Objective: To explore the values of neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), neutrophil to albumin ratio (NAR), prognostic nutritional index (PNI), systemic immune inflammatory index (SII) and red cell distribution width to albumin ratio (RA) for evaluating the risk of 30-day mortality of ischemic stroke or hemorrhagic stroke patients.Methods: In this cohort study, the data of 1,601 patients diagnosed with stroke were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. Among them, 908 were hemorrhagic stroke patients and 693 were ischemic stroke patients. Demographic and clinical variables of patients were collected. Univariate and multivariable Cox regression were performed to evaluate the predictive values of NLR, PLR, SII, NAR, RA, and PNI for 30-day mortality in hemorrhagic stroke or ischemic stroke patients. The receiver operator characteristic (ROC) curves were plotted to assess the predictive values of NLR, NAR, and RA for 30-day mortality of hemorrhagic stroke patients.Results: At the end of follow-up, 226 hemorrhagic stroke patients and 216 ischemic stroke patients died. The elevated NLR level was associated with increased risk of 30-day mortality in hemorrhagic stroke [hazard ratio (HR) = 1.17, 95% confidence interval (CI): 1.06–1.29]. The increased NAR level was associated with elevated risk of 30-day mortality in hemorrhagic stroke (HR = 1.16, 95% CI: 1.02–1.30). The high RA level was linked with increased risk of 30-day mortality (HR = 1.44, 95% CI: 1.23–1.69). No significant correlation was observed in these inflammation biomarkers with the risk of 30-day mortality in ischemic stroke patients. The area under the curves (AUCs) of NLR, RA, and NAR for evaluating the risk of 30-day mortality of hemorrhagic stroke patients were 0.552 (95% CI: 0.503–0.601), 0.644 (95% CI: 0.590–0.699) and 0.541 (95% CI: 0.490–0.592).Conclusion: NLR, NAR, and RA were potential prognostic biomarkers for predicting 30-day mortality of hemorrhagic stroke patients, which might provide clinicians an easy and cheap way to quickly identify patients with high risk of mortality.

Background: Non-small cell lung cancer (NSCLC) has high incidence and mortality rates. The discovery of an effective biomarker for predicting prognosis and treatment response in patients with NSCLC is of great significance. Bacterial lipopolysaccharide-related genes (LRGs) play a critical role in tumor development and the formation of an immunosuppressive microenvironment; however, their relevance in NSCLC prognosis and immune features is yet to be discovered.Methods: Differentially expressed LRGs associated with NSCLC prognosis were identified in the TCGA dataset. Prognostic LRG scoring and nomogram models were established using single-variable Cox regression, Least Absolute Shrinkage, and Selection Operator (LASSO) regression. The prognostic value of the scoring and nomogram models was evaluated using Kaplan-Meier (KM) analysis and further validated using an external dataset. Patients were stratified into high- and low-risk groups based on the nomogram score, and drug sensitivity analysis was performed. Additionally, clinical characteristics, mutation features, immune infiltration characteristics, and responses to immunotherapy were compared between the two groups.Results: We identified 15 differentially expressed LRGs associated with NSCLC prognosis. A prognostic prediction model consisting of 6 genes (VIPR1, NEK2, HMGA1, FERMT1, SLC7A, and TNS4) was established. Higher LRG scores were associated with worse clinical prognosis and were independent prognostic factors for NSCLC. Subsequently, a clinical risk prediction nomogram model for NSCLC was constructed, incorporating the status of patients with tumor burden, tumor T-stage, and LRG scores. The nomogram model demonstrated good predictive performance upon validation. Additionally, NSCLC patients classified as high risk based on the model’s predictions exhibited not only a poorer prognosis but also a more pronounced inflammatory immune microenvironment phenotype than low-risk patients. Furthermore, high-risk patients showed disparate predicted responses to various drugs and immunotherapies compared with low-risk patients.Conclusion: The LRGs scoring model can serve as a biomarker that contributes to the establishment of a reliable prognostic risk-prediction model, potentially facilitating the development of personalized treatment strategies for patients with NSCLC.

Objective: It is still a challenge to distinguish sentinel lesions of primary central nervous system lymphoma (PCNSL) from atypical tumefactive demyelinating lesions (TDLs) in clinical practice. We aimed to investigate potential differences of clinical features, neuroimaging findings and pathological characteristics between PCNSL and TDLs, improving early accurate diagnosis.Methods: It was a retrospective study involving 116 patients with TDLs and 150 patients with PCNSLs. All cases were pathologically confirmed. Clinical features, neuroimaging findings and pathological characteristics between two groups were analyzed.Results: The onset age was 37 ± 14 years in TDLs and 58 ± 13 years in PCNSL(p=0.000). Main onset symptom was headache in TDLs, while cognitive impairment was frequently noted in PCNSL. CT brain scan image showed hypodense lesions in most cases of TDL (110/116, 94.8%), while approximately 80% patients (120/150) with PCNSL had hyperdense lesions. Furthermore, we found that the presence of Creutzfeldt-Peters cells (might be misdiagnosed as tumor cells) may serve as an important feature in TDLs.Conclusions: Onset age of patients with TDLs was younger than PCNSL. Neuroimaging features on brain CT scan might provide clues to make a differential diagnosis. Pathological features of PCNSL with sentinel lesions or following steroids therapy might mimic TDLs. Dynamic neuroimaging pathological and follow-up information were essential for an accurate diagnosis.

