OBJECTIVES: Sepsis-associated acute lung injury (S-ALI) is one of the major causes of death in intensive care unit (ICU) patients, yet its mechanisms remain incompletely understood and effective therapies are lacking. Lytic cell death of macrophages is a key driver of the inflammatory cascade in S-ALI. PANoptosis, a newly recognized form of lytic cell death characterized by PANoptosome assembly and activation, involves plasma membrane rupture (PMR) mediated by ninjurin-1 (NINJ1), a recently identified pore-forming protein. Itaconic acid is known for its anti-inflammatory effects, but its role in macrophage PANoptosis during S-ALI is unclear. This study aims to investigate the protective effect of itaconic acid on macrophage PANoptosis in S-ALI to provide new therapeutic insights. METHODS: Male specific-pathogen-free C57BL/6J mice (6-8 weeks, 18-20 g) received intraperitoneal lipopolysaccharide (LPS) to establish a classical S-ALI model. Western blotting was used to assess PANoptosome-related proteins and enzymes involved in the itaconic acid metabolic pathway, while real-time reverse transcription polymerase chain reaction and metabolomics quantified itaconic acid levels. Primary peritoneal macrophages (PMs) were pretreated with the itaconate derivative 4-octyl itaconate (4-OI) and then exposed to tumor necrosis factor alpha (TNF-α) plus interferon gamma (IFN-γ) to induce PANoptosis. Cell viability was evaluated by cell counting kit-8 (CCK-8) assay. Western blotting was employed to quantify enzymes of the itaconate-metabolic pathway in PANoptotic macrophages, to evaluate the impact of 4-OI on PANoptosome-associated proteins, and to determine NINJ1 abundance in lung tissues from S-ALI mice and in PANoptotic macrophages. Fluorescent dye FM_4-64 was used to visualize 4-OI-mediated changes in PMR, whereas immunofluorescence staining mapped the effect of 4-OI on both the expression level and membrane localization of NINJ1 in PANoptotic macrophages. The effect of 4-OI on lactate dehydrogenase (LDH) release in culture supernatants and peripheal blood serum was assessed using a LDH assay kit, and non-denataring polyacylamide gel electrophoresis was used to assess the expression of NINJ1 in S-ALI mouse lung tissues and the impact of 4-OI on the expression of PANoptosis-associated NINJ1 multimeric reflected protein in macropahges. RESULTS: In S-ALI mouse lungs, PANoptosome components [NOD-like receptor thermal protein domain associated protein 3 (NLRP3), Gasdermin D (GSDMD), Caspase-1, Z-DNA binding protein (ZBP1), and Caspase-3] and phosphorylated mixed lineage kinase domain-like protein (MLKL) S345 were significantly upregulated (all P<0.05), while metabolomics showed compensatory increases in itaconic acid and its key enzymes [aconitate decarboxylase 1 (ACOD1)/immunoresponsive gene 1 (IRG1)]. In macrophages, 4-OI obviously suppressed PANoptosome protein expression, reduced LDH release, restored plasma membrane integrity, and inhibited NINJ1 expression and oligomerization at the membrane (P<0.05). CONCLUSIONS Itaconic acid may alleviate macrophage PANoptosis in S-ALI by inhibiting NINJ1-mediated plasma membrane rupture. Targeting NINJ1 or enhancing itaconate pathways may offer a novel therapeutic strategy for S-ALI.
