Esophageal squamous-cell carcinoma is a highly prevalent and lethal malignancy, and its tumor ecosystem is complex and poorly understood; therefore, how malignant epithelial states cooperate with stromal fibroblasts to drive tumor progression remains unclear. Here, we constructed a comprehensive single-cell atlas of primary ESCC tumors, which enabled the subsequent identification of thirteen epithelial subpopulations and seven fibroblast subtypes with distinct functional roles and spatial niches. Further trajectory analysis revealed that progenitor-like PLA2G2A+ fibroblasts differentiate hierarchically into tumor-promoting ACTA2+ and MMP1+ subtypes. Notably, SPRR2A+ epithelial cells and MMP1+ fibroblasts exhibited pronounced spatial co-localization, which may imply reciprocal signaling via TGFB1 and IL6, contributing to the observed extracellular matrix remodeling and malignant behavior. Moreover, functional experiments confirmed that SPRR2A promotes ESCC cell migration and invasion. Altogether, our study characterizes a coordinated epithelial-fibroblast corsstalk and a defined fibroblast differentiation hierarchy, offering new mechanistic insights into the ESCC pro-tumorigenic niche.

IntroductionSystematic reviews and meta-analyses serve as the cornerstone of clinical guidelines, yet their validity hinges on the currency of the included evidence. The publication lag measured as the interval from the last search date to online publication remains unclear in top-tier general medical journals and the Cochrane Database of Systematic Reviews (CDSR). Existing data are largely outdated and lack exploration of associated factors. Our study aims to fill this gap by quantifying the current publication lag in top-tier general medical journals and the CDSR and identifying its independent predictors.MethodsThis meta-epidemiological study will analyze interventional, RCT-based meta-analyses published in top-tier general medical journals and the CDSR between 2023 and 2025. We will calculate the publication lag, assess compliance with AMSTAR 2 timeliness standards, and compare the performance between top-tier general medical journals and the CDSR. Multivariable regression analysis will be employed to determine independent factors which associated with the extent of publication delay.DiscussionOur study will systematically quantify the current status and determinants of publication lag in top-tier general medical journals and the CDSR. While our reliance on publicly available dates precludes a granular distinction between author-related revisions and editorial processing durations, this limitation may introduce information bias. Specifically, if certain journals attract more complex reviews requiring extensive author revisions, the observed lag may overstate editorial inefficiency. Conversely, high-performance editorial workflows might mask prolonged author delays. By acknowledging these potential directions of bias, our findings will provide a more nuanced, actionable framework for assessing evidence currency.Systematic review registrationhttps://osf.io/cjtk.

BackgroundNetwork meta-analysis (NMA) can synthesize direct and indirect evidence across multiple interventions and is increasingly used to inform comparative-effectiveness decisions. When randomized controlled trials (RCTs) and non-randomized studies of interventions (NRSI) are jointly analyzed, naïve pooling of design-dissimilar evidence without design-aware modelling may violate exchangeability and distort treatment effect estimates and rankings.Methods and analysisWe will conduct a meta-epidemiological study of published clinical NMAs identified through systematic searches of Ovid MEDLINE(R) ALL, Embase via Ovid, EBM Reviews-Cochrane Database of Systematic Reviews via Ovid, and Web of Science Core Collection. Eligible reports will be full-text articles published between 1 January 2020 and 31 December 2025 that included both RCTs and at least one comparative NRSI in the review evidence base. The primary outcome will be the prevalence of naïve pooling in the main analysis. We will apply a prespecified four-category decision framework to distinguish unacknowledged naïve pooling, acknowledged but unmitigated naïve pooling, naïve main analysis with post hoc quantitative mitigation, and no naïve pooling in the main analysis. We will estimate prevalence with exact binomial 95% confidence intervals, assess whether naïve pooling has become more or less common over time, explore characteristics associated with naïve pooling or with not using quantitative methods to address design-related bias, summarize reporting completeness, protocol or registration availability, prespecification of design-handling methods, and availability of extractable paired alternative results, and evaluate empirical changes in effect direction, null-value crossing or statistical significance, and treatment ranking in articles reporting paired mixed-design and RCT-restricted or design-aware results.DiscussionThis study will provide contemporary evidence on how published NMAs handle mixed randomized and non-randomized evidence, distinguish lack of risk recognition from failure to implement corrective analyses, and quantify how often naïve pooling may change conclusions. The protocol includes prespecified procedures to describe reporting completeness and to compare articles with and without extractable paired alternative analyses. The findings may inform methodological training, journal peer review, and evidence appraisal in guideline development.Systematic review registrationhttps://doi.org/10.17605/OSF.IO/AM2T6, Unique Identifier: 10.17605/OSF.IO/AM2T6.

