Inappropriate use of antibiotics is a significant factor contributing to secondary invasive fungal infection (IFI) in patients with sepsis in the intensive care unit (ICU). Our study aimed to evaluate the relationship between the number of antibiotic types use and the risk of IFI in ICU sepsis patients. This retrospective study included adult sepsis patients admitted to the ICU of a large tertiary hospital from 2014 to 2023. Multivariate logistic regression was used to measure the adjusted correlation between the number of types of antibiotics used and the risk of IFI, as well as the simultaneous combined use of antibiotics. Among the 768 patients ultimately included in the study, 165 (21.5

Timely administration of antibiotics is critical in the management of infectious diseases, particularly in preventing progression to sepsis. Despite the urgency, the appropriate timing of antibiotic treatment, especially in non-septic infections, remains unclear. This study aimed to assess the association between antibiotic timing and progression to sepsis among patients admitted to the Emergency Department (ED) for suspected infection. A retrospective cohort study utilized data from three tertiary-care hospital EDs between January 2021 and June 2023. Adult patients hospitalized for clinical infection were included. The primary outcome was sepsis development, while secondary outcomes included hospital mortality, Intensive Care Unit (ICU) admission, ICU length of stay (LOS), and hospital LOS. The main exposure was the duration from ED arrival to initial antibiotic administration. Multivariable logistic and negative binomial regression were employed to adjust for confounders and assess associations. The study included 1279 infected adult patients, with 20.5

Background Venous thromboembolism (VTE), which includes deep vein thrombosis (DVT) and pulmonary embolism (PE), significantly contributes to morbidity and mortality among hospitalized patients. Despite the existence of various VTE risk assessment models (RAMs), their performance in accuracy, sensitivity and specificity remain suboptimal, highlighting opportunities to improve predictive accuracy for clinical decision-making. Methods We conducted a retrospective multicenter study involving three hospitals, which enrolled patients with VTE from January 1, 2021, to December 30, 2023. A novel RAM (Weng score) was developed through three different strategies: clinical knowledge-driven model (Model A), data-driven model (Model B), and decision tree-based model (Model C). The primary outcome was in-hospital VTE. Prediction of PE alone was examined as a secondary outcome. Model performance was evaluated through discrimination, calibration, precision, and decision curve analysis (DCA). Results A total of 1,791 patients were analyzed, with 680 VTE events recorded during hospitalization. The Weng score, derived from Model A, demonstrated superior predictive performance for VTE and PE compared to existing RAMs, with an area under the receiver operating characteristic curve (AUROC) of 0.895 (95% confidence interval (CI) [0.880–0.909]) for VTE and 0.877 (95% CI [0.851–0.903]) for PE. In comparison, the AUROCs for existing RAMs (Caprini, Padua, Wells, Geneva, and Autar scores) ranged from 0.687 to 0.789 for VTE prediction and from 0.682 to 0.769 for PE prediction. The Weng score also demonstrated excellent calibration and discrimination, outperforming the Caprini, Padua, Wells, Geneva, and Autar scores in hospitalized patients. The Weng score’s clinical utility for relative risk stratification was further supported by DCA within this case-control sampled cohort, showing a higher net benefit in predicting VTE and PE than existing RAMs. Conclusions We developed and internally validated the Weng score using retrospective data from Chinese hospitals. While it showed more favorable calibration and discrimination than existing RAMs in our cohort, external validation in diverse settings and prospective studies accounting for anticoagulation management are essential before clinical adoption. The Weng score is intended for VTE risk stratification only; clinical decisions regarding thromboprophylaxis should integrate both VTE and bleeding risk assessments using validated tools. Because the current model was derived from a case-control sampled cohort (oversampled VTE events), the absolute risk estimates and net benefit findings reflect relative risk ranking and require external calibration in a representative prospective cohort before any clinical implementation.