Animals ; Acute Lung Injury/pathology* ; Succinates/pharmacology* ; Sepsis/complications* ; Mice, Inbred C57BL ; Male ; Mice ; Macrophages/pathology* ; Cell Membrane/metabolism* ; Lipopolysaccharides ; Hydro-Lyases

OBJECTIVES: Global epidemiological data indicate that 20% to 30% of intensive care unit (ICU) sepsis patients progress to deep vein thrombosis (DVT) due to coagulopathy, with an associated mortality rate of 25% to 40%. Existing prognostic tools have limitations. This study aims to develop and validate nomogram and machine learning models to predict in-hospital mortality in sepsis patients with DVT and assess their clinical applicability. METHODS: This multicenter retrospective study drew on data from the Medical Information Mart for Intensive Care IV (MIMIC-IV; n=2 235), the eICU Collaborative Research Database (eICU-CRD; n=1 274), and the Patient Admission Dataset from the ICU of Third Xiangya Hospital, Central South University (CSU-XYS-ICU; n=107). MIMIC-IV was split into a training set (n=1 584) and internal validation set (n=651), with the remaining datasets used for external validation. Predictors were selected via least absolute shrinkage and selection operator (LASSO) regression and Bayesian Information Criterion (BIC), and a nomogram model was constructed. An extreme gradient boosting (XGBoost) algorithm was used to build the machine learning model. Model performance was assessed by the concordance index (C-index), calibration curves, Brier score, decision curve analysis (DCA), and net reclassification improvement index (NRI). RESULTS: Five key predictors, age [odds ratio (OR)=1.02, 95% CI 1.01 to 1.03, P<0.001], minimum activated partial thromboplastin (APTT; OR=1.09, 95% CI 1.08 to 1.11, P<0.001), maximum APTT (OR=1.01, 95% CI 1.00 to 1.01, P<0.001), maximum lactate (OR=1.56, 95% CI 1.39 to 1.75, P<0.001), and maximum serum creatinine (OR=2.03, 95% CI 1.79 to 2.30, P<0.001), were included in the nomogram. The model showed robust performance in internal validation (C-index=0.845, 95% CI 0.811 to 0.879) and external validation (eICU-CRD: C-index=0.827, 95% CI 0.800 to 0.854; CSU-XYS-ICU: C-index=0.779, 95% CI 0.687 to 0.871). Calibration curves indicated good agreement between predicted and observed outcomes (Brier score<0.25), and DCA confirmed clinical benefit. The XGBoost model achieved an area under the receiver operating characteristic curve (AUC) of 0.982 (95% CI 0.969 to 0.985) in the training set, but performance declined in external validation (eICU-CRD, AUC=0.825, 95% CI 0.817 to 0.861; CSU-XYS-ICU, AUC=0.766, 95% CI 0.700 to 0.873), though it remained above clinical thresholds. Net reclassification improvement was slightly lower for XGBoost compared with the nomogram (NRI=0.58). CONCLUSIONS Both the nomogram and XGBoost models effectively predict in-hospital mortality in sepsis patients with DVT. However, the nomogram offers superior generalizability and clinical usability. Its visual scoring system provides a quantitative tool for identifying high-risk patients and implementing individualized interventions.
Humans ; Sepsis/complications* ; Machine Learning ; Nomograms ; Venous Thrombosis/complications* ; Retrospective Studies ; Hospital Mortality ; Male ; Female ; Middle Aged ; Aged ; Intensive Care Units ; Prognosis ; Bayes Theorem

With the development of critical medical emergency technology, the success rate of sepsis treatment has been significantly improved, and the improvement of the long-term quality of life of sepsis survivors has also attracted more and more attention. ICU-acquired weakness (ICU-AW) refers to a group of syndromes with systemic and symmetrical muscle weakness during the intensive care unit (ICU) hospitalization and cannot be explained by the patient's own disease, which often involve diaphragm and skeletal muscle, resulting in difficulty in weaning and nosocomial infection. The incidence of ICU-AW in sepsis patients is over 50%, making it an important factor affecting the prognosis of these patients. The occurrence of sepsis ICU-AW is related to many factors, which can be summarized into two categories, including sepsis-related factors such as sepsis-associated inflammatory response, sepsis-associated encephalopathy (SAE), and treatment-related factors such as physical immobilization and insufficient nutritional support. The current ICU-AW risk assessment tools are mainly on subjective assessment scales, but there are some limitations in clinical application, and objective assessment tools including predictive model and imaging assessment, which are still in the research stage. "ABCDEF bundle strategy" is an important measure to prevent ICU-AW, in which early rehabilitation is the core element. This review of the literature from the risk factors, risk assessment and early rehabilitation of ICU-AW, and focuses on the timing, content, method and safety assessment of early rehabilitation, aims to improve the understanding of ICU-AW, strengthen the prevention of sepsis with ICU-AW, and improve the prognosis of sepsis patients, not only survive, but also live better.
