“…Finally, 86 studies were included after two updated searches in February 2015 and September 2016 (Fig. 1) (Abidi et al 2008; Ahmadinejad et al 2009; Al-Nawas et al 1996; Anand et al 2015; Balc et al 2003; Barati et al 2010; Battista et al 2016; Bell et al 2003; Beqja-Lika et al 2013; Carpio et al 2015; Castelli et al 2004; Clec’h et al 2006; de Pablo et al 2013; Dorizzi et al 2006; Du et al 2003; Endo et al 2012; Farag et al 2013; Feng et al 2012; Gaini et al 2006; Garnacho-Montero et al 2014; Gerrits et al 2013; Giamarellos-Bourboulis et al 2008; Gibot et al 2004; Godnic et al 2015; Guven et al 2002; Han et al 2016; Harbarth et al 2001; Hoenigl et al 2013; Hou et al 2012, 2016; Hsu et al 2011; Ishikura et al 2014; Ivancevic et al 2008; Jekarl et al 2013, 2014; Jiang et al 2015; Kim and Zhang 2012; Kofoed et al 2007; Latour-Perez et al 2010; Lewis et al 2015; Li et al 2013a; Lin et al 2015; Matera et al 2013; Mat-Nor et al 2016; Mearelli et al 2014; Meynaar et al 2011; Miglietta et al 2015; Miller et al 1999; Muthiah et al 2007, Naeini and Montazerolghaem 2006; Oshita et al 2010; Papadimitriou-Olivgeris et al 2015; Ratzinger et al 2013; Reichsoellner et al 2014; Righi et al 2014; Rivera-Chavez and Minei 2009; Rogina et al 2014; Romualdo et al 2014; Ruiz-Alvarez et al 2009; Sakr et al 2008; Scherpereel et al 2006; Schulte et al 2011; Selberg et al 2000; Seok et al 2012; Shozushima et al 2011; Sierra et al 2004; Su et al 2012, 2013; Sungurtekin et al …”
Section: Resultsmentioning
confidence: 99%
“…Furthermore, the study by Lin et al was divided into a training group and validation group. The results of these three studies were divided into six parts (Anand et al 2015; Clec’h et al 2006; Lin et al 2015). Fig.…”
BackgroundSepsis is one of the most common diseases that seriously threaten human health. Although a large number of markers related to sepsis have been reported in the last two decades, the diagnostic accuracy of these biomarkers remains unclear due to the lack of similar baselines among studies. Therefore, we conducted a large systematic review and meta-analysis to evaluate the diagnostic value of biomarkers from studies that included non-infectious systemic inflammatory response syndrome patients as a control group.MethodsWe searched Medline, Embase and the reference lists of identified studies beginning in April 2014. The last retrieval was updated in September 2016.ResultsUltimately, 86 articles fulfilled the inclusion criteria. Sixty biomarkers and 10,438 subjects entered the final analysis. The areas under the receiver operating characteristic curves for the 7 most common biomarkers, including procalcitonin, C-reactive protein, interleukin 6, soluble triggering receptor expressed on myeloid cells-1, presepsin, lipopolysaccharide binding protein and CD64, were 0.85, 0.77, 0.79, 0.85, 0.88, 0.71 and 0.96, respectively. The remaining 53 biomarkers exhibited obvious variances in diagnostic value and methodological quality.ConclusionsAlthough some biomarkers displayed moderate or above moderate diagnostic value for sepsis, the limitations of the methodological quality and sample size may weaken these findings. Currently, we still lack an ideal biomarker to aid in the diagnosis of sepsis. In the future, biomarkers with better diagnostic value as well as a combined diagnosis using multiple biomarkers are expected to solve the challenge of the diagnosis of sepsis.Electronic supplementary materialThe online version of this article (doi:10.1186/s40064-016-3591-5) contains supplementary material, which is available to authorized users.
