ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

Objective To examine the impact of climate, land use and their interaction effect on the population density of Oncomelania hupensis. Methods O. hupensis snail surveillance data in Yunnan Province from 2013 to 2022 were obtained from the National Information System for Parasitic Diseases Prevention and Control of Chinese Information System for Disease Control and Prevention, and the density of living snails was calculated in each county-level administrative district. Climate data were obtained from the China Meteorological Forcing Dataset version 2.0, and land use data were captured from the China Land Cover Dataset. The raster climate data and land use data were clipped to the administrative border of Yunnan Province in the R package version 4.5, and the climate data were resampled to a spatial resolution of 30 m × 30 m consistent with the land use data using bilinear interpolation. Annual meteorological indicators were extracted from each county-level schistosomiasis surveillance administrative area in Yunnan Province from 2013 to 2022, including average temperature, maximum temperature, minimum temperature, temperature difference, average precipitation rate, maximum precipitation rate, minimum precipitation rate, downward shortwave radiation flux, downward longwave radiation flux, air pressure, wind speed, specific humidity and relative humidity. Annual land use structure and landscape pattern index in each county-level schistosomiasis surveillance administrative area in Yunnan Province from 2013 to 2022 were extracted and calculated, including the proportion of areas occupied by each type of land use, patch density, largest patch index, landscape separation index, landscape fragmentation index, landscape segmentation index, contagion index, patch cohesion index, edge density, and shape index. Land use entropy index was introduced to represent the degree of habitat fragmentation and ecological niche breadth. The density of living snails and environmental factors were subjected to rank correlation analysis, and variables with no statistically significant correlation (P>0.1) were excluded. Then, a correlation coefficient matrix was constructed, and |r_s| of 0.85 and greater was defined as the threshold of high collinearity. For highly correlated variables in each group, indicators with a more biological explanatory power or a better statistical efficiency were retained. A generalized additive model (GAM) was constructed with O. hupensis snail density as a response variable and screened environmental variables as independent variables, and the model performance was evaluated using the variance explained. Results The area occupied by O. hupensis snail habitats was 1 056 to 1 680 hm² in Yunnan Province from 2013 to 2022, appearing an overall tendency towards a decline; however, the density of living snails appeared a tendency towards a slight rise. Based on the correlation coefficient matrix, 14 core explanatory variables were retained, including farmland, water bodies, bare land, impervious surface, landscape separation index, landscape fragmentation index, edge density, shape index, land use entropy index, downward longwave radiation flux, downward shortwave radiation flux, maximum temperature, minimum precipitation rate and specific humidity. Two types of GAM were constructed, including the main-effects model without interaction terms and the interaction model with interaction terms. The corrected Akaike information criterion (AICc) of the optimal main-effects model was −285.223, and the core variables included bare land, impervious surface, landscape separation index, edge density, shape index, land use entropy index and downward shortwave radiation flux. Following introduction of second-order interaction terms, the AICc value of the optimal interaction model was −345.526, and the significant interaction combinations included: farmland × impervious surface, farmland × landscape separation index, farmland × shape index, farmland × land use entropy index, impervious surface × landscape separation index, impervious surface × edge density, and shape index × downward shortwave radiation flux. The proportion of the main-effects model explaining the variation of O. hupensis snail density was 39.8%, and the explanatory power of GAM increased to 79.0% following introduction of interaction terms. Conclusion Landscape separation index, edge density, shape index and other landscape pattern indicators pose significant impacts on the intensity and direction of changes in O. hupensis snail density in Yunnan Province.

