European Journal of Medical Research最新文献

Background: Extracorporeal membrane oxygenation (ECMO) is a life-saving intervention for patients with severe respiratory and/or cardiac failure. In patients with severe pneumonia, severe septic shock led to the need for vasopressor and inotropic drugs to maintain the patients' circulatory function. The vasoactive inotropic score (VIS) is calculated as a weighted sum of all administered vasopressor and inotropic medications and quantifies the amount of pharmacological cardiovascular support. This study aimed to evaluate the association between preoperative VIS score and clinical outcomes among adult severe pneumonia patients with sepsis undergoing ECMO support.

Methods: Adult patients diagnosed with severe pneumonia complicated with sepsis from January 2013 to June 2022 were obtained from the Chinese Society of Extracorporeal Life Support (CSECLS) registry database. The study endpoints included in-hospital mortality and failure of weaning for ECMO. Restricted cubic spline (RCS) was used to explore the association between VIS and the risk of adverse clinical outcomes. A backward stepwise logistic multivariable regression was used for assessing influence factors of study endpoints. Unadjusted and adjusted odds ratio (OR) and 95% confidence interval (CI) were calculated to identify the association.

Results: Among 825 enrolled patients, there were 386 cases of in-hospital mortality and 241 cases of ECMO weaning failure. Patients in the in-hospital death group were older, had a higher SOFA score, lower mean arterial pressure, and higher VIS. A linear relationship existed between VIS and the risk of in-hospital death as well as the risk of failed weaning from ECMO support. Regardless of whether patients received VV-ECMO assistance or VA-ECMO support, as the VIS level increased, both the risk of in-hospital mortality and the risk of ECMO weaning failure also increased linearly. In the further subgroup analysis, the results were found to be robust.

Conclusion: Linear correlation existed between VIS score and the risk of in-hospital death as well as the risk of ECMO weaning failure in adult patients with severe pneumonia combined with sepsis. With the increase of VIS score, the risk of in-hospital death and ECMO weaning failure also increased. VIS may be a useful practical tool for risk stratification of adverse clinical outcomes.

Background: This study aimed to develop and validate a novel nomogram that incorporates the neutrophil percentage-to-albumin ratio (NPAR) for predicting 30-day and 90-day unfavorable outcomes in acute-on-chronic liver failure (ACLF) patients.

Methods: We retrospectively enrolled 641 ACLF patients from the First Affiliated Hospital of Anhui Medical University between January 2017 and June 2024, randomly assigning them to training (n = 448) and validation (n = 193) cohorts. Univariate Cox regression, the Least Absolute Shrinkage and Selection Operator (LASSO) regression, and multivariate Cox analysis identified seven independent predictors: bacterial infection, hepatic encephalopathy, age, prothrombin time (PT), total bilirubin (TBIL), lymphocyte count, and NPAR.

Results: The nomogram demonstrated superior predictive performance in the training cohort, with area under the curve (AUC) values of 0.874 (95% CI 0.838-0.910) and 0.877 (95% CI 0.845-0.909) for 30-day and 90-day outcomes, respectively, and a concordance index (C-index) of 0.825 (95% CI 0.796-0.853), significantly outperforming the MELD, MELD-Na, CLIF-C ACLFs and COSSH-ACLF II scores. Calibration curves showed strong concordance between predicted and observed survival probabilities, and decision curve analysis confirmed broad clinical applicability. We have also validated the predictive value of the new model for ACLF in a validation cohort (n = 193). Compared with COSSH-ACLF II, the model exhibited significant improvements in net reclassification index (NRI) and integrated discrimination improvement (IDI) (P < 0.001). Risk stratification effectively categorized patients into low-, intermediate-, and high-risk groups, revealing varied survival rates. In addition, a user-friendly dynamic web-based calculator was developed.

Conclusions: This nomogram that integrates inflammatory and nutritional indicators provides a high-precision tool for short-term prognosis assessment in ACLF patients and is expected to guide clinical management.

Background: Insulin resistance and chronic inflammation are closely associated with cognitive impairments. This study systematically investigates the relationship between biomarkers of insulin resistance/chronic inflammation and cognitive dysfunction in patients with non-disabling ischemic cerebrovascular events (NICE).

Methods: We collected demographic information and clinical data from 236 patients with NICE. Based on Montreal Cognitive Assessment (MoCA) scores, participants were categorized into normal cognitive function (NCF) and VCI groups. Propensity score matching (PSM) was applied to balance baseline characteristics. Differences in chronic inflammatory markers and insulin resistance levels were compared between groups. LASSO regression was used to identify independent risk factors, while restricted cubic spline (RCS) analysis was performed to validate dose-response relationships. A nomogram model was constructed using LASSO-selected predictors, and its performance was evaluated by ROC curves, calibration plots, and decision curve analysis (DCA). Internal validation was performed through simple cross-validation, with both accuracy and Kappa statistics reported.

