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Background Ovarian endometrioma (OMA) is the most prevalent form of endometriosis. Conservative surgical management of the condition is associated with a relatively high recurrence rate, the degree of which is potentially linked to disease severity. Recently, the American Association of Gynecologic Laparoscopists (AAGL) staging system was developed to reflect the severity of endometriosis and the surgical complexity. However, its predictive value for recurrence following conservative surgery in OMA patients remains unestablished. Methods To evaluate the predictive value of the AAGL staging system for recurrence following conservative surgery in OMA patients. A retrospective cohort study was conducted at Fuzhou University Affiliated Provincial Hospital and included patients who were diagnosed with OMA and underwent conservative surgery (ovarian cystectomy) between January 1, 2018, and December 31, 2022. All patients were assessed with the AAGL staging system and the revised American Society for Reproductive Medicine (r-ASRM) staging system according to the intraoperative findings. The primary outcome was the postoperative recurrence rate. Secondary outcomes included the consistency between the AAGL and r-ASRM systems in assessing patient condition and the correlation between the AAGL stage and surgical complexity as defined by the endometriosis surgery complexity score. Maximally selected rank statistics were used to determine the optimal AAGL score threshold and assess the correlation between the AAGL score and recurrence risk. Landmark analysis was used to assess the predictive value of the AAGL staging system for recurrence following conservative surgical treatment for OMA. Kappa statistics were used to analyse the consistency between the AAGL and r-ASRM staging systems. Kendall’s coefficient of concordance was used to assess the relationships between the staging systems and the surgical complexity. Results A total of 299 patients with OMA were included in the study. A total of 49 patients (16.4%) experienced postoperative recurrence, whereas 250 patients (83.6%) did not. The median postoperative follow-up duration was 39.6 months. The cumulative recurrence rates at 12, 24, 36, 48, and 60 months post-surgery were 2.4%, 7.0%, 13.1%, 23.3%, and 29.6%, respectively. Patients with an AAGL score > 16 had a significantly greater risk of recurrence following conservative surgery than those with an AAGL score ≤ 16 ( P  = 0.022). At 36 months post-conservative surgery and beyond, patients with an AAGL score > 16 presented a significantly higher recurrence rate than did those with a score ≤ 16 ( P  = 0.043). A comparison of the AAGL and r-ASRM systems in all patients revealed poor agreement between the two in terms of disease stage (weighted κ = 0.243). Furthermore, the AAGL staging system demonstrated stronger concordance with the surgical complexity scale than the r-ASRM system did (Kendall W coefficient = 0.613, P  = 0.005; Kendall W coefficient = 0.552, P  = 0.106, respectively). Conclusions The cumulative recurrence rate following conservative surgery for OMA patients progressively increased over time. The AAGL staging system was useful for predicting recurrence in OMA patients following conservative surgery, particularly starting at 36 months post-surgery. The AAGL staging system offers an improved assessment of surgical complexity in OMA patients.

Importance Rheumatoid arthritis (RA), a chronic autoimmune disease linked to higher mortality, benefits from physical activity (PA), which has been shown to reduce disease activity and improve physical function. However, PA’s association with all-cause mortality in RA patients remains unclear. Objective To investigate the relationship between various levels of PA and all-cause mortality among patients with RA. Design, setting, and participants This dual-cohort observational study used data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018 and the UK Biobank database. PA was assessed using self-reported questionnaires in NHANES and 7-day wrist-worn accelerometers in the UK Biobank. Main outcomes and measures Cox proportional-hazards models and restricted cubic spline (RCS) analysis were employed to evaluate the association between PA and all-cause mortality. Subgroup and interaction analyses were conducted to examine the robustness of the findings. Stratified analyses were performed using polygenic risk scores for RA in the UK Biobank cohort. An analysis combining results from both cohorts was conducted using random-effects models to estimate pooled associations and assess heterogeneity. Results A total of 1493 patients with RA from the NHANES cohort and 1724 from the UK Biobank cohort were included. Across both cohorts, PA was significantly associated with a lower risk of all-cause mortality. In fully adjusted models, active and highly active groups showed reduced mortality risks compared with the inactive group [NHANES: hazard ratio (HR): active = 0.381, highly active = 0.675; UK Biobank: HR: active = 0.557, highly active = 0.491]. RCS analysis revealed a U-shaped association between PA and mortality in the NHANES cohort, with moderate PA levels showing the greatest protective effect. However, an L-shaped pattern was observed in the UK Biobank cohort, where the highly active group had the lowest mortality risk. A joint analysis in NHANES revealed that active work-related PA combined with inactive recreational PA yielded the greatest mortality reduction. In the UK Biobank, moderate-to-vigorous PA remained protective even among patients with high genetic risk. A pooled analysis combining both cohorts confirmed a robust inverse association between PA and all-cause mortality (HR: active = 0.48, highly active = 0.61), with low heterogeneity across studies. Conclusions and relevance PA is associated with reduced all-cause mortality in patients with RA. Key points Question What is the relationship between various levels of PA and all-cause mortality among patients with RA? Findings In two large cohorts (NHANES, UK Biobank), higher PA levels significantly reduced death risk. Active (150–300 min/week) and highly active (>300 min/week) groups had lower mortality vs inactive groups (HRs: 0.381–0.675). Meaning PA is robustly linked to longer survival in RA, supporting personalized recommendations balancing activity type (work vs. recreational) and intensity to optimize outcomes.

