Diagnosing sepsis: a step forward, and possibly a step back

Use of Biomarkers to Improve 28-Day Mortality Stratification in Patients with Sepsis and SOFA ≤ 6

Early diagnosis and appropriate treatments are crucial to reducing mortality risk in septic patients. Low SOFA scores and current biomarkers may not adequately discern patients that could develop severe organ dysfunction or have an elevated mortality risk. The aim of this prospective observational study was to evaluate the predictive value of the biomarkers mid-regional pro-adrenomedullin (MR-proADM), procalcitonin (PCT), C-reactive protein (CRP), and lactate for 28-day mortality in patients with sepsis, and patients with a SOFA score ≤6. 284 were included, with a 28-day all-cause mortality of 8.45% (n = 24). Non-survivors were older (p = 0.003), required mechanical ventilation (p = 0.04), were ventilated for longer (p = 0.02), and had higher APACHE II (p = 0.015) and SOFA (p = 0.027) scores. Lactate showed the highest predictive ability for all-cause 28-day mortality, with an area under the receiver-operating characteristic curve (AUROC) of 0.67 (0.55-0.79). The AUROC for all-cause 28-day mortality in patients with community-acquired infection was 0.69 (0.57-0.84) for SOFA and 0.70 (0.58-0.82) for MR-proADM. A 2.1 nmol/L cut-off point for this biomarker in this subgroup of patients discerned, with 100% sensibility, survivors from non-survivors at 28 days. In patients with community-acquired sepsis and initial SOFA score ≤ 6, MR-proADM could help identify patients at risk of 28-day mortality.

Construction of an HLA Classifier for Early Diagnosis, Prognosis, and Recognition of Immunosuppression in Sepsis by Multiple Transcriptome Datasets

Background: Sepsis is a clinical syndrome, due to a dysregulated inflammatory response to infection. Accumulating evidence shows that human leukocyte antigen (HLA) genes play a key role in the immune responses to sepsis. Nevertheless, the effects of HLA genes in sepsis have still not been comprehensively understood.

Methods: A systematical search was performed in the Gene Expression Omnibus (GEO) and ArrayExpress databases from inception to 10 September 2021. Random forest (RF) and modified Lasso penalized regression were conducted to identify hub genes in multi-transcriptome data, thus we constructed a prediction model, namely the HLA classifier. ArrayExpress databases, as external validation, were utilized to evaluate its diagnostic, prognostic, and predictive performance. Immune cell infiltration score was calculated via CIBERSORTx tools and single-sample gene set enrichment analysis (ssGSEA). Gene set variation analysis (GSVA) and ssGSEA were conducted to determine the pathways that are significantly enriched in different subgroups. Next, we systematically correlated the HLA classifier with immunological characteristics from multiple perspectives, such as immune-related cell infiltration, pivotal molecular pathways, and cytokine expression. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to validate the expression level of HLA genes in clinical samples.

Results: A total of nine datasets comprising 1,251 patients were included. Based on RF and modified Lasso penalized regression in multi-transcriptome datasets, five HLA genes (B2M, HLA-DQA1, HLA-DPA1, TAP1, and TAP2) were identified as hub genes, which were used to construct an HLA classifier. In the discovery cohort, the HLA classifier exhibited superior diagnostic value (AUC = 0.997) and performed better in predicting mortality (AUC = 0.716) than clinical characteristics or endotypes. Encouragingly, similar results were observed in the ArrayExpress databases. In the E-MTAB-7581 dataset, the use of hydrocortisone in the HLA high-risk subgroup (OR: 2.84, 95% CI 1.07–7.57, p = 0.037) was associated with increased risk of mortality, but not in the HLA low-risk subgroup. Additionally, immune infiltration analysis by CIBERSORTx and ssGSEA revealed that B cells, activated dendritic cells, NK cells, T helper cells, and infiltrating lymphocytes (ILs) were significantly richer in HLA low-risk phenotypes, while Tregs and myeloid-derived suppressor cells (MDSCs) were more abundant in HLA high-risk phenotypes. The HLA classifier was significantly negatively correlated with B cells, activated dendritic cells, NK cells, T helper cells, and ILs, yet was significantly positively correlated with Tregs and MDSCs. Subsequently, molecular pathways analysis uncovered that cytokine-cytokine receptor (CCR) interaction, human leukocyte antigen (HLA), and antigen-presenting cell (APC) co-stimulation were significantly enriched in HLA low-risk endotypes, which was significantly negatively correlated with the HLA classifier in multi-transcriptome data. Finally, the expression levels of several cytokines (IL-10, IFNG, TNF) were significantly different between the HLA subgroups, and the ratio of IL-10/TNF was significantly positively correlated with HLA score in multi-transcriptome data. Results of qRT-PCR validated the higher expression level of B2M as well as lower expression level of HLA-DQA1, HLA-DPA1, TAP1, and TAP2 in sepsis samples compared to control sample.

