Heart failure (HF) is the end-stage of all cardiac diseases, characterized by high prevalence, high mortality, and heavy social and economic burden. Early warning of HF exacerbation is of great value for outpatient management and reducing readmission rates. Currently, remote dynamic monitoring technology, which captures changes in hemodynamic and physiological parameters of HF patients, has become the primary method for early warning and is a hot research topic in clinical studies. This paper systematically reviews the progress in this field, which was categorized into invasive monitoring based on implanted devices, non-invasive monitoring based on wearable devices, and other monitoring technologies based on audio and video. Invasive monitoring primarily involves direct hemodynamic parameters such as left atrial pressure and pulmonary artery pressure, while non-invasive monitoring covers parameters such as thoracic impedance, electrocardiogram, respiration, and activity levels. These parameters exhibit characteristic changes in the early stages of HF exacerbation. Given the clinical heterogeneity of HF patients, multi-source information fusion analysis can significantly improve the prediction accuracy of early warning models. The results of this study suggest that, compared with invasive monitoring, non-invasive monitoring technology, with its advantages of good patient compliance, ease of operation, and cost-effectiveness, combined with AI-driven multimodal data analysis methods, shows significant clinical application potential in establishing an outpatient management system for HF.
Humans ; Heart Failure/physiopathology* ; Monitoring, Physiologic/methods* ; Wearable Electronic Devices ; Remote Sensing Technology ; Early Diagnosis ; Electrocardiography ; Hemodynamics

Lung cancer is a leading cause of cancer-related deaths worldwide, with its high mortality rate primarily attributed to delayed diagnosis. Radiomics, by extracting abundant quantitative features from medical images, offers novel possibilities for early diagnosis and precise treatment of lung cancer. This article reviewed the latest advancements in radiomics for lung cancer management, particularly its integration with artificial intelligence (AI) to optimize diagnostic processes and personalize treatment strategies. Despite existing challenges, such as non-standardized image acquisition parameters and limitations in model reproducibility, the incorporation of AI significantly enhanced the precision and efficiency of image analysis, thereby improving the prediction of disease progression and the formulation of treatment plans. We emphasized the critical importance of standardizing image acquisition parameters and discussed the role of AI in advancing the clinical application of radiomics, alongside future research directions.
Humans ; Lung Neoplasms/diagnosis* ; Artificial Intelligence ; Early Detection of Cancer/methods* ; Precision Medicine ; Image Processing, Computer-Assisted/methods* ; Tomography, X-Ray Computed ; Radiomics

Objective To mine and analyze the routine blood test data of children with allergic rhinitis (AR), identify routine blood parameters related to childhood allergic rhinitis, establish an effective diagnostic model, and evaluate the performance of the model. Methods This study was a retrospective study of clinical cases. The experimental group comprised a total of 1110 children diagnosed with AR at the First Affiliated Hospital of Air Force Medical University during the period from December 12, 2020 to December 12, 2021, while the control group included 1109 children without a history of allergic rhinitis or other allergic diseases who underwent routine physical examinations during the same period. Information such as age, sex and routine blood test results was collected for all subjects. The levels of routine blood test indicators were compared between AR children and healthy children using comprehensive intelligent baseline analysis, with indicators of P≥0.05 excluded; variables were screened by Lasso regression. Binary Logistic regression was used to further evaluate the influence of multiple routine blood indexes on the results. Five kinds of machine model algorithms were used, namely extreme value gradient lift (XGBoost), logistic regression (LR), gradient lift decision tree (LGBMC), Random forest (RF) and adaptive lift algorithm (AdaBoost), to establish the diagnostic models. The receiver operating characteristic (ROC) curve was used to screen the optimal model. The best LightGBM algorithm was used to build an online patient risk assessment tool for clinical application. Results Statistically significant differences were observed between the AR group and the control group in the following routine blood test indicators: mean cellular hemoglobin concentration (MCHC), hemoglobin (HGB), absolute value of basophils (BASO), absolute value of eosinophils (EOS), large platelet ratio (P-LCR), mean platelet volume (MPV), platelet distribution width (PDW), platelet count (PLT), absolute values of leukocyte neutrophil (W-LCC), leukocyte monocyte (W-MCC), leukocyte lymphocyte (W-SCC), and age. Lasso regression identified these variables as important predictors, and binary Logistic regression further analyzed the significant influence of these variables on the results. The optimal machine learning algorithm LightGBM was used to establish a multi-index joint detection model. The model showed robust prediction performance in the training set, with AUC values of 0.8512 and 0.8103 in the internal validation set. Conclusion The identified routine blood parameters can be used as potential biomarkers for early diagnosis and risk assessment of AR, which can improve the accuracy and efficiency of diagnosis. The established model provides scientific basis for more accurate diagnostic tools and personalized prevention strategies. Future studies should prospectively validate these findings and explore their applicability in other related diseases.
Humans ; Male ; Female ; Rhinitis, Allergic/blood* ; Child ; Biomarkers/blood* ; Retrospective Studies ; Early Diagnosis ; Child, Preschool ; ROC Curve ; Logistic Models ; Hematologic Tests ; Algorithms ; Adolescent ; Machine Learning