Pangenomes are revolutionizing our ability to resolve genomic regions with complex variations1. However, existing human pangenomes2,3, constrained by small sample sizes, provide limited utility for medical and population genetic applications. Here we generated 1,116 diploid genome assemblies (55 de novo and 1,061 pangenome-informed) with an average size of 2.98 Gb and a mean quality value of 46 as part of the 1000 Chinese Pangenome (1KCP) project. On the basis of these assemblies, we constructed a pangenome comprising 405.3 million base pairs of sequences absent from the current references GRCh38 and CHM13, including 26.2 million base pairs of functional genic and predicted regulatory elements. We catalogued a full spectrum of genetic variation, including 35.4 million small variants, 110,530 structural variants (SVs), 485,575 tandem repeats (TRs) and 0.86 million nested variants embedded in non-reference sequences. This extensive dataset enabled detailed characterization of multiscale genic variations relevant to medical genetics, including gene-altering SVs, TR expansions, gene cluster variations and HLA gene haplotypes. Coupled with the 1KCP gene expression data, we conducted pan-variant expression quantitative trait locus (eQTL) mapping to analyse diverse variant types. We identified 3,256 eQTLs involving complex variants (SVs, TRs and nested variants) and elucidated their regulatory complexity. Finally, we developed a 1KCP pan-variant imputation reference panel, which provides multitype genetic markers to enhance the resolution of future association studies. This resource advances our understanding of complex variants and their functional implications to provide new insights into human health.

Background Pulmonary arterial hypertension (PAH) in children and adolescents is a significant global health challenge, leading to a range of severe medical complications and an increased risk of premature death. In this study, we assessed the trends and cross-country disparities in the burden of PAH among children and adolescents from 1990 to 2021, and further predicted its changes to 2050. Results GBD 2021 estimated 5,049 incident cases, 1,972 deaths, and 170,371 DALYs of PAH in children and adolescents globally in 2021. South Asia reported the highest numbers of incident, death, and DALYs cases, while Eastern Sub-Saharan Africa had the highest age-standardized incidence rate (ASIR), and the Caribbean recorded the highest age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR). Between 1990 and 2021, the ASIR in this population showed an overall increasing trend, whereas the ASMR and ASDR demonstrated a consistent decline. The ASIR, ASMR, and ASDR were found to decrease exponentially with rising SDI levels. DALYs were disproportionately concentrated in countries with lower sociodemographic development levels. The ASIR is projected to remain globally stable, while both the ASMR and ASDR are expected to decline annually through 2050. Conclusions The burden of PAH in children and adolescents is concentrated in low-SDI countries. While ASIR has increased, ASMR and ASDR have steadily declined and are projected to continue decreasing through 2050. Strengthening international collaboration, improving healthcare, and targeting high-risk regions are crucial to reducing the disease burden and promoting global health equity.

Recursive splice sites are rare motifs postulated to facilitate splicing across massive introns and shape isoform diversity, especially for long, brain-expressed genes. The necessity of this unique mechanism remains unsubstantiated, as does the role of recursive splicing (RS) in human disease. From analyses of rare copy number variants (CNVs) from almost one million individuals, we previously identified large, heterozygous deletions eliminating an RS site (RS1) in the first intron of CADM2 that conferred substantial risk for attention deficit hyperactivity disorder (ADHD) and other neurobehavioral traits. CADM2 encodes a neuronally expressed cell adhesion molecule that has repeatedly been associated with ADHD and numerous similar traits. To explore the molecular impact of RS ablation in CADM2 , we used CRISPR to model patient deletions and to target a smaller region (~500 base pairs) containing RS1 in both human induced neurons (iNs) and rats. Transcriptome analyses in unedited iNs provided a catalog of CADM2 transcripts, including novel transcripts that retained RS exons. Intriguingly, ablating RS1 altered the gradient of RNA abundance across the first intron of CADM2 , decreased the level of CADM2 expression, and impacted transcript usage. Decreased CADM2 expression was reflected in reduced exon usage downstream of the RS1 site and global alteration to genes involved in neuronal processes including synapse and axon development. Given the scale of our analyses and the widespread association of CADM2 with neurobehavioral traits, we sought to validate these findings using in vivo models and found that rodent models harboring Cadm2 RS1 deletions exhibited significant changes in relevant behaviors and functional brain connectivity. In summary, our analyses demonstrate a functional role for RS as a noncoding regulatory mechanism in a gene associated with a spectrum of neuropsychiatric and behavioral traits.

