Clinical Laboratory Indicators Research Articles

Reduced heart rate variability is associated with altered clinical laboratory profile in people living with HIV

BackgroundWe compared heart rate variability (HRV) indices between people living with HIV (PLWH) and HIV-negative individuals to ascertain the independent association between HIV infection and reduced HRV, and further investigated whether distinct clinical laboratory profiles exist between PLWH with and without reduced HRV. MethodsThis cross-sectional analysis included 304 PLWH and 147 HIV-negative individuals with comparable age and sex. Thirty-two routine clinical laboratory indices (including hematology and biochemistry) closest to the survey were extracted from the Electronic Medical Record System. HRV indices were divided into two categories: low (lowest quartile, Q1) and moderate-to-high (combined, Q2‒Q4). ResultsThe time domain indices, ln(SDNN), ln(RMSSD), and ln(PNN50), as well as the frequency domain indices, ln(HF), ln(LF), and ln(VLF), were all significantly reduced in PLWH versus HIV-negative individuals (all p < 0.05). These associations remained for ln(SDNN), ln(PNN50), ln(HF) and ln(LF) even after adjusting for potential confounders in multivariable models. PLWH with low HRV indices exhibited distinct clinical laboratory profiles that were characterized by an elevation in fasting plasma glucose, white blood cell count, neutrophil count, neutrophil%, and a reduction in albumin, total protein, urine creatinine, lymphocyte%, red blood cell count (RBC) and nadir CD4 count. The final stepwise logistic regression models for low SDNN included older age, decreased total cholesterol levels, elevated neutrophil count, and the use of antidiabetic medications, whereas the final model for low LF included older age, reduced RBC and the use of antidiabetic medications. ConclusionPLWH exhibit impaired parasympathetic activity, as evidenced by reduced SDNN, PNN50, LF and HF. Furthermore, PLWH who have reduced HRV indices exhibits distinct clinical laboratory profiles that are related to systematic inflammatory response and diabetes.

Original Moxonidine and Generics: Where is the Edge of Difference?

To compare the efficacy of adding original moxonidine and its generics to previous ineffective antihypertensive therapy in patients with poorly controlled arterial hypertension (AH). This observational prospective non-randomized study included 120 patients with poorly controlled blood pressure on the previous antihypertensive therapy. All patients underwent clinical evaluation, including anthropometric and laboratory indexes, and 24-hour blood pressure monitoring (24-h BPM) at baseline and after 12 weeks of observation. Office systolic and diastolic blood pressure (SBP and DBP) and heart rate (HR) were recorded after 4 and 12 weeks of treatment. During the observation period, 4 equal groups were formed: group 1, Physiotens was added to the treatment; group 2, Moxonitex; group 3, Moxonidine SZ; and group 4, Moxonidine Canon. Statistical analysis was performed with the StatTech v.4.2.7 software (© OOO StatTech, Russia). After 4 weeks of therapy, the BP target was achieved significantly more frequently in group 1 (63% of patients) compared to groups 2 (36.7% of patients), 3 (16.7% of patients), and 4 (16.7% of patients) (p&lt;0.05). At 12 weeks, office SBP, DBP, and HR were significantly decreased in all groups, but the decrease was significantly greater in group 1. The therapy was associated with a more pronounced decrease in all studied 24-h BPM parameters in the Physiotens group than in other groups, as well as with a significantly more frequent normalization of the 24-h BP profile, in 66.7% of patients vs. 46.7%, 33.4%, and 23.2% of patients in groups 2, 3, and 4, respectively. The treatment with original moxonidine demonstrated advantages over generic drugs in terms of achieving the BP goal, reducing office BP and HR, and improving 24-h BPM parameters.