BACKGROUND AND AIM:The triglyceride-glucose (TyG) index combined with obesity indices (TyG-OIs) predicts the risk of cardiovascular disease (CVD). However, evidence regarding the cumulative exposure to TyG and TyG-OIs, their short-term changes, and their associations with CVD remains limited. This study aims to address these gaps. METHODS AND RESULTS:Using data from the China Health and Retirement Longitudinal Study (CHARLS), which included 2510 participants and 340 incident CVD cases, we calculated seven indices-TyG alone and six TyG-related obesity indices (TyG-OIs)-at baseline (2011-2012) and at Wave 3 (2015). We assessed cumulative exposure using the area under the curve and evaluated short-term changes through K-means clustering. Logistic regression analysis was performed to examine associations. Baseline TyG-WC, TyG-WHtR, TyG-ABSI, and TyG-WWI were significantly associated with CVD. Cumulative exposure to all indices except TyG-BMI showed positive associations, with TyG-WHtR demonstrating the strongest effects (Q2 OR = 1.73, Q3 OR = 1.95, Q4 OR = 1.81). Short-term changes in TyG, TyG-WC, TyG-BMI, TyG-ABSI, and TyG-WWI remained significant. TyG-WC, TyG-ABSI, and TyG-WWI were consistently associated with CVD across all three exposure metrics. CONCLUSION:The association between TyG and TyG-OIs with CVD risk varies depending on the exposure metric used. TyG-WC, TyG-ABSI, and TyG-WWI consistently predict CVD risk across baseline, cumulative, and short-term measures. Repeated monitoring of fasting glucose, triglycerides, waist circumference, ABSI, and WWI may improve long-term CVD risk assessment.

BACKGROUND AND OBJECTIVES:Exacerbations of asthma-chronic obstructive pulmonary disease overlap (EACO) are associated with high mortality, yet the acute-phase heterogeneity remains poorly characterized. This study aimed to identify distinct inflammatory phenotypes of EACO during hospitalization and evaluate their associations with clinical outcomes. METHODS:A prospective two-centre cohort study enrolled 2444 EACO patients (training and validation cohort). Baseline inflammatory markers and clinical data were collected. Unsupervised k-means clustering identified inflammatory phenotypes, with sensitivity analysis excluding demographic variables. In-hospital clinical outcomes (ICU admission, invasive ventilation, in-hospital mortality) were assessed. Logistic regression and causal mediation analysis evaluated phenotype-outcome associations. A nomogram was developed and validated using receiver operating characteristic curves (AUC). RESULTS:Three distinct phenotypes were identified: Cluster T1 (neutrophil-to-lymphocyte ratio [NLR]-elevated hypoeosinophilic systemic inflammatory), Cluster T2 (eosinophilic), and Cluster T3 (eosinophil-neutrophil balanced). Cluster T1 exhibited systemic hyperinflammation (elevated white blood cell count, neutrophils, NLR, C-reactive protein (CRP), procalcitonin (PCT), and interleukin-6 (IL-6)), and the highest composite adverse outcome rate (24.2%; p < 0.001). Logistic regression revealed absolute neutrophil count (β = 0.38, p < 0.001), D-dimer (β = 0.25, p < 0.001), and absolute lymphocyte count (β = -0.41, p < 0.001) as key outcome predictors, confirmed by causal mediation analysis. The nomogram showed robust predictive performance (AUC training = 0.775; validation = 0.766). CONCLUSION:Inflammatory phenotypes during EACO predict differential in-hospital outcomes, with neutrophil-dominant phenotypes conferring the highest risk. Early phenotype-based risk stratification using simple blood biomarkers may guide individualized EACO management.