“…Finally, 86 studies were included after two updated searches in February 2015 and September 2016 (Fig. 1) (Abidi et al 2008; Ahmadinejad et al 2009; Al-Nawas et al 1996; Anand et al 2015; Balc et al 2003; Barati et al 2010; Battista et al 2016; Bell et al 2003; Beqja-Lika et al 2013; Carpio et al 2015; Castelli et al 2004; Clec’h et al 2006; de Pablo et al 2013; Dorizzi et al 2006; Du et al 2003; Endo et al 2012; Farag et al 2013; Feng et al 2012; Gaini et al 2006; Garnacho-Montero et al 2014; Gerrits et al 2013; Giamarellos-Bourboulis et al 2008; Gibot et al 2004; Godnic et al 2015; Guven et al 2002; Han et al 2016; Harbarth et al 2001; Hoenigl et al 2013; Hou et al 2012, 2016; Hsu et al 2011; Ishikura et al 2014; Ivancevic et al 2008; Jekarl et al 2013, 2014; Jiang et al 2015; Kim and Zhang 2012; Kofoed et al 2007; Latour-Perez et al 2010; Lewis et al 2015; Li et al 2013a; Lin et al 2015; Matera et al 2013; Mat-Nor et al 2016; Mearelli et al 2014; Meynaar et al 2011; Miglietta et al 2015; Miller et al 1999; Muthiah et al 2007, Naeini and Montazerolghaem 2006; Oshita et al 2010; Papadimitriou-Olivgeris et al 2015; Ratzinger et al 2013; Reichsoellner et al 2014; Righi et al 2014; Rivera-Chavez and Minei 2009; Rogina et al 2014; Romualdo et al 2014; Ruiz-Alvarez et al 2009; Sakr et al 2008; Scherpereel et al 2006; Schulte et al 2011; Selberg et al 2000; Seok et al 2012; Shozushima et al 2011; Sierra et al 2004; Su et al 2012, 2013; Sungurtekin et al …”
Section: Resultsmentioning
confidence: 99%
“…Furthermore, the study by Lin et al was divided into a training group and validation group. The results of these three studies were divided into six parts (Anand et al 2015; Clec’h et al 2006; Lin et al 2015). Fig.…”
BackgroundSepsis is one of the most common diseases that seriously threaten human health. Although a large number of markers related to sepsis have been reported in the last two decades, the diagnostic accuracy of these biomarkers remains unclear due to the lack of similar baselines among studies. Therefore, we conducted a large systematic review and meta-analysis to evaluate the diagnostic value of biomarkers from studies that included non-infectious systemic inflammatory response syndrome patients as a control group.MethodsWe searched Medline, Embase and the reference lists of identified studies beginning in April 2014. The last retrieval was updated in September 2016.ResultsUltimately, 86 articles fulfilled the inclusion criteria. Sixty biomarkers and 10,438 subjects entered the final analysis. The areas under the receiver operating characteristic curves for the 7 most common biomarkers, including procalcitonin, C-reactive protein, interleukin 6, soluble triggering receptor expressed on myeloid cells-1, presepsin, lipopolysaccharide binding protein and CD64, were 0.85, 0.77, 0.79, 0.85, 0.88, 0.71 and 0.96, respectively. The remaining 53 biomarkers exhibited obvious variances in diagnostic value and methodological quality.ConclusionsAlthough some biomarkers displayed moderate or above moderate diagnostic value for sepsis, the limitations of the methodological quality and sample size may weaken these findings. Currently, we still lack an ideal biomarker to aid in the diagnosis of sepsis. In the future, biomarkers with better diagnostic value as well as a combined diagnosis using multiple biomarkers are expected to solve the challenge of the diagnosis of sepsis.Electronic supplementary materialThe online version of this article (doi:10.1186/s40064-016-3591-5) contains supplementary material, which is available to authorized users.