A combination model of CT-based radiomics and clinical biomarkers for staging liver fibrosis in the patients with chronic liver disease

A combined model was developed using contrast-enhanced CT-based radiomics features and clinical characteristics to predict liver fibrosis stages in patients with chronic liver disease (CLD). We retrospectively analyzed multiphase CT scans and biopsy-confirmed liver fibrosis. 160 CLD patients were randomly divided into 7:3 training/validation ratio. Clinical laboratory indicators associated with liver fibrosis were identified using Spearman's correlation and multivariate logistic regression correlation. Radiomic features were extracted after segmenting the entire liver from multiphase CT images. Feature dimensionality reduction was performed using RF-RFE, LASSO, and mRMR methods. Six radiomics-based models were developed in the training cohort of 112 patients. Internal validation was conducted on 48 randomly assigned patients. Receptor Operating Characteristic (ROC) curves and confusion matrices were constructed to evaluate model performance. The radiomics model exhibited robust performance, with AUC values of 0.810 to 1.000 for significant fibrosis, advanced fibrosis, and cirrhosis. The integrated clinical-radiomics model had superior diagnostic efficacy in the validation cohort, with AUC values of 0.836 to 0.997. Moreover, these models outperformed established biomarkers such as the aspartate aminotransferase to platelet ratio index (APRI) and the fibrosis 4 score (FIB-4), as well as the gamma glutamyl transpeptidase to platelet ratio (GPR), in predicting the fibrotic stages. The clinical-radiomics model holds considerable promise as a non-invasive diagnostic tool for the assessment and staging of liver fibrosis in the patients with CLD, potentially leading to better patient management and outcomes.

Combined application of Er:YAG laser and low-level laser in non-surgical treatment of periodontitis.

To compare the efficacy of combined treatment of Er:YAG laser (ERL) and low-level laser therapy (LLLT) with single laser applications, and scaling and root planing (SRP) for non-surgical periodontal treatment. In a randomized controlled trial, 25 non-smoking Stage II or Stage III periodontitis patients were recruited. The four intraoral quadrants were randomly assigned to four different treatments: (1) combined application with ERL plus SRP plus LLLT; (2) ERL plus SRP; (3) SRP plus LLLT; and (4) SRP. We assessed periodontal indexes, including probing depth (PD), clinical attachment level (CAL), bleeding index (BI), and plaque index (PLI), along with three cytokines (IL-1β, TNF-α, IL-10) from gingival crevicular fluid and red complex pathogens from subgingival dental plaque at baseline, 3 months, and 6 months. For initial moderate pockets (4mm≤PD≤6mm), quadrants treated with ERL+SRP+LLLT, ERL+SRP, and SRP+LLLT exhibited greater PD improvement compared to the control (SRP) quadrants at the 3-month follow-up (1.25±1.06, 1.23±1.12, 1.00±1.21vs. 0.98±1.21mm) and the 6-month follow-up (1.35±1.06, 1.23±1.17, 1.35±0.98vs. 0.98±1.23mm) (p=0.002). Quadrants treated with ERL+SRP+LLLT and SRP+LLLT showed more CAL gain means than the control quadrants at the 3-month follow-up (0.96±1.42, 0.61±1.39vs. 0.55±1.57mm) and the 6-month follow-up (0.84±1.54, 0.89±1.49vs. 0.48±1.68mm) (p=0.008). For initial deep pockets (PD≥7mm), the ERL+SRP+LLLT quadrants had more PD improvement and CAL gain compared to the control quadrants at follow-up. There were no significant differences in BI, PLI, inflammatory cytokines, and periodontal pathogens among the four groups. The combined application of ERL and LLLT demonstrated potential efficacy in reducing PD, particularly for deep pockets. To compare the therapy effect of combined use of Er:YAG laser (ERL) and low level laser therapy (LLLT) with single laser applications, and traditional periodontal treatment (SRP). A total of 25 nonsmoking patients with periodontitis were involved, and their mouths were divided into four sections, each receiving a different treatment: ERL+SRP+LLLT, ERL+SRP, SRP+LLLT, and SRP. Clinical indexes and laboratory indicators were assessed at baseline, 3 months, and 6 months. After six months, for initial moderate pockets, combined laser group and single laser group showed better improvements than traditional group in reducing the depth of periodontal pockets and increasing attachment levels. But for initial deep pockets, only combined laser group showed better improvement than traditional group. There were no significant differences in bleeding, plaque, inflammation, or harmful bacterial levels among the groups. These findings suggest that the integration of Er:YAG laser and lowlevel laser therapy into standard periodontal treatment may enhance the treatment's benefits in reducing pocket depth, especially for severe conditions.