Objective: This study aimed to summarize the clinical characteristics and prognosis of patients with anti- acetylcholine receptor (AChR) positive myasthenia gravis (MG) with a combination of anti-LRP4 or Titin antibodies.Methods: A total of 188 patients with generalized MG before immunotherapy were retrospectively collected and then divided into three groups: single anti-AChR positive-MG (AChR-MG, 101 cases), anti-AChR combined with anti-low-density lipoprotein receptor-related protein four-positive MG (AChR+LRP4-MG, 29 cases), and anti-AChR combined with anti-Titin-positive MG (AChR+Titin-MG, 58 cases). Clinical manifestations, therapeutic responses to immunotherapy, and follow-up information were analyzed.Results: Of the 188 seropositive MG patients, 29 (15.4%) were positive for both AChR and LRP4 antibodies, and 58 (30.9%) were positive for both AChR and Titin antibodies. The mean disease onset ages in the three groups were 47.41 ± 7.0, 49.81 ± 9.2, and 48.11 ± 6.5 years, respectively. AChR+LRP4-MG showed female predominance (27.6% were males and 72.4% were females), with mild overall clinical symptoms. The AChR+Titin-MG group showed shorter times for conversion to generalized MG (5.14 ± 0.0 months) than the AChR-MG group (11.69 ± 0.0 months) and the AChR+LRP4-MG group (13.08 ± 0.5 months; P < 0.001 in both cases). Furthermore, AChR+Titin-MG group had increased bulbar dysfunction, higher incidences of thymoma (32.8 vs. 19.8% and 3.4%, P=0.035), more severe quantitative MG scores, as assessed by both QMG scores [15.5 (11.75–22.5) vs. 13 (8–19), P = 0.005; and 9 (6–14) P < 0.001], and MG-ADL scores [10 (8–13) vs. 8 (5–13), P = 0.018; and 6 (4–8), P < 0.001]. Treatment for AChR+Titin-MG was largely dependent on corticosteroids and immunosuppressive agents (56.7 vs. 19.2% and 16.7%, p = 0.028). The rates of achieving s(MMS) or better within 2 years following immunotherapy in the three groups were 51.5, 62.1, and 51.7%, respectively (P = 0.581).Conclusion: Clinical symptoms of anti-AChR positive MG combined with Titin antibody were more severe and progressed faster than those in the AChR + LRP4 and AChR groups. Regardless of antibody status, all patients responded well to immunotherapy and had relatively good prognoses.

Late-onset myasthenia gravis (LOMG) often has comorbidities, and its initial symptoms may be ignored or misdiagnosed as other diseases. There were few large surveys on LOMG. Our study aimed to summarize clinical characteristics of LOMG to improve the rate of correct MG diagnosis. A retrospective cohort study included 240 LOMG patients with onset age ≥65 years old who were treated at PLA General Hospital from January 1, 2003 to January 1, 2023. The male to female ratio was 1:1.2 (P = 0.699). MGFA clinical classification: Class I 31.3%, Class IIa 12.9%, Class IIb 51.3%, Class IIIa 0.8%, Class IIIb 0.8%, Class IV 0.4%, Class V2.5%. The onset symptom was ptosis in 78.8% and diplopia was in 18.8%. Swallowing dysfunction in the stage of LOMG was in 41.7%. The incidence of thymoma in LOMG was 14.2%. 85.4% of patients antibodies against the muscle acetylcholine receptor (AChR) are detected. The overall incidence of supramaximal repetitive nerve stimulation (Jolly test) was 57.1%, among which the highest positive rate (50.7%) was in the facial nerve. Jolly test of Class IIb was tested in the highest positive rate and Class I was in the lowest one (χ2 = 7.023, P = 0.030). There was no significant difference in the incidence of LOMG between males and females. The clinical manifestations were mainly Class I and Class II, and severe MG was rare. The most common onset symptom was ptosis. The incidence of LOMG with thymoma was low. Supramaximal repetitive nerve stimulation (Jolly test) of the facial nerve was the easiest to detect and Jolly test of Class IIb was tested in the highest positive rate and Class I was in the lowest one.