Achondroplasia (ACH) is a common skeletal dysplasia in children, primarily caused by mutations in the fibroblast growth factor receptor 3 (FGFR3) gene. These mutations disrupt the process of endochondral ossification in different types of bones, including long bones of the limbs and vertebrae. Children with ACH typically present with short stature and may experience severe multi-system complications. The diagnosis of ACH is based on typical clinical manifestations, imaging features, and genetic testing results. Treatment options mainly include pharmacological interventions and surgical procedures aimed at improving height, as well as symptomatic management for associated complications. This article discusses both prenatal and clinical diagnostic approaches for ACH, as well as treatment strategies focused on enhancing height, aiming to deepen the understanding of this condition.
Humans ; Achondroplasia/therapy* ; Child ; Body Height ; Early Diagnosis ; Receptor, Fibroblast Growth Factor, Type 3/genetics*

OBJECTIVES: To investigate the clinical and immunological features of children with primary immune thrombocytopenia (pITP) or connective tissue disease (CTD) with thrombocytopenia as the initial manifestation at initial diagnosis, and to provide a basis for early differentiation. METHODS: A retrospective study was performed on 236 children with pITP (pITP group) or CTD with thrombocytopenia as the initial manifestation (CTD-TP group) who were admitted from January 2019 to August 2024. Clinical and immunological indicators were compared between the two groups to identify potential influencing factors for early differentiation and their discriminative validity. RESULTS: Compared with the pITP group, the CTD-TP group had a significantly older age of onset and significantly lower leukocyte count, eosinophil count, lymphocyte count, and complement C4 level (P<0.05), as well as significantly higher levels of C-reactive protein, IgE, and IgM (P<0.05). The logistic regression analysis showed that age, IgE, IgM, total B cells, and complement C4 were predictive factors for early differentiation between pITP and CTD-TP (P<0.05). The receiver operating characteristic curve analysis showed that a combination of these five factors had a good discriminative validity, with an area under the curve of 0.944. The correlation analysis showed a negative correlation between IgG and platelet count in the pITP group (r_s=-0.363, P<0.05) and a positive correlation between NK cells and platelet count in the CTD-TP group (r_s=0.713, P<0.05). CONCLUSIONS There is heterogeneity in the clinical and immunological indicators between children with pITP and CTD-TP at initial diagnosis, and these research findings can help with the early differentiation between the two diseases.
Purpura, Thrombocytopenic, Idiopathic/immunology* ; Diagnosis, Differential ; Connective Tissue Diseases/immunology* ; Retrospective Studies ; Early Diagnosis ; Age of Onset ; Leukocyte Count ; Complement C4/immunology* ; C-Reactive Protein/immunology* ; Immunoglobulin E/immunology* ; Immunoglobulin M/immunology* ; Humans ; Male ; Female ; Infant ; Child, Preschool ; Child ; Adolescent ; Biomarkers/blood*