Background:Hospitalization due to exacerbations of chronic obstructive pulmonary disease (ECOPD) is linked to substantial mortality rates. Objective:This study aimed to identify the clinical and inflammatory phenotypes of patients with ECOPD, as well as to examine their associations with in-hospital outcomes. We sought to explore the underlying mechanisms that contribute to the relationship between ECOPD phenotypes and these outcomes. Methods:A k-means cluster analysis was conducted on 20,890 recruited patients hospitalized for ECOPD. Logistic regression analyses were utilized to evaluate the associations between the identified phenotypes and in-hospital outcomes, such as mortality, invasive mechanical ventilation (IMV), and intensive care unit (ICU) admission. Additionally, a mediation analysis was performed to elucidate the immunoinflammatory mechanisms underlying the relationship between ECOPD phenotypes and in-hospital outcomes. Results:Three distinct phenotypes were identified: Cluster 1 (n=4,944, 23.67%) exhibited a "Female Eosinophilic Phenotype", Cluster 2 (n=10,814, 51.77%) displayed a "Male Eosinophilic Phenotype", and Cluster 3 (n=5,132, 24.57%) presented as an "Geriatric Multimorbidity-Associated Neutrophilic Systemic Inflammatory Phenotype". Clusters 2 and 3 were associated with higher risks of in-hospital mortality (adjusted odds ratio [ORadj]=1.88 and 17.07, respectively) and IMV (ORadj=2.52 and 7.59, respectively) compared to Cluster 1. Patients in Cluster 3 also experienced an extended hospital stay (median of 13 days) and an increased risk of ICU admission (ORadj=7.72). Additionally, blood eosinophils, neutrophils, CRP, and albumin played a mediating role in the relationship between ECOPD phenotypes and the composite outcome. Conclusion:Our study identified three phenotypes stratified by sex, multimorbidity burden, and inflammatory endotypes, which advanced threshold definition for eosinophilic exacerbations and provided prognostic insights for ECOPD management.

Background While obesity is a recognized stroke risk factor, traditional measures like body mass index (BMI) have limitations in assessing body fat distribution. Novel central obesity indices—including waist-to-height ratio (WHtR), body roundness index (BRI), conicity index (CI), a body shape index (ABSI), and weight-adjusted waist index (WWI)—offer accessible alternatives reflecting visceral fat. However, previous studies have often focused on single-time obesity measurements, neglecting how changes over time and their cumulative effects influence stroke risk. Methods This prospective cohort study utilized longitudinal data (2011-2018) from the China Health and Retirement Longitudinal Study (CHARLS). We analyzed 5,896 adults aged ≥45 years without baseline stroke. Seven obesity indices (waist circumference [WC], BMI, WHtR, BRI, CI, ABSI, WWI) were measured at baseline (Wave1, 2011-2012), Wave2 (2013), and Wave 3 (2015). Their longitudinal trajectories from 2012 to 2013 and then to 2015 were modeled using K-means clustering. Their relative change was calculated from 2012 to 2015. Multivariable logistic regression evaluated associations between these obesity measures and incident stroke, adjusting for demographics, lifestyle, and comorbidities. Results As of the 2018 survey, 426 participants (7.23 %) experienced incident strokes. Baseline WC was significantly associated with stroke risk: each 1 cm increase corresponded to a 1 % higher risk (OR =1.01, 95 % CI: 1.001-1.02), and participants in the highest WC quartile had a 37 % greater risk compared to those in the lowest quartile (OR = 1.37; 95 % CI: 1.01–1.87). Other baseline obesity measures did not show significant associations. Regarding recent measurements in 2015, only the second quartile of ABSI was significantly associated with stroke risk (OR = 1.36; 95 % CI: 1.01–1.83 versus the first quartile). Crucially, individuals with a consistently high WC trajectory had a 27 % higher risk of stroke compared to those with a low trajectory (OR = 1.27, 95 % CI: 1.02–1.58). In contrast, relative changes in all indices were not associated with stroke risk. Conclusion Baseline WC and a sustained high WC trajectory are significant predictors of stroke, outperforming other obesity indices. This underscores the critical importance of long-term waist circumference monitoring and management in stroke prevention strategies for middle-aged and older adults.