Objective To analyze the current quality of treatment for hospitalized cancer patients in Bei-jing,identify major issues in treatment practices,and propose improvements.Methods Nine hospitals in Beijing were selected for examination.Expert on-site interviews and medical record sampling were conducted.The"Bei-jing Cancer Diagnosis and Treatment Quality Control Checklist"was used to assess the hardware,management,anti-cancer drug therapy,radiation therapy,and surgical treatment during cancer treatment at these hospitals from January to October 2023.The relevant problems were analyzed.Results Among the nine hospitals,two(22.2％)were equipped with laminar flow rooms,and three(33.3％)had intravenous drug preparation centers.In terms of institutional management,seven hospitals(77.8％)had standardized anti-cancer drug prescription authority management,eight(88.9％)had complete emergency plans,and five(55.6％)had oncology specialist pharmacists.Regarding anti-cancer drug therapy,the areas with higher completion rates included pathology diag-nosis support(97.6％),routine pre-treatment examinations(96.3％),adverse reaction evaluation(92.7％),discharge summaries(95.1％),and admission records(91.5％).However,the accuracy of tumor staging before treatment(70.7％)and the evaluation of therapeutic efficacy after drug treatment(76.9％)needed improvement.The oncology specialty significantly outperformed the non-oncology specialty in terms of the accuracy rate of TNM staging(86.0％vs.46.9％,P＜0.001),the completeness of informed consent forms(100％vs.68.8％,P＜0.001),the completeness of drug indication evaluation(96.0％vs.78.1％,P=0.025),the completeness of admission medical history records(98.0％vs.81.3％,P=0.008),the rationality of drug dosage(96.0％vs.75.0％,P=0.005),the rationality of drug infusion time(100％vs.62.5％,P＜0.001),and the rationality of the order of drug infusion(100％vs.87.5％,P=0.010).Although the quality of radiation therapy was high,the subsequent evaluation of therapeutic efficacy(39.3％)requires enhancement.In surgical treatment,the preoper-ative pathology diagnosis support rate(78.1％)and the accuracy of tumor staging(37.5％)were relatively low,indicating issues with incomplete preoperative evaluation and the absence of multidisciplinary discussions.Conclusions There remains significant room for improvement in the quality of cancer treatment in China.It is recommended to standardize tumor staging assessment processes,strengthen entry assessments for non-oncology departments,promote the implementation of multidisciplinary treatment models,and establish a multi-department collaborative management model.Continuous monitoring of cancer diagnosis and treatment quality indicators is es-sential to promote ongoing improvements in cancer treatment quality.

OBJECTIVE: To report the blood group antigen and antibody specificity identification methods for a patient with high-frequency antibodies, and the process of finding and providing compatible blood for the patient. METHODS: A patient sent from the Blood Transfusion Department of Shanxi Provincial People's Hospital to Blood Transfusion Technology Research Laboratory of Taiyuan Blood Center in November 2022 was selected for the study. Classical serological methods were used to determine the patient's blood type, screen for unexpected antibodies, identify antibodies, and perform crossmatching. High-frequency antibody identification was carried out using red blood cells treated with various enzymes. Blood group genotyping was conducted using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF) and Sanger sequencing. Multiple strategies were employed to address the patient's blood source problem. The study was approved by the Medical Ethics Committee of Taiyuan Blood Center [Ethics No. 2024 Ethics Review No.(2)]. RESULTS: The patient's blood type was B, RhD positive. Initial screening of the patient's serum with multiple screening cells and antibody identification cells in saline medium was negative, but positive in antiglobulin medium. The patient's serum showed varying reaction intensities with red blood cells treated with different enzymes. MALDI-TOF mass spectrometry and Sanger sequencing revealed a homozygous nonsense variant c.376C>T (p.Gln126Ter) in the ABCG2 gene, resulting in the Jr(a-) phenotype. During family donor selection, the patient's son was found to have a heterozygous variant c.376C>T (p.Gln126Ter), and another heterozygous variant c.421C>A (p.Gln141Lys), which predicted a Jr(a+w) phenotype. Crossmatch tests confirmed the compatibility of blood from the patient's son, which was used to address the urgent blood requirement. Later, rare blood from a Jr(a-) donor from the Guangzhou Blood Center was used for the patient's ongoing treatment, saving the patient's life. CONCLUSION Combining classic serological testing with blood group gene typing techniques successfully identified the rare Jr(a-) blood type and high-frequency anti-Jra antibodies. Enzyme-treated red blood cell identification methods confirmed the presence of anti-Jra antibodies. By searching within the family and seeking help from other blood centers, compatible blood was found. This approach may provide insights for resolving similar complex blood matching problems in the future.
Humans ; Blood Grouping and Crossmatching/methods* ; Blood Group Antigens/immunology* ; Blood Transfusion ; Male ; Isoantibodies/blood* ; Female ; Genotype