The prevalence of type 1 diabetes (T1DM) is increasing annually, and its complications seriously impair the quality of life of affected children. Early screening for T1DM helps reduce the occurrence of diabetic ketoacidosis, protect β-cell function, and delay disease onset in high-risk populations. This article summarizes current domestic and international screening technologies for T1DM. Screening methods remain centered on detection of diabetes-related antibodies and glycometabolic markers, while factors related to disease pathogenesis hold promise as sensitive screening markers. Expanding T1DM screening in China is expected to improve early diagnosis and treatment.
Diabetes Mellitus, Type 1/diagnosis* ; Humans ; Early Diagnosis ; Autoantibodies/blood* ; Mass Screening/methods*

OBJECTIVE: To study the correlation between miR-122 and early HBV infection and analyze its application value in early infection of voluntary blood donors. METHODS: A total of 150 samples from voluntary blood donors in Fujian Blood Center from May 2021 to July 2022 were collected and divided into group N (normal group), group E (ELISA single positive group), and group D (both ELISA and nucleic acid positive group), and the general information of the three groups of blood donors was collected. Total RNA was extracted from the three groups of samples, and the expression level of miR-122 was detected by qRT-PCR. The expression differences of miR-122 among the three groups of samples were statistically analyzed, and the correlation between the expression level of miR-122 in group D and its HBV DNA copy number was analyzed. The miRNA database was used to predict the potential target genes of miRNA and perform bioinformatics analysis. RESULTS: There was no statistical difference in gender, education level, and occupation distribution among the three groups, but the age distribution and number of blood donations among different groups were statistically significant. Compared with group N, the relative expression levels of miR-122 in the plasma of group E and group D were significantly downregulated (P < 0.05); the relative expression level of miR-122 in group D was more significantly downregulated than that in group E (P < 0.001). Pearson correlation analysis showed that the expression level of miR-122 in group D was negatively correlated with the HBV-DNA copy number (R ²=-0.804,P < 0.01). Two potential target genes were screened using the miRNA database: ALDOA(aldolase A) and PKM (pyruvate kinase). GO analysis results showed that the potential target genes of miRNA mainly involved in biological processes including cell homeostasis and regulation of transcriptional processes. CONCLUSION Downregulation of miR-122 expression is closely related to early HBV infection and replication activity.
Humans ; MicroRNAs ; Blood Donors ; Hepatitis B/diagnosis* ; Hepatitis B virus ; DNA, Viral/blood* ; Male ; Female ; Early Diagnosis ; Adult

OBJECTIVE: To construct an integrated management model for early screening and diagnosis of PCa based on the Innovative Care for Chronic Conditions Framework (ICCC) and the 1+1 contract-based tiered diagnosis and treatment system (TDTS) in China. METHODS: Based on the 1+1 contract-based TDTS platform, we conducted PCa screening for the male residents aged 60 years and above during health check-ups in Pujin Community Health Center from January 1, 2023 to December 31, 2023. For those with abnormal total prostate-specific antigen (tPSA) ≥ 4 μg/L, we promptly referred them to higher-level hospitals for further diagnosis and treatment via the two-way referral green channel platform and information sharing service using the 1+1 contract model. We further analyzed the relevant data on screening and diagnosis. RESULTS: A total of 4 080 males aged 71.39±5.059 years received PCa screening from January to December 2023. PSA screening was performed in 43.96% of the male residents, revealing 654 cases of PSA abnormality, with a PSA positivity rate of 16.03%, which was higher than that found in the previous large-scale PCa screenings in other regions of China. Among the males with PSA abnormality, 292 (44.65%) expressed their willingness for medical referral, while the others did not seek further medical attention for reasons of being asymptomatic, low awareness of the disease, no accompany for medical visits, and concerns about further costs of diagnosis and treatment. Prostate biopsy was recommended to 154 cases after further examinations, which was accepted by 92 (59.74%). Fifty-eight cases were diagnosed with Pa, and thedetection rate reached 63.04%. CONCLUSION The integrated management model for PSA examination-based early screening and diagnosis of PCa using the 1+1 contract-based TDTS platform is plays a significant role in enhancing people's awareness and knowledge of PCa and improving the early detection rate of the malignancy.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Early Detection of Cancer ; Prostate-Specific Antigen/blood* ; Aged ; China ; Mass Screening ; Middle Aged ; Chronic Disease