“…Studies in this clinical setting only exist regarding CRP[19,20,63-75] and PCT[76-80] and their findings are not without controversies. In Table 2 we summarized available data on clinical significance of CRP and PCT in short or long-term mortality of patients with cirrhosis.…”
AIMTo evaluate the diagnostic and prognostic value of presepsin in cirrhosis-associated bacterial infections.METHODSTwo hundred and sixteen patients with cirrhosis were enrolled. At admission, the presence of bacterial infections and level of plasma presepsin, serum C-reactive protein (CRP) and procalcitonin (PCT) were evaluated. Patients were followed for three months to assess the possible association between presepsin level and short-term mortality.RESULTSPresent 34.7 of patients had bacterial infection. Presepsin levels were significantly higher in patients with infection than without (median, 1002 pg/mL vs 477 pg/mL, P < 0.001), increasing with the severity of infection [organ failure (OF): Yes vs No, 2358 pg/mL vs 710 pg/mL, P < 0.001]. Diagnostic accuracy of presepsin for severe infections was similar to PCT and superior to CRP (AUC-ROC: 0.85, 0.85 and 0.66, respectively, P = NS for presepsin vs PCT and P < 0.01 for presepsin vs CRP). At the optimal cut-off value of presepsin > 1206 pg/mL sensitivity, specificity, positive predictive values and negative predictive values were as follows: 87.5%, 74.5%, 61.8% and 92.7%. The accuracy of presepsin, however, decreased in advanced stage of the disease or in the presence of renal failure, most probably because of the significantly elevated presepsin levels in non-infected patients. 28-d mortality rate was higher among patients with > 1277 pg/mL compared to those with ≤ 1277 pg/mL (46.9% vs 11.6%, P < 0.001). In a binary logistic regression analysis, however, only PCT (OR = 1.81, 95%CI: 1.09-3.01, P = 0.022) but neither presepsin nor CRP were independent risk factor for 28-d mortality after adjusting with MELD score and leukocyte count.CONCLUSIONPresepsin is a valuable new biomarker for defining severe infections in cirrhosis, proving same efficacy as PCT. However, it is not a useful marker of short-term mortality.
“…In this context, a role of the caspase-3-mediated cell death in favoring bacterial dissemination was assumed, but this mechanism is restricted to tissues in which macrophages play a central role in pathogen uptake and killing, such as the liver [ 2 ]. In mice, death of animals infected with F. tularensis appears to result from widespread sepsis and inflammation [ 29 – 31 ], and mortality was correlated with the extent of the inflammatory response [ 17 ] including release of pro-inflammatory IL-6, an early diagnostic marker of bacterial sepsis [ 32 ].…”
BackgroundFrancisella tularensis, a gram-negative bacterium replicates intracellularly within macrophages and efficiently evades the innate immune response. It is able to infect and replicate within Kupffer cells, specialized tissue macrophages of the liver, and to modulate the immune response upon infection to its own advantage. Studies on Francisella tularensis liver infection were mostly performed in animal models and difficult to extrapolate to the human situation, since human infections and clinical observations are rare.ResultsUsing a human co-culture model of macrophages and hepatocytes we investigated the course of infection of three Francisella tularensis strains (subspecies holarctica – wildtype and live vaccine strain, and mediasiatica - wildtype) and analyzed the immune response triggered upon infection. We observed that hepatocytes support the intracellular replication of Franciscella species in macrophages accompanied by a specific immune response inducing TNFα, IL-1β, IL-6 and fractalkine (CX3CL1) secretion and the induction of apoptosis.ConclusionsWe could demonstrate that this human macrophage / hepatocyte co-culture model reflects strain-specific virulence of Francisella tularensis. We developed a suitable tool for more detailed in vitro studies on the immune response upon liver cell infection by F. tularensis.Electronic supplementary materialThe online version of this article (doi:10.1186/s12866-015-0621-3) contains supplementary material, which is available to authorized users.
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