Optimal combination of early biomarkers for infection and sepsis diagnosis in the emergency department: The BIPS study

Velly, Laetitia; Volant, Steven; Fitting, Catherine; Ghazali, Daniel Aiham; Salipante, Florian; Mayaux, Julien; Monsel, Gentiane; Cavaillon, Jean‐Marc; Hausfater, Pierre

doi:10.1016/j.jinf.2021.02.019

Cited by 10 publications

(5 citation statements)

References 52 publications

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“…Our findings suggest that mHLA‐DR, PD‐1 of CD4‐CD8‐T cells, and the nCD64 index, when combined with plasma PCT, may prove a valuable tool to predict mortality in sepsis. These results are consistent with previous studies, 27 , 28 such as nCD64 expression combined with the SOFA score is a valuable panel for early diagnosis of infection in sepsis, risk stratification and evaluation of prognosis in sepsis patients in the emergency department. 29 In additon, these findings have potential clinical relevance and biological plausibility.…”

Section: Discussionsupporting

confidence: 93%

An integrative model with HLA‐DR, CD64, and PD‐1 for the diagnostic and prognostic evaluation of sepsis

Chen,

Chong,

Zhang

et al. 2024

Immunity Inflam & Disease

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BackgroundSepsis is a life‐threatening organ dysfunction caused by a dysregulated host response to infection and progressive immunosuppression with high mortality. HLA‐DR, CD64, and PD‐1 were assumed to be useful biomarkers for sepsis prediction. However, the ability of a combination of these biomarkers has not been clarified.MethodsAn observational case‐control study was conducted that included 30 sepsis patients, 30 critically ill patients without sepsis admitted to the intensive care unit (ICU), and 32 healthy individuals. The levels of HLA‐DR, CD64, and PD‐1 expression in peripheral blood immune cells and subsets was assayed on Days 1, 3, and 5, and the clinical information of patients was collected. We compared these biomarkers between groups and evaluated the predictive validity of single and combined biomarkers on sepsis mortality.ResultsThe results indicate that PD‐1 expression on CD4−CD8−T (PD‐1+CD4−CD8−T) (19.19% ± 10.78% vs. 9.88% ± 1.79%, p = .004) cells and neutrophil CD64 index (nCD64 index) (9.15 ± 5.46 vs. 5.33 ± 2.34, p = .001) of sepsis patients were significantly increased, and HLA‐DR expression on monocytes (mHLA‐DR+) was significantly reduced (13.26% ± 8.06% vs. 30.17% ± 21.42%, p = 2.54 × 10−4) compared with nonsepsis critically ill patients on the first day. Importantly, the expression of PD‐1+CD4−CD8−T (OR = 0.622, 95% CI = 0.423–0.916, p = .016) and mHLA‐DR+ (OR = 1.146, 95% CI = 1.014–1.295, p = .029) were significantly associated with sepsis mortality. For sepsis diagnosis, the mHLA‐DR+, PD‐1+CD4−CD8−T, and nCD64 index showed the moderate individual performance, and combinations of the three biomarkers achieved greater diagnostic value (AUC = 0.899, 95% CI = 0.792–0.962). When adding PCT into the combined model, the AUC increased to 0.936 (95% CI = 0.840–0.983). For sepsis mortality, combinations of PD‐1+CD4−CD8−T and mHLA‐DR+, have a good ability to predict the prognosis of sepsis patients, with an AUC = 0.921 (95% CI = 0.762–0.987).ConclusionThese findings indicate that the combinations of HLA‐DR, CD64, and PD‐1 outperformed each of the single indicator in diagnosis and predicting prognosis of sepsis.

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Section: Discussionsupporting

confidence: 93%

An integrative model with HLA‐DR, CD64, and PD‐1 for the diagnostic and prognostic evaluation of sepsis

Chen,

Chong,

Zhang

et al. 2024

Immunity Inflam & Disease

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“…The pathogenesis is that the bacteria and infected foci caused by the infection in the patient have an adverse effect on the balance of local blood circulation, which makes the microcirculation function of relevant tissues disordered in the process of disease, thus affecting the patient's heart and other organs. This will lead to myocardial cell damage and insufficient heart filling, imbalance of oxygen supply, and demand in tissues and organs [ 10 , 11 ]. In recent years, medical institutions have carried out a large number of clinical studies on the treatment of sepsis.…”