Results: Among 236 NICE patients, 115 (48.73%) were diagnosed with VCI. Following propensity score matching, the VCI group exhibited significantly higher levels of insulin resistance and chronic inflammation compared to the NCF group. LASSO regression identified the metabolic score for insulin resistance (METS-IR) as an independent risk factor for cognitive impairment (OR = 1.11, 95% CI: 1.06-1.17). RCS confirmed a linear negative correlation between METS-IR and MoCA scores (P for overall = 0.014, P for non-linear = 0.715). Mediation analysis revealed that the systemic Immune-Inflammation Index (SII) partially mediated the association between METS-IR and MoCA scores. The nomogram model demonstrated good discrimination (AUC = 0.78, 95% CI: 0.72-0.83), with calibration plots showing high consistency between predicted and observed probabilities (Hosmer-Lemeshow test P = 0.718). DCA confirmed a favorable clinical net benefit. Cross-validation results demonstrated favorable model accuracy and consistency (accuracy = 0.71, Kappa value = 0.43).

Conclusions: Cognitive impairment in NICE patients is strongly associated with elevated insulin resistance and chronic inflammation. METS-IR exhibits a linear negative association with cognitive function, serving as an independent risk predictor. The constructed nomogram provides a reliable tool for early VCI detection with robust discrimination and calibration. Notably, SII partially mediates the association between METS-IR and cognition, highlighting inflammatory pathways as a candidate target for future interventional studies.

Objective: To evaluate the association between very high high-density lipoprotein cholesterol (HDL-C) levels and cardiovascular mortality in a general adult population.

Methods: In this retrospective cohort study, 3,758 adults undergoing lipid profiling at a tertiary care center were categorized into five HDL-C groups: Very Low (< 30 mg/dL), Low (30-49 mg/dL), Normal (50-69 mg/dL), High (70-89 mg/dL), and Very High (≥ 90 mg/dL in men or ≥ 110 mg/dL in women). Demographic, clinical, and laboratory data were collected. The primary outcome was cardiovascular mortality over a median follow-up of 5.9 years. Kaplan-Meier survival curves and Cox proportional hazards models were used to assess associations, adjusting for age, sex, comorbidities, and medications.

Results: The Very High HDL-C group demonstrated the highest cardiovascular mortality rate (11.3 per 1,000 person-years) and significantly reduced survival compared to the Normal group (log-rank p = 0.00028). Multivariable analysis revealed that very high HDL-C was associated with increased cardiovascular mortality (adjusted HR: 1.52; 95% CI 1.04-2.24; p = 0.03). Subgroup analyses showed elevated risk in older adults, diabetics, and non-statin users.

Conclusion: Extremely high HDL-C levels were independently associated with increased cardiovascular mortality, suggesting a U-shaped relationship. These findings warrant cautious interpretation of high HDL-C values in clinical practice.

Background: Tumor heterogeneity and invasive sampling limit traditional tissue-based PD-L1 testing in advanced lung cancer. We explored a non-invasive alternative by assessing PD-L1 expression on circulating tumor cells (CTC PD-L1) via liquid biopsy to predict immunotherapy outcomes.

Methods: Fifty-two advanced lung cancer patients were recruited, and 38 individuals received a combination of chemotherapy and PD-1/PD-L1 inhibitor therapy, with serial blood samples (baseline, during treatment, and at progression) analyzed using the LiquidBiopsy^™ platform and CTC PD-L1 assay. Primary endpoints included objective response rate (ORR), progression-free survival (PFS), and overall survival (OS).

Results: CTC PD-L1 was identified on special phenotype with a ratio of CK/CD45 > 1.7 and PD-L1/CD45 > 3.2. At baseline, 71.2% (37/52) of patients had detectable CTCs, with 50.0% (26/52) being CTC PD-L1⁺. CTC PD-L1⁺ patients exhibited significantly higher ORR (84.2% vs. 36.8%), longer median PFS (16 months vs 4 months; HR = 0.28, 95% CI 0.096-0.78, p = 0.0041), and superior OS (median survival, undefined; HR = 0.19, 95% CI 0.05-0.74, p = 0.017). Multivariate analysis confirmed CTC PD-L1⁺ as an independent predictor of response (p = 0.003) and potential as a complementary biomarker to tPD-L1.

Conclusions: We developed a novel procedure to detect and characterize PD-L1 expression on CTCs, which was a feasible, non-invasive biomarker for potentially predicting the combination of chemotherapy and immunotherapy efficacy in advanced lung cancer, addressing tissue sampling limitations and enhancing patient stratification and monitoring.