Conclusion: Based on five HLA genes, a diagnostic and prognostic model, namely the HLA classifier, was established, which is closely correlated with responses to hydrocortisone and immunosuppression status and might facilitate personalized counseling for specific therapy.

Characterization of immune-related genes andimmune infiltration features for early diagnosis, prognosis and recognition of immunosuppression in sepsis

Among the body systems, the immune system plays a fundamental role in the pathophysiology of sepsis. The effects of immunogenomic and immune cell infiltration in sepsis were still not been systematically understood. Based on modified Lasso penalized regression and RF, 8 DEIRGs (ADM, CX3CR1, DEFA4, HLA-DPA1, MAPK14, ORM1, RETN, and SLPI) were combined to construct an IRG classifier. In the discovery cohort, IRG classifier exhibited superior diagnostic efficacy and performed better in predicting mortality than clinical characteristics or MARS/SRS endotypes. Encouragingly, similar results were observed in the ArrayExpress databases. The use of hydrocortisone in IRG high-risk subgroup was associated with increased risk of mortality. In IRG low-risk phenotypes, NK cells, T helper cells, and infiltrating lymphocyte (IL) are significantly richer, while T cells regulatory (Tregs) and myeloid-derived suppressor cells (MDSC) are more abundant in IRG high-risk phenotypes. IRG score were significantly negatively correlated with Cytokine cytokine receptor interaction (CCR) and human leukocyte antigen (HLA). Between the IRG subgroups, the expression levels of several cytokines (IL-10, IFNG, TNF) were significantly different, and IRG score was significantly positively correlated with ratio of IL-10/TNF. Results of qRT-PCR validated that higher expression level of ADM, DEFA4, MAPK14, ORM1, RETN, and SLPI as well as lower expression level of CX3CR1 and HLA-DPA1 in sepsis samples compared to control sample. A diagnostic and prognostic model, namely IRG classifier, was established based on 8 IRGs that is closely correlated with responses to hydrocortisone and immunosuppression status and might facilitate personalized counseling for specific therapy.

Impact of different consensus definition criteria on sepsis diagnosis in a cohort of critically ill patients-Insights from a new mathematical probabilistic approach to mortality-based validation of sepsis criteria

Background

Sepsis-3 definition uses SOFA score to discriminate sepsis from uncomplicated infection, replacing SIRS criteria that were criticized for being inaccurate. Eligibility of sepsis-3 criteria for sepsis diagnosis and the applied validation methodology using mortality as endpoint are topic of ongoing debate. We assessed the impact of different criteria on sepsis diagnosis in our ICU and devised a mathematical approach for mortality-based validation of sepsis criteria. As infectious status is often unclear at clinical deterioration, we integrated non-infected patients into analysis.

Methods

Suspected infection, SOFA and SIRS were captured for an ICU cohort of a university center over one year. For raw scores (SIRS/SOFA) and sepsis criteria (SIRS≥2/SOFA≥2/SOFA_change≥2) frequencies and associations with in-hospital mortality were assessed. Using a mathematical approach, we estimated the correlation between sepsis and in-hospital mortality serving as reference for evaluation of observed mortality correlations of sepsis criteria.

