C-Reactive Protein and Hemogram Parameters for the Non-Sepsis Systemic Inflammatory Response Syndrome and Sepsis: What Do They Mean?

Identifying prognostic factors for survival in intensive care unit patients with SIRS or sepsis by machine learning analysis on electronic health records

BACKGROUND

Systemic inflammatory response syndrome (SIRS) and sepsis are the most common causes of in-hospital death. However, the characteristics associated with the improvement in the patient conditions during the ICU stay were not fully elucidated for each population as well as the possible differences between the two.

GOAL

The aim of this study is to highlight the differences between the prognostic clinical features for the survival of patients diagnosed with SIRS and those of patients diagnosed with sepsis by using a multi-variable predictive modeling approach with a reduced set of easily available measurements collected at the admission to the intensive care unit (ICU).

METHODS

Data were collected from 1,257 patients (816 non-sepsis SIRS and 441 sepsis) admitted to the ICU. We compared the performance of five machine learning models in predicting patient survival. Matthews correlation coefficient (MCC) was used to evaluate model performances and feature importance, and by applying Monte Carlo stratified Cross-Validation.

RESULTS

Extreme Gradient Boosting (MCC = 0.489) and Logistic Regression (MCC = 0.533) achieved the highest results for SIRS and sepsis cohorts, respectively. In order of importance, APACHE II, mean platelet volume (MPV), eosinophil counts (EoC), and C-reactive protein (CRP) showed higher importance for predicting sepsis patient survival, whereas, SOFA, APACHE II, platelet counts (PLTC), and CRP obtained higher importance in the SIRS cohort.

CONCLUSION

By using complete blood count parameters as predictors of ICU patient survival, machine learning models can accurately predict the survival of SIRS and sepsis ICU patients. Interestingly, feature importance highlights the role of CRP and APACHE II in both SIRS and sepsis populations. In addition, MPV and EoC are shown to be important features for the sepsis population only, whereas SOFA and PLTC have higher importance for SIRS patients.

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.

Haemogram-Derived Indices for Screening and Prognostication in Critically Ill Septic Shock Patients: A Case-Control Study

This study aimed (1) to assess the diagnostic accuracy of neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), monocyte-to-lymphocyte (MLR) and platelet count-to-mean platelet volume (PLT/MPV) ratios in predicting septic shock in patients on admission to the intensive care unit (ICU) and (2) to compare it with the role of C-reactive protein (CRP), procalcitonin (PCT) and lactate level. We also sought (3) to verify whether the indices could be useful in ICU mortality prediction and (4) to compare them with Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II) and Sequential Organ Failure Assessment (SOFA) scores. This retrospective study covered 138 patients, including 61 subjects with multi-organ failure due to septic shock (study group) and 77 sex- and age-matched controls. Septic patients had significantly higher NLR (p < 0.01) and NLR predicted septic shock occurrence (area under the ROC curve, AUROC = 0.66; 95% CI 0.58-0.74). PLR, MLR and PLT/MPV were impractical in sepsis prediction. Combination of CRP with NLR improved septic shock prediction (AUROC = 0.88; 95% CI 0.81-0.93). All indices failed to predict ICU mortality. APACHE II and SAPS II predicted mortality with AUROC = 0.68; 95% CI 0.54-0.78 and AUROC = 0.7; 95% CI 0.57-0.81, respectively. High NLR may be useful to identify patients with multi-organ failure due to septic shock but should be interpreted along with CRP or PCT. The investigated indices are not related with mortality in this specific clinical setting.

Utility and Prognostic Significance of Neutrophil-to-Lymphocyte Ratio in Dogs with Septic Peritonitis

Systemic inflammation is known to cause WBC abnormalities, specifically neutrophilia and lymphopenia. The neutrophil-to-lymphocyte ratio (NLR) is a simple and affordable biomarker that has been used in human clinical settings of sepsis but has not been investigated in veterinary species. We evaluated NLR in dogs with septic and nonseptic systemic inflammatory diseases and compared with a healthy dog population. An NLR ≥6 had an 84.39% sensitivity and 86.95% specificity to identify dogs with systemic inflammatory states; however, no ratio distinguished septic and nonseptic causes. The NLR was not associated with length of hospitalization, morbidity based on the acute patient physiologic laboratory evaluation scoring system, or mortality. The disassociation may be due to the retrospective nature of the study, including a restricted population size and acquisition of only a one-time blood sample. NLR is currently of limited use for diagnosis and prognosis in systemic inflammatory states in dogs, and larger, prospective studies are necessary to further evaluate NLR.