BackgroundDespite therapeutic advancements, asthma exacerbations (AEs) remain a major clinical challenge, with immune-inflammatory patterns incompletely characterized. Current guidelines lack robust multidimensional tools for predicting in-hospital adverse outcomes.ObjectiveTo develop and validate the Asthma Outcome Risk Index for Hospitalized Patients (AORI-HAP), integrating multidimensional predictors, and investigate immune-inflammatory mechanisms underlying adverse outcomes.MethodsThis real-world cohort study enrolled hospitalized AE patients. Univariate analyses identified associations between multidimensional biomarkers and composite outcome (death, ICU admission, invasive ventilation). LASSO logistic regression derived the AORI-HAP, stratifying patients into risk categories. Mediation analysis elucidated mechanistic contributions to adverse outcomes.ResultsThe AORI-HAP identified five independent predictors of adverse outcomes: elevated neutrophil-to-lymphocyte ratio (NLR > 8.3, OR = 9.26, p < 0.001), increased AST/ALT ratio (>1.41, OR = 3.73, p < 0.001), smoking history ≥10 pack-years (OR = 3.54, p = 0.005), D-Dimer levels ≥5 mg/L (OR = 3.25, p = 0.002), and fasting glucose ≥7 mmol/L (OR = 3.20, p = 0.001). Each 3-point increment in the AORI-HAP score corresponded to an additional hospital day (β = 0.997, 95% CI: 0.78–1.21, p < 0.001), with the model demonstrating strong predictive performance (AUC 0.91, 95% CI 0.86–0.95; sensitivity 90.5%, specificity 69.6%). Mediation analysis revealed that NLR accounted for 26.7% of the total effect linking high-risk status to composite adverse outcome, underscoring its mechanistic relevance.ConclusionAORI-HAP facilitates early risk stratification at admission and personalized management in hospitalized asthma patients. NLR’s mediating role underscores its utility as a predictive biomarker and potential therapeutic target.

Type 2 diabetes mellitus (T2DM) is a progressive disease involving multiple pathophysiologic defects, and combination therapy is often required to achieve and sustain glycaemic control. Triple oral therapy with metformin, dipeptidyl peptidase-4 inhibitors (DPP-4i), and sodium-glucose cotransporter-2 inhibitors (SGLT2i) has demonstrated high and durable glycaemic-lowering efficacy, favourable safety and tolerability, and additional metabolic benefits in T2DM patients with diverse background therapies, including those who are treatment-naïve and those with inadequate control on monotherapy or dual therapy. In light of the increasing clinical use of this triple regimen and the absence of established consensus to guide its use, the Diabetes Committee of the Chinese Research Hospital Association convened an expert panel comprising endocrinologists and evidence-based experts. Through a systematic literature review and a Delphi process, the panel formulated 11 consensus recommendations (8 strong and 3 weak recommendations) on the clinical use of metformin + DPP-4i + SGLT2i, including fixed-dose combination formulations. Safety considerations regarding its use were also described. This consensus aimed to provide clinicians with practical guidance to optimize the effective and safe use of metformin + DPP-4i + SGLT2i in T2DM management.

BACKGROUND:Despite optimal treatment, asthma exacerbations (AEs) can lead to severe adverse events, including mortality. Effective management of comorbidities is critical, as they are common in asthma patients and significantly impact quality of life, healthcare use, and treatment outcomes. Currently, no comprehensive clinical tool exists for assessing and managing these comorbidities during AE. METHODS:We conducted a real-world study involving inpatients with AE. We assessed the risk of in-hospital composite outcome including death, intensive care unit admission, or invasive ventilation, associated with individual comorbidities, comorbidity systems, and the total number of comorbidities. We developed a predictive tool, the Asthma Exacerbation Comorbidity Index (AECI), which incorporates the major comorbidities identified. Patients were categorized into three risk groups based on their AECI scores. RESULTS:Among the 43 comorbidities assessed, nine were significantly associated with the composite outcome. Each additional comorbidity increased the risk of the composite outcome by 25% (95% CI, 16.5%-34.1%; P < 0.001). The most prevalent comorbidity systems were the endocrine (51.7%), respiratory (50.9%), and cardiovascular (43.3%) systems, with 54.1% of patients exhibiting multiple comorbidity systems. The AECI exhibited an area under the curve (AUC) of 75.98%. A one-point increase in the AECI was associated with a 0.51-fold increase in the risk of composite outcome (95% CI, 0.41-0.62; P < 0.001). CONCLUSION:The high prevalence of comorbidities among patients with AEs is associated with a poorer prognosis. The AECI proves to be a valuable tool to assess comorbidities, enabling clinicians to identify inpatients at higher risk of adverse in-hospital events and to make informed treatment decisions.