Trial registration: The study was approved by the Medical Ethics Committee of Fourth Affiliated Hospital of Soochow University, with ethics approval number 220154 on 23th January, 2022 and retrospectively registered under clinical trial number ChiCTR2500096312 on 21th January, 2025.

Background: Allergic rhinitis (AR), a major subtype of rhinitis, is characterized by dysregulated apoptosis in the nasal mucosa, a process intrinsically correlated with its inflammatory pathology. The aim of this study was to identify pan-apoptosis-related genes with diagnostic and therapeutic relevance in AR.

Methods: We analyzed AR-related datasets (GSE75011 and GSE50223) from Gene expression Omnibus (GEO) database. Differentially expressed genes (DEGs) from GSE75011 were intersected with pan-apoptosis-related genes identified by WGCNA. Biomarkers closely associated with AR progression were screened applying LASSO and Recursive Feature Elimination (RFE). Functional enrichment was assessed via GSEA, and single-sample GSEA (ssGSEA) was utilized to analyze the association between immune cell infiltration and the biomarkers. In vitro assays were carried out to further elucidate the role of H1FX in an AR model.

Results: DEGs were mainly enriched in IL-17 signaling pathway and MAPK signaling pathway. H1FX was identified as a key pan-apoptosis-related biomarker, with an AUC > 0.7 in ROC analysis. GSEA revealed differential enrichment of VEGF signaling pathway, MAPK signaling pathway, and Spliceosome and HALLMARK_G2M_CHECKPOINT between high and low expression groups of H1FX. ssGSEA analysis showed that H1FX expression was positively linked to Activated B cells, Central memory CD4 T cells, and significantly negatively correlated with Activated CD4 T cells in AR. Cellular assays confirmed that H1FX regulated proliferation and apoptosis in the AR model.

Conclusion: Integrating computational analyses and experimental validation, we identified H1FX as a pivotal regulator of pan-apoptosis and inflammatory responses in AR, highlighting its potential as a diagnostic biomarker and therapeutic target.

Background: The hypoxia-inducible factor-1α (HIF-1α)/Bcl-2/adenovirus E1B 19-kDa interacting protein (BNIP3) pathway, a key regulator of mitophagy, has demonstrated protective effects in renal and cardiac ischemia/reperfusion (I/R) injury. However, its specific role and mechanism in cerebral I/R injury (CIRI) are not fully understood.

Methods: An oxygen-glucose deprivation/reoxygenation (OGD/R) model in SH-SY5Y neuroblastoma cells and a transient middle cerebral artery occlusion (MCAO) model in rats were established to simulate CIRI. HIF-1α overexpression plasmids was then introduced into the two models. Mitophagic activity was assessed through immunoblotting of BNIP3, microtubule-associated protein 1 light chain 3B (LC3B), and p62 protein, quantification of LC3B-mitochondria colocalization, and transmission electron microscopic analysis of mitochondrial ultrastructure and autophagosomes. NOD-, LRR-, and pyrin domain-containing 3 (NLRP3) inflammasome activation was evaluated by measuring levels of NLRP3, cleaved caspase-1, interleukin (IL)-1β, and IL-18. The cell-type specificity of the HIF-1α/BNIP3/mitophagy pathway was evaluated by comparative analysis in SH-SY5Y neuronal cells and BV-2 microglia. Mechanistic dependency was tested NLRP3 agonist nigericin using the autophagy inhibitor 3-methyladenine (3-MA) and the specific NLRP3 inflammasome agonist nigericin in rescue experiments. In addition, cerebral infarction and neurological deficits were assessed in rats.

Results: HIF-1α transcriptionally upregulated BNIP3 in SH-SY5Y cells. HIF-1α overexpression increased BNIP3 and LC3B II levels, reduced p62 level, increased autophagosome accumulation, and enhanced mitophagy in SH-SY5Y cells. This enhanced mitophagy suppressed OGD/R-induced apoptosis and NLRP3 inflammasome activation, while these effects were abolished by 3-MA or nigericin. Comparative analysis revealed the HIF-1α/BNIP3/mitophagy pathway to be a predominant and potent mechanism in SH-SY5Y cells, rather than BV-2 microglia. In addition, HIF-1α overexpression enhanced mitophagy and attenuated NLRP3 inflammasome activation in brain tissues, thereby alleviating cerebral infarction and neurological deficits in MCAO rats.

Conclusions: Activation of the HIF-1α/BNIP3 pathway drives protective mitophagy to suppress the NLRP3 inflammasome in neuronal cells, thereby conferring neuroprotection against CIRI. This study provides mechanistic insights into the protective role of HIF-1α/BNIP3-mediated mitophagy against CIRI, highlighting its potential as a therapeutic target for ischemic injury.

