International Journal of General Medicine最新文献

Objective: Neutrophil-to-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR), Red-cell-distribution width (RDW) and Platelet-distribution width(PDW) have been proved to be related to the severity of a variety of diseases and poor prognosis. But their predictive value in neonatal pneumonia is still unknown. Therefore, this study explored the predictive value of NLR, PLR, RDW and PDW in the adverse prognosis of neonatal pneumonia.

Methods: We retrospectively analyzed 132 neonates with pneumonia treated in our hospital from April 2022 to October 2024. At the same time, 50 healthy newborns delivered in our hospital during the same period were selected as the control group. The levels of NLR, PLR, RDW and PDW in children with different disease severity and prognosis were analyzed; The correlation between NLR, PLR, RDW, PDW levels and disease severity was analyzed, and the predictive value for the adverse prognosis of neonatal pneumonia.

Results: Among 132 children, 65 were mild, 44 moderate and 23 severe; 26 cases had poor prognosis. The levels of NLR, PLR, RDW and PDW in children with different disease severity were significantly different (P<0.05). Spearman test showed that NLR, PLR, RDW, PDW were significantly positively correlated with the severity of neonatal pneumonia (P<0.05). Multivariate logistic regression analysis showed that NLR, PLR, RDW and PDW were the related factors influencing the poor prognosis of neonatal pneumonia (p<0.05). ROC curve analysis showed that the value of combined prediction of four indicators for poor prognosis of neonatal pneumonia was higher than that of single indicators, and the sensitivity of combined prediction was 100%, and the specificity was 94.9%.

Conclusion: NLR, PLR, RDW, PDW were positively correlated with the severity of neonatal pneumonia, and the value of combined prediction of poor prognosis was higher.

The complexity of cancer care is continuously increasing in the era of personalized medicine and there is a paradigm shift in the diagnosis and management of cancer. This is the era of precision oncology whose main objective is to identify cancer patients who are candidates for specific targeted therapies. This advanced approach to cancer care formulates treatment strategies for cancer patients based on the specific molecular characteristics of a malignant tumor which are identified through advanced molecular testing. This is the age of advanced prognostic and predictive biomarkers. Targeted therapies represent a groundbreaking shift in cancer therapy and are the cornerstone of precision oncology. Termed "tumor agnostic therapy", these drugs can treat different cancer types across multiple organs which demonstrate the same molecular alterations. A targeted drug in a specific cancer may be effective in another non-related cancer if the same genomic alteration is present. Pathologists need to appreciate these radical and exciting changes and adapt their practices as they will be required to be collaborative clinicians in the new era with a role in diagnosis, prognostication, and treatment of cancer. Pathologists need to become familiar with the ever-expanding number of new biomarkers and their crucial role in cancer care. They need to understand and adapt to new technologies such as Next Generation Sequencing and Comprehensive Genomic Profiling, liquid biopsies, DNA and transcriptome studies etc. They also need to familiarize themselves with tumor agnostic therapies, and concepts such as tumor heterogeneity and resistance to therapy. They can no longer be just morphologists but assume a central role in cancer care. Pathologists in developing countries and resource limited settings who may not currently have access to advanced molecular techniques need to be aware of and understand these fundamental shifts in cancer care and especially their role in the new era. The major changes in cancer care in the era of personalized medicine are discussed in this review mainly for the benefit of pathologists working in LMICs.

Background: The evaluation of a prolonged activated partial thromboplastin time (APTT) traditionally relies on a diagnostic cascade, including mixing studies to screen for inhibitors, specific factor activity assays, and specialized tests like lupus anticoagulant detection. Activated partial thromboplastin time-based clot waveform analysis (CWA-APTT) has emerged as an optical technique that captures the entire kinetic profile of clot formation, offering potential for enhanced diagnostic triage and monitoring. However, conventional analysis of CWA-APTT parameters, particularly peak-related metrics, is confounded by variables like fibrinogen concentration, limiting their specificity for accurately quantifying coagulation factor activity. Furthermore, the diagnostic utility of time-distribution parameters remains underexplored, especially for distinguishing between factor deficiencies and phospholipid-dependent inhibitors. This study aims to improve the correlation between peak-related parameters in APTT-based clotting curves and coagulation factor activity through novel data analysis methods and to investigate the potential clinical utility of time-distribution parameters in distinguishing sample types.