In recent decades, the prevalence of hyperuricemia and gout has increased dramatically due to lifestyle changes. The drugs currently recommended for hyperuricemia are associated with adverse reactions that limit their clinical use. In this study, we report that berberine (BBR) is an effective drug candidate for the treatment of hyperuricemia, with its mechanism potentially involving the modulation of gut microbiota and its metabolite, succinic acid. BBR has demonstrated good therapeutic effects in both acute and chronic animal models of hyperuricemia. In a clinical trial, oral administration of BBR for 6 months reduced blood uric acid levels in 22 participants by modulating the gut microbiota, which led to an increase in the abundance of Bacteroides and a decrease in Clostridium sensu stricto_1. Furthermore, Bacteroides fragilis was transplanted into ICR mice, and the results showed that Bacteroides fragilis exerted a therapeutic effect on uric acid similar to that of BBR. Notably, succinic acid, a metabolite of Bacteroides, significantly reduced uric acid levels. Subsequent cell and animal experiments revealed that the intestinal metabolite, succinic acid, regulated the upstream uric acid synthesis pathway in the liver by inhibiting adenosine monophosphate deaminase 2 (AMPD2), an enzyme responsible for converting adenosine monophosphate (AMP) to inosine monophosphate (IMP). This inhibition resulted in a decrease in IMP levels and an increase in phosphate levels. The reduction in IMP led to a decreased downstream production of hypoxanthine, xanthine, and uric acid. BBR also demonstrated excellent renoprotective effects, improving nephropathy associated with hyperuricemia. In summary, BBR has the potential to be an effective treatment for hyperuricemia through the gut-liver axis.

Osteoarthritis (OA), the most prevalent joint disease of late life, is closely linked to cellular senescence. Previously, we found that the senescence of fibroblast-like synoviocytes (FLS) played an essential role in the degradation of cartilage. In this work, single-cell sequencing data further demonstrated that cartilage acidic protein 1 (CRTAC1) is a critical secreted factor of senescent FLS, which suppresses mitophagy and induces mitochondrial dysfunction by regulating SIRT3 expression. In vivo, deletion of SIRT3 in chondrocytes accelerated cartilage degradation and aggravated the progression of OA. Oppositely, intra-articular injection of adeno-associated virus expressing SIRT3 effectively alleviated OA progression in mice. Mechanistically, we demonstrated that elevated CRTAC1 could bind with NRF2 in chondrocytes, which subsequently suppresses the transcription of SIRT3 in vitro. In addition, SIRT3 reduction could promote the acetylation of FOXO3a and result in mitochondrial dysfunction, which finally contributes to the degradation of chondrocytes. To conclude, this work revealed the critical role and underlying mechanism of senescent FLSs-derived CRTAC1 in OA progression, which provided a potential strategy for the OA therapy.

Glutamine provides carbon and nitrogen to support the proliferation of cancer cells. However, the precise reason why cancer cells are particularly dependent on glutamine remains unclear. In this study, we report that glutamine modulates the tumor suppressor F-box and WD repeat domain-containing 7 (FBW7) to promote cancer cell proliferation and survival. Specifically, lysine 604 (K604) in the sixth of the 7 substrate-recruiting WD repeats of FBW7 undergoes glutaminylation (Gln-K604) by glutaminyl tRNA synthetase. Gln-K604 inhibits SCFFBW7-mediated degradation of c-Myc and Mcl-1, enhances glutamine utilization, and stimulates nucleotide and DNA biosynthesis through the activation of c-Myc. Additionally, Gln-K604 promotes resistance to apoptosis by activating Mcl-1. In contrast, SIRT1 deglutaminylates Gln-K604, thereby reversing its effects. Cancer cells lacking Gln-K604 exhibit overexpression of c-Myc and Mcl-1 and display resistance to chemotherapy-induced apoptosis. Silencing both c-MYC and MCL-1 in these cells sensitizes them to chemotherapy. These findings indicate that the glutamine-mediated signal via Gln-K604 is a key driver of cancer progression and suggest potential strategies for targeted cancer therapies based on varying Gln-K604 status.
Glutamine/metabolism* ; Myeloid Cell Leukemia Sequence 1 Protein/genetics* ; Humans ; Proto-Oncogene Proteins c-myc/genetics* ; Cell Proliferation ; Signal Transduction ; Neoplasms/pathology* ; F-Box-WD Repeat-Containing Protein 7/genetics* ; Cell Survival ; Cell Line, Tumor ; Apoptosis