Chronic kidney disease represents a significant global health burden. Exposure to environmental endocrine-disrupting chemicals, particularly heavy metals and phthalate metabolites, is increasingly associated with renal dysfunction. However, previous research has primarily focused on individual chemicals, leaving a gap in understanding the health effects of real-world co-exposure to complex mixtures of these contaminants. We applied several statistical analysis methods (including multivariable logistic regression, restricted cubic splines regression, quantile g-computation, and Bayesian kernel machine regression) to examine data from 6902 adults participating in the National Health and Nutrition Examination Survey between 2005 and 2018. Lead (Pb) and cadmium were consistently associated with an increased risk of impaired renal function across all models. Pb exhibited a U-shaped exposure-response relationship. Mercury was not significantly associated with renal impairment. Among phthalates metabolites, mono-(2-ethyl-5-oxohexyl) phthalate was associated with an increased risk, whereas mono-(2-ethyl)hexyl phthalate was linked to a reduce risk. In mixture analyses, metals predominated the overall nephrotoxic associations (Bayesian kernel machine regression group PIP = 0.997), with Pb identified as the primary contributor. Significant interactions were observed between Pb and other metals, as well as several phthalate metabolites. Pb and cadmium are associated with nephrotoxicity, and their combined effects may be amplified when present in mixtures. Phthalates exhibit metabolite-specific associations and primarily act as effect modifiers. Regulatory frameworks must transition from single-chemical assessments to cumulative risk assessment paradigms to effectively address real-world co-exposures.

This systematic review aimed to systematise the different models used to deliver pulmonary rehabilitation (PR) during chronic respiratory diseases (CRDs) and explore which ones are the most effective in terms of dyspnea, exercise capacity, and health-related quality of life (HRQoL). The literature search strategy involved structured searches of PubMed, Web of Science, and Cochrane Library for relevant articles published from January 2013 to March 2025. The risk of bias was assessed using ROB 2.0. Descriptive analysis and meta-analysis were performed. Forest plots and the node-splitting model presented results. Network meta-analysis was conducted in R 4.3.2. 33 studies(n = 2538) were included in this review and of those, 27 studies(n = 2106) were used for meta-analysis. 22 (66.7

Background : Asthma poses substantial global health challenges due to its variable clinical manifestations and unmet needs in early risk stratification. Current prediction models lack generalizability for those with susceptibility, particularly when early symptoms are nonspecific. A rigorous synthesis of existing models for adult asthma is needed to evaluate their validity, prioritize predictors, and guide targeted prevention strategies. Objective : This study aims to synthesize early asthma prediction models in undiagnosed populations, evaluating their performance metrics and clinical utility to try defining "pre-asthma" by integrating multidimensional predictors, specifically demographic, genetic, environmental, phenotypic/endotypic biomarkers, and symptom trajectories. Methods: Following the CHARMS framework, we will systematically search PubMed, Web of Science, Embase, Cochrane Library, Scopus and IEEE Xplore (inception–April 2025) for studies developing or externally validating adult asthma prediction models. Data extraction and risk of bias assessment (by PROBAST and TRIPOD criteria) will be performed independently by two reviewers. Meta-analysis using random-effects models will synthesize the performance measures, with heterogeneity explored by meta-regression. Methodological rigor and clinical relevance of predictors will be evaluated to establish evidence-based recommendations and used to define "pre-asthma". Study registration number : CRD420251047047

BACKGROUND:Exacerbations of asthma-bronchiectasis overlap syndrome (ABOS) are clinically heterogeneous, with poorly defined inflammatory phenotypes and their links to outcomes. OBJECTIVE:To identify phenotypes in ABOS exacerbations and their associations with in-hospital outcomes. METHODS:In this prospective study, 343 patients with ABOS exacerbation were clustered using multidimensional data; findings were validated in 147 independent patients. Associations between phenotypes and outcomes (Intensive Care Unit [ICU] admission, invasive mechanical ventilation [IMV], mortality) were analyzed via multivariable regression. RESULTS:Three phenotypes were identified: female-paucigranulocytic (Cluster T1), young male-eosinophilic (Cluster T2), and neutrophilic-lymphopenic (Cluster T3). Cluster T3 had the highest risks of ICU admission (adjusted relative risk [RRadj] = 7.84, 95% CI: 2.21-27.78), IMV (RRadj=7.84, 95% CI: 2.21-27.78), and mortality (RRadj=6.86, 95% CI: 2.33-37.67). Neutrophilia showed a dose-dependent association with adverse outcomes (Ptrend<0.001), with elevated levels independently predicting composite outcomes (RRadj=2.06, 95% CI: 1.42-3.03). CONCLUSIONS:ABOS exacerbations exhibit distinct inflammatory phenotypes. The neutrophilic-lymphopenic phenotype strongly predicts in-hospital adverse outcomes, highlighting its potential for acute risk stratification in hospitalized patients.

