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Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are common and devastating clinical disorders with high mortality and no specific therapy. An excessive inflammatory response results in the progression of ALI/ARDS, and the NLRP3 inflammasome is a key participant in inflammation. Erythropoietin (EPO), which is clinically used for anemia, reportedly exerts pleiotropic effects in ALI. However, whether EPO could protect against lipopolysaccharide (LPS)-induced ALI by regulating the NLRP3 inflammasome and its underlying mechanisms remain poorly elucidated. This study aimed to explore whether the therapeutic effects of EPO rely on the suppression of the NLRP3 inflammasome and the specific mechanisms in an LPS-induced ALI mouse model. ALI was induced in C57BL/6 mice by intraperitoneal (i.p.) injection of LPS (15 mg/kg). EPO was administered intraperitoneally at 5 U/g after LPS challenge. The mice were sacrificed 8 h later. Our findings indicated that application of EPO markedly diminished LPS-induced lung injury by restoring histopathological changes, lessened lung wet/dry (W/D) ratio, protein concentrations in bronchoalveolar lavage fluid (BALF) and myeloperoxidase (MPO) levels. Meanwhile, EPO evidently decreased interleukin-1β (IL-1β) and interleukin-18 (IL-18) secretion, the expression of NLRP3 inflammasome components including pro-IL-1β, NLRP3, and cleaved caspase-1 as well as phosphorylation of nuclear factor-κB (NF-κB) p65, which may be associated with activation of EPO receptor (EPOR), phosphorylation of Janus-tyrosine kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3). However, all the beneficial effects of EPO on ALI and modulation NLRP3 inflammasome were remarkably abrogated by the inhibition of EPOR/JAK2/STAT3 pathway and knockout (KO) of NLRP3 gene. Taken together, this study indicates that EPO can effectively attenuate LPS-induced lung injury in mice by suppressing the NLRP3 inflammasome, which is dependent upon activation of EPOR/JAK2/STAT3 signaling and inhibition of the NF-κB pathway.

The definition of sepsis was updated to sepsis-3 in February 2016. However, the performance of the previous and new definition of sepsis remains unclear in China. This was a retrospective multicenter study in six intensive care unit (ICUs) from five university-affiliated hospitals to compare the performance between sepsis-1 and sepsis-3 in China. From May 1, 2016 to June 1, 2016, 496 patients were enrolled consecutively. Data were extracted from the electronic clinical records. We evaluated the performance of sepsis-1 and sepsis-3 by measuring the area under the receiver operating characteristic curves (AUROC) to predict 28-day mortality rates. Of 496 enrolled patients, 186 (37.5%) were diagnosed with sepsis according to sepsis-1, while 175 (35.3%) fulfilled the criteria of sepsis-3. The AUROC of systemic inflammatory response syndrome (SIRS) is significantly smaller than that of sequential organ failure assessment (SOFA) (0.55 [95% confidence interval, 0.46–0.64] vs. 0.69 (95% confidence interval, 0.61–0.77], P = 0.008) to predict 28-day mortality rates of infected patients. Moreover, 5.9% infected patients (11 patients) were diagnosed as sepsis according to sepsis-1 but not to sepsis-3. The APACHE II, SOFA scores, and mortality rate of the 11 patients were significantly lower than of patients whose sepsis was defined by both the previous and new criteria (8.6±3.5 vs. 16.3±6.2, P =  < 0.001; 1 (0–1) vs. 6 (4–8), P = <0.001; 0.0 vs. 33.1%, P = 0.019). In addition, the APACHE II, length of stay in ICU, and 28-day mortality rate of septic patients rose gradually corresponding with the raise in SOFA score (but not the SIRS score). Sepsis-3 performed better than sepsis-1 in the study samples in ICUs in China.