Results

Of 791 patients, 369 (47%) were infected and 422 (53%) non-infected, with an in-hospital mortality of 39% and 15%. SIRS≥2 indicated sepsis in 90% of infected patients, SOFA≥2 in 99% and SOFA_change≥2 in 77%. In non-infected patients, SIRS, SOFA and SOFA_change were ≥2 in 78%, 88% and 58%. In AUROC analyses neither SOFA nor SIRS displayed superior mortality discrimination in infected compared to non-infected patients. The mathematically estimated correlation of sepsis and in-hospital mortality was 0.10 in infected and 0 in non-infected patients. Among sepsis criteria, solely SIRS≥2 agreed with expected correlations in both subgroups (infected: r = 0.19; non-infected: r = 0.02).

Conclusions

SOFA≥2 yielded a more liberal sepsis diagnosis than SIRS≥2. None of the criteria showed an infection specific occurrence that would be essential for reliable sepsis detection. However, SIRS≥2 matched the mortality association pattern of a valid sepsis criterion, whereas SOFA-based criteria did not. With this study, we establish a mathematical approach to mortality-based evaluation of sepsis criteria.

Improved Outcomes After Regional Implementation of Sepsis Alert: A Novel Triage Model

OBJECTIVES

To assess whether the triage model Sepsis Alert for Emergency Departments results in improved initial care of patients with severe infections.

DESIGN

Interventional study comparing patient care before and after the start of a new triage model, including 90-day follow-up.

SETTING

Eight emergency departments in Skåne County, Sweden.

SUBJECTS

Patients with suspected severe infection.

INTERVENTIONS

Patients with severely deviating vital signs and suspected infection were triaged into a designated sepsis line called Sepsis Alert, for rapid evaluation supported by an infectious disease specialist. Also, all emergency department staff participated in a designated sepsis education before the model was introduced.

MEASUREMENTS AND MAIN RESULTS

Medical records were evaluated for a 3-month period 1 year before the triage system was started in 2016 and for a 3-month period 1 year after. Of 195,607 patients admitted to these emergency departments during two 3-month periods, a total of 5,321 patients presented severely abnormal vital signs. Of these, 1,066 patients who presented with fever greater thanor equal to 38°C or history of fever/chills were considered to be patients at risk of having severe sepsis. Among patients triaged according to Sepsis Alert, 89.3% received antibiotic treatment within 1 hour after arrival to the emergency department (median time to antibiotics, 26 min), which was significantly better than before the start of the new triage: 67.9% (median time to antibiotics, 37 min) (p < 0.001). Additionally, sepsis treatment quality markers were significantly improved after the introduction of Sepsis Alert, including number of blood cultures and lactate measurements taken, percentage of patients receiving IV fluids, and appropriate initial antibiotic treatment. There were no differences in 28- or 90-day mortality rates.

CONCLUSIONS

The implementation of the new triage model Sepsis Alert with special attention to severe sepsis patients led to faster and more accurate antibiotic treatment and improved diagnostic procedures and supportive care.

Biomarkers and clinical scores to aid the identification of disease severity and intensive care requirement following activation of an in-hospital sepsis code

BACKGROUND

Few validated biomarker or clinical score combinations exist which can discriminate between cases of infection and other non-infectious conditions following activation of an in-hospital sepsis code, as well as provide an accurate severity assessment of the corresponding host response. This study aimed to identify suitable blood biomarker (MR-proADM, PCT, CRP and lactate) or clinical score (SOFA and APACHE II) combinations to address this unmet clinical need.

METHODS

A prospective, observational study of patients activating the Vall d'Hebron University Hospital sepsis code (ISC) within the emergency department (ED), hospital wards and intensive care unit (ICU). Area under the receiver operating characteristic (AUROC) curves, logistic and Cox regression analysis were used to assess performance.