Senescent alveolar epithelial cells (AEC) play a pivotal role in the progression of idiopathic pulmonary fibrosis (IPF), attracting increasing attention from researchers. Central to the pathogenesis of pulmonary fibrosis (PF) is the excessive deposition of extracellular matrix (ECM). However, there remains a significant gap in understanding how the ECM microenvironment influences senescence in type II alveolar epithelial cells (AEC II). This study investigates the activation of the integrin-β1/FAK/YAP signaling pathway and its role in inducing cellular senescence in both in vivo and in vitro models of bleomycin (BLM)-induced PF. We employed decellularized lung scaffolds (DLS) to replicate the natural ECM microenvironment, aiming to elucidate whether the fibrotic ECM promotes AEC II senescence through the integrin-β1/FAK/YAP pathway. Notably, our findings indicate that exogenous integrin-β1 does not induce AEC II senescence. This suggests that the fibrotic ECM microenvironment regulates AEC II senescence via the integrin-β1/FAK/YAP pathway independently of exogenous integrin-β1. Therefore, targeting alterations in the fibrotic ECM microenvironment may represent a promising therapeutic strategy for IPF by modulating AEC II senescence.

Early detection and intervention of precancerous lesions are crucial in reducing cancer morbidity and mortality. Comprehensive analysis of genomic, transcriptomic, proteomic and epigenomic alterations can provide insights into the early stages of carcinogenesis. However, the lacke of an integrated, well-curated data resource of molecular signatures limits our understanding of precancerous processes. Here, we introduce a comprehensive PreCancerous Molecular Resource (PCMR), which compiles 25,828 molecular profiles of precancerous samples paired with normal or malignant counterparts. These profiles cover precancerous lesions of 35 cancer types across 20 organs and tissues, derived from tissue samples, liquid biopsies, cell lines and organoids, with data from transcriptomics, proteomics and epigenomics. PCMR includes 62,566 precancer-gene associations derived from differential analysis and text-mining using the ChatGPT large language model. We examined PCMR dataset reliability and significance by the authoritative precancerous molecular signature, along with its biological and clinical relevance. Overall, PCMR will serve as a valuable resource for advancing precancer research and ultimately improving patient outcomes.

The complexity and variability of high-resolution pathological images present significant challenges in computational pathology. While AI-driven pathology foundation models have advanced the field, they require large-scale datasets, substantial storage, and significant computational resources, as well as rigorous validation for clinical applicability. We present PathOrchestra, a versatile pathology foundation model trained on 287,424 slides from 21 tissue types across three centers. Evaluated on 112 tasks from 61 private and 51 public datasets, covering digital slide preprocessing, pan-cancer classification, lesion identification, multi-cancer subtype classification, biomarker assessment, gene expression prediction, and structured report generation. Across 27,755 whole slide images and 9,415,729 region-of-interest images, it achieved over 0.950 accuracy in 47 tasks, including pan-cancer classification, lymphoma subtyping, and bladder cancer screening. It is the first to generate structured reports for colorectal cancer and lymphoma. Overall, PathOrchestra demonstrates the clinical readiness of large-scale self-supervised pathology foundation models, achieving high accuracy and offering potential to digital medicine integration.

BackgroundChaihu Longgu Muli Decoction (CLM) is a classical herbal formula originally documented in Shang Han Lun. With an 1800-year clinical history, CLM remains widely prescribed for depression (“Yu Zheng” in Traditional Chinese Medicine theory). Emerging evidence suggests that chronic stress-induced depression is closely linked to lung cancer progression and metastasis. However, the therapeutic potential of CLM in this context remains unexplored.MethodsA lung cancer cell xenograft model combined with chronic unpredictable mild stress (CUMS) was used to evaluate the effect of CLM on lung cancer growth. Proteomic analysis was performed to explore the underlying mechanisms by which CLM alleviates CUMS-induced lung cancer progression. Western blot and qPCR were conducted to detect changes in Rap1/ERK-mediated epithelial-mesenchymal transition (EMT) progression. Finally, Rap1 agonists were utilized to determine the therapeutic mechanism of CLM on cortisol or corticosterone (Cort)-induced EMT progression in lung cancer cells and a mouse lung cancer model.ResultsIn our study, CUMS promoted lung cancer xenograft growth, increased the expression of the proliferation marker Ki67, and elevated serum Cort levels. CLM treatment not only alleviated CUMS-induced depression-like behaviors, but also suppressed stress-driven tumor growth. These effects were replicated in a urethane-induced lung cancer model combined with CUMS. Proteomic analysis revealed that CLM’s anti-tumor effects were associated with modulation of the Rap1 pathway. Mechanistically, CUMS downregulated Rap1GAP, activating Rap1 and subsequent ERK1/2 phosphorylation, thereby promoting EMT in lung cancer tissues. CLM effectively reversed these effects by inhibiting Rap1/ERK-mediated EMT. In vitro, CLM suppressed cortisol-induced migration, invasion, and EMT in lung cancer cells, and these effects were attenuated by Rap1 agonists. Furthermore, CLM inhibited Cort-induced EMT and depression-like behaviors in vivo, while Rap1 activation diminished CLM’s efficacy against Cort-driven tumor growth.ConclusionThese findings suggest that Rap1/ERK-mediated EMT is a hallmark of chronic stress-associated lung cancer progression. CLM exerts its therapeutic effects by targeting this pathway, offering a novel strategy to mitigate stress-aggravated oncogenesis.