Immune checkpoint inhibitor (ICI) therapy is the new standard treatment for advanced or metastatic hepatocellular carcinoma (HCC); however, many patients still fail to respond. This study explored the expression and prognosis of programmed death ligand 1 (PD-L1), cluster of differentiation 24 (CD24), and cluster of differentiation 47 (CD47) in patients with hepatitis B virus-associated HCC (HBV-associated HCC). We analyzed sequencing data from the Cancer Genome Atlas (TCGA) and investigated the expression of PD-L1, CD24, and CD47 in HBV-associated HCC patients by immunohistochemistry and their relationship with prognosis and clinicopathological factors. HCC data from the TCGA database show that PD-L1 was substantially correlated with various immune cells. In 67 patients with HBV-associated HCC, high PD-L1 and CD24 expression levels were related to poor overall survival (OS) and progression-free survival (PFS). PD-L1 expression was significantly associated with the staging of HBV-associated HCC ( p  = 0.011) and Ki67 expression ( p  = 0.024). Correlation analysis between variables reveals that PD-L1 was significantly positively correlated with CD24 and CD47. High expression of PD-L1 and CD24 are risk factors for poor prognosis in HBV-associated HCC patients following curative resection. PD-L1 is significantly correlated with CD24 and CD47.

Recently, anti-protein arginine methyltransferase 5 (PRMT5) antibodies has been identified a novel marker for systemic sclerosis (SSc). The present study aimed to to explore the association between anti-PRMT5 antibodies and rheumatoid arthritis (RA). The study recruited a cohort of 33 patients diagnosed with SSc, 87 patients with RA, and 31 healthy control subjects. Serum levels of the anti-PRMT5 antibodies were measured using a double-antigen sandwich enzyme-linked immunosorbent assay (ELISA). Patients with SSc exhibited higher serum levels ( p  < 0.001) and seropositivity rates (48.5% vs. 0%, p  < 0.0001) of anti-PRMT5 antibodies compared to healthy subjects. Notably, serum levels of anti-PRMT5 antibodies were significantly elevated in patients with RA compared to healthy controls ( p  < 0.001), with a corresponding increase in the rate of seropositivity (14.9% vs. 0%, p  < 0.05). Receiver operating curve analysis for anti-PRMT5 antibody levels yielded area under the curve values of 0.768 for distinguishing RA patients from healthy controls, and 0.903 for distinguishing SSc patients from controls. Furthermore, elevated levels of anti-PRMT5 antibodies were significantly associated with the presence of interstitial lung disease (ILD) ( p  < 0.0001) and antinuclear antibody positivity ( p  < 0.01). This study not only confirms the association of the anti-PRMT5 antibodies with SSc but also, for the first time, demonstrates a significant association between the anti-PRMT5 antibodies and RA, particularly in the context of RA-associated ILD.

In epidemiology, indicators such as the relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (S) are commonly used to assess additive interactions between two variables. However, the results of these indicators are sometimes inconsistent in real world applications and it may be difficult to draw conclusions from them. Based on the relationship between the RERI, AP, and S, we propose a method with consistent results, which are achieved by constraining , and the interpretation of the results is simple and clear. We present two pathways to achieve this end: one is to complete the constraint by adding a regular penalty term to the model likelihood function; the other is to use model selection. Using simulated and real data, our proposed methods effectively identified additive interactions and proved to be applicable to real-world data. Simulations were used to evaluate the performance of the methods in scenarios with and without additive interactions. The penalty term converged to 0 with increasing λ, and the final models matched the expected interaction status, demonstrating that regularized estimation could effectively identify additive interactions. Model selection was compared with classical methods (delta and bootstrap) across various scenarios with different interaction strengths, and the additive interactions were closely observed and the results aligned closely with bootstrap results. The coefficients in the model without interaction adhered to a simplifying equation, reinforcing that there was no significant interaction between smoking and alcohol use on oral cancer risk. In summary, the model selection method based on the Hannan-Quinn criterion (HQ) appears to be a competitive alternative to the bootstrap method for identifying additive interactions. Furthermore, when using RERI, AP, and S to assess the additive interaction, the results are more consistent and the results are simple and easy to understand.

