Intensive Care Infection Score--A new approach to distinguish between infectious and noninfectious processes in intensive care and medicosurgical patients

Sysmex-derived COVID-19 prognostic score as an early prognostic marker for severity of the COVID-19 disease

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a life-threatening disease with a heterogeneous course. Even some young patients are at increased risk of severe course or death, as they can face severe complications. It would be very useful to have a cheap and easily available marker to predict COVID-19 course in the early stages of the disease. The COVID-19 prognostic score could be a very useful clinical indicator available at the time of primary contact with the patient.

METHODS

The COVID-19 prognostic score and the clinical condition together with selected laboratory parameters were evaluated in patients with respiratory tract infection and a positive PCR test for the SARS-CoV-2 during the first contact with the patient. Prognostic significance was evaluated using receiver operating characteristic curves (ROC) and area under the curve (AUC). Selected parameters of the blood count and hemostasis, as well as selected biochemical indicators, were examined too.

RESULTS

Thirty-seven of 164 patients developed serious symptoms. The COVID-19 score had one of the highest AUC values (0.855) of all markers. The highest combination of sensitivity (91.9%) and specificity (71.7%) for identifying patients with a subsequent moderate and severe course of the disease was achieved at the threshold 1.5. The predictive value of a negative test is beneficial too (0.968).

CONCLUSIONS

The COVID-19 prognostic score is a promising indicator stratifying patients with COVID-19 into prognostic groups at the time of the first contact, thus allowing the timely provision of increased care in patients at high risk of severe development.

Value of new advanced hematological parameters in early prediction of severity of COVID-19

INTRODUCTION

COVID-19 usually presents with upper respiratory tract infection in varying severity which can lead to sepsis. Early prediction of sepsis may reduce mortality by timely interventions. The intended purpose of this study was to determine whether the advanced parameters like the extended inflammation parameters (EIPs) can predict prognosis and early progression to sepsis as a sequel of COVID-19 infection and can be used as a screening profile. Also, to evaluate the Intensive Care Infection Score (ICIS) and the COVID-19 prognostic score and validate the scores for our population.

METHODS

Prospective observational study of 50 reverse transcription- polymerase chain reaction (RT-PCR) proven admitted COVID-19 patients. The data assessed included complete blood counts (CBC) with EIP measurements, from Day 1 of admission to Day 10. The following groups were studied: noncritical (NC) and critical illness (CI) in COVID-19 positive cases, COVID negative sepsis and nonsepsis cases, and healthy volunteers for reference range.

RESULTS

The parameters that showed statistically significant higher mean in CI group compared to the NC group are reactive lymphocyte number and percentage (RE-LYMPH#, RE-LYMPH%), antibody synthesizing lymphocyte number and percentage (AS-LYMPH#, AS-LYMPH%), Reactive monocyte count and percentage (RE-MONO#, RE-MONO%/M), ICIS, COVID-19 prognostic score (p-value <0.05). The AUC confirmed the diagnostic accuracy of all these parameters. From the multivariate logistic regression, the significant risk factor was RE-LYMPH# with cut-off >0.10 (p value: 0.011).

CONCLUSION

The new EIP parameters, RE-MONO#, RE-MONO%/M, ICIS score and COVID-19 prognostic score are useful for early prediction of critical illness. AS-LYMPH is the most useful predictor of critical illness on multivariate analysis. RE-MONO# and RE-MONO%/M parameter are useful in distinguishing critical and noncritical non-COVID and COVID-19 patients.

Intensive Care Infection Score (ICIS) is elevated in patients with moderate and severe COVID-19 in the early stages of disease

Background

Coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus is still a very dangerous and life-threatening disease with an extremely heterogeneous course. Older patients and those with comorbidities are at increased risk of death from the disease but young patients can develop potentially lethal complications too. For those reasons, numerous recent studies focus on the analysis of markers associated with early assessment of COVID-19 prognosis. Previous publications provided evidence for the Intensive Care Infection Score (ICIS) as an easy to use tool to assess the risk for bacterial infection in ICU patients based on a combination of haematologic parameters. This study evaluated the performance of ICIS as a prognostic marker of stages of disease in COVID-19 patients.

Methods

A total of 205 COVID-19 patients admitted to the University Hospital Hradec Kralove, Czech Republic, with symptoms of respiratory tract infection and a positive RT-PCR test for SARS-CoV-2 virus were enrolled in this study. Forty-nine patients developed mild COVID-19 symptoms (no oxygen therapy needed), 156 patients developed moderate or severe symptoms (supplemental oxygen therapy or death).

