International Journal of General Medicine最新文献

Objective: This study aimed to investigate factors influencing fetal growth restriction (FGR) occurrence and assess the clinical significance of fetal cardiac parameters in FGR prediction.

Methods: Pregnant women with clinically suspected FGR (n=179) and uncomplicated pregnancies (n=53) were included. All had undergone routine obstetric ultrasonography and fetal echocardiography. Umbilical artery flow (UAF) and fetal cardiac parameters (left atrial transverse diameter (LAd), right atrial transverse diameter (RAd), left ventricular transverse diameter (LVd), right ventricular transverse diameter (RVd), foramen ovale width, atrial septum diameter, interventricular septal thickness, left ventricular posterior wall thickness, right ventricular free wall thickness, aortic diameter, pulmonary artery diameter, mitral E velocity, mitral A velocity, tricuspid E velocity, tricuspid A velocity, aortic valve peak flow velocity, and pulmonary valve peak flow velocity) were detected. Follow up was conducted until birth, various fetal clinical parameters were collected: maternal body mass index (BMI), hypertensive disorders complicating pregnancy (HDCP), abnormal umbilical artery flow, placental or umbilical cord anomalies, low amniotic fluid volume, preterm birth, emergency cesarean delivery, maternal height, maternal age, gestational diabetes mellitus (GDM), hypothyroidism, assisted reproductive technology (ART), parity, and neonatal gender. Participants were categorized into confirmed FGR (n=119) and control (n=113) groups based on neonatal birth weight.

Results: Significant differences were observed between groups in maternal BMI, HDCP, abnormal UAF, placental or umbilical cord anomalies, low amniotic fluid volume, preterm birth, and emergency cesarean delivery. FGR was positively related to abnormal UAF, placental or umbilical cord anomalies, preterm birth and emergency cesarean delivery and negatively to maternal BMI (r=-0.276). Compared to the control group, the FGR group exhibited significantly larger RAd, RVd, RA/LA, and RV/LV.

Conclusion: Fetal growth-restricted fetuses have enlarged right heart structures. Fetal cardiac examinations are valuable for early FGR diagnosis, potentially improving neonatal body weight and reducing adverse pregnancy outcomes.

Background: Integrating Traditional Chinese Medicine (TCM) knowledge with modern technology, especially machine learning (ML), has shown immense potential in enhancing TCM diagnostics and treatment. This study aims to systematically review and analyze the trends and developments in ML applications in TCM through a bibliometric analysis.

Methods: Data for this study were sourced from the Web of Science Core Collection. Data were analyzed and visualized using Microsoft Office Excel, Bibliometrix, and VOSviewer.

Results: 474 documents were identified. The analysis revealed a significant increase in research output from 2000 to 2023, with China leading in both the number of publications and research impact. Key research institutions include the Shanghai University of Traditional Chinese Medicine and the China Academy of Chinese Medical Sciences. Major research hotspots identified include ML applications in TCM diagnosis, network pharmacology, and tongue diagnosis. Additionally, chemometrics with ML are highlighted for their roles in quality control and authentication of TCM products.

Conclusion: This study provides a comprehensive overview of ML applications' development trends and research landscape in TCM. The integration of ML has led to significant advancements in TCM diagnostics, personalized medicine, and quality control, paving the way for the modernization and internationalization of TCM practices. Future research should focus on improving model interpretability, fostering international collaborations, and standardized reporting protocols.

Purpose: Artificial intelligence (AI) holds great potential for revolutionizing health care by providing clinicians with data-driven insights that support more accurate and efficient clinical decisions. However, applying AI in clinical settings is often challenging due to the complexity and vastness of medical information. This perspective article explores how AI development methodologies can be adapted to support clinicians in their decision-making processes, emphasizing the importance of a hybrid approach that combines AI capabilities with clinicians' expertise.