Section: Related Workmentioning

confidence: 99%

Analysis of the Predictive Effect of Lactic Acid Combined with Cardiac Troponin T and 5-Hydroxytryptophan on the Severity of Sepsis in ICU Patients and Its Correlation with Prognosis

Jiang

Wang

et al. 2022

Contrast Media & Molecular Imaging

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In order to explore the effective markers of presepsis in the prediction of clinical disease and disease severity, the predictive effect of lactic acid (Lac) combined with cardiac troponin T (cTnT) and 5-hydroxytryptophan (5-HT) on the severity of sepsis in intensive care unit (ICU) patients and its correlation with prognosis is investigated. A total of 85 sepsis patients admitted to the ICU of our hospital from January 2020 to June 2021 are selected to establish the ICU sepsis group, and 72 health examination patients who received physical examination in our hospital during the same period are included in the healthy control group. The experimental results demonstrate that combined detection mode of serum Lac, cTnT, and 5-HT indicators has a high predictive value for the condition of patients with ICU sepsis and those indicators are closely correlated with the prognosis of patients. It suggests that the follow-up clinical monitoring of serum Lac, cTnT, and 5-HT indicators for patients with ICU sepsis can evaluate their condition and improve and optimize the clinical diagnosis and treatment plan effectively.

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“…Additionally, reduced CX3CR1 mRNA expression levels have been identified as an independent biomarker in severe sepsis cases 25 . A clinical study involving 291 patients further indicated the potential of CX3CR1 as an early diagnostic biomarker for infections and sepsis in emergency settings 26 . Moreover, CX3CR1 plays a significant role in the immunomodulatory interaction between macrophages and the endothelium during sepsis, offering positive prognostic implications for affected individuals 27 .…”

Section: Discussionmentioning

confidence: 99%

Development of macrophage-associated genes prognostic signature predicts clinical outcome and immune infiltration for sepsis

Ma,

Wu,

et al. 2024

Sci Rep

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Sepsis is a major global health problem, causing a significant burden of disease and death worldwide. Risk stratification of sepsis patients, identification of severe patients and timely initiation of treatment can effectively improve the prognosis of sepsis patients. We procured gene expression datasets for sepsis (GSE54514, GSE65682, GSE95233) from the Gene Expression Omnibus and performed normalization to mitigate batch effects. Subsequently, we applied weighted gene co-expression network analysis to categorize genes into modules that exhibit correlation with macrophage activity. To pinpoint macrophage-associated genes (MAAGs), we executed differential expression analysis and single sample gene set enrichment analysis. We then established a prognostic model derived from four MAAGs that were significantly differentially expressed. Functional enrichment analysis and immune infiltration assessments were instrumental in deciphering the biological mechanisms involved. Furthermore, we employed principal component analysis and conducted survival outcome analyses to delineate molecular subgroups within sepsis. Four novel MAAGs—CD160, CX3CR1, DENND2D, and FAM43A—were validated and used to create a prognostic model. Subgroup classification revealed distinct molecular profiles and a correlation with 28-day survival outcomes. The MAAGs risk score was developed through univariate Cox, LASSO, and multivariate Cox analyses to predict patient prognosis. Validation of the risk score upheld its prognostic significance. Functional enrichment implicated ribonucleoprotein complex biogenesis, mitochondrial matrix, and transcription coregulator activity in sepsis, with an immune infiltration analysis indicating an association between MAAGs risk score and immune cell populations. The four MAAGs exhibited strong diagnostic capabilities for sepsis. The research successfully developed a MAAG-based prognostic model for sepsis, demonstrating that such genes can significantly stratify risk and reflect immune status. Although in-depth mechanistic studies are needed, these findings propose novel targets for therapy and provide a foundation for future precise clinical sepsis management.

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Optimal combination of early biomarkers for infection and sepsis diagnosis in the emergency department: The BIPS study

Cited by 10 publications

References 52 publications

An integrative model with HLA‐DR, CD64, and PD‐1 for the diagnostic and prognostic evaluation of sepsis

An integrative model with HLA‐DR, CD64, and PD‐1 for the diagnostic and prognostic evaluation of sepsis

Analysis of the Predictive Effect of Lactic Acid Combined with Cardiac Troponin T and 5-Hydroxytryptophan on the Severity of Sepsis in ICU Patients and Its Correlation with Prognosis

Development of macrophage-associated genes prognostic signature predicts clinical outcome and immune infiltration for sepsis

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