Assessment of Renal Fibrosis in Patients With Chronic Kidney Disease Using Shear Wave Elastography and Clinical Features: A Random Forest Approach

Role of shearing wave elastography in detecting early diabetic nephropathy

BACKGROUND

Diabetes mellitus is one of the systemic diseases affecting the kidneys that eventually develop end-stage kidney disease. Shear wave elastography (SWE) is a reliable and non-invasive ultrasonography test used to determine tissue elasticity. The aim of this study is to detect early diabetic nephropathy by measuring renal stiffness using shear wave elastography (SWE), renal resistivity indices, and laboratory findings in DN patients.

METHODS

Shear wave elastography and color duplex sonography assessments were performed in 60 diabetic nephropathy patients (divided according to eGFR into 3 stages: stage I-II-III diabetic nephropathy with equal groups of 20 patients in each stage) and 20 healthy age-matched control subjects. The SWE-derived mean value of the tissue stiffness, given in kilopascals (kPa), was correlated to patients' clinico-laboratory data (serum creatinine and eGFR) and resistive index.

RESULTS

There is a statistically significant increase in SWE and RI in the diabetic group than control group and a statistically significant increase in SWE (mean) in CKD stage II and III when compared with CKD stage I, SWE can be used to discriminate between diabetic groups and control group at a cutoff level of > 10.5 (kPa), and also, SWE (mean) can be used to discriminate between CKD stage II and III patients at a cutoff level of > 41 (kPa), with 66.7% sensitivity and 64.9% specificity.

CONCLUSION

Shear wave elastography is a sensitive, non-invasive, and specific diagnostic tool for the detection of diabetic nephropathy and differentiation between different stages of DN.

Shear-Wave Elastography Improves Diagnostic Accuracy in Chronic Kidney Disease Compared to Conventional Ultrasound

PURPOSE

Non-invasive tests are increasingly demanded for diagnosing and prognostication of chronic kidney disease (CKD). Shear-wave elastography (SWE), an emerging technique for measuring tissue stiffness, shows promise for distinguishing between individuals with different stages of renal fibrosis. This study aimed to compare the diagnostic accuracy of two-dimensional SWE (2D-SWE) and conventional ultrasound for detecting CKD, employing renal biopsy as the gold standard.

METHODS

From May 2020 to October 2023, this prospective study included 30 healthy volunteers and 169 patients with CKD who had undergone 2D-SWE and conventional ultrasound of both kidneys. Cortical and medullary stiffness, cortical pixel intensity, renal length, parenchymal and cortical thickness, interlobar artery peak systolic velocity, end-diastolic velocity (EDV), and resistive index were measured. The diagnostic accuracy of 2D-SWE and conventional ultrasound was compared using the receiver operating characteristic curve (ROC) and Delong test.

RESULTS

For diagnosing CKD, the area under the ROC (AUC) of cortical stiffness (0.96 [95% CI, 0.93, 0.99]) was significantly higher than that of all conventional ultrasound parameters, including EDV (0.78 [95% CI, 0.71, 0.86]) and cortical thickness (0.74 [95% CI, 0.67, 0.80]). The sensitivity of cortical stiffness (91%) was significantly higher than that of EDV (68%) and cortical thickness (53%). No significant difference was found in the specificity of cortical stiffness (96%) compared to that of EDV (79%) and cortical thickness (100%).

CONCLUSION

Two-dimensional SWE showed higher diagnostic accuracy than that of conventional ultrasound for detecting CKD.

Depressive symptoms and its influencing factors of older people with cataracts in China: a national cross-sectional survey

Background

Depressive symptoms are a common complication in patients with cataracts and may exacerbate cataract symptoms. Therefore, it is important to focus on depressive symptoms and their influencing factors in older people with cataracts. The purpose of this study was to investigate the prevalence rate of depressive symptoms and influencing factors in Chinese older people with cataracts.

Methods

Descriptive analyses were used to report the sociodemographic characteristics, lifestyle, health status, and depressive symptoms of old people with cataracts in China. The chi-square test was used to compare differences between subjects with different demographic characteristics. Binary logistic regression was used to analyze the factors that influenced the depressive symptoms of cataract patients. Meanwhile, a random forest model was developed in this study to rank the importance of the influencing factors.