Effect of interleukin-31 on septic shock through regulating inflammasomes and interleukin-1β

Sepsis with severe systemic inflammation remains a great challenge for the intensive care unit in clinics. Although biomarkers have been identified to diagnose, monitor and predict these syndromes, novel therapeutic approaches are required for the amelioration of symptoms of sepsis and septic shock. The present study demonstrated that interleukin (IL)-31 was able reduce the mortality rate of lipopolysaccharide (LPS)-induced sepsis with the reduction of inflammatory cytokines in the sera. IL-31 also inhibited IL-1β production in the peritoneal lavage fluid in LPS-induced or cecal ligation and puncture-induced sepsis. The in vitro mechanism responsible for IL-31 regulation on peritoneal IL-1β activation following LPS challenge was explored. It was demonstrated that IL-1β secretion was suppressed by IL-31 treatment from LPS-challenged peritoneal macrophages following adenosine triphosphate stimulation, which is an activator of NLR family, pyrin domain-containing 3 (NLRP3). Furthermore, IL-31 inhibited the expression of NLRP3 at the transcriptional level. In human THP-1 cells, anti-IL-31/anti-IL-31 receptor (R) neutralizing antibody enhanced NLRP3 expression as well as IL-1β activation, suggesting a role of the IL-31-IL-31R-NLRP3-IL-1β signaling axis in the physiological status of sepsis. On the other hand, IL-31 displayed a negative effect on the NLRP1 inflammasome, but not on NLRP3 on the LPS-primed human peripheral blood monocytes, resulting in reduction of the inflammatory cytokine, tumor necrosis factor (TNF)-α, in the supernatant. Taken together, the present data implied that T helper 2-type cytokine, IL-31, may be a promising therapeutic option for treatment of sepsis and septic shock in clinics.

Pitfalls in studies of eosinopenia and neutrophil-to-lymphocyte count ratio

There is a number of publications evaluating the eosinophil count and the neutrophil-to-lymphocyte count ratio for diagnosis, prognosis or monitoring of patients. Of special interest is the use of these parameters for discrimination between the different causes of fever (e.g. bacterial versus viral vs. non-infectious causes of fever) and for monitoring the efficacy of therapy and predict the course of the patient. However, pitfalls in previous study designs prevent applicability to clinical practice. Here, we provide a short review of the relevant literature and summarize important factors that should be taken into account when designing studies, with special attention to the selection of a proper and clinically meaningful study population and the effects of the stress response and of corticosteroids.

Serum Level of HMGB1 Protein and Inflammatory Markers in Patients with Secondary Peritonitis: Time Course and the Association with Clinical Status

Background

Intra-abdominal infection in secondary peritonitis drives as excessive production of inflammatory mediators and the development of systemic inflammatory response syndrome (SIRS) or sepsis. Finding a specific marker to distinguish SIRS from sepsis would be of immense clinical importance for the therapeutic approach. It is assumed that high-mobility group box 1 protein (HMGB1) could be such a marker. In this study, we examined the time course changes in the blood levels of HMGB1, C-reactive protein (CRP), procalcitonin (PCT) and serum amyloid A (SAA) in patients with secondary peritonitis who developed SIRS or sepsis.

Methods

In our study, we evaluated 100 patients with diffuse secondary peritonitis who developed SIRS or sepsis (SIRS and SEPSIS group) and 30 patients with inguinal hernia as a control group. Serum levels of HMGB1, CRP, PCT, and SAA were determined on admission in all the patients, and monitored daily in patients with peritonitis until discharge from hospital.

Results

Preoperative HMGB1, CRP, PCT and SAA levels were statistically highly significantly increased in patients with peritonitis compared to patients with inguinal hernia, and significantly higher in patients with sepsis compared to those with SIRS. All four inflammatory markers changed significantly during the follow-up. It is interesting that the patterns of change of HMGB1 and SAA over time were distinctive for SIRS and SEPSIS groups.

Conclusions

HMGB1 and SAA temporal patterns might be useful in distinguishing sepsis from noninfectious SIRS in secondary peritonitis.