Interaction identification is important in epidemiological studies and can be detected by including a product term in the model. However, as Rothman noted, a product term in exponential models may be regarded as multiplicative rather than additive to better reflect biological interactions. Currently, the additive interaction is largely measured by the relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), and the synergy index (S), and confidence intervals are developed via frequentist approaches. However, few studies have focused on the same issue from a Bayesian perspective. The present study aims to provide a Bayesian view of the estimation and credible intervals of the additive interaction measures. Bayesian logistic regression was employed, and estimates and credible intervals were calculated from posterior samples of the RERI, AP and S. Since Bayesian inference depends only on posterior samples, it is very easy to apply this method to preventive factors. The validity of the proposed method was verified by comparing the Bayesian method with the delta and bootstrap approaches in simulation studies with example data. In all the simulation studies, the Bayesian estimates were very close to the corresponding true values. Due to the skewness of the interaction measures, compared with the confidence intervals of the delta method, the credible intervals of the Bayesian approach were more balanced and matched the nominal 95% level. Compared with the bootstrap method, the Bayesian method appeared to be a competitive alternative and fared better when small sample sizes were used. The proposed Bayesian method is a competitive alternative to other methods. This approach can assist epidemiologists in detecting additive-scale interactions.

Background Unfavourable lipid and glucose levels may play a crucial role in the pathogenesis of gestational diabetes mellitus (GDM). However, there is a lack of prospective studies on the relationship between lipid profiles, lipid ratios and GDM during pregnancy. Aims To prospectively investigate the relationship between lipid profile and lipid ratios in early and mid-pregnancy and their pattern of change from early to mid-pregnancy and the risk of GDM. Methods This nested case-control study was based on maternal and child healthcare hospitals from Fujian Province, China. We included pregnant women who delivered in the hospital from January 2021 to June 2023. Lipid profiles (TC, TG, ApoA1, ApoB, HDL-c, LDL-c) and fasting glucose were measured before 14 weeks of gestation and between 20 and 28 weeks of gestation, and lipid ratios (triglyceride glucose index, TG/HDL-c and TC/HDL-c) was constructed. Logistic regression was used to assess the relationship between lipid profile, lipid ratios and GDM. Results Of 1586 pregnant women, 741 were diagnosed with GDM. After adjusting for potential confounders, TG, ApoA1, ApoB, LDL-c, triglyceride glucose index, TG/HDL-c, and TC/HDL-c in early pregnancy were positively associated with the risk of GDM (odds ratios [95% CI] for extreme interquartile comparisons were 2.040 (1.468–2.843), 1.506 (1.091–2.082), 1.529 (1.110–2.107), 1.504 (1.086–2.086), 1.952 (1.398–2.731), 2.127 (1.526–2.971), and 2.370 (1.700-3.312), all trend P  < 0.05). HDL-c was negatively associated with the risk of GDM (0.639: 0.459–0.889, trend P all less than 0.05). Similarly, in mid-pregnancy, lower levels of HDL-c, higher levels of triglyceride glucose index, TG/HDL-c ratio, and TC/HDL-c ratio were associated with increased risk of GDM (all trends P  < 0.05). Stably high levels (both ≥ median for early and mid-pregnancy) of triglyceride glucose index, TG/HDL-c and TC/HDL-c were associated with increased risk of GDM (OR [95% CI]: 2.369 (1.438–3.940), 1.588 (1.077–2.341), 1.921 (1.309–2.829), respectively). The opposite was true for HDL-c, where stable high levels were negatively associated with GDM risk (OR [95% CI]: 0.599 (0.405–0.883)). Conclusion Increases in triglyceride glucose index, TG/HDL-c ratio, and TC/HDL-c ratio in early and mid-pregnancy, as well as their stable high levels from early to mid-pregnancy, are associated with a higher risk of GDM. In contrast, increased levels of HDL-c, both in early and mid-pregnancy, and their stable high levels from early to mid-pregnancy were associated with a lower risk of GDM. That highlighted their possible clinical relevance in identifying those at high risk of GDM.