New triple therapy for the diagnosis of CKD-MBD: a cross-sectional study in Shanxi province

ObjectivesTo seek a triple combination of biomarkers for early diagnosis of chronic kidney disease-mineral and bone metabolic disorder and to explore the diagnostic efficacy of β2-microglobulin, parathyroid hormone and blood...

Application effect of 18F-FDG PET/CT technique in diagnosis and prognosis evaluation of lymphoma

The objective of the study was to research diagnostic and prognostic values of 18F fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) in patients with diffuse large B-cell lymphoma (DLBCL). The diagnostic sensitivity (Sen) of PET/CT (94.75 %) was remarkably higher than 83.56 % of B-US. Age ≥ 65 years old, maximum focal diameter ≥5 cm, clinical stages III-IV, systemic symptoms, increased lactate dehydrogenase level, high modified international prognostic index score, Ecog score ≥1, B-cell lymphoma 2 (Bcl-2) gene, MYC protein expression rate, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were all factors that influenced the recurrence or progression of DLBCL. With higher MTV and TLG, patients would have a greater probability of recurrence or progression. 18F-FDG PET/CT showed a high diagnostic Sen in lymphoma lesions, and could accurately guide clinical staging. Combined with clinical parameters, laboratory indicators, and metabolic parameters, prognostic indicators of patients could be evaluated more accurately.

Analysis of pulmonary microecology and clinical characteristics of patients carrying human herpesvirus.

Aim: To investigate the impact of human herpes virus (HHV) carriage on lung microbiota, and its correlation with clinical features and laboratory indicators in patients.Methods: Retrospective analysis was conducted on 30 outpatient lung infection cases, which were divided into HHV (n=15) and non-HHV (n=15) groups. mNGS detected microbial composition. Microbial diversity and abundance were tested using Shannon and Chao1 indices. Their relationship with laboratory indicators were explored.Results: Significant differences in microbial abundance and distribution were found between two groups (p<0.05). Moreover, HHV group showed negative correlations (p<0.05) between Prevotella, Porphyromonas, Streptococcus and basophil/eosinophil percentages.Conclusion: HHV carriage impacts lung microbiota, emphasizing the need for clinicians to pay attention to HHV reactivation in outpatient lung infection patients.

Establishment of a nomogram model for predicting therapy complications in patients with polycythemia and deep venous thrombosis.

Patients with deep venous thrombosis (DVT) residing at high altitudes can only rely on anticoagulation therapy, missing the optimal window for surgery or thrombolysis. Concurrently, under these conditions, patient outcomes can be easily complicated by high-altitude polycythemia (HAPC), which increases the difficulty of treatment and the risk of recurrent thrombosis. To prevent reaching this point, effective screening and targeted interventions are crucial. Thus, this study analyzes and provides a reference for the clinical prediction of thrombosis recurrence in patients with lower-extremity DVT combined with HAPC. To apply the nomogram model in the evaluation of complications in patients with HAPC and DVT who underwent anticoagulation therapy. A total of 123 patients with HAPC complicated by lower-extremity DVT were followed up for 6-12 months and divided into recurrence and non-recurrence groups according to whether they experienced recurrence of lower-extremity DVT. Clinical data and laboratory indices were compared between the groups to determine the influencing factors of thrombosis recurrence in patients with lower-extremity DVT and HAPC. This study aimed to establish and verify the value of a nomogram model for predicting the risk of thrombus recurrence. Logistic regression analysis showed that age, immobilization during follow-up, medication compliance, compliance with wearing elastic stockings, and peripheral blood D-dimer and fibrin degradation product levels were indepen-dent risk factors for thrombosis recurrence in patients with HAPC complicated by DVT. A Hosmer-Lemeshow goodness-of-fit test demonstrated that the nomogram model established based on the results of multivariate logistic regression analysis was effective in predicting the risk of thrombosis recurrence in patients with lower-extremity DVT complicated by HAPC (χ 2 = 0.873; P > 0.05). The consistency index of the model was 0.802 (95%CI: 0.799-0.997), indicating its good accuracy and discrimination. The column chart model for the personalized prediction of thrombotic recurrence risk has good application value in predicting thrombotic recurrence in patients with lower-limb DVT combined with HAPC after discharge.