Patients and methods: We developed a conceptual framework designed to integrate AI-driven hybrid intelligence into clinical practice to enhance decision-making. This framework focuses on adapting key AI concepts, such as backpropagation, quantization, and avoiding overfitting, to help clinicians better interpret complex medical data and improve diagnosis and treatment planning.

Results: Several AI methodologies were adapted to enhance clinical decision-making. First, backpropagation allows clinicians to refine initial assessments by revisiting them as new data emerges, improving diagnostic accuracy over time. Second, quantization helps break down complex medical problems into manageable components, enabling clinicians to prioritize critical elements of care. Finally, avoiding overfitting encourages clinicians to balance rare diagnoses with more common explanations, reducing the risk of diagnostic errors and unnecessary complexity.

Conclusion: The integration of AI-driven hybrid intelligence has the potential to enhance clinical decision-making. By adapting AI methodologies, clinicians can enhance their ability to analyze data, prioritize treatments, and make more accurate diagnoses while preserving the essential human aspect of health care. This framework highlights the importance of combining AI's strengths with clinicians' expertise for more effective and balanced decision-making in clinical practice. This perspective highlights the value of hybrid intelligence in achieving more balanced, effective, and patient-centered decision-making in health care.

Background: This study aims to evaluate the predictive value of bedside ultrasound evaluation of diaphragmatic dynamics in determining successful extubation outcomes for patients eligible for weaning.

Methods: This prospective observational study was conducted on patients who were mechanically ventilated and ready for weaning during the spontaneous breathing trial (SBT). The diaphragm contraction and motion-related parameters of patients such as end inspiratory diaphragm thickness (DT-insp), end respiratory diaphragm thickness (DT-exp), diaphragm thickening fraction (DTF), diaphragmatic thickening fraction rapid shallow breathing index (DTF-RSBI), diaphragmatic excursion (DE), diaphragmatic excursion rapid shallow breathing index (DE-RSBI) were recorded and the association with failure in ventilatory extubation was analyzed. A receiver operating characteristic (ROC) curve was conducted to analyze the prediction of successful weaning.

Results: Out of 95 patients, 14 (14.74%) died, and 68 (71.58%) were successfully extubated. There were significant differences between the two groups in all parameters except DT-exp. The results indicated that duration of mechanical ventilation (OR = 0.850, 95% CI: 0.770-0.938, P = 0.001), DTF (OR = 1.214, 95% CI: 1.108-1.330, P = 0.000), DTF-RSBI (OR = 0.917, 95% CI: 0.880-0.954, P = 0.000), DE (OR = 127.02, 95% CI: 15.004-1075.291, P = 0.000), DE-RSBI (OR = 0.752, 95% CI: 0.657-0.861, P = 0.000) had predictive value for weaning. DTF and DE had a high sensitivity of 91.18%, 100%, respectively. Whereas, duration of mechanical ventilation, DTF-RSBI, DE-RSBI showed a high specificity of 81.48,85.19%, 81.48%. Considering all the above factors, the sensitivity was 88.24% and the specificity was 88.89%.

Conclusion: Bedside ultrasound assessment of diaphragmatic parameters enables the detection of diaphragmatic dysfunction, thus proving valuable in predicting extubation success and facilitating a favorable weaning outcome.

Purpose: To explore the changing trends in the prevalence and epidemiological characteristics of congenital heart defects (CHDs) in perinatal infants (PIs) in Guangxi, China.

Patients and methods: During 2016 and 2020, the Guangxi Birth Defects Monitoring Network (GXBDMN) monitored a total of 3627108 PIs in this study. The CHDs data for PIs can be obtained from the GXBDMN. The study analyzed the changing trends of total CHDs prevalence and each subtype of CHDs prevalence per year using prevalence-rate ratios (PRR). The correlation between characteristics (such as year, infant gender, maternal age, and quarter) and the prevalence of CHDs was also examined by the PRR.