RESULTS

148 patients fulfilled the Vall d'Hebron ISC criteria, of which 130 (87.8%) were retrospectively found to have a confirmed diagnosis of infection. Both PCT and MR-proADM had a moderate-to-high performance in discriminating between infected and non-infected patients following ISC activation, although the optimal PCT cut-off varied significantly across departments. Similarly, MR-proADM and SOFA performed well in predicting 28- and 90-day mortality within the total infected patient population, as well as within patients presenting with a community-acquired infection or following a medical emergency or prior surgical procedure. Importantly, MR-proADM also showed a high association with the requirement for ICU admission after ED presentation [OR (95% CI) 8.18 (1.75-28.33)] or during treatment on the ward [OR (95% CI) 3.64 (1.43-9.29)], although the predictive performance of all biomarkers and clinical scores diminished between both settings.

CONCLUSIONS

Results suggest that the individual use of PCT and MR-proADM might help to accurately identify patients with infection and assess the overall severity of the host response, respectively. In addition, the use of MR-proADM could accurately identify patients requiring admission onto the ICU, irrespective of whether patients presented to the ED or were undergoing treatment on the ward. Initial measurement of both biomarkers might therefore facilitate early treatment strategies following activation of an in-hospital sepsis code.

Procalcitonin as a prognostic marker for sepsis based on SEPSIS-3

BACKGROUND

The revised definition of sepsis is life-threatening organ dysfunction caused by a dysregulated host response to infection (SEPSIS-3). The objective of this study was to evaluate procalcitonin (PCT) for the diagnosis and prognosis of sepsis using SEPSIS-3.

METHODS

We enrolled 248 patients, who were admitted to the emergency department with suspected bacterial infection from June 2016 to February 2017. Definite bacterial infection was defined by proven culture results, and probable bacterial infection was based on diagnostic modalities other than culture. The sequential organ failure assessment (SOFA) score of 2 points or more from the baseline was diagnosed as sepsis. PCT was measured by the AFIAS-6 immunoassay system (Boditech Med Inc.) using whole blood. White blood cell (WBC), C-reactive protein (CRP), and erythrocyte sedimentation rate (ERS) were evaluated.

RESULTS

The final diagnosis was sepsis in 185 patients with infection of respiratory and genitourinary tract constituted 84.6%. The area under the receiver operating characteristic curve (AUROC) with 95% confidence interval (CI) was as follows: PCT, 0.682 (0.589-0.765); CRP, 0.583 (0.487-0.673); ESR, 0.540 (0.515-0.699); and WBC, 0.611 (0.455-0.633), respectively. In multivariate analysis, age, SOFA, and PCT (log scale) predicted non-survivors with an odds ratio with 95% confidence interval of 1.055 (1.008-1.105), 1.303 (1.142-1.486), and 2.004 (1.240-3.238), respectively. Among sepsis group, initial PCT was increased in non-survivor (23.2 ng/dL) compared to survivor group (8.1 ng/dL) with statistical significance (P = .005).

CONCLUSIONS

PCT could support and predict the unfavorable prognosis of sepsis based on SEPSIS-3, whereas diagnostic potential of PCT requires further evaluations.

The early identification of disease progression in patients with suspected infection presenting to the emergency department: a multi-centre derivation and validation study

Background

There is a lack of validated tools to assess potential disease progression and hospitalisation decisions in patients presenting to the emergency department (ED) with a suspected infection. This study aimed to identify suitable blood biomarkers (MR-proADM, PCT, lactate and CRP) or clinical scores (SIRS, SOFA, qSOFA, NEWS and CRB-65) to fulfil this unmet clinical need.

Methods

An observational derivation patient cohort validated by an independent secondary analysis across nine EDs. Logistic and Cox regression, area under the receiver operating characteristic (AUROC) and Kaplan-Meier curves were used to assess performance. Disease progression was identified using a composite endpoint of 28-day mortality, ICU admission and hospitalisation > 10 days.