Combined pulmonary fibrosis and emphysema (CPFE) commonly coexists with connective tissue diseases (CTD), such as rheumatoid arthritis (RA). However, the risk factors contributing to the development of CTD-CPFE remain largely unidentified. This study aimed to characterize CPFE using a large cohort of consecutive RA patients and to elucidate potential risk factors associated with RA- CPFE development. A total of 976 RA patients were enrolled in this cross-sectional study to characterize RA-CPFE. Multiple logistic analyses were conducted to identify potential risk factors for RA-CPFE development. Patient IgG and IgM autoantibodies to primary human bronchial epithelial cells (HBEC) from healthy donors were assessed using flow cytometry. Among the 976 RA patients, 414 (42.4%) developed interstitial lung disease (ILD), with 74 (7.6%) experiencing CPFE. In comparison to RA-CPFE patients with centrilobular or paraseptal emphysema, those with panacinar emphysema had higher emphysema scores and decreased pulmonary function parameters. Multiple logistic regression analysis revealed that male gender, cigarette smoking, occupational exposure to dust, high ILD score, high rheumatoid factor (RF) titers, and the presence of anti-SSA were associated with an increased risk for RA-CPFE. Additionally, levels of IgG and IgM autoantibodies to HBEC were elevated in RA-CPFE patients compared to healthy controls and positively correlated with RF levels. This study is the first to demonstrate the association of RA-CPFE with high titer of RF and the presence of autoantibodies against HBEC, suggesting a link between autoimmunity to the lung and RA-CPFE.

Objective The objective of this study was to evaluate the clinical significance of carbohydrate antigen (CA) 153 and its correlation with Krebs von den Lungen-6 (KL-6) in the prediction and determination of the severity of interstitial lung disease (ILD) in rheumatoid arthritis (RA) patients. Methods Data was collected retrospectively on a cohort of 357 RA patients who were admitted to our hospital from January 2018 to December 2020. The classification of patients into subgroups was based on high-resolution computed tomography (HRCT) of the chest, resulting in 135 patients with RA but no ILD, 107 patients with RA and indeterminate ILD, 91 patients with RA and mild ILD, and 24 patients with RA and advanced ILD. The levels of CA153 and KL-6 were determined by chemiluminescence analysis. Results The serum levels of CA153 were found to be significantly higher in both the RA-mild ILD group and the RA-advanced ILD group compared to the RA-no ILD group (8.00 vs. 6.40, q = 0.039; 20.30 vs. 6.40, q < 0.001). Multivariate analysis demonstrated that CA153 was an independent risk factor for RA-ILD (RA-mild ILD + RA-advanced ILD) [odds ratio (OR) = 1.124, 95% confidence interval (CI) = (1.060–1.191), p  < 0.001] and RA-advanced ILD (OR = 1.583, 95% CI = 1.247–2.010, p  < 0.001). Furthermore, the receiver operating characteristic (ROC) analysis indicated that CA153 had diagnostic value for both RA-ILD (RA-mild ILD + RA-advanced ILD) and RA-advanced ILD. The best area under ROC curve (AUC) of CA153 for RA-ILD (RA-mild ILD + RA-advanced ILD) was 0.66 ( p  < 0.001; sensitivity = 57.27%; specificity = 72.03%). The AUC of CA153 for RA-advanced ILD was 0.95 ( p  < 0.001; sensitivity = 95.65%; specificity = 83.05%). Moreover, CA153 was negatively correlated with forced vital capacity percent predicted (FVC% pred) ( r = -0.383, p  = 0.037) but positively related to KL-6 ( r  = 0.762, p  < 0.001). Conclusion It was concluded that CA153 was positively associated with KL-6 and might be a significant and clinical availably measurable serum marker to predict the diagnosis and severity of ILD in RA patients.

ObjectivesThis study aims to explore the dynamics of neurological functional disability in patients with intracerebral haemorrhage (ICH) using a multistate Markov model and to investigate the factors influencing the shift in neurological functional disability.DesignA prospective cohort study.SettingElectronic medical record data for adults, from July 2019 and October 2023 in neurosurgery at 27 national centres in China.ParticipantsPatients with ICH with cerebral haemorrhage in the supratentorial parenchyma confirmed by CT of the brain within 48 hours of onset of symptoms. Secondary cerebral haemorrhage due to aneurysm, vascular malformation, haemorrhagic infarction, tumour or coagulation disorders was excluded.Primary and secondary outcome measuresParticipants evaluated neurological functional status through the modified Rankin Scale, which we graded to construct a multistate Markov model.ResultsAfter treatment, patients with ICH who achieve good recovery of neurological function are 2.66 times more likely to transition to a state of no neurological impairment than to severe impairment. Patients in states of no neurological impairment and mild impairment tend to remain relatively stable, while those with severe impairment are at higher risk of transitioning to states that could result in mortality. A person with no disability post-ICH can expect to spend 19.42 (12.87~29.30) months in that state, and 9.99 (8.39~11.89) months in state S2 and 8.87 (7.79~10.09) months in state 3 during their lifetime.ConclusionsIn the year following treatment and discharge, the neurological functional disability of most patients with ICH tends to remain stable. For patients undergoing state transitions, the probability of neurological improvement is higher than the likelihood of deterioration. Risk factors associated with deterioration include advanced age, preonset neurological impairment, a history of cerebrovascular disease, larger haematoma volume, and critical conditions. Patients with these risk factors should receive close monitoring after discharge.