Methods: A total of 263 blood samples collected from patients with hemophilia A, hemophilia B, or lupus anticoagulant positivity were used to perform CWA-APTT. Normalization methods were applied to process the characteristic parameters in CWA-APTT. Then, the correlation between the processed peak-related parameters and coagulation factor activity was analyzed, and the ability of time-distribution parameters to distinguish different sample types was investigated.

Results: Following normalization, peak-related parameters more accurately reflect coagulation factor activity. Time-distribution parameters can also monitor coagulation factor activity and exhibit a certain degree of sample specificity. Combined analysis of time-distribution parameters enhances the ability to distinguish sample types, achieving a higher concordance rate in curve feature recognition compared to APTT correction tests.

Conclusion: This study innovatively explored new applications of CWA-APTT characteristic parameters. It was found that normalization enables peak-related parameters to more accurately reflect coagulation factor activity, and multi-parameter combined analysis can significantly enhance the ability of CWA-APTT to distinguish clinical samples.

Purpose: To evaluate whether tumor zonal origin is associated with clinical, pathological, and prognostic outcomes in patients with prostate cancer (PC) treated with radical prostatectomy (RP).

Patients and methods: This retrospective cohort study analyzed 488 patients who underwent RP at UNICAMP between 1997 and 2017. Tumor zonal origin was defined by the dominant (index) lesion, identified through standardized whole-mount pathological analysis based on the highest ISUP grade and largest tumor volume. The primary endpoint was a composite of biochemical recurrence and/or metastasis, selected to capture clinically significant disease relapse and ensure statistical robustness in a long-term cohort. Associations were assessed using the Mann-Whitney U-test and the Chi-square test. Multivariate logistic regression was performed to identify independent predictors of progression (p < 0.05).

Results: The index tumor originated in the peripheral zone (PZ) in 79.9% of cases and in the transition zone (TZ) in 6.5%. During follow-up, 38.3% of patients experienced biochemical recurrence or metastasis. Tumor location was not significantly associated with biochemical recurrence or metastasis (p = 0.428). Independent predictors included clinical stage (risk classification), pathological ISUP grade, positive surgical margins, and extra prostatic extension. Notably, biopsy ISUP grade and lymph node status were not independently predictive. The limited representation of TZ tumors may have constrained the statistical power to detect subtle prognostic differences.

Conclusion: Within the limitations of this cohort, tumor zonal origin was not independently associated with biochemical recurrence or metastasis following RP. Established pathological factors remain the primary determinants of disease progression.

Objective: Primary intracerebral hemorrhage (ICH) is a severe stroke subtype characterized by high mortality and disability rates, largely attributable to secondary brain injury (SBI). While programmed cell death (PCD) pathways contribute to SBI, their mechanisms remain incompletely understood. This research investigated PANoptosis, a newly defined integrated PCD pathway, and its interactions with immune responses in ICH.

Methods: The transcriptomic dataset GSE24265 was analyzed to identify differentially expressed genes (DEGs), which were intersected with a PANoptosis-related gene set. PANoptosis-related DEGs were analyzed through protein-protein interaction (PPI) networks, functional enrichment, and machine learning (LASSO and Random Forest) to identify signature genes. The diagnostic utility was evaluated using nomograms and receiver operating characteristic (ROC) curves. Immune interactions were assessed using CIBERSORT. Key findings were validated in clinical specimens using qRT-PCR and Western blot.

Results: We identified 50 PANoptosis-related DEGs in ICH and derived five signature genes (AKR1C2, SLC2A14, FTL, TNFRSF12A, and SLC2A3) that were significantly upregulated and had high diagnostic accuracy. These genes were implicated in an inflammatory cell death hub, as their expression correlated with altered proportions of T follicular helper and T gamma delta cells, linking PANoptosis to immune dysregulation. Experimental validation confirmed the upregulation of mRNA levels of SLC2A3, SLC2A14, and TNFRSF12A in perihematomal tissues, along with increased protein levels of SLC2A3 and SLC2A14. Functional enrichment analysis linked these genes to HIF-1, NF-κB, and TNF signaling pathways in ICH PANoptosis.

Conclusion: Our study identifies PANoptosis as a pathological hub connecting SBI and neuroinflammation in ICH, with five signature genes serving as key diagnostic biomarkers. Notably, SLC2A3 was significantly elevated in peripheral blood, highlighting its potential as a non-invasive plasma biomarker for ICH. These genes likely contribute to neuroinflammation through immune crosstalk and metabolic reprogramming, offering novel mechanistic insights and potential therapeutic targets for SBI post-ICH.