Results

One thousand one hundred seventy-five derivation and 896 validation patients were analysed with respective 28-day mortality rates of 7.1% and 5.0%, and hospitalisation rates of 77.9% and 76.2%. MR-proADM showed greatest accuracy in predicting 28-day mortality and hospitalisation requirement across both cohorts. Patient subgroups with high MR-proADM concentrations (≥ 1.54 nmol/L) and low biomarker (PCT < 0.25 ng/mL, lactate < 2.0 mmol/L or CRP < 67 mg/L) or clinical score (SOFA < 2 points, qSOFA < 2 points, NEWS < 4 points or CRB-65 < 2 points) values were characterised by a significantly longer length of hospitalisation (p < 0.001), rate of ICU admission (p < 0.001), elevated mortality risk (e.g. SOFA, qSOFA and NEWS HR [95%CI], 45.5 [10.0–207.6], 23.4 [11.1–49.3] and 32.6 [9.4–113.6], respectively) and a greater number of disease progression events (p < 0.001), compared to similar subgroups with low MR-proADM concentrations (< 1.54 nmol/L). Increased out-patient treatment across both cohorts could be facilitated using a derivation-derived MR-proADM cut-off of < 0.87 nmol/L (15.0% and 16.6%), with decreased readmission rates and no mortalities.

Conclusions

In patients presenting to the ED with a suspected infection, the blood biomarker MR-proADM could most accurately identify the likelihood of further disease progression. Incorporation into an early sepsis management protocol may therefore aid rapid decision-making in order to either initiate, escalate or intensify early treatment strategies, or identify patients suitable for safe out-patient treatment.

Electronic supplementary material

The online version of this article (10.1186/s13054-019-2329-5) contains supplementary material, which is available to authorized users.

Diagnosis of sepsis from a drop of blood by measurement of spontaneous neutrophil motility in a microfluidic assay

Current methods for the diagnosis of sepsis have insufficient precision, causing regular misdiagnoses. Microbiological tests can help diagnose sepsis but are usually too slow to have an impact on timely clinical-decision making. Neutrophils have high sensitivity to infections, yet measurements of neutrophil surface markers, genomic changes, and phenotype alterations have had only a marginal effect on sepsis diagnosis. Here, we report a microfluidic assay that measures the spontaneous motility of neutrophils in the context of plasma, in one droplet of blood. We measured the performance of the assay in two independent cohorts of critically ill patients suspected of sepsis. In the first cohort, we developed a machine-learning-based scoring system (sepsis score) that segregated patients with sepsis from those without sepsis. In the second cohort, we validated the sepsis score in a double-blinded, prospective case-control study. For the 42 patients across the two cohorts, the assay identified sepsis patients with 97% sensitivity and 98% specificity. The neutrophil assay could potentially be used to accurately diagnose and monitor sepsis in larger populations of at-risk patients.

SIRS in the Time of Sepsis-3

Severe sepsis is a common, deadly, and diagnostically vexing condition. Recent recommendations for diagnosing sepsis, referred to as consensus guidelines, provide a definition of sepsis and remove the systemic inflammatory response syndrome (SIRS) as a component of the diagnostic process. A concise definition of sepsis is welcomed. However, the approach to developing these guidelines, although thorough, had weaknesses. Emphasis is placed on mortality prediction rather than on early diagnosis. Diagnostic criteria are recommended to replace current criteria without evidence of any effect that their use would have on mortality. SIRS is a prevalent feature of patients with sepsis, should remain an important component of the diagnostic process, and remains a valuable term for discussing patients with life-threatening organ dysfunction caused by infection.

Sepsis and Septic Shock Strategies

Three therapeutic principles most substantially improve organ dysfunction and survival in sepsis: early, appropriate antimicrobial therapy; restoration of adequate cellular perfusion; timely source control. The new definitions of sepsis and septic shock reflect the inadequate sensitivity, specify, and lack of prognostication of systemic inflammatory response syndrome criteria. Sequential (sepsis-related) organ failure assessment more effectively prognosticates in sepsis and critical illness. Inadequate cellular perfusion accelerates injury and reestablishing perfusion limits injury. Multiple organ systems are affected by sepsis and septic shock and an evidence-based multipronged approach to systems-based therapy in critical illness results in improve outcomes.