectious triggers on genitourinary epigenetic machinery activity invite novel avenues for targeting epigenetic modifications associated with these non-cancer diseases in urology. This includes the use of deactivated CRISPR-based technologies for precise epigenome targeting and editing. Overall, we underscore the importance of understanding epigenetic regulation in pediatric urology for the development of innovative therapeutic and management strategies.
Cécile Trottet, Manuel Schürch, Ahmed Allam
et al.
We propose a deep generative approach using latent temporal processes for modeling and holistically analyzing complex disease trajectories, with a particular focus on Systemic Sclerosis (SSc). We aim to learn temporal latent representations of the underlying generative process that explain the observed patient disease trajectories in an interpretable and comprehensive way. To enhance the interpretability of these latent temporal processes, we develop a semi-supervised approach for disentangling the latent space using established medical knowledge. By combining the generative approach with medical definitions of different characteristics of SSc, we facilitate the discovery of new aspects of the disease. We show that the learned temporal latent processes can be utilized for further data analysis and clinical hypothesis testing, including finding similar patients and clustering SSc patient trajectories into novel sub-types. Moreover, our method enables personalized online monitoring and prediction of multivariate time series with uncertainty quantification.
Speaker anonymization is an effective privacy protection solution that conceals the speaker's identity while preserving the linguistic content and paralinguistic information of the original speech. To establish a fair benchmark and facilitate comparison of speaker anonymization systems, the VoicePrivacy Challenge (VPC) was held in 2020 and 2022, with a new edition planned for 2024. In this paper, we describe our proposed speaker anonymization system for VPC 2024. Our system employs a disentangled neural codec architecture and a serial disentanglement strategy to gradually disentangle the global speaker identity and time-variant linguistic content and paralinguistic information. We introduce multiple distillation methods to disentangle linguistic content, speaker identity, and emotion. These methods include semantic distillation, supervised speaker distillation, and frame-level emotion distillation. Based on these distillations, we anonymize the original speaker identity using a weighted sum of a set of candidate speaker identities and a randomly generated speaker identity. Our system achieves the best trade-off of privacy protection and emotion preservation in VPC 2024.
Aim The aim of this article is to present the method and results of the data quality control system and audit within the Netherlands Heart Registration (NHR) using data of patients treated with percutaneous coronary intervention (PCI) in the Netherlands as an example. Methods The NHR is a Dutch nationwide registry of all cardiac interventions, comprising data from all 71 hospitals, of which 30 are cardiac intervention or heart centres. Each year, within the NHR, data validation and verification is performed by standard quality controls and monitoring visits (audits). For the audit in 2019, a sample of 50–100 medical records of patients treated with PCI in 2016 and 2017 were reviewed in each hospital by an independent auditor. The data received by the NHR were compared with the information in the hospitals’ medical records. In total 12 patient characteristics, 5 intervention variables and 3 outcome variables were screened. The value of a variable was considered discrepant if more than 10% of the medical records reviewed regarding this variable were not consistent with the reported data received by the NHR. Results For all variables together, the consistency was high, 97.6%. All variables, except multivessel disease (9.3% discrepancy in the 2622 medical records reviewed), had an accuracy above 95%. Conclusion The results of the audit of the PCI medical records show that the overall quality of the data is high. For variables such as multivessel disease it is important to improve knowledge of the definitions and to train all those involved in the registration process.
Antonio Franco, Devin Rogers, Savio D. Pandolfo
et al.
ABSTRACT Aim: Renal leiomyoma is a rare benign mesenchymal tumor arising from the smooth muscle cells of the kidney. Renal capsule is its most common location (1). Large tumor may require surgical excision which can be challenging in case of proximity to major vessels (2). Indications of robotic partial nephrectomy (RPN) have exponentially expanded over the past few years (3). We aim to report a case of large renal leiomyoma successfully managed with RPN. Methods: A 59-year-old female patient with BMI 51 presented with chief complaint of abdominal discomfort. The patient underwent a CT scan that revealed a massive circumscribed exophytic complex solid cystic mass of 4.5 × 7.7 × 6.2 cm, arising from the lower pole of right kidney and abutting the inferior vena cava. RENAL score was 11ah (high complexity). Past surgical history included mid-urethral sling, breast reduction, and hysterectomy with salpingectomy. Preoperative creatinine and eGFR were 0.9 (mg/dL) and 77 (mL/min), respectively. A robotic excision of this mass was successfully performed by using Da Vinci Xi platform. Main steps of the procedure are illustrated in the present video. Results: Dissection and isolation of the tumor were carefully performed after identifying key anatomical structures such as the ureter, the IVC and the renal hilum. Intraoperative ultrasound was used to confirm the margins of the mass. The renal artery was clamped and then the tumor was resected/enucleated. Renal parenchyma was re-approximated with a single layer of interrupted CT-1 Vicryl 0 with sliding clip technique. Warm ischemia time was 19 min. Estimated blood loss (EBL) was 250 ml. Operative time was 165 min. No intraoperative complications occurred. No drain was placed. Patient was discharged on postoperative day 2. Post-operative hypotension was managed with fluid bolus. Postoperative creatinine and eGFR were 1,0 (mg/dL) and 69 (mL/min/1.72m2), respectively. Pathology revealed a leiomyoma of genital stromal origin with hyalinization and calcification. Conclusions: To the best of our knowledge, this is the first description of RPN for the management of a large (about 8 cm) renal leiomyoma. Robotic assisted surgery allows to expand the indications of minimally invasive conservative renal surgery whose feasibility becomes even more clinically significant in case of benign masses which can be managed without sacrificing healthy renal parenchyma.