Etiology, Clinical Characteristics and Prognosis of Secondary Hemophagocytic Syndrome

To understand the etiology, clinical characteristics and prognosis of secondary hemophagocytic syndrome (HLH), so as to improve the understanding of HLH and reduce the rates of misdiagnosis and missed diagnosis of HLH. A retrospective study was conducted to analyze the cause, clinical characteristics, laboratory findings, therapy and outcomes of 75 adult patients with secondary HLH admitted to our hospital from January 2015 to December 2021. Follow-up continued until the last discharge time. Among 75 patients, infection-related HLH was the most common (45.33%), followed by lymphoma-related HLH (17.33%). Fever was the most common clinical manifestation (97.67%). Laboratory indicators such as NK cell activity (98.31% low or absent), sCD25 (93.22% increased), and serum ferritin (94.44% elevated) had higher sensitivity in diagnosis. By comparing the clinical manifestations and laboratory indicators of HLH patients with different causes, sex, lymph node enlargement and bone marrow morphology were more valuable for the diagnosis of primary disease (all P <0.05). By comparing the treatment and clinical outcomes of HLH patients with different causes, the highest clinical remission rate (83.3%) was achieved in patients with autoimmune disease-related HLH treated with hormone+cyclosporine (P <0.05). The overall 12-month survival rate of all patients was 26.7%, in which the infection-related HLH was the lowest (14.7%) while autoimmune disease-related HLH was the highest (63.6%). The causes and clinical characteristics of adult secondary HLH are varied, with poor prognosis and heterogeneity in disease severity. It is important to identify HLH cause early for diagnosis and needed to further understand HLH.

Machine learning-based prediction model of lower extremity deep vein thrombosis after stroke.

This study aimed to apply machine learning (ML) techniques to develop and validate a risk prediction model for post-stroke lower extremity deep vein thrombosis (DVT) based on patients' limb function, activities of daily living (ADL), clinical laboratory indicators, and DVT preventive measures. We retrospectively analyzed 620 stroke patients. Eight ML models-logistic regression (LR), support vector machine (SVM), random forest (RF), decision tree (DT), neural network (NN), extreme gradient boosting (XGBoost), Bayesian (NB), and K-nearest neighbor (KNN)-were used to build the model. These models were extensively evaluated using ROC curves, AUC, PR curves, PRAUC, accuracy, sensitivity, specificity, and clinical decision curves (DCA). Shapley's additive explanation (SHAP) was used to determine feature importance. Finally, based on the optimal ML algorithm, different functional feature set models were compared with the Padua scale to select the best feature set model. Our results indicated that the RF algorithm demonstrated superior performance in various evaluation metrics, including AUC (0.74/0.73), PRAUC (0.58/0.58), accuracy (0.75/0.77), and sensitivity (0.78/0.80) in both the training set and test set. DCA analysis revealed that the RF model had the highest clinical net benefit. SHAP analysis showed that D-dimer had the most significant influence on DVT, followed by age, Brunnstrom stage (lower limb), prothrombin time (PT), and mobility ability. The RF algorithm can predict post-stroke DVT to guide clinical practice.

Development and Validation of an Interpretable Machine Learning Model for Early Prognosis Prediction in ICU Patients with Malignant Tumors and Hyperkalemia.

This study aims to develop and validate a machine learning (ML) predictive model for assessing mortality in patients with malignant tumors and hyperkalemia (MTH). We extracted data on patients with MTH from the Medical Information Mart for Intensive Care-IV, version 2.2 (MIMIC-IV v2.2) database. The dataset was split into a training set (75%) and a validation set (25%). We used the Least Absolute Shrinkage and Selection Operator (LASSO) regression to identify potential predictors, which included clinical laboratory indicators and vital signs. Pearson correlation analysis tested the correlation between predictors. In-hospital death was the prediction target. The Area Under the Curve (AUC) and accuracy of the training and validation sets of 7 ML algorithms were compared, and the optimal 1 was selected to develop the model. The calibration curve was used to evaluate the prediction accuracy of the model further. SHapley Additive exPlanations (SHAP) and Local Interpretable Model-agnostic Explanations (LIME) enhanced model interpretability. 496 patients with MTH in the Intensive Care Unit (ICU) were included. After screening, 17 clinical features were included in the construction of the ML model, and the Pearson correlation coefficient was <0.8, indicating that the correlation between the clinical features was small. eXtreme Gradient Boosting (XGBoost) outperformed other algorithms, achieving perfect scores in the training set (accuracy: 1.000, AUC: 1.000) and high scores in the validation set (accuracy: 0.734, AUC: 0.733). The calibration curves indicated good predictive calibration of the model. SHAP analysis identified the top 8 predictive factors: urine output, mean heart rate, maximum urea nitrogen, minimum oxygen saturation, minimum mean blood pressure, maximum total bilirubin, mean respiratory rate, and minimum pH. In addition, SHAP and LIME performed in-depth individual case analyses. This study demonstrates the effectiveness of ML methods in predicting mortality risk in ICU patients with MTH. It highlights the importance of predictors like urine output and mean heart rate. SHAP and LIME significantly enhanced the model's interpretability.