Results

ICIS predicted the mild or moderate/severe course with the highest AUC (0.773). The cut-off value (ICIS = 3.5) was selected as the value with the highest Youden index (0.423). The cut-off value could predict a mild or moderate/severe course of the disease with the highest specificity (77.6%) and positive predictive value (90.2%) of all markers used in this study. Sensitivity was 64.7%.

Conclusion

ICIS is a reliable, cheap, fast and simply interpretable score for the early identification of moderate/severe course of COVID-19 in an early stage of the disease. ICIS> 3 predicts a severe course of the disease with high specificity and positive predictive value.

Reviewing the value of leukocytes cell population data (CPD) in the management of sepsis

Sepsis is a medical emergency that describes the body's systemic immune response to an infection and can lead to end-stage organic dysfunction and death. Despite the advances in understanding the pathophysiology of this syndrome and therapies, sepsis remains one of the leading causes of morbidity and mortality in critically ill patients. Early diagnosis and rapid intervention are essential to improve outcomes, which inspired the concept "golden hour," during which the correction of shock and organic dysfunction can improve the patients' outcomes. But the initial presentation of sepsis is often nonspecific and its severity is difficult to assess. Anomalies in temperature, heart and respiratory rates and leukocyte counts are manifestations of systemic inflammatory response syndrome (SIRS). Diagnosis, management and follow-up of patients with sepsis remains a challenge, and diverse biomarkers have been proposed for the timely diagnosis and prognosis of septic patients: lactic acid, procalcitonin (PCT), C-reactive protein, immature granulocytes. The host's initial response to infection is a humoral, cellular and neuroendocrine reaction to infection, and leukocytes interact with endothelial cells. The new generation of hematological analyzers incorporates technological innovations allowing to expand the information derived from the complete blood count: new leukocyte derived parameters are emerging as potentially useful markers in different clinical situations. Additional research parameters cell population data (CPD), characterizing different leukocyte populations have become available, and preliminary observations suggest their utility in the diagnosis of sepsis. This review emphasizes the value of CPD, reported by modern cellular counters for early recognition of sepsis, and therefore the potential improvement in patient outcomes.

Time series analysis of delta neutrophil index as the predictor of sepsis in patients with acute poisoning

Delta neutrophil index (DNI), which reflects the fraction of immature granulocytes, is used to detect infection and sepsis from noninfectious conditions, but few studies have evaluated in the early stage of acute poisoning. This retrospective observational study was performed on acute poisoning patients who visited to the emergency department (ED) and were consecutively admitted in intensive care units over 18-month period. The serial DNI, conventional inflammatory biomarkers, and culture results were obtained in the ED and after admission. The outcomes were the identification of sepsis, bacteremia, and 30-day mortality. Of 166 patients (mean age, 56.0 years) in this cohort, 59 (35.5%) had sepsis and 29 (17.5%) had bacteremia. Initial and peak DNI fractions 24 h after ED admission were strong independent predictors of sepsis development. Analysis of the area under the curve according to multiple receiver operating characteristics showed that DNI had a higher capability to predict sepsis than other parameters (0.815 for DNI, 0.700 for procalcitonin, 0.681 for C-reactive protein, and 0.741 for white blood cell). Using multivariable logistic regression analysis, it was found that DNI was an independent predictor of sepsis (95% confidence interval (CI) of odds: 1.03-1.18) and bacteremia (95% CI: 1.01-1.14). Therefore, initial and serial measurement of DNI may serve as useful risk predictor for development of sepsis or bacteremia in acute poisoning.

A novel diagnostic algorithm equipped on an automated hematology analyzer to differentiate between common causes of febrile illness in Southeast Asia

BACKGROUND

Distinguishing arboviral infections from bacterial causes of febrile illness is of great importance for clinical management. The Infection Manager System (IMS) is a novel diagnostic algorithm equipped on a Sysmex hematology analyzer that evaluates the host response using novel techniques that quantify cellular activation and cell membrane composition. The aim of this study was to train and validate the IMS to differentiate between arboviral and common bacterial infections in Southeast Asia and compare its performance against C-reactive protein (CRP) and procalcitonin (PCT).

METHODOLOGY/PRINCIPAL FINDINGS

600 adult Indonesian patients with acute febrile illness were enrolled in a prospective cohort study and analyzed using a structured diagnostic protocol. The IMS was first trained on the first 200 patients and subsequently validated using the complete cohort. A definite infectious etiology could be determined in 190 of 463 evaluable patients (41%), including 89 arboviral infections (81 dengue and 8 chikungunya), 94 bacterial infections (26 murine typhus, 16 salmonellosis, 6 leptospirosis