Humans ; Sepsis/complications* ; Muscle Weakness/etiology* ; Intensive Care Units ; Prognosis ; Quality of Life

OBJECTIVE: To explore the risk factors affecting the prognosis of patients with sepsis complicated with acute pulmonary embolism, and to construct and validate a nomogram predictive model for in-hospital mortality risk. METHODS: Based on the American Medical Information Mart for Intensive Care (MIMIC-III, MIMIC-IV) databases, the data were collected on patients with sepsis complicated with acute pulmonary embolism from 2001 to 2019, including baseline characteristics, and vital signs, disease scores, laboratory tests within 24 hours of admission to the intensive care unit (ICU), and interventions. In-hospital mortality was the outcome event. The total samples were divided into training and testing sets in a 7:3 ratio by random sampling. Univariate Cox regression analysis was used to verify the impact of all variables on the risk of in-hospital mortality, thereby screen potential influencing factors. Subsequently, a stepwise bi-directional regression method was applied to select factors one by one, leading to the construction of a nomogram prediction model. Collinearity testing was used to demonstrate the absence of strong multicollinearity among the influencing factors in the nomogram prediction model. The discrimination of the nomogram model, sequential organ failure assessment (SOFA), and simplified pulmonary embolism severity index (sPESI) was evaluated using C-index in the test set. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of various models for in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism. RESULTS: A total of 562 patients with sepsis complicated with acute pulmonary embolism were included, including 393 in the training set and 169 in the testing set. Univariate Cox regression analysis showed that 30 factors associated with in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism. Through stepwise bi-directional regression, 12 variables were ultimately selected, including gender, presence of malignant tumors, body temperature, red cell distribution width (RDW), blood urea nitrogen (BUN), serum potassium, prothrombin time (PT), 24-hour urine output, mechanical ventilation, vasoactive drugs, warfarin use, and sepsis-induced coagulopathy (SIC). Collinearity testing indicated no strong multicollinearity among the influencing factors [all variance inflation factor (VIF) > 10]. A nomogram model was constructed using the 12 variables mentioned above. The nomogram model predicted the C-index and its 95% confidence interval (95%CI) of in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism better than SOFA score and sPESI [0.771 (0.725-0.816) vs. 0.579 (0.519-0.639), 0.608 (0.554-0.663)]. The ROC curve showed that the area under the curve (AUC) and its 95%CI of the nomogram model were higher than those of the SOFA score and sPESI [0.811 (0.766-0.857) vs. 0.630 (0.568-0.691), 0.623 (0.566-0.680)]. These findings were consistently replicated in the internal validation of the testing set. In both the training and testing sets, Delong's test showed that the AUC of the nomogram model was significantly higher than the SOFA score and sPESI (both P < 0.05). CONCLUSION The nomogram model demonstrated good predictive effectiveness for the risk of in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism, enabling clinicians to predict mortality risk in advance and take timely interventions to reduce mortality.
