Chi-square test under indeterminacy: an application using pulse count data

The application and effect evaluation of continuity precision nursing in patients undergoing coronary angiography and stent implantation: A study of clinical outcomes

Coronary artery disease is a major global health burden, with percutaneous coronary intervention (PCI) serving as a key treatment strategy. Despite its efficacy, challenges such as in-stent restenosis, medication nonadherence, unhealthy lifestyles, and psychological distress hinder optimal recovery. Continuity-based precision nursing, which integrates personalized care and multidisciplinary support, offers a potential solution. Therefore, the purpose of this study is to evaluate the effectiveness of continuity-based precision nursing compared to conventional nursing in improving postoperative outcomes for PCI patients. This includes assessing its impact on cardiac function recovery, complication prevention, medication adherence, lifestyle modifications, psychological well-being, and overall quality of life. This study included 112 PCI patients treated from January 2023 to January 2024, divided into an experimental group (continuity-based precision nursing) and a control group (conventional nursing). Propensity score matching resulted in 45 matched pairs. Data collected included demographics, postoperative cardiac function, medication adherence, lifestyle changes, psychological status, complications, satisfaction, and health-related quality of life. Statistical analyses were performed using SPSS, with P < .05 considered significant. Continuity-based precision nursing showed significant benefits over conventional nursing. At 1 month post-PCI, the experimental group had higher left ventricular ejection fraction ≥ 50% rates (86.7% vs 75.6%) and lower in-stent restenosis (6.7% vs 17.8%) and residual stenosis rates (8.9% vs 24.4%, P = .048). Medication adherence was improved (86.7% vs 66.7%, P = .02), with higher rates eof smoking cessation (77.8% vs 55.6%, P = .01), healthy eating (84.4% vs 66.7%, P = .03), and regular exercise (80.0% vs 62.2%, P = .02). Anxiety and depression scores were significantly lower in the experimental group post-intervention. Patient satisfaction (92.5 ± 4.2 vs 85.7 ± 6.1, P < .01) and health-related quality of life (88.4 ± 5.0 vs 81.2 ± 6.0, P < .01) were also markedly higher. Continuity-based precision nursing significantly enhances postoperative outcomes in PCI patients, improving cardiac function, adherence, lifestyle behaviors, and psychological well-being. This model provides a comprehensive framework for coronary artery disease care, with potential for broader clinical application. Further research should evaluate its long-term impact and scalability in diverse settings.

A retrospective prognostic evaluation using unsupervised learning in the treatment of COVID-19 patients with hypertension treated with ACEI/ARB drugs

Introduction

This study aimed to evaluate the prognosis of patients with COVID-19 and hypertension who were treated with angiotensin-converting enzyme inhibitor (ACEI)/angiotensin receptor B (ARB) drugs and to identify key features affecting patient prognosis using an unsupervised learning method.

Methods

A large-scale clinical dataset, including patient information, medical history, and laboratory test results, was collected. Two hundred patients with COVID-19 and hypertension were included. After cluster analysis, patients were divided into good and poor prognosis groups. The unsupervised learning method was used to evaluate clinical characteristics and prognosis, and patients were divided into different prognosis groups. The improved wild dog optimization algorithm (IDOA) was used for feature selection and cluster analysis, followed by the IDOA-k-means algorithm. The impact of ACEI/ARB drugs on patient prognosis and key characteristics affecting patient prognosis were also analysed.

Results

Key features related to prognosis included baseline information and laboratory test results, while clinical symptoms and imaging results had low predictive power. The top six important features were age, hypertension grade, MuLBSTA, ACEI/ARB, NT-proBNP, and high-sensitivity troponin I. These features were consistent with the results of the unsupervised prediction model. A visualization system was developed based on these key features.

Conclusion

Using unsupervised learning and the improved k-means algorithm, this study accurately analysed the prognosis of patients with COVID-19 and hypertension. The use of ACEI/ARB drugs was found to be a protective factor for poor clinical prognosis. Unsupervised learning methods can be used to differentiate patient populations and assess treatment effects. This study identified important features affecting patient prognosis and developed a visualization system with clinical significance for prognosis assessment and treatment decision-making.

Lipopolysaccharide-induced depression-like model in mice: meta-analysis and systematic evaluation

Depression is a complex and biologically heterogeneous disorder. Recent studies have shown that central nervous system (CNS) inflammation plays a key role in the development of depression. Lipopolysaccharide (LPS)-induced depression-like model in mice is commonly used to studying the mechanisms of inflammation-associated depression and the therapeutic effects of drugs. Numerous LPS-induced depression-like models in mice exist and differ widely in animal characteristics and methodological parameters. Here, we systematically reviewed studies on PubMed from January 2017 to July 2022 and performed cardinal of 170 studies and meta-analyses of 61 studies to support finding suitable animal models for future experimental studies on inflammation-associated depression. Mouse strains, LPS administration, and behavioral outcomes of these models have been assessed. In the meta-analysis, forced swimming test (FST) was used to evaluate the effect size of different mouse strains and LPS doses. The results revealed large effect sizes in ICR and Swiss mice, but less heterogeneity in C57BL/6 mice. For LPS intraperitoneal dose, the difference did not affect behavioral outcomes in C57BL/6 mice. However, in ICR mice, the most significant effect on behavioral outcomes was observed after the injection of 0.5 mg/kg LPS. Our results suggests that mice strains and LPS administration play a key role in the evaluation of behavioral outcomes in such models.