From Biomechanical Properties to Morphological Variations: Exploring the Interplay between Aortic Valve Cuspidity and Ascending Aortic Aneurysm.

Background: This research explores the biomechanical and structural characteristics of ascending thoracic aortic aneurysms (ATAAs), focusing on the differences between bicuspid aortic valve aneurysms (BAV-As) and tricuspid aortic valve aneurysms (TAV-As) with non-dilated aortas to identify specific traits of ATAAs. Methods: Clinical characteristics, laboratory indices, and imaging data from 26 adult patients operated on for aneurysms (BAV-A: n = 12; TAV-A: n = 14) and 13 controls were analyzed. Biomechanical parameters (maximal aortic diameter, strain, and stress) and structural analyses (collagen fiber organization, density, fragmentation, adipocyte deposits, and immune cell infiltration) were assessed. Results: Significant differences in biomechanical parameters were observed. Median maximal strain was 40.0% (control), 63.4% (BAV-A), and 45.3% (TAV-A); median maximal stress was 0.59 MPa (control), 0.78 MPa (BAV-A), and 0.48 MPa (TAV-A). BAV-A showed higher tangential modulus and smaller diameter, with substantial collagen fragmentation (p < 0.001 vs. TAV and controls). TAV-A exhibited increased collagen density (p = 0.025), thickening between media and adventitia layers, and disorganized fibers (p = 0.036). BAV-A patients had elevated adipocyte deposits and immune cell infiltration. Conclusions: This study highlights distinct pathological profiles associated with different valve anatomies. BAV-A is characterized by smaller diameters, higher biomechanical stress, and significant collagen deterioration, underscoring the necessity for tailored clinical strategies for effective management of thoracic aortic aneurysm.

Application of metagenomic next-generation sequencing for rapid molecular identification in spinal infection diagnosis.

This study aimed to determine the sensitivity and specificity of metagenomic next-generation sequencing (mNGS) for detecting pathogens in spinal infections and to identify the differences in the diagnostic performance between mNGS and targeted next-generation sequencing (tNGS). A total of 76 consecutive patients with suspected spinal infections who underwent mNGS, culture, and histopathological examinations were retrospectively studied. The final diagnosis of the patient was determined by combining the clinical treatment results, pathological examinations, imaging changes and laboratory indicators. The sensitivity and specificity of mNGS and culture were determined. The difference between the two detection rates was statistically significant (p < 0.001), with mNGS exhibiting a significantly higher detection rate (77.6% versus 18.4%). The average diagnosis time of mNGS was significantly shorter than that of bacterial culture (p < 0.001, 1.65 versus 3.07 days). The sensitivity and accuracy of mNGS were significantly higher than that of the culture group (p < 0.001, 82.3% versus 17.5%; 75% versus 27.6%), whereas the specificity of mNGS (42.9%) was lower than that of the culture group (p > 0.05, 42.9% versus 76.9%). The sensitivity, specificity, accuracy, and positive predictive value (PPV) of pus were higher than those of tissue samples for mNGS, whereas for culture, the sensitivity, specificity, accuracy, and PPV of tissue samples were higher than those of pus. tNGS demonstrated higher sensitivity and accuracy in diagnosing tuberculosis (TB) than mNGS (80% versus 50%; 87.5% versus 68.8%). mNGS for spinal infection demonstrated better diagnostic value in developing an antibiotic regimen earlier, and it is recommended to prioritize pus samples for testing through mNGS. Moreover, tNGS outperformed other methods for diagnosing spinal TB and identifying antibiotic-resistance genes in drug-resistant TB.