Purpose Sepsis-associated coagulopathy (SAC) contributes to the development of multiple organ failure (MOF) and increasing mortality. The present study was conducted to investigate whether coagulative biomarkers on admission to the intensive care unit (ICU) can predict acute kidney injury (AKI) and mortality in patients with septic shock caused by intra-abdominal infection (IAI). Patients and methods An observational retrospective study was conducted in the surgical ICU. We studied patients who met the criteria of septic shock (Sepsis-3) caused by IAI between January 1, 2013, and December 31, 2016. By adjusting for baseline characteristics, multivariate regression analyses were employed to identify independent risk factors for predicting AKI and mortality. Results Of the 138 enrolled patients, 65 patients developed AKI. The patients who developed AKI exhibited a dramatically higher Sequential Organ Failure Assessment (SOFA) score (median, 12), Acute Physiology and Chronic Health Evaluation (APACHE) II score (median, 27.5) and mortality rate. In both models, we found that activated partial thromboplastin time (APTT) (odds ratio (OR)=1.074, 95% confidence interval (CI) 1.030–1.120, p =0.001), prothrombin time (PT) (OR=1.162, 95% CI 1.037–1.302, p =0.010) and D-dimer level (OR=1.098, 95% CI 1.002–1.202, p =0.045) on admission to the ICU were significant risk factors for AKI. Moreover, Cox regression analysis showed that prolonged APTT (OR=1.065, 95% CI 1.025–1.107, p =0.001) was independently associated with high mortality. Conclusion In patients with septic shock caused by IAI, APTT, PT and D-dimer level on admission to the ICU were significantly associated with AKI. Furthermore, APTT was an independent predictor of 30-day mortality.

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medRxiv preprint regression. This diagnostic nomogram was assessed by the internal and external validation data set. Further, we plotted decision curves and clinical impact curve to evaluate the clinical usefulness of this diagnostic nomogram. RESULTS:The predictive factors including the epidemiological history, wedgeshaped or fan-shaped lesion parallel to or near the pleura, bilateral lower lobes, ground glass opacities, crazy paving pattern and white blood cell (WBC) count were contained in the nomogram. In the primary cohort, the C-statistic for predicting the probability of the COVID-19 pneumonia was 0.967, even higher than the C-statistic (0.961) in initial viral nucleic acid nomogram which was established using the univariable regression.The C-statistic was 0.848 in external validation cohort. Good calibration curves were observed for the prediction probability in the internal validation and external validation cohort. The nomogram both performed well in terms of discrimination and calibration.Moreover, decision curve and clinical impact curve were also beneficial for COVID-19 pneumonia patients.

DEFA1/DEFA3, genes encoding human neutrophil peptides (HNP) 1–3, display wide-ranging copy number variations (CNVs) and is functionally associated with innate immunity and infections. To identify potential associations between DEFA1/DEFA3 CNV and hospital-acquired infections (HAIs), we enrolled 106 patients with HAIs and 109 controls in the intensive care unit (ICU) and examined their DEFA1/DEFA3 CNVs. DEFA1/DEFA3 copy number ranged from 2 to 16 per diploid genome in all 215 critically ill patients, with a median of 7 copies. In HAIs, DEFA1/DEFA3 CNV varied from 2 to 12 with a median of 6, which was significantly lower than that in controls (2 to 16 with a median of 8, p = 0.017). Patients with lower DEFA1/DEFA3 copy number (CNV < 7) were far more common in HAIs than in controls (52.8% in HAIs versus 35.8% in controls; p = 0.014; OR, 2.010; 95% CI, 1.164–3.472). The area under the receiver operating characteristic (AUROC) of DEFA1/DEFA3 CNV combined with clinical characteristics to predict the incidence of HAIs was 0.763 (95% CI 0.700–0.827), showing strong predictive ability. Therefore, lower DEFA1/DEFA3 copy number contributes to higher susceptibility to HAIs in critically ill patients, and DEFA1/DEFA3 CNV is a significant hereditary factor for predicting HAIs.

Background The COVID-19 virus is an emerging virus associated with severe respiratory illness first detected in December, 2019, and rapidly spread worldwide. The aim of this study was to establish an effective diagnostic nomogram for suspected COVID-19 pneumonia patients. Methods We used the LASSO aggression and multivariable logistic regression methods to explore the predictive factors associated with COVID-19 pneumonia, and established the diagnostic nomogram for COVID-19 pneumonia using multivariable regression. This diagnostic nomogram was assessed by the internal and external validation data set. Further, we plotted decision curves and clinical impact curve to evaluate the clinical usefulness of this diagnostic nomogram. Results The predictive factors including the epidemiological history, wedge-shaped or fan-shaped lesion parallel to or near the pleura, bilateral lower lobes, ground glass opacities, crazy paving pattern and white blood cell (WBC) count were contained in the nomogram. In the primary cohort, the C-statistic for predicting the probability of the COVID-19 pneumonia was 0.967, even higher than the C-statistic (0.961) in initial viral nucleic acid nomogram which was established using the univariable regression. The C-statistic was 0.848 in external validation cohort. Good calibration curves were observed for the prediction probability in the internal validation and external validation cohort. The nomogram both performed well in terms of discrimination and calibration. Moreover, decision curve and clinical impact curve were also beneficial for COVID-19 pneumonia patients. Conclusion Our nomogram can be used to predict COVID-19 pneumonia accurately and favourably.