BACKGROUND:There is ongoing uncertainty in comparing surgical and nonsurgical therapies, with or without systemic options, in heterogeneous early-stage non-small cell lung cancer without lymph node involvement (eNSCLC-N0). MATERIALS AND METHODS:We conducted an integrated evidence synthesis of prospective randomized controlled trials (RCTs) and non-RCTs, covering four databases through September 1, 2024. Treatment effects were evaluated using single-arm, pair-wise, and Bayesian random-effects network meta-analyses. Primary outcomes were overall survival and disease-free survival (DFS); secondary outcomes included recurrence and grade ≥3 adverse events. RESULTS:This report included 31 clinical trials (24 RCTs) with 12 049 patients. In the network analyses, adjuvant targeted therapy (ATKI) (rank 1) significantly improved DFS compared with mixed radical resection (hazard ratio [HR], 0.21; 95% confidence interval [CI], 0.05-0.90; rank 14; GRADE, very low) in the overall population. For patients with wild-type/unknown EGFR status, stereotactic body radiation therapy (SBRT) plus immune checkpoint inhibitors (rank 1) showed DFS benefit over SBRT alone (HR, 0.17; 95% CI, 0.03-0.83; rank 3; GRADE, high) and was non-inferior to adjuvant platinum-based chemotherapy (HR, 0.18; 95% CI, 0.02-1.65; rank 2; GRADE, very low). CONCLUSION:These findings suggest the combination of systemic therapies, such as surgery plus ATKI or SBRT plus immunotherapy, superior approaches for patients with eNSCLC-N0 depending on the genomic mutation status and patient tolerability.

Background:Hypofibrinogenemia in cardiac surgery increases bleeding risk, but the efficacy and safety of fibrinogen concentrate vs. cryoprecipitate remain unclear. This meta-analysis compares the patient-important outcomes associated with the use of fibrinogen concentrate vs. cryoprecipitate for the management of acquired hypofibrinogenemia in cardiac surgery. Methods:Medline, Embase, Cochrane Library, and Transfusion Evidence Library were searched from their inception until June 2024. Eligible studies included randomized clinical trials (RCTs). Effect estimates were synthesized using risk ratios (RR) and standardized mean differences (SMD), along with their corresponding 95% confidence intervals (CIs). Results:We analyzed 4 RCTs (945 participants: 823 adults, 122 children) comparing fibrinogen concentrate with cryoprecipitate undergoing cardiac surgery. Meta-analysis showed no difference in mortality (RR = 1.25, 95% CI: 0.79-1.96; moderate GRADE), blood loss (SMD = -0.14, 95% CI: -0.46-0.18), transfusion rates (blood cells: RR = 0.98, 0.77-1.26; platelets: RR = 0.17, 0.02-1.40; fresh frozen plasma: RR = 0.48, 0.16-1.45; cryoprecipitate: RR = 1.02, 0.58-1.81), infections (RR = 0.91, 0.64-1.28), volume overload (RR = 1.95, 0.18-21.34), transfusion reactions (RR = 0.98, 0.06-15.54), or postoperative thrombosis (RR = 0.76, 0.47-1.22). No allergic reactions were reported. Subgroup analysis revealed substantial heterogeneity (I2 = 0% to 98%) in most outcome measures between adults and children. Using the GRADE criteria, we assessed the quality of the evidence for mortality as moderate, whereas the quality of evidence for other outcomes was judged to be low. Conclusions:For patients undergoing cardiac surgery who experience clinically significant bleeding and hypofibrinogenemia, the available trial data provide moderate evidence that fibrinogen concentrate, compared to cryoprecipitate, does not increase the short-term risk of all-cause mortality. However, for the rate of transfusion of allogeneic or individual blood components, and adverse events, the existing evidence is of low certainty. Given the relatively small sample size, the group of children may not be representative of all children. Systematic Review Registration:(https://www.who.int/clinical-trials-registry-platform), identifier CRD42023421670.