Background: SGLT-2 inhibitors and GLP-1 receptor agonists exhibit metabolic benefits on improving obesity, diabetes, hypertension and hyperlipidemia, but the differences between them remain unclear. We evaluated the comparative efficacy of these two agents on metabolic benefits in adults with T2DM.

Method: This study has searched the electronic databases from the inception of the databases up to March 30, 2025. Primary outcome was the efficacy for weight loss. Secondary outcomes included the effectiveness for HbA_1c levels, blood pressure, and plasma lipid levels. We conducted a Bayesian network meta-analysis. This protocol was cataloged with PROSPERO (CRD42021247584).

Results: 168 RCTs of 72,195 adults were deemed eligible. For losing weight, GLP-1 receptor agonists were more effective than SGLT-2 inhibitors (MD - 1.08 kg,95% CrI: - 1.78 to -0.36). In subgroup analyses, compared to SGLT-2 inhibitors, GLP-1 receptor agonists displayed a stronger weight-loss effect in subgroup of 30 kg/m² ≤ BMI < 35 kg/m² (- 0.95 kg, - 1.91 to - 0.01) and BMI ≥ 35 kg/m² (- 1.11 kg, - 6.73 to - 4.60), while had a weaker weight-loss effect in subgroup of 25 kg/m² ≤ BMI < 30 kg/m² (1.33 kg, 0.79-1.83). For lowering plasma glucose, GLP-1 receptor agonists showed a stronger effect on reducing HbA_1c level (- 0.38%,- 0.52 to - 0.25). For decreasing blood pressure, both GLP-1 receptor agonists (- 2.10 mmHg, - 3.66 to - 0.49) and SGLT-2 inhibitors (- 3.20 mmHg, - 4.0 to - 2.39) decreased systolic blood pressure, while only SGLT-2 inhibitors (- 1.35 mmHg, - 1.67 to - 1.01) decreased diastolic blood pressure compared to placebo. For regulating serum lipids, both GLP-1 receptor agonists (- 0.14 mmol/L, - 0.22 to - 0.08) and SGLT-2 inhibitors (- 0.12 mmol/L, - 0.18 to - 0.07) lowered triglycerides, while only GLP-1 receptor agonists lowered LDL-c level (- 0.14 mmol/L, - 0.22 to - 0.06) compared to placebo.

Conclusion: Both GLP-1 receptor agonists and SGLT-2 inhibitors have been shown to confer metabolic benefits. GLP-1 receptor agonists displayed stronger effects on weight reduction for patients with obesity (BMI ≥ 30 kg/m²), lowering HbA_1c levels and improving lipid profiles. SGLT-2 inhibitors demonstrated greater efficacy in losing weight for patients with overweight (25 kg/m2 ≤ BMI < 30 kg/m2) and decreasing blood pressure.

Registration number: CRD42021247584. The name of the registry: PROSPERO. The URL to the registration: https://www.crd.york.ac.uk/PROSPERO/.

Background: The incidence of Mycobacterium avium complex (MAC)-pulmonary disease (PD) is increasing in South Korea, posing significant diagnostic and therapeutic challenges. Treatment guidelines recommend initiating therapy after serial computed tomography monitoring. Patients with the nodular bronchiectatic (NB) form often respond positively to drug therapy, whereas those with the fibrocavitary (FC) form frequently experience persistent disease despite treatment. Identifying phenotype-specific transcriptomic biomarkers could improve early diagnosis and inform personalized therapeutic strategies.

Methods: We utilized surgically resected lung specimens from 21 MAC-PD patients, a valuable clinical resource, as lung surgery is uncommon in MAC-PD management. Each patient provided paired samples of affected and unaffected lung tissues, enabling direct transcriptomic comparisons. Quantitative RNA sequencing was performed on samples from 11 NB and 10 FC cases. Comprehensive bioinformatics and in silico analyses, including gene ontology (GO) and protein-protein interaction (PPI) network analyses, were conducted to identify key diagnostic signatures and biological pathways.

Results: RNA sequencing revealed distinct and shared transcriptomic signatures correlated with radiological phenotypes. GO and PPI analyses identified significant gene clusters involved in B cell proliferation and immune regulation across both NB and FC forms. Additionally, NB-specific signatures highlighted genes predominantly regulating antimicrobial immune responses, while FC-specific signatures enriched genes related to extracellular matrix remodeling.

Conclusions: This study is the first to characterize transcriptomic differences between MAC-PD phenotypes using paired lung tissue samples. Although the identified transcriptomic markers require functional validation, their strong correlation with radiologic subtypes provides preliminary evidence supporting their potential diagnostic value. These findings lay the groundwork for precision diagnostics in MAC-PD and require further validation in larger patient cohorts and through functional assays.