Results

Three hundred and six (25.27%) of 1,211 cataract patients included in this study suffered from depressive symptoms. Logistic regression analysis suggested that poor economic situation (AOR = 3.162, 95%CI: 1.719-5.817), social participation (AOR = 1.530, 95%CI: 1.053-2.222), having hearing disorder (AOR = 1.445, 95%CI: 1.040-2.008), poor self-reported health status (AOR = 2.646, 95%CI: 1.705-4.106), poor life satisfaction (AOR = 3.586, 95%CI: 1.652-7.784) were risk factors for depressive symptoms in cataract patients and consumption of fresh fruits (AOR = 0.587, 95%CI: 0.369-0.933) was a protective factor for depressive symptoms in cataract patients. The results of the random forest showed that self-reported health status was the most important factor influencing depressive symptoms in cataract patients. The other factors, in order of importance, were life satisfaction, economic situation, fruits, hearing disorder, and social participation.

Conclusion

The results suggested that the development of depressive symptoms in cataract patients was influenced by various factors. Medical staff should monitor these influencing factors more closely when treating and caring for patients with cataracts.

Enhanced interpretable thyroid disease diagnosis by leveraging synthetic oversampling and machine learning models

Thyroid illness encompasses a range of disorders affecting the thyroid gland, leading to either hyperthyroidism or hypothyroidism, which can significantly impact metabolism and overall health. Hypothyroidism can cause a slowdown in bodily processes, leading to symptoms such as fatigue, weight gain, depression, and cold sensitivity. Hyperthyroidism can lead to increased metabolism, causing symptoms like rapid weight loss, anxiety, irritability, and heart palpitations. Prompt diagnosis and appropriate treatment are crucial in managing thyroid disorders and improving patients' quality of life. Thyroid illness affects millions worldwide and can significantly impact their quality of life if left untreated. This research aims to propose an effective artificial intelligence-based approach for the early diagnosis of thyroid illness. An open-access thyroid disease dataset based on 3,772 male and female patient observations is used for this research experiment. This study uses the nominal continuous synthetic minority oversampling technique (SMOTE-NC) for data balancing and a fine-tuned light gradient booster machine (LGBM) technique to diagnose thyroid illness and handle class imbalance problems. The proposed SNL (SMOTE-NC-LGBM) approach outperformed the state-of-the-art approach with high-accuracy performance scores of 0.96. We have also applied advanced machine learning and deep learning methods for comparison to evaluate performance. Hyperparameter optimizations are also conducted to enhance thyroid diagnosis performance. In addition, we have applied the explainable Artificial Intelligence (XAI) mechanism based on Shapley Additive exPlanations (SHAP) to enhance the transparency and interpretability of the proposed method by analyzing the decision-making processes. The proposed research revolutionizes the diagnosis of thyroid disorders efficiently and helps specialties overcome thyroid disorders early.

Kangxianling formula attenuates renal fibrosis by regulating gut microbiota

BACKGROUND

Renal fibrosis (RF) produced adverse effect on kidney function. Recently, intestinal dysbiosis is a key regulator that promotes the formation of renal fibrosis. This study will focus on exploring the protective mechanism of Kangxianling Formula (KXL) on renal fibrosis from the perspective of intestinal flora.

METHODS

Unilateral Ureteral Obstruction (UUO) was used to construct rats' model with RF, and receive KXL formula intervention for 1 week. The renal function indicators were measured. Hematoxylin-eosin (HE), Masson and Sirus red staining were employed to detect the pathological changes of renal tissue in each group. The expression of α-SMA, Col-III, TGF-β, FN, ZO-1, and Occuludin was detected by immunofluorescence and immunohistochemistry. Rat feces samples were collected and analyzed for species' diversity using high-throughput sequencing 16S rRNA.

RESULTS

Rats in UUO groups displayed poor renal function as well as severe RF. The pro-fibrotic protein expression in renal tissues including α-SMA, Col-III, TGF-β and FN was increased in UUO rats, while ZO-1 and Occuludin -1 expression was downregulated in colon tissues. The above changes were attenuated by KXL treatment. 16S rRNA sequencing results revealed that compared with the sham group, the increased abundance of pathogenic bacteria including Acinetobacter, Enterobacter and Proteobacteria and the decreased abundance of beneficial bacteria including Actinobacteriota, Bifidobacteriales, Prevotellaceae, and Lactobacillus were found in UUO group. After the administration of KXL, the growth of potential pathogenic bacteria was reduced and the abundance of beneficial bacteria was enhanced.

CONCLUSION

KXL displays a therapeutical potential in protecting renal function and inhibiting RF, and its mechanism of action may be associated with regulating intestinal microbiota.