This study aimed to analyze the associations between depressive and anxiety symptoms and risk of incident kidney failure in patients with biopsy-proven diabetic nephropathy (DN). This retrospective study enrolled 241 type 2 diabetic patients with biopsy-proven DN. Huaxi Emotional-Distress Index (HEI) was used to evaluate the depression and anxiety status of patients on admission. According to the HEI score, DN patients were divided into HEI score ≤ 8 group (without depression and anxiety) and HEI score > 8 group (with depression and anxiety). The study endpoint was defined as progression to kidney failure. The cox proportional hazard analysis was performed to investigate the risk factors for progression to kidney failure in DN patients. Twenty-three patients had HEI score > 8, accounting for about 9.5

Background: With the exponential growth of publications in the field of investigator-initiated research/trials (IIRs/IITs), it has become necessary to employ text mining and bibliometric analysis as tools for gaining deeper insights into this area of study. By using these methods, researchers can effectively identify and analyze research topics within the field. Methods: This study retrieved relevant publications from the Web of Science Core Collection and conducted bioinformatics analysis. The latent Dirichlet allocation model, which is based on machine learning, was utilized to identify subfield research topics. Results: A total of 4315 articles related to IIRs/IITs were obtained from the Web of Science Core Collection. After excluding duplicates and articles with missing abstracts, a final dataset of 3333 articles was included for bibliometric analysis. The number of publications showed a steady increase over time, particularly since 2000. The United States, Germany, the United Kingdom, the Netherlands, Canada, Denmark, Japan, Switzerland, and France emerged as the most productive countries in terms of IIRs/IITs. The citation analysis revealed intriguing trends, with certain highly cited articles showing a significant increase in citation frequency in recent years. A model with 45 topics was deemed the best fit for characterizing the extensively researched fields within IIRs/IITs. Our analysis revealed 10 top topics that have garnered significant attention, spanning domains such as community health, cancer treatment, brain development and disease mechanisms, nursing research, and stem cell therapy. These top topics offer researchers valuable directions for further investigation and innovation. Additionally, we identified 12 hot topics, which represent the most cutting-edge and highly regarded research areas within the field. Conclusion: This study contributes to a comprehensive understanding of the current research landscape and provides valuable insights for researchers working in this domain.

Background An improper host immune response to Mycoplasma pneumoniae generates excessive inflammation, which leads to the impairment of pulmonary ventilation function (PVF). Azithromycin plus inhaled terbutaline has been used in the treatment of Mycoplasma pneumoniae pneumonia (MPP) in children with impaired pulmonary function, but previous randomized controlled trials (RCTs) showed inconsistent efficacy and safety. This study is aimed to firstly provide a systematic review of the combined therapy. Methods This study was registered at the International Prospective Register of Systematic Reviews (PROSPERO CRD42023452139). A PRISMA-compliant systematic review and meta-analysis was performed. Six English and four Chinese databases were comprehensively searched up to June, 2023. RCTs of azithromycin sequential therapy plus inhaled terbutaline were selected. The revised Cochrane risk of bias tool for randomized trials (RoB2) was used to evaluate the methodological quality of all studies, and meta-analysis was performed using Stata 15.0 with planned subgroup and sensitivity analyses. Publication bias was evaluated by a funnel plot and the Harbord' test. Certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluation recommendations. Results A total of 1,938 pediatric patients from 20 RCTs were eventually included. The results of meta-analysis showed that combined therapy was able to significantly increase total effectiveness rate (RR = 1.20, 95%CI 1.15 to 1.25), forced expiratory volume in one second (SMD = 1.14, 95%CIs, 0.98 to 1.29), the ratio of forced expiratory volume in one second/forced vital capacity (SMD = 2.16, 95%CIs, 1.46 to 2.86), peak expiratory flow (SMD = 1.17, 95%CIs, 0.91 to 1.43). The combined therapy was associated with a 23% increased risk of adverse reactions compared to azithromycin therapy alone, but no significant differences were found. Harbord regression showed no publication bias (P = 0.148). The overall quality of the evidence ranged from moderate to very low. Conclusions This first systematic review and meta-analysis suggested that azithromycin sequential therapy plus inhaled terbutaline was safe and beneficial for children with MPP. In addition, the combined therapy represented significant improvement of PVF. Due to lack of high-quality evidence, our results should be confirmed by adequately powered RCTs in the future.