Clinical Characteristics and Diagnosis of Nonaccelerating MDS/MPN-U Patient with Granulocyte Dysplasia.

The goal was to improve the clinical cognition of nonaccelerating myelodysplastic/myeloproliferative neoplasms-unclassifiable (MDS/MPN-U) and avoid misdiagnosis or delayed diagnosis. The clinical manifestations, laboratory indicators, histopathology, and therapeutic effects of a patient with nonaccelerating MDS/MPN-U were analyzed and the relevant literature was reviewed. Blood routine: white blood cell 98.48 x 109/L, red blood cell 3.20 x 1012/L, basophils 0.42 x 109/L, eosinophils 1.31 x 109/L, hemoglobin 112 g/L, and platelet 113 x 109/L. Blood smears showed granulocytosis and cells at various stages, polylobular granulocytes also can be seen. Bone marrow images show granulocytosis and dysplastic neutrophils, such as binuclear granulocyte, cyclic nuclear granulocyte, nuclear punch, cytoplasm vacuoles, polylobular granulocytes and so on. Bone marrow biopsy: Bone marrow proliferation tumor, combined with cell morphology and molecular biochemistry is recommended. Gene test showed Jak-2 positive, BCR/ABL and MPL negative. Chromosome examination indicated the presence of 46, XY, add (2)(p25), del (12) (p11.2p13)[16]/46, XY. MDS/MPN-U with granulocytosis and dysplastic neutrophils is rare, mostly in the elderly, and the diagnosis should be made except for other myeloid tumors. Currently, there is no uniform treatment guideline or expert consensus. The treatment options are limited and need to be further confirmed by more studies. MDS/ MPN-U with granulocytosis and dysplastic neutrophils has adverse prognostic factors such as advanced age, increase of bone marrow original cells and related gene mutations. Whether the adverse prognosis is related to specific gene mutations and cytogenetic variation remains to be clarified by more research data.

Sex-specific differences in the clinical profile among psychiatric patients with pulmonary Embolism: a hospital-based retrospective study

BackgroundPulmonary embolism (PE) is a severe and life-threatening complication of venous thromboembolism. However, there is a lack of systematic studies on differences between female and male PE patients. This paper aimed to compare the sex-specific differences in clinical characteristics and laboratory indicators in psychotic patients with PE.MethodsThis retrospective study enrolled psychiatric patients with PE from June 2018 to June 2022 at Shenzhen Kangning Hospital (Shenzhen Mental Health Center). Demographic characteristics, factors associated with PE, and laboratory indices were collected to assess sex-specific differences.ResultsOf the 168 patients, 87 (51.8%) were female and 81 (48.2%) were male, with a mean age of 58 years for females and 46 years for male patients. The male group had higher ratio of hyperprolactinemia, more patients using antipsychotic medications, higher D-dimer levels at PE onset, greater D-dimer difference, and a higher rate of D-dimer elevation than the female group (p < 0.05). Female patients were significantly older, exhibited a higher prevalence of diabetes, and had a greater number of patients taking antidepressants and hypnotics/sedatives than male patients (p < 0.05). Schizophrenia spectrum disorders were more prevalent in male patients, while female patients had a higher incidence of mood disorders (p < 0.05). Among patients aged < 45 years, the male group had higher D-dimer levels at PE onset and greater D-dimer difference (p < 0.05). Among all 112 patients aged ≥ 45 years, male patients were more likely than female patients to have respiratory tract infections, higher D-dimer levels at PE onset, greater D-dimer difference, and a higher rate of D-dimer elevation (p < 0.05). The multiple linear regression analysis indicated that hyperprolactinemia and the use of first-generation antipsychotics (FGAs) were associated with D-dimer levels at PE onset in male patients, while the time of PE onset and protective restraints were associated with D-dimer levels at PE onset in female patients (p < 0.05).ConclusionPE-associated clinical features differ between male and female patients. These differences may imply that the processes and mechanisms of PE onset are sex specific. Male patients are more likely to have respiratory tract infections and higher D-dimer levels at PE onset than female patients. The use of FGAs may be associated with increased D-dimer in male psychiatric patients, while protective restraints may be associated with increased D-dimer in female psychiatric patients.