Invasive fungal infections (IFI) represent a significant contributor to mortality among sepsis patients in the Intensive Care Unit (ICU). Early diagnosis of IFI is challenging, and currently, there are no predictive tools for identifying sepsis patients who may develop IFI. Our study aims to develop a predictive scoring system to assess the risk of IFI in patients with sepsis admitted to the ICU. A retrospective collection of data from a total of 549 patients was conducted. Data-driven, clinically knowledge-driven, and decision tree models were used to identify predictive variables for risk of IFI in ICU patients with sepsis. Demographic data, vital signs, laboratory values, comorbidities, medication use, and clinical outcomes were all collected. The optimal model was selected based on model performance and clinical utility to establish a risk score. Among adult patients with sepsis admitted to the ICU, 127 patients (23.1

BACKGROUND:The influence of anesthesia type and duration on the occurrence of pulmonary embolism (PE) after surgery remains controversial. This study investigates the association between anesthesia type and duration with postoperative PE. METHODS:A retrospective cohort of adult patients undergoing surgery from May 2020 to August 2024 at large-scale general hospitals was analyzed. Multivariable logistic regression models were employed to adjust for potential confounders, and sensitivity analyses (using overlap weighting and array approach) were performed to validate the findings. RESULTS:A total of 178,052 patients were included in the analysis, of whom 91 developed PE after surgery. The median duration of general anesthesia (GA) was 1.72 h, with an interquartile range (IQR) of 1.17-2.52 h. The median duration of regional anesthesia was 1.54 h, with an IQR of 1.20-2.03 h. Anesthesia type and the duration of regional anesthesia were not associated with PE occurrence (adjusted odds ratio [aOR] [95% confidence interval, CI], 1.148 [0.671-2.098], p = 0.631), (aOR [95% CI], 1.117 [0.498-1.557], p = 0.738). The rates of PE consistently increased with GA prolongation (aOR [95% CI], 1.308 [1.176-1.432], p < 0.001). Compared with GA durations < 3 h, prolonged anesthesia was significantly associated with increased PE incidence (aOR [95% CI], 4.398 [2.585-7.565], p < 0.001). These findings were also confirmed by sensitivity analyses. CONCLUSIONS:Our study demonstrates that prolonged GA, particularly > 3 h, significantly increases the risk of PE.

OBJECTIVE:The objective of this study was to evaluate risk assessment models (RAMs) for venous thromboembolism (VTE) in surgical inpatients. BACKGROUND:VTE significantly contributes to morbidity and mortality among surgical inpatients, with the postoperative period being particularly vulnerable. Accurate risk assessment is essential for guiding thromboprophylaxis. Although various RAMs have been developed, their comparative effectiveness in surgical populations remains unclear. METHODS:This retrospective cohort study, SURG-VTE, was conducted across four centers from 2020 to 2022. This study evaluated the predictive performance of six RAMs: Caprini, Padua, Wells, Geneva, Autar, and IMPROVE scores. The primary outcome was objectively confirmed symptomatic VTE. The association between RAMs and VTE was examined using logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to assess each model's discrimination. Calibration was assessed using the GiViTI calibration belt, while overall performance was quantified by the Brier score. Decision Curve Analysis (DCA) was performed to evaluate the clinical utility of the RAMs. Sensitivity and subgroup analyses were conducted to further assess the models' performance. RESULTS:Of the 4851 surgical inpatients, 826 (17.0%) experienced VTE, with significant differences in VTE rates between high- and low-risk groups as classified by most RAMs. However, the overall discriminative performance of the RAMs was poor, with AUCs ranging from 0.594 for the Geneva score to 0.713 for the Padua score. Sensitivity was highest for the Autar score (70.5%) and specificity for the Wells score (99.2%). The clinical utility of RAMs was further questioned as the positive net benefit was suboptimal for all models. Similar results were observed in sensitivity and subgroup analyses. CONCLUSIONS:While RAMs can distinguish between high- and low-risk groups for VTE, but show poor discrimination, limited precision, and suboptimal calibration (except IMPROVE), suggesting the need for more reliable and clinically relevant VTE risk prediction strategies in surgical care. TRIAL REGISTRATION CLINICALTRIALS.GOV: NCT06502600.