Prostate cancer is a common tumor of the male genitourinary system, with its incidence continuously increasing. Early accurate diagnosis is crucial for treatment and prognosis. PSA and MRI are important methods for screening and diagnosis of prostate cancer. However, there is still controversy over whether patients with PSA levels between 4-10 μg/L and PI-RADS score of 3 need to undergo prostate biopsy. Radiomics technology provides a new approach for the early and accurate diagnosis of prostate cancer by mining and analyzing medical image information in a high throughput, which helps to reduce unnecessary biopsies. This article reviews the research progress of MRI radiomics in the screening of prostate cancer in the "gray zone" of PSA and PI-RADS score of 3, aiming to improve diagnostic accuracy and provide references for future research in the field of radiomics.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Prostate-Specific Antigen/blood* ; Magnetic Resonance Imaging ; Early Detection of Cancer ; Biopsy ; Prostate/pathology*

OBJECTIVE: To explore the role of prostate health index (PHI) and its derivatives for early screening in patients with PI-RADS score 3 and prostate-specific antigen (PSA) levels of 4－20 μg/L. METHODS: Clinical data of 203 patients with a score of 3 on the PI-RADS v2.1 scoring system who underwent ultrasound-guided transperineal prostate aspiration biopsy from April 2021 to April 2024 from Provincial Hospital of Shandong First Medical University, Qilu Hospital of Shandong University and Weifang People's Hospital were collected. Patients who met the inclusion criteria were divided into prostate cancer (PCa) group (62 cases) and benign prostatic hyperplasia (BPH) group (141 cases). Serum total prostate-specific antigen (tPSA), serum free prostate-specific antigen (fPSA), and PSA isoform 2 (p2PSA) were routinely detected after admission. And prostate-specific antigen density (PSAD), prostate health index (PHI) and prostate health index density (PHID) were calculated with the basic personal information being collected. The efficacy of each parameter in early screening of patients with PI-RADS score of 3 and PSA level of 4－20 μg/L was assessed using ROC curve approach. RESULTS: There was no statistical difference in tPSA, fPSA and fPSA/tPSA between the two groups (P>0.05). There was a statistical difference in p2PSA, PSAD, PHI, PHID and age between the two groups (P<0.05). PHI (AUC=0.783 7, 95% CI: 0.711 3－0.856 1) and PHID (AUC=0.782 3, 95% CI: 0.708 3－0.856 4) showed a good predictive ability in the early screening of prostate cancer. In the clinically significant prostate cancer (csPCa) group, the ROC curve areas of PHI and PHID were 0.823 0 and 0.788 5, respectively, which showed better predictive efficacy of prediction of csPCa. The ROC curves of the combined diagnostic indexes were plotted on the basis of the independent ROC curves, and the area under the curve of PHI combined with age, p2PSA and PHID (AUC=0.843 6) was the largest and had the best predictive ability among all the combined diagnostic indexes. CONCLUSION In patients with PI-RADS score 3 and PSA level between 4 and 20 μg/L, PHI and its derivatives (PHI and PHID) provide a new way for early screening of prostate cancer compared with the traditional index tPSA, which has a high value of application in reducing the over-penetration.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Prostate-Specific Antigen/blood* ; Prostatic Hyperplasia/diagnosis* ; Prostate/pathology* ; Early Detection of Cancer ; ROC Curve ; Middle Aged ; Aged