WNT16 as a promising biomarker for systemic lupus erythematosus and its role in regulating cell proliferation and apoptosis.

To investigate the expression and function of WNT16, a member of the WNT family protein, in the context of systemic lupus erythematosus (SLE). WNT16 expression was assessed in peripheral blood mononuclear cells (PBMCs) from 35 SLE patients and 25 healthy individuals using quantitative polymerase chain reaction. Additionally, serum WNT16 protein levels were quantified via enzyme-linked immunosorbent assay in 162 SLE patients, 96 healthy controls (HC), and disease controls comprised 154 individuals with rheumatoid arthritis (RA) and Sjögren's syndrome (SS). We investigated the associations between WNT16 protein levels and clinical manifestations, laboratory indices, and disease activity in SLE patients. Receiver operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic potential of serum WNT16 for SLE. Furthermore, we performed a knockdown assay on Jeko-1 cells and assessed cell proliferation and apoptosis using Cell Counting Kit-8 and flow cytometry. WNT16 mRNA in SLE patients' PBMCs were significantly lower than those in HC. Furthermore, serum WNT16 in SLE patients were markedly reduced compared to HC, RA, and SS cohorts. ROC curve analysis indicated that plasma WNT16 levels could serve as a potential biomarker for SLE identification (AUC=0.809, SLE vs. HC; AUC=0.760, SLE vs. RA; AUC=0.710, SLE vs. SS). Notably, a weak positive correlation was observed between WNT16 protein and both alkaline phosphatase and lymphocyte percentages. Conversely, a weak negative correlation existed between WNT16 and low-density lipoprotein, neutrophil percentage, and the incidence of pleurisy and disease activity. Additionally, our study confirmed that WNT16 knockdown impairs cell proliferation and enhances apoptosis. Serum WNT16 levels effectively differentiate SLE patients from healthy controls and individuals with other autoimmune disorders. WNT16 serves as a potential biomarker with high sensitivity. The diminished expression of WNT16 in SLE may have a significant role in its pathogenesis through the regulation of cell proliferation and apoptosis.

The risk factors in diabetic foot ulcers and predictive value of prognosis of wound tissue vascular endothelium growth factor

Diabetic foot ulcer (DFU) is a leading cause of high-level amputation in DM patients, with a low wound healing rate and a high incidence of infection. Vascular endothelial growth factor (VEGF) plays an important role in diabetes mellitus (DM) related complications. This study aims to explore the VEGF expression and its predictive value for prognosis in DFU, in order to provide basis for the prevention of DFU related adverse events. We analyzed 502 patients, with 328 in healing group and 174 in non-healing/recurrent group. The general clinical data and laboratory indicators of patients were compared through Spearman correlation analysis, ROC analysis and logistic regression analysis. Finally, the independent risk factors for adverse prognosis in DFU patients were confirmed. Spearman analysis reveals a positive correlation between the DFU healing rate and ABI, VEGF in wound tissue, and positive rate of VEGF expression, and a negative correlation with DM duration, FPG, HbA1c, TC, Scr, BUN, and serum VEGF. Further logistic regression analysis finds that the DM duration, FPG, HbA1c, ABI, serum VEGF, VEGF in wound tissue, and positive rate of VEGF expression are the independent risk factors for adverse prognosis in DFU (p < 0.05). DM duration, FPG, HbA1c, ABI, serum VEGF, VEGF in wound tissue, and positive rate of VEGF expression are the independent risk factors for prognosis in DFU patients. Patients with these risk factors should be screened in time, which is of great significance to prevent DFU related adverse events and improve outcomes.

Development of a grading diagnostic model for schistosomiasis-induced liver fibrosis based on radiomics and clinical laboratory indicators

To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People's Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients'radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients'radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = -5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.