The objective of this study is to investigate the associated risk factors of pulmonary infection in individuals diagnosed with chronic kidney disease (CKD). The primary goal is to develop a predictive model that can anticipate the likelihood of pulmonary infection during hospitalization among CKD patients. This retrospective cohort study was conducted at two prominent tertiary teaching hospitals. Three distinct models were formulated employing three different approaches: (1) the statistics-driven model, (2) the clinical knowledge-driven model, and (3) the decision tree model. The simplest and most efficient model was obtained by comparing their predictive power, stability, and practicability. This study involved a total of 971 patients, with 388 individuals comprising the modeling group and 583 individuals comprising the validation group. Three different models, namely Models A, B, and C, were utilized, resulting in the identification of seven, four, and eleven predictors, respectively. Ultimately, a statistical knowledge-driven model was selected, which exhibited a C-statistic of 0.891 (0.855–0.927) and a Brier score of 0.012. Furthermore, the Hosmer–Lemeshow test indicated that the model demonstrated good calibration. Additionally, Model A displayed a satisfactory C-statistic of 0.883 (0.856–0.911) during external validation. The statistical-driven model, known as the A-C2GH2S risk score (which incorporates factors such as albumin, C2 [previous COPD history, blood calcium], random venous blood glucose, H2 [hemoglobin, high-density lipoprotein], and smoking), was utilized to determine the risk score for the incidence rate of lung infection in patients with CKD. The findings revealed a gradual increase in the occurrence of pulmonary infections, ranging from 1.84

Pulmonary fibrosis (PF) results from excessive extracellular matrix (ECM) deposition and tissue remodeling after activation of fibroblasts into myofibroblasts. Abnormally deposited fibrotic ECM, in turn, promotes fibroblast activation and accelerates loss of lung structure and function. However, the molecular mediators and exact mechanisms by which fibrotic ECM promotes fibroblast activation are unclear. In a bleomycin-induced PF mouse model, we found Galectin-1 (Gal-1) expression was significantly increased in lung tissue, and overexpression of Gal-1 plasmid-transfected fibroblasts were activated into myofibroblasts. Using the decellularization technique to prepare decellularized fibrotic ECM and constructing a 3D in vitro co-culture system with fibroblasts, we found that decellularized fibrotic ECM induced a high expression of Gal-1 and promoted the activation of fibroblasts into myofibroblasts. Therefore, Gal-1 has been identified as a pivotal mediator in PF. Further, we found that decellularized fibrotic ECM delivered mechanical signals to cells through the Gal-1-mediated FAK-Src-P130Cas mechanical signalling pathway, while the CYP450 enzymes (mainly involved in CYP1A1, CYP24A1, CYP3A4, and CYP2D6 isoforms) acted as a chemical signalling pathway to receive mechanical signals transmitted from upstream Gal-1, thereby promoting fibroblast activation. The Gal-1 inhibitor OTX008 or the CYP1A1 inhibitor 7-Hydroxyflavone prevented PF in mice and inhibited the role of fibrotic ECM in promoting fibroblast activation into myofibroblasts, preventing PF. These results reveal novel molecular mechanisms of lung fibrosis formation and identify Gal-1 and its downstream CYP1A1 as potential therapeutic targets for PF disease treatmnts.