Humans ; Pulmonary Embolism/mortality* ; Hospital Mortality ; Nomograms ; Sepsis/complications* ; Prognosis ; Risk Factors ; Intensive Care Units ; Male ; Female ; Middle Aged ; Aged

Sepsis is a life-threatening organ dysfunction syndrome caused by a dysregulated host response to infection. Septic acute kidney injury (SAKI) is one of the most common complications of sepsis, and the occurrence of acute kidney injury (AKI) indicates that the patient's condition is critical with a poor prognosis. The traditional view holds that the main mechanism of SAKI is the reduction of renal blood flow, inadequate renal perfusion, inflammatory response, and microcirculatory dysfunction caused by sepsis, which subsequently leads to ischemia and necrosis of renal tubular cells. Recent research findings indicate that processes such as autophagy and other forms of programmed cell death play an increasingly important role. Autophagy is a programmed intracellular degradation process and is a form of programmed cell death. Cells degrade their cytoplasmic components via lysosomes, breaking down and recycling intracellular constituents to meet their metabolic needs, maintain intracellular homeostasis, and renew organelles. During SAKI, autophagy plays a crucial protective role through various mechanisms, including regulating inflammation and immune responses, clearing damaged organelles, and maintaining stability in the intracellular environment. In recent years, the role of autophagy in the pathogenesis and treatment of SAKI has received widespread attention. Research has confirmed that various intracellular signaling pathways and signaling molecules targeting autophagy [such as mammalian target of rapamycin (mTOR) signaling pathway, AMP-activated protein kinase (AMPK) signaling pathway, nuclear factor-κB (NF-κB) signaling pathway, and Sirtuins (SIRT), autophagy associated factor Beclin-1, and Toll-like receptor (TLR)] are involved in the development of SAKI. Due to the complex pathogenesis of SAKI, current treatment strategies include fluid management, infection control, maintenance of internal environment balance, and renal replacement therapy; however, the mortality remains high. In recent years, it has been found that autophagy plays a critical protective role in sepsis-mediated AKI. As a result, an increasing number of drugs are being developed to alleviate SAKI by regulating autophagy. This article reviews the latest advances in the role of autophagy in the pathogenesis and treatment of SAKI, with the aim of providing insights for the development of new drugs for SAKI patients.
Humans ; Acute Kidney Injury/etiology* ; Autophagy ; Sepsis/complications* ; Signal Transduction

OBJECTIVE: To explore the current status, evolution, hot topics, and future research trends in the field of burn-related sepsis research through a visual analysis of literature. METHODS: A bibliometric method was employed to retrieve articles related to burn-related sepsis from January 1, 1994, to May 16, 2024, in the China National Knowledge Infrastructure (CNKI) and the Web of Science database. The CiteSpace 6.3.R1 software was used to analyze the retrieved literature. The number of publications, authors, countries, and institutions in both Chinese and English literature was statistically analyzed. Co-occurrence analysis, clustering analysis, and co-citation analysis of keywords were performed. RESULTS: A total of 1 090 articles from the CNKI database and 1 143 articles from the Web of Science database were retrieved. Over the past 20 years, the volume of Chinese publications has remained stable, although there has been a slight decline in the past two years. In contrast, the number of English publications, after a period of growth, showed a sharp decline over the past three years. In Chinese literature, 1 457 authors published articles on burn-related sepsis as first authors, with 14 core authors publishing four or more articles. In English literature, 98 authors published articles on burn-related sepsis as first authors. Research on burn-related sepsis was conducted by 76 countries, with the United States having the most collaborations and publications. Globally, 1 349 institutions published articles on burn-related sepsis, with the top institutions being the First Affiliated Hospital of the PLA General Hospital (8 articles) for Chinese literature and the University of Texas Medical Branch (57 articles) for English literature. In the co-occurrence analysis, 208 Chinese keywords and 211 English keywords were included. Excluding keywords related to search terms, the top five most frequent keywords in Chinese literature were burn, sepsis, infection, severe burn, and procalcitonin; the top five most frequent keywords in English literature were sepsis, septic shock, mortality, injury, and burn injury. Chinese keyword analysis identified six clusters, with the largest being sepsis, followed by procalcitonin, infection, and severe burn. English keyword analysis identified seven clusters, with the largest being expression, followed by epidemiology, inhalation injury, and acute kidney injury. The persistent clusters in Chinese literature were procalcitonin, with recent emerging nodes being severe burn, inflammatory response, platelets, and predictive value. In English literature, the persistent clusters were inhalation injury and nitric oxide, with recent emerging nodes being continuous renal replacement therapy, hemorrhagic shock, and early enteral nutrition. The longest-lasting emergent keyword in Chinese literature was delayed resuscitation (2003-2010), with the highest emergent strength being severe burn. In English literature, the longest-lasting emergent keywords, each lasting five years, were nitric oxide (2007-2012), management (2019-2024), and impact (2019-2024), with the highest emergent strength being thermal injury. CONCLUSIONS Research on burn-related sepsis has shifted from focusing on early studies on pathogenesis and mortality to focus on prevention, treatment, and early diagnosis. Future research is expected to focus on early diagnosis and risk factors of burn-related sepsis.