Analysis of Clinical Characteristics and Laboratory Indicators in Patients with Solid Malignant Tumor-Associated Venous Thromboembolism

To analyze the clinical features and laboratory indicators in patients with solid malignant tumor-associated venous thromboembolism (Ta-VTE), and to study the risk factors for Ta-VTE. The hospitalized patients with VTE in Guizhou Provincial People's Hospital from January to December 2020 were enrolled, and they were divided into Ta-VTE group and pure VTE group based on the presence or absence of solid malignant tumor. The differences in clinical data and laboratory indicators between the two groups were analyzed, and the indicators with significant differences were included in logistic regression model to analyze the risk factors of Ta-VTE. A total of 288 patients with VTE were included in this study, including 64 cases in Ta-VTE group and 224 cases in pure VTE group, respectively. There were significant differences in the following indexes between the two groups, including the hospitalization time (14.20±15.29 d vs 10.05±6.90 d, t=3.112, P =0.002), pain (35.94% vs 65.18%, χ2=17.554, P =0.000), recent surgery (75.00% vs 37.50%, χ2=28.196, P =0.000), D-dimer [2.8 (0.92, 7.55) μg/ml vs 5.69 (2.25, 13.91) μg/ml, Z=-2.710, P =0.007], PLR[198.59 (139.54, 312.16) vs 149.76 (114.08, 233.66), Z=-2.924, P =0.003] and TBIL[10.90 (7.63, 15.68) μmol/L vs 12.90 (9.33, 18.28) μmol/L, Z=-2.066, P =0.039]. There was no significant difference in the other indicators (P >0.05). The result of multivariate logistic regression analysis showed that elevated PLR (OR =1.003, 95%CI : 1.000-1.006, P =0.027), recent surgery (OR =4.312, 95%CI : 2.093-8.885, P =0.000) and prolonged hospitalization (OR =1.037, 95%CI : 1.002-1.074, P =0.038）were independent risk factors for Ta-VTE. However, pain (OR =0.274, 95%CI : 0.133-0.564, P =0.000) was a protective factor. Elevated PLR level, recent surgery and prolonged hospital stay are independent risk factors for Ta-VTE patients, and rational use of these indicators is helpful for the clinical diagnosis and treatment of Ta-VTE patients.

Correlation of LP-PLA2 and MMP-9 with the occurrence of early neurological deterioration in patients with acute ischemic stroke.

Early neurological deterioration is a common complication of acute ischemic stroke (AIS), which aggravates symptoms, worsens the condition, and counteracts the benefits of clinical treatment. The aim of this paper was to analyze the correlation between lipoprotein-associated phospholipase A2 (Lp-PLA2), matrix metalloproteinase-9 (MMP-9), and the occurrence of early neurological deterioration (END) in patients with AIS and to explore the clinical prediction of END by the combination of the 2 assays for the clinical prediction of END. A total of 500 AIS patients admitted to our hospital from October 2022 to October 2023 were included as study subjects, and the clinical data of all AIS patients were collected and organized to detect the levels of Lp-PLA2 and MMP-9. Categorized into END and non-END groups according to whether END occurred within 7 days of the onset of AIS, and comparing the clinical baseline data and laboratory index levels of the 2 groups. Logistic regression analysis was performed to determine the independent predictors of END, and the predictive effects of Lp-PLA2 and MMP-9 levels on END were assessed by subject work characteristics (ROC) curves. END occurred in 111 (22.2%) of 500 AIS patients. Multivariate logistic regression analysis showed that diabetes (OR 2.717, 95% CI:1.53-4.81, P < .001), baseline NIHSS score (OR 1.65, 95% CI:1.41-1.94, P < .001), Lp-PLA2 (OR 1.07, 95% CI:1.05-1.09, P < .001) and MMP-9 (OR 1.12, 95% CI:1.09-1.16, P < .001) levels were independent influences on the occurrence of END in patients with AIS after correcting for confounders. ROC curve analysis showed that Lp-PLA2, MMP-9, and a combination of both predicted END with an area under the curve was 0.730, 0.763, and 0.831, respectively, and the area under the curve for the combination of both predicting END was significantly higher than that for any of the inflammatory markers alone (P < .05). Both inflammatory markers, Lp-PLA2 and MMP-9, were independent predictors of the development of END in patients with AIS, and the combination of the two had a higher predictive value.