Background Irreversible pulmonary fibrosis induced by paraquat is the most prevalent cause of death in patients with paraquat poisoning. Pulmonary fibrosis is characterized by abnormal deposition of extracellular matrix (ECM). Currently, the role of fibrotic ECM microenvironment in paraquat-induced pulmonary fibrosis has not been established. Methods Rat pulmonary fibrosis model was induced by paraquat, ATN-161 (an integrin-β1 antagonist) was given to investigate their effect on Rat survival and pulmonary fibrosis. Lungs were decellularized to generate normal and fibrotic acellular ECM scaffolds using Triton and SDS. Fibroblasts were cocultured with ECM scaffolds to established 3D culture systems to investigate the relationship between fibrotic ECM and the differentiation of fibroblasts. Then we explored the effect of fibrotic ECM microenvironment systematically promoting on integrin-β1/FAK/ERK1/2 pathway and established 3D culture systems to investigate the relationship between fibrotic ECM and the differentiation of fibroblasts. Results Antagonism of integrin-β1 could alleviate paraquat-induced pulmonary fibrosis and ameliorate survival status of rats. Compared to normal ECM, fibrotic extracellular microenvironment promoted the differentiation of fibroblasts to myofibroblasts. Antagonism of integrin-β1 could also ameliorate the promotion of fibrotic extracellular microenvironment on differentiation of fibroblasts to myofibroblasts. Fibrotic ECM microenvironment promotes fibroblasts transforming into myofibroblasts through integrin-β1/FAK/ERK1/2 signaling pathway. Moreover, this phenomenon holds independent on exogenous integrin-β1. Conclusions Activation of integrin-β1/FAK/ERK1/2 pathway aggravates paraquat-induced pulmonary fibrosis depend on fibrotic ECM and integrin-β1 may be a prospective therapeutic target for paraquat-induced pulmonary fibrosis in the future.

BACKGROUND:The performance of host immune responses biomarkers and clinical scores was compared to identify infection patient populations at risk of progression to sepsis, ICU admission and mortality. METHODS:Immune response biomarkers were measured and NEWS, SIRS, and MEWS. Logistic and Cox regression models were employed to evaluate the strength of association. RESULTS:IL-10 and NEWS had the strongest association with sepsis development, whereas IL-6 and CRP had the strongest association with ICU admission and in-hospital mortality. IL-6 [HR (95%CI) = 2.68 (1.61-4.46)] was associated with 28-day mortality. Patient subgroups with high IL-10 (≥ 5.03 pg/ml) and high NEWS (> 5 points) values had significantly higher rates of sepsis development (88.3% vs 61.1%; p < 0.001), in-hospital mortality (35.0% vs. 16.7%; p < 0.001), 28-day mortality (25.0% vs. 5.6%; p < 0.001), and ICU admission (66.7% vs. 38.9%; p < 0.001). CONCLUSIONS:Patients exhibiting low severity signs of infection but high IL-10 levels showed an elevated probability of developing sepsis. Combining IL-10 with the NEWS score provides a reliable tool for predicting the progression from infection to sepsis at an early stage. Utilizing IL-6 in the emergency room can help identify patients with low NEWS or SIRS scores.

BackgroundThis study was aimed to identify the independent risk factors for falls n hospitalized older patients and develop a corresponding predictive model.MethodsA retrospective observational study design was adopted, comprising 440 older patients with falls history and 510 older patients without falls history during hospitalization. Data collected included demographic information, vital signs, comorbidities, psychiatric disorder, function absent, current medication, other clinical indicators.ResultsMobility disability, high-risk medications use, frequency of hospitalizations, psychiatric disorder, visual impairment are independent risk factors for falls in older patients. The A-M2-HPV scoring system was developed. The AUC value of the nomogram was 0.884, indicating the model has excellent discriminative ability. The AUC value of the A-M2-HPV score was 0.788, demonstrating better discrimination and stratification capabilities.ConclusionThe A-M2-HPV scoring system provides a valuable tool to assess the risk of falls in hospitalized older patients and to aid in the implementation of preventive measures.

To determine the optimal fluid resuscitation volume in septic patients with acutely decompensated heart failure (ADHF). Septic patients with ADHF were identified from a tertiary urban medical center. The generalized additive models were used to explore the association between fluid resuscitation volume and endpoints, and the initial 3 h fluid resuscitation volume was divided into four groups according to this model: < 10 mL/kg group, ≥ 10 to ≤ 15 mL/kg group, > 15 to ≤ 20 mL/kg group, and > 20 mL/kg group. Logistic and Cox regression models were employed to explore the association between resuscitation volume and primary endpoint, in-hospital mortality, as well as secondary endpoints including 30-day mortality, 1-year mortality, invasive ventilation, and ICU admission. A total of 598 septic patients with a well-documented history of HF were enrolled in the study; 405 patients (68.8