Results: Between 2016 and 2020, 10817 PIs were diagnosed with CHDs, resulting in an overall CHDs prevalence of 29.82 [95% confidence intervals (CI): 29.26-30.38] per 10000 PIs. CHDs accounted for 24.50% of all types of BDs, making them the most common type of BDs. Atrial septal defect / patent foramen ovale (ASD/PFO), patent ductus arteriosus (PDA), ventricular septal defect (VSD), atrioventricular septal defect (AVSD), persistent left superior vena cava (PLSVC), and tetralogy of Fallot (TOF) were the 6 most common subtypes of CHDs. Together they accounted for 86.24% of all CHDs cases, with a total prevalence of 25.72 (95% CI: 25.20-26.24) per 10000 PIs. The study period saw a significant increase in the prevalence of CHDs (PRR = 1.300, 95% CI: 1.283-1.318), and the maternal age also played a significant role in this increase (PRR = 2.738, 95% CI: 2.428-3.087).

Conclusion: The prevalence of CHDs in Guangxi is rising and has an upward trend with maternal age. ASD/PFO, PDA, VSD, AVSD, PLSVC, and TOF were the top six subtypes of CHDs.

Background: Endoplasmic reticulum stress (ERS) is closely associated with Osteoporosis (OP). In order to explore the role of ERS related genes in OP and its molecular mechanism.

Methods: OP-related transcriptome data were retrieved from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was applied to screen OP-related genes. Differentially expressed ERS-related genes (DE-ERSGs) between OP and controls were identified by overlapping OP-related, differentially expressed genes (DEGs), and ERS-related genes. ERS-related genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to explore their functions. Receiver operating characteristic (ROC) curves assessed the diagnostic value of DE-ERSGs, and comparative toxicogenomics database (CTD) was used to predict targeting agents for key DE-ERSGs. Finally, biomarker expression was verified by real time quantitative polymerase chain reaction (RT-qPCR).

Results: A total of 10 DE-ERSGs were screened in OP patients. GO and KEGG analyses indicated their enrichment in Alcoholic liver disease, Endometrial cancer, and Glycerolipid metabolism. ROC curve analysis revealed that RPN2, FOXO3, ERGIC2, and MYO9A had significant diagnostic value, thus being identified as key DE-ERSGs. Moreover, the key DE-ERSGs-drug interaction network showed that some drugs such as bisphenol A, Cisplatin, Cyclosporine, and Valproic Acid might play roles by targeting key DE-ERSGs in OP. The expression validation analysis of key DE-ERSGs revealed that RPN2, ERGIC2, and MYO9A was significantly expressed in the GSE62402. Ultimately, The blood samples RT-qPCR verification results show that RPN2, ERGIC2, and MYO9A were significantly lower in OP samples compared to normal samples (p < 0.05), whereas there was no difference in the expression levels of FOXO3.

Conclusion: RPN2, FOXO3, ERGIC2 and MYO9A as the biomarkers associated with ERS in OP by bioinformatics analysis, which may provide new biological targets for clinical treatment.

Background: Hemoglobin decrement is a common complication after aneurysmal subarachnoid hemorrhage (aSAH) and is associated with poor outcome. However, the mediating variables on the causal pathway between hemoglobin decrement and poor outcome in aSAH are not clear.

Methods: This is a single-center retrospective observational study containing all consecutive patients with aSAH admitted to our hospital between January 1, 2019, and June 30, 2022. Hemoglobin decrement was defined as the hemoglobin at admission minus the minimum hemoglobin during hospitalization. Calculation of cutoff value using ROC curve Youden index. The main exposure of interest was a hemoglobin decrement greater than the cutoff value. The primary outcome was poor outcome at 3 months (mRS 4-6).