Eosinophilic heart disease (EHD) is an inflammatory cardiac disorder characterized by the infiltration and subsequent heart tissue damage mediated by eosinophils. The clinical manifestations of EHD vary widely, ranging from asymptomatic to severe, life-threatening conditions. Diagnosis relies on a multimodal approach, incorporating clinical presentations, laboratory findings (e.g. hypereosinophilia), and advanced imaging studies such as cardiac magnetic resonance imaging (MRI) and echocardiography. However, the gold standard for definitive diagnosis remains endomyocardial biopsy, which demonstrates eosinophilic infiltration and associated myocardial injury. Currently, there is no established consensus on specific therapeutic protocols for EHD. Management primarily targets the underlying etiology and mitigates eosinophil-induced cardiac damage. Prognosis is highly variable and largely dependent on the causative pathology, with outcomes spanning from rapidly progressive and fatal courses to indolent, chronic disease progression. Given the heterogeneity in clinical presentation and treatment responses, there is an urgent need for evidence-based clinical guidelines to standardize the management of EHD.

Objective: Winter low temperatures may affect the occurrence of acute cerebral infarction by affecting blood pressure, but little is known about the association between seasonal variation and the clinical severity of acute cerebral infarction. This study aims to explore the seasonal variation of acute cerebral infarction and its relationship with stroke severity and vascular risk factors.

Methods: A five-year retrospective study was conducted including 692 patients with acute cerebral infarction admitted to a second class A hospital. Patients were stratified by season of onset. Stroke severity was assessed using NIHSS, and multivariable logistic regression was applied to analyze associations and interactions.

Results: While incidence did not differ significantly by season, stroke severity was highest in winter. Spring onset might be independently associated with lower odds of severe stroke (OR = 0.38, 95% CI: 0.14-0.94, p = 0.05). Significant interactions were observed for alcohol use in summer (OR = 10.69, 95% CI: 1.42-222.84) and atrial fibrillation in spring (OR = 7.30, 95% CI: 1.13-66.12). Sex-stratified analysis revealed that spring onset was associated with lower incidence of moderate-to-severe stroke (NIHSS ≥ 8) among females, while atrial fibrillation and hypertension were risk factors for moderate-to-severe cerebral infarction in males.

Conclusion: A seasonal variation was found in the clinical severity of acute cerebral infarction and was highest in winter. Due to the lack of direct environmental exposure data collection (such as environmental temperature, humidity, air pollution), the specific mechanism still needs further exploration.

Background: MicroRNAs (miRNAs) are small molecules that regulate gene expression and may influence the severity and progression of rare hereditary anemias. Understanding their role can support the development of targeted treatments. To our knowledge, this multicenter longitudinal cohort is among the first to characterize miRNA profiles-particularly miR-155-in pediatric patients with rare hereditary anemias presenting with sepsis, and to report exploratory translational observations relevant to gene-based modulation frameworks.

Objective: This study aimed to profile miRNA expression in septic patients with rare hereditary anemias and evaluate associations with disease severity, progression, and response to gene therapy.

Methods: This prospective cohort study was conducted at five medical centers in the United States and Saudi Arabia, enrolling 400 participants-200 patients with rare hereditary anemias and 200 healthy controls. Blood samples were analyzed using high-throughput sequencing and advanced bioinformatics. Randomization and blinding procedures were applied to ensure data integrity and minimize bias.

Results: At baseline enrollment during septic presentation, patients exhibited significantly lower mean hemoglobin levels compared to controls (9.2 g/dL vs 12.5 g/dL, p < 0.001). Patients with hereditary anemia had significantly lower average hemoglobin levels (9.2 g/dL) compared to controls (12.5 g/dL, p < 0.001) and higher reticulocyte counts. miR-155 was upregulated 2.5-fold in affected patients (p < 0.01). These patients required an average of six transfusions annually, compared to none in the control group (p < 0.001). Thirty-five percent of patients experienced worsening anemia over time. ROC curve analysis demonstrated miR-155 as a strong diagnostic biomarker, with 85% sensitivity, 90% specificity, and an AUC of 0.97.

Conclusion: miR-155 plays a key role in the progression of rare hereditary anemias in septic patients and shows potential as both a diagnostic and therapeutic target. These findings highlight opportunities for personalized, miRNA-based therapies to improve disease management and patient outcomes. No clinically evident severe vector-related adverse events were observed during follow-up.

Clinical trial number: ECRIN-EU-TRIAL-2025-002739.