Burns/complications* ; Sepsis/etiology* ; Humans ; Bibliometrics ; China

Sepsis is a life-threatening organ dysfunction caused by the body's dysregulated response to infection. Reversible myocardial dysfunction caused by sepsis is known as septic cardiomyopathy. A thorough understanding of the pathogenesis of septic cardiomyopathy is crucial for early intervention to prevent its progression and improve the success rate of sepsis treatment. At present, the research on the pathogenesis of septic cardiomyopathy mainly focuses on two aspects: the systemic neuroimmune mechanism and the local changes of cardiomyocytes. The former mainly includes the autonomic nervous dysfunction mainly caused by sympathetic overactivation and the inflammatory storm induced by immune response disorder. The latter covers the dysregulation of calcium homeostasis, mitochondrial dysfunction and energy metabolism disorder of cardiomyocytes. Immune dysfunction is one of the key factors that cause the poor prognosis of patients with septic cardiomyopathy. Macrophages are sentinel cells of the body's innate immunity. Cardiac macrophages have been confirmed to be one of the most heterogeneous immune cells in the heart. According to their origin and differentiation, they can be divided into bone marrow-derived tissue infiltrating macrophages and cardiac resident macrophages, which have roles of polarization, phagocytosis, regulation of inflammatory response, and participate in innate and adaptive immunity. In the occurrence and development of septic cardiomyopathy, cardiac macrophages recruited from the blood participate in balancing the inflammation and repair of myocardial tissue through the conversion of pro-inflammatory phenotype and anti-inflammatory phenotype. Cardiac resident macrophages mediate immune phagocytosis to maintain the local homeostasis of cardiomyocytes, and the glycometabolic reprogramming of macrophages regulates the release of inflammatory factors, while macrophage metabolic reprogramming regulates the release of inflammatory factors. A deeper understanding of the biological behavior of macrophages, and regulating the polarization, metabolism and phagocytosis of cardiac macrophages, could serve as new target for the prevention and treatment of septic cardiomyopathy. Therefore, this article reviews the key pathogenesis of septic cardiomyopathy and the role of macrophages of different origins and differentiation, revealing the possibility of developing new strategies for the prevention and treatment of septic cardiomyopathy.