Results: A total of 480 patients with aSAH were included in the study, 414 (71.1%) had a favorable and 66 (28.9%) had a poor outcome at 3 months. The cut-off value for calculating the degree of hemoglobin decrease using the ROC curve was 12.5 g/l. Hemoglobin decrement greater than the cutoff value was significantly associated with pneumonia (OR 3.12; 95% CI 1.78-5.57; p < 0.001), cerebral infarction (OR 3.06; 95% CI 1.80-5.30; p < 0.001), and poor prognosis (OR 2.88; 95% CI 1.44-5.92; p = 0.003) at 3 months. The mediation effect was significant for both pneumonia and cerebral infarction, with the average causal mediation effect (ACME) were 0.04 (95% CI 0.02-0.08; p < 0.05) and 0.05 (95% CI 0.02-0.08; p < 0.001), respectively.

Conclusion: Hemoglobin decrement during hospitalization was significantly associated with poor prognosis after aSAH, and the increased risk of cerebral infarction and pneumonia might mediate this effect. Avoiding hemoglobin decrement greater than 12.5g/l may improve the prognosis of patients with aSAH.

Objective: This study targeted elucidating the intricate correlation of the blood urea nitrogen (BUN)-to-albumin (BUN/Alb) ratio with adverse outcomes (AOs) at 3-month in acute ischemic stroke (AIS) cases within a Korean cohort.

Methods: The cohort involved a comprehensive dataset of 1850 AIS cases from a South Korean hospital, spanning from January 2010 to December 2016. To discern the linear relationship of the BUN/Alb ratio with AOs in AIS cases, utilization of a binary logistic regression model (BLRM) was implemented. Additionally, it was attempted to utilize sophisticated statistical techniques, such as generalized additive models (GAMs) and smooth curve fitting methods, to unravel the nonlinear association of the BUN/Alb ratio with AOs in such patients.

Results: The incidence of AOs was determined to be 28.49%, with the median BUN/Alb ratio being 3.85. After adjusting for a number of covariates, the BLRM disclosed that the linear association of BUN/Alb ratio with the risk of AOs particularly in AIS cases did not achieve statistical significance. However, a noticeable nonlinear relationship emerged, with an inflection point identified at 2.86. To the left of this inflection point, the relationship is not statistically significant. On the right side of the inflection point, there was a remarkable 9.47% rise in the risk of AOs (odds ratio (OR) = 1.09, 95% confidence interval (CI): 1.00, 1.19, P = 0.04).

Conclusion: The outcomes illuminate the complex and nonlinear relationship of the BUN/Alb ratio with 3-month AOs in AIS cases. This study established a robust groundwork for the future research, underscoring the potential clinical utility of monitoring the BUN/Alb ratio to enhance the prognostic assessment and management of AIS cases.

Background: Early neurologic deterioration (END) in acute ischemic stroke could result in significant worsening of clinical prognosis. Neutrophil lymphocyte ratio (NLR) is related to stroke severity and might be a predictor of short-term mortality in acute ischemic stroke. This study investigated the relationship between NLR and END in anterior circulation stroke patients.

Methods: Consecutive patients with first-ever acute ischemic stroke admitted to hospital within 24-hour of symptom onset were analyzed. NLR was calculated according to the Laboratory parameters obtained during the first 24 hours after admission. The rate of the END was recorded during the first 72-hours of admission. Multivariate logistic regression was applied to investigate the relationship between NLR and END.

Results: We included 228 consecutive patients within 24-hours of symptom onset for the final analysis. In total, 64 (28.1%) experienced END during the first 72 hours after admission. Patients with END were more likely to have higher NLR (median NLR 3.8 vs 2.4; p<0.001) compared with those without END. Multivariate logistic regression revealed that NLR>2.65 (OR, 4.019; 95% CI, 1.937-8.337; p<0.001) was an independent predictor of END. Also, patients in high NLR subgroup (NLR>2.65) at admission were more likely to have prolonged length of stays (median length of stays 12 vs 4; p<0.001).

Conclusion: This study found NLR was an independent predictor of END in patients with anterior circulation stroke.