OBJECTIVE: To investigate the incidence of sepsis in Xinjiang Uygur Autonomous Region and the compliance with sepsis diagnosis and treatment guidelines in intensive care unit (ICU) at different levels of hospitals, and to identify the risk factors associated with poor prognosis in patients with sepsis in this region. METHODS: A prospective cross-sectional survey was conducted in ICU of Xinjiang Uygur Autonomous Region Critical Care Medicine Alliance. The survey period was from 10:00 on January 31, 2024, to 09:59 on February 1, 2024. The patients diagnosed with sepsis admitted to the ICU during the study period were included in the analysis. Data on patient demographics, physiology, microbiology, and treatment protocols were collected, with follow-up until the 28th day after ICU admission or death. Baseline characteristics and treatment information of septic patients across different hospital levels were compared, as well as clinical data of septic patients with different 28-day outcomes. Multivariate Cox proportional hazards model was used to identify risk factors for 28-day death in septic patients. RESULTS: A total of 77 units of Xinjiang Uygur Autonomous Region Critical Care Medicine Alliance from 14 prefectures/cities in Xinjiang participated in the survey. On the survey day, 727 patients were admitted to ICU, of whom 179 (24.6%) were diagnosed with sepsis, and 64 (35.8%) died within 28 days, 115 (64.2%) survived. Among the participating institutions, 33 were tertiary hospitals (42.9%), managing 97 septic cases (54.2%), and 44 were secondary hospitals (57.1%), managing 82 septic cases (45.8%). The lactic acid monitoring rate and continuous renal replacement therapy (CRRT) rate for septic patients in tertiary hospitals were significantly higher than those in secondary hospitals [lactic acid monitoring rate: 92.8% (90/97) vs. 82.9% (68/82), CRRT rate: 17.5% (17/97) vs. 3.7% (3/82), both P < 0.05]. No statistically significant differences were observed between tertiary and secondary hospitals in length of ICU stay or 28-day mortality [length of ICU stay (days): 11.0 (16.0) vs. 10.0 (22.0), 28-day mortality: 35.1% (34/97) vs. 36.6% (30/82), both P > 0.05]. Compared with survivors, non-survivors had higher acute physiology and chronic health evaluation II (APACHE II) score, sequential organ failure assessment (SOFA) score, Charlson comorbidity index (CCI) score and lower Glasgow coma scale (GCS) score. Significant differences were noted in vital signs [heart rate, blood pressure, body temperature, pulse oxygen saturation (SpO₂)], laboratory markers [red blood cell count (RBC), white blood cell count (WBC), lymphocyte ratio (LYM%), blood urea nitrogen (BUN), total protein (TP), albumin (Alb), pH value, base excess (BE)], and monitoring, diagnosis and treatment information (invasive blood pressure monitoring, mechanical ventilation, CRRT, usage of norepinephrine). Multivariate Cox proportional hazards model indicated that body temperature [hazard ratio (HR) = 1.416, 95% confidence interval (95%CI) was 1.022-1.961, P = 0.037] and WBC (HR = 1.040, 95%CI was 1.010-1.071, P = 0.009) were independent risk factors for 28-day death in patients with sepsis. CONCLUSIONS Sepsis in Xinjiang Uygur Autonomous Region is characterized by a high mortality. In this region, tertiary hospitals demonstrate better compliance with bundled treatment strategies such as lactic acid monitoring and the usage of CRRT compared to secondary hospitals, yet they do not show significant advantages in clinical outcomes. Body temperature and WBC are independent risk factors for 28-day death in patients with sepsis in this region. However, clinicians should still consider the actual situation of patients, along with more optimal early warning indicators and comprehensive system assessments, to identify and prevent risk factors for adverse outcomes in patients.
Humans ; Sepsis/diagnosis* ; Cross-Sectional Studies ; Prospective Studies ; Risk Factors ; Intensive Care Units ; Prognosis ; China/epidemiology* ; Male ; Female ; Middle Aged ; Aged ; Proportional Hazards Models ; Incidence