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Objective: To compare the effects of different vitamins on patients with septic shock (SS) through Bayesian network meta-analysis.
Methods: Randomized controlled trials (RCTs) on vitamins for septic shock patients were retrieved from PubMed, Embase, Cochrane Library, Web of Science, etc. The retrieval time was set from the establishment of the database to May 20, 2024. All relevant studies on vitamin treatment for septic shock were retrieved and screened according to the established inclusion and exclusion criteria. Intensive care unit (ICU) length of stay, mechanical ventilation time, Sequential Organ Failure Assessment (SOFA) scores after 24 h, total hospital stay, and 28-day mortality were used as outcome measures. The quality of the included studies was evaluated for risk of bias, and R software was used for data analysis.
Results: A total of 36 articles were included in the analysis, covering 4,473 patients with septic shock. The vitamins included vitamin B (VB), vitamin C (VC), vitamin D (VD), vitamin E (VE), hydroxocobalamin (HYD), and vitamin combinations such as hydrocortisone plus vitamin C plus vitamin B (HYDVCVB), vitamin D plus probiotics (VDP), vitamin C plus vitamin B (VCVB), and hydrocortisone plus vitamin C (HYDVC). The network meta-analysis results showed that in terms of ICU length of stay, VD was superior to the control group [mean difference (MD) = 4.57, 95% CI (1.01, 9.69)] and HYDVCVB [MD = 5.4, 95% CI (0.51, 11.66)], with statistically significant differences. In terms of mechanical ventilation time, VC, VD, VCVB, and HYDVCVB showed no statistically significant differences compared to the control group. Regarding the SOFA score after 24 h, VDP was superior to the control group [MD = 2.98, 95% CI (0.27, 5.62)], as well as HYDVCVB [MD = 3.32, 95% CI (0.59, 6.04)], VB [MD = 2.96, 95% CI (0.18, 5.67)], VC [MD = 2.91, 95% CI (0.17, 5.57)], VCVB [MD = 3.18, 95% CI (0.31, 5.9)], and VD [MD = 2.91, 95% CI (0.05, 5.71)], with statistically significant differences. In terms of total hospital stay, VD was superior to the control group [MD = 7.61, 95% CI (2.59, 12.63)], as well as HYDVCVB [MD = 7.71, 95% CI (2.55, 12.9)], VB [MD = 7.6, 95% CI (0.84, 14.39)], VC [MD = 9.93, 95% CI (3.9, 15.92)], and VCVB [MD = 8.1, 95% CI (1.79, 14.41)], with statistically significant differences. Regarding 28-day mortality, VB, VC, VD, VDP, VCVB, HYDVCVB showed no statistically significant differences compared to the control group.
Conclusion: In patients with septic shock, the use of VD shows certain advantages in reducing ICU length of stay and total hospital length of stay. Moreover, its combination with probiotics may help reduce the SOFA scores after 24 h. However, these interventions have not significantly impacted 28-day mortality or mechanical ventilation time.
Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, PROSPERO: CRD42024599094.
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http://dx.doi.org/10.3389/fnut.2025.1566422 | DOI Listing |
Nan Fang Yi Ke Da Xue Xue Bao
August 2025
Anhui Provincial Key Laboratory of Immunology in Chronic Diseases, Bengbu Medical University, Bengbu 233030, China.
Objectives: To investigate the effect of avitinib for suppressing NLRP3 inflammasome activation and alleviating septic shock and explore the underlying mechanism.
Methods: Mouse bone marrow-derived macrophages (BMDM), human monocytic leukemia cell line THP-1, and peripheral blood mononuclear cells (PBMC) isolated from healthy volunteers were pre-treated with avitinib, followed by activation of the canonical NLRP3 inflammasome using agonists including nigericin, monosodium urate (MSU) crystals, or adenosine triphosphate (ATP). Non-canonical NLRP3 inflammasome activation was induced intracellular transfection of lipopolysaccharide (LPS).
Int J Infect Dis
September 2025
Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini 4, 20090, Pieve Emanuele, Milan, Italy; Infectious Diseases Unit - IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089, Rozzano, Milan, Italy.
Background: Echinocandins represent first-line therapy for Candida Bloodstream Infections (C-BSIs). Incidence of treatment failure (TF) remains high with unclear risk factors.
Aim: to evaluate predictors of echinocandin TF for C-BSIs.
Chest
September 2025
Department of Critical Care Medicine, Respiratory Institute, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH, USA; Cleveland Clinic Lerner College of Medicine, Cleveland, OH, USA.
Topic Importance: Sepsis-induced cardiomyopathy (SICM) is a heterogeneous cardiovascular dysfunction associated with sepsis and septic shock. While traditionally defined by reversible left ventricular (LV) systolic dysfunction, recent evidence has revealed a broader spectrum, including LV diastolic dysfunction, hyperdynamic LV systolic states, and right ventricular (RV) injury, occurring independently or in combination. Despite their prognostic significance, these phenotypes remain underrecognized and understudied.
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August 2025
Department of Imaging, Taixing People's Hospital Affiliated to Yangzhou University, Taixing, Jiangsu, China.
Objective: To analyze the clinical characteristics, etiological distribution, and treatment outcomes of Hepatic Portal Venous Gas (HPVG) in a cohort of elderly patients with multiple comorbidities, and to evaluate the impact of early surgical intervention on survival rates.
Methods: A retrospective study was conducted on 25 patients with HPVG admitted to Taixing People's Hospital of Yangzhou University from January 2010 to June 2024. The study included demographic characteristics, symptoms, comorbidities, etiology, laboratory and abdominal CT results, treatment, and outcomes.
J Microbiol Immunol Infect
August 2025
Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Pharmacy, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan. Electronic address:
Background: Machine learning (ML) techniques are increasingly being used in health outcome research to develop predictive models. However, ML models are often referred to as "black box models" because they lack interpretability. Our goal was to develop an ML model to predict mortality risk in patients with community-onset bacteremia.
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