Humans ; Cardiomyopathies/pathology* ; Macrophages/immunology* ; Sepsis/complications* ; Myocytes, Cardiac

OBJECTIVE: To investigate the application value of pediatric sepsis-induced coagulation (pSIC) score and mean platelet volume/platelet count (MPV/PLT) ratio in the diagnosis of pediatric sepsis and the determination of critical pediatric sepsis. METHODS: A retrospective cohort study was conducted, selecting 112 children with sepsis (sepsis group) admitted to pediatric intensive care unit (PICU) of Liaocheng Second People's Hospital from January 2020 to December 2023 as the study objects, and 50 children without sepsis admitted to the pediatric surgery department of our hospital during the same period for elective surgery due to inguinal hernia as the control (control group). The children with sepsis were divided into two groups according to the pediatric critical case score (PCIS). The children with PCIS score of ≤ 80 were classified as critically ill group, and those with PCIS score of > 80 was classified as non-critically ill group. pSIC score, coagulation indicators [prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (APTT), and fibrinogen (FIB)], and platelet related indicators (PLT, MPV, and MPV/PLT ratio) were collected. Pearson correlation method was used to analyze the correlation between pSIC score and MPV/PLT ratio as well as their correlation with coagulation indicators. Multivariate Logistic regression analysis was used to screen the independent risk factors for pediatric sepsis and critical pediatric sepsis. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the application value of the above independent risk factors on the diagnosis of pediatric sepsis and the determination of critical pediatric sepsis. RESULTS: 112 children with sepsis and 50 children without sepsis were enrolled in the final analysis. pSIC score, PT, INR, APTT, FIB, MPV, and MPV/PLT ratio in the sepsis group were significantly higher than those in the control group [pSIC score: 0.93±0.10 vs. 0.06±0.03, PT (s): 14.76±0.38 vs. 12.23±0.15, INR: 1.26±0.03 vs. 1.06±0.01, APTT (s): 40.08±0.94 vs. 32.47±0.54, FIB (g/L): 3.51±0.11 vs. 2.31±0.06, MPV (fL): 8.86±0.14 vs. 7.62±0.11, MPV/PLT ratio: 0.037±0.003 vs. 0.022±0.001, all P < 0.01], and PLT was slightly lower than that in the control group (×10⁹/L: 306.00±11.01 vs. 345.90±10.57, P > 0.05). Among 112 children with sepsis, 46 were critically ill and 66 were non-critically ill. pSIC score, PT, INR, APTT, MPV, and MPV/PLT ratio in the critically ill group were significantly higher than those in the non-critically ill group [pSIC score: 1.74±0.17 vs. 0.36±0.07, PT (s): 16.55±0.80 vs. 13.52±0.23, INR: 1.39±0.07 vs. 1.17±0.02, APTT (s): 43.83±1.72 vs. 37.77±0.95, MPV (fL): 9.31±0.23 vs. 8.55±0.16, MPV/PLT ratio: 0.051±0.006 vs. 0.027±0.001, all P < 0.05], PLT was significantly lower than that in the non-critically ill group (×10⁹/L: 260.50±18.89 vs. 337.70±11.90, P < 0.01), and FIB was slightly lower than that in the non-critically ill group (g/L: 3.28±0.19 vs. 3.67±0.14, P > 0.05). Correlation analysis showed that pSIC score was significantly positively correlated with MPV/PLT ratio and coagulation indicators including PT, APTT and INR in pediatric sepsis (r value was 0.583, 0.571, 0.296 and 0.518, respectively, all P < 0.01), and MPV/PLT ratio was also significantly positively correlated with PT, APTT and INR (r value was 0.300, 0.203 and 0.307, respectively, all P < 0.05). Multivariate Logistic regression analysis showed that pSIC score and MPV/PLT ratio were independent risk factors for pediatric sepsis and critical pediatric sepsis [pediatric sepsis: odds ratio (OR) and 95% confidence interval (95%CI) for pSIC score was 14.117 (4.190-47.555), and the OR value and 95%CI for MPV/PLT ratio was 1.128 (1.059-1.202), both P < 0.01; critical pediatric sepsis: the OR value and 95%CI for pSIC score was 8.142 (3.672-18.050), and the OR value and 95%CI for MPV/PLT ratio was 1.068 (1.028-1.109), all P < 0.01]. ROC curve analysis showed that pSIC score and MPV/PLT ratio had certain application value in the diagnosis of pediatric sepsis [area under the ROC curve (AUC) and 95%CI was 0.754 (0.700-0.808) and 0.720 (0.643-0.798), respectively] and the determination of critical pediatric sepsis [AUC and 95%CI was 0.849 (0.778-0.919) and 0.731 (0.632-0.830)], and the combined AUC of the two indictors was 0.815 (95%CI was 0.751-0.879) and 0.872 (95%CI was 0.806-0.938), respectively. CONCLUSIONS pSIC score and MPV/PLT ratio have potential application value in the diagnosis of pediatric sepsis and the determination of critical pediatric sepsis, and the combined application of both is more valuable.
Humans ; Sepsis/complications* ; Platelet Count ; Mean Platelet Volume ; Retrospective Studies ; Child ; Blood Coagulation Disorders/diagnosis* ; Intensive Care Units, Pediatric ; Male ; Female ; Partial Thromboplastin Time ; Child, Preschool ; Blood Coagulation ; International Normalized Ratio ; Infant

OBJECTIVE: To analyze the factors influencing the development of refeeding syndrome (RFS) in patients with sepsis and its impact on clinical prognosis. METHODS: A retrospective case-control study method was used to collect the clinical data of patients with sepsis admitted to the intensive care unit (ICU) of Qingdao Municipal Hospital from December 2018 to December 2023. The patients were divided into RFS and non-RFS groups according to whether RFS occurred, and the basic data, nutritional status and assessment scale, laboratory indicators, nutritional intake, medical history and prognosis were compared between the two groups. Binary multifactorial Logistic regression analysis was used to screen the influencing factors of the occurrence of RFS in patients with sepsis. RESULTS: A total of 544 patients with sepsis were finally enrolled, of whom 250 did not develop RFS and 294 developed RFS, with an incidence of 54.0%. Compared with the non-RFS group, the patients in the RFS group had lower body mass index (BMI), albumin, prealbumin, baseline electrolytes (serum phosphorus, serum potassium, and serum magnesium), creatinine-height index, and protein intake, and had higher nutritional risk screening 2002 (NRS2002) score, sequential organ failure assessment (SOFA) score, calorie intake, and the proportions of feedings during the 48 hours of ICU admission, history of diabetes and septic shock. Binary multifactorial Logistic regression analysis showed that BMI [odds ratio (OR) = 0.910, 95% confidence interval (95%CI) was 0.857-0.947, P < 0.001], SOFA score (OR = 1.166, 95%CI was 1.085-1.254, P < 0.001), albumin (OR = 0.946, 95%CI was 0.902-0.991, P = 0.019), baseline serum phosphorus (OR = 0.343, 95%CI was 0.171-0.689, P = 0.003), baseline serum potassium (OR = 0.531, 95%CI was 0.377-0.746, P < 0.001), creatinine-height index (OR = 0.891, 95%CI was 0.819-0.970, P = 0.008), caloric intake (OR = 1.108, 95%CI was 1.043-1.178, P = 0.001), protein intake (OR = 0.107, 95%CI was 0.044-0.260, P < 0.001), and feedings during the 48 hours of ICU admission (OR = 0.592, 95%CI was 0.359-0.977, P = 0.040) and septic shock (OR = 0.538, 95%CI was 0.300-0.963, P = 0.037) were independent influence factors on the occurrence of RFS in septic patients. Of the 544 patients, 267 died at 28 days, with a mortality of 49.1%. The 28-day mortality of patients in the RFS group was significantly higher than that in the non-RFS group [54.4% (160/294) vs. 42.8% (107/250); χ² = 7.302, P = 0.007]. 544 patients had a length of ICU stay of 20 (17, 24) days. The patients in the RFS group had a significantly longer length of ICU stay than that in the non-RFS group [days: 20 (17, 25) vs. 19 (17, 23); Z = -2.312, P = 0.021]. CONCLUSIONS The incidence of RFS in septic patients is high. Factors influencing the occurrence of RFS in septic patients include BMI, SOFA score, albumin, baseline serum phosphorus, baseline serum potassium, caloric intake, protein intake, feeding within 48 hours of ICU admission, and septic shock. RFS prolongs the length of ICU stay and increases the 28-day mortality in patients with sepsis.
Humans ; Retrospective Studies ; Sepsis/complications* ; Prognosis ; Refeeding Syndrome/etiology* ; Case-Control Studies ; Intensive Care Units ; Male ; Nutritional Status ; Female ; Risk Factors ; Middle Aged ; Logistic Models ; Body Mass Index ; Aged

OBJECTIVE: To explore the relationship between serum sodium level and the risk of delirium in patients with sepsis. METHODS: Based on the Medical Information Mart for Intensive Care-IV (MIMIC-IV), adult patients with sepsis in the intensive care unit (ICU) were enrolled. The serum sodium level prior to the onset of sepsis during hospitalization was used as the exposure variable. Delirium was assessed using the ICU-confusion assessment method (ICU-CAM) as the primary outcome. Patients were divided into delirium and non-delirium groups based on the occurrence of delirium. The relationship between serum sodium level and delirium risk was described using restricted cubic spline (RCS) to determine the optimal reference range for serum sodium. Logistic regression analysis was used to evaluate the effect of blood sodium levels on delirium in sepsis patients. Subgroup analyses were performed to explore potential interactions and further validate the robustness of the results. Receiver operator characteristic curve (ROC curve) analysis was performed to assess the predictive value of serum sodium level for delirium occurrence in patients with sepsis. RESULTS: A total of 13 889 patients with sepsis were included, of which 4 831 experienced delirium. The maximum and mean serum sodium values were significantly higher in the delirium group compared to the non-delirium group, while there were no statistically significant differences in terms of initial and minimum serum sodium values between the two groups. Compared with the non-delirium group, the delirium group had a higher mortality and longer hospital stay. The RCS curve showed that a "U"-shaped relationship between serum sodium level and delirium risk in patients with sepsis, with the optimal reference range for average serum sodium was 135.3-141.3 mmol/L. Group based on this reference range, compared to the group with 135.3 mmol/L ≤ serum sodium ≤ 141.3 mmol/L, the delirium incidence and mortality were significantly higher, and the hospital stay was longer in the groups with serum sodium < 135.3 mmol/L and serum sodium ≥ 141.3 mmol/L [delirium incidence: 36.92%, 40.88% vs. 31.22%; 28-day mortality: 23.08%, 20.15% vs. 13.39%; 90-day mortality: 30.75%, 24.81% vs. 18.26%; in-hospital mortality: 19.53%, 17.48% vs. 11.61%; ICU mortality: 14.35%, 14.05% vs. 9.00%; hospital length of stay (days): 10.1 (6.1, 17.7), 9.4 (5.4, 17.0) vs. 8.9 (5.5, 15.4), length of ICU stay (days): 3.7 (2.1, 7.1), 4.0 (2.1, 8.9) vs. 3.2 (1.9, 6.8); all P < 0.01]. Logistic regression analysis showed that, in the initial model and each factor-adjusted models, compared to the reference group with 135.3 mmol/L ≤ serum sodium < 141.3 mmol/L, serum sodium < 135.3 mmol/L increased the risk of delirium in septic patients by 21% to 29% [odds ratio (OR) was 1.21-1.29, all P < 0.01], while serum sodium ≥ 141.3 mmol/L increased the delirium risk by 28%-52% (OR was 1.28-1.52, all P < 0.01). Subgroup analyses based on gender, age, race, diuretic use, and sequential organ failure assessment (SOFA) score revealed there was no significant interactions between subgroup variables and serum sodium, and the results supported that both serum sodium < 135.3 mmol/L and serum sodium ≥ 141.3 mmol/L were risk factors for delirium in septic patients. ROC curve analysis showed that the area under the curve (AUC) for predicting delirium in septic patients based on serum sodium was 0.614, with a cut-off value of 139.5 mmol/L yielding a specificity of 67.5% and sensitivity of 50.9%. CONCLUSIONS The risk of delirium in patients with sepsis is associated with serum sodium level in a "U"-shaped manner. Both high and low serum sodium levels are associated with increased risk of delirium, higher all-cause mortality, and prolonged hospital stays in patients with sepsis. Abnormal serum sodium levels may have predictive value for sepsis-associated delirium and could serve as an early biomarker for identifying delirium in septic patients, although further validation is needed.
Humans ; Delirium/etiology* ; Sepsis/complications* ; Sodium/blood* ; Intensive Care Units ; Risk Factors ; Male ; Middle Aged ; Female ; Aged ; Logistic Models ; Adult