Currently intelligent diagnosis systems lack the ability of continually learning to diagnose new diseases once deployed, under the condition of preserving old disease knowledge. In particular, updating an intelligent diagnosis system with training data of new diseases would cause catastrophic forgetting of old disease knowledge. To address the catastrophic forgetting issue, an Adapter-based Continual Learning framework called ACL is proposed to help effectively learn a set of new diseases at each round (or task) of continual learning, without changing the shared feature extractor. The learnable lightweight task-specific adapter(s) can be flexibly designed (e.g., two convolutional layers) and then added to the pretrained and fixed feature extractor. Together with a specially designed task-specific head which absorbs all previously learned old diseases as a single "out-of-distribution" category, task-specific adapter(s) can help the pretrained feature extractor more effectively extract discriminative features between diseases. In addition, a simple yet effective fine-tuning is applied to collaboratively fine-tune multiple task-specific heads such that outputs from different heads are comparable and consequently the appropriate classifier head can be more accurately selected during model inference. Extensive empirical evaluations on three image datasets demonstrate the superior performance of ACL in continual learning of new diseases. The source code is available at https://github.com/GiantJun/CL_Pytorch.
Haider Sultan, Hafiza Farwa Mahmood, Noor Fatima
et al.
Like other fields of Traditional Medicines, Unani Medicines have been found as an effective medical practice for ages. It is still widely used in the subcontinent, particularly in Pakistan and India. However, Unani Medicines Practitioners are lacking modern IT applications in their everyday clinical practices. An Online Clinical Decision Support System may address this challenge to assist apprentice Unani Medicines practitioners in their diagnostic processes. The proposed system provides a web-based interface to enter the patient's symptoms, which are then automatically analyzed by our system to generate a list of probable diseases. The system allows practitioners to choose the most likely disease and inform patients about the associated treatment options remotely. The system consists of three modules: an Online Clinical Decision Support System, an Artificial Intelligence Inference Engine, and a comprehensive Unani Medicines Database. The system employs advanced AI techniques such as Decision Trees, Deep Learning, and Natural Language Processing. For system development, the project team used a technology stack that includes React, FastAPI, and MySQL. Data and functionality of the application is exposed using APIs for integration and extension with similar domain applications. The novelty of the project is that it addresses the challenge of diagnosing diseases accurately and efficiently in the context of Unani Medicines principles. By leveraging the power of technology, the proposed Clinical Decision Support System has the potential to ease access to healthcare services and information, reduce cost, boost practitioner and patient satisfaction, improve speed and accuracy of the diagnostic process, and provide effective treatments remotely. The application will be useful for Unani Medicines Practitioners, Patients, Government Drug Regulators, Software Developers, and Medical Researchers.
Utsav Mondal, S. Viswanathan, Sreerag Sreenivasan Kodakkattil
Background The study aimed to determine the various indications for percutaneous nephrostomy (PCN) primarily in patients with a urinary tract infection and to determine the various complications arising in these patients due to the procedure. Materials and methods A retrospective study of five-year data based on registers of the Department of Urology was performed. Among 716 patients, 226 inpatient data were obtained, curated, and analyzed. Indications for PCN, the periprocedural complications, the PCN's duration, details of antibiotics, risk factors for UTI, development of acute kidney injury, and renal replacement therapy were recorded. Results Patients were mostly female (53.1%, n=120/226). Malignancy (n=109, carcinoma cervix=68/109) and nephrolithiasis (n=70) contributed to 79.2%. Infections such as pyelonephritis, renal abscess, perinephric abscess, and genitourinary tuberculosis were identified in 47. Infectious diseases were significantly associated with younger age, female gender, diabetes, and prior pyelonephritis. PCN was placed at a median of two days after admission, and bilateral PCN was placed in 36 (15.2%) patients. Hydroureteronephrosis (probably infected) was an indication for PCN in 164/226 patients. In 33 patients with an infectious disease, PCN was performed for an obstructed urinary system. One major and two minor complications gave a rate of 0.06% for patients with infections, which was less than the accepted threshold of 4%. Conclusions We intended to study the utility and problems with placing a PCN catheter in patients with complicated urinary infections. We conclude that PCN is a safe and effective procedure in urinary tract infections with obstructed drainage.
The use of secondary hospital-based clinical data and electronical health records (EHR) represent a cost-efficient alternative to investigate chronic conditions. We present the Clinical Network Big Data and Personalised Health project, which collects EHRs for patients accessing hospitals in Central-Southern Italy, through an integrated digital platform to create a digital hub for the collection, management and analysis of personal, clinical and environmental information for patients, associated with a biobank to perform multi-omic analyses. A total of 12,864 participants (61.7% women, mean age 52.6 ± 17.6 years) signed a written informed consent to allow access to their EHRs. The majority of hospital access was in obstetrics and gynaecology (36.3%), while the main reason for hospitalization was represented by diseases of the circulatory system (21.2%). Participants had a secondary education (63.5%), were mostly retired (25.45%), reported low levels of physical activity (59.6%), had low adherence to the Mediterranean diet and were smokers (30.2%). A large percentage (35.8%) were overweight and the prevalence of hypertension, diabetes and hyperlipidemia was 36.4%, 11.1% and 19.6%, respectively. Blood samples were retrieved for 8686 patients (67.5%). This project is aimed at creating a digital hub for the collection, management and analysis of personal, clinical, diagnostic and environmental information for patients, and is associated with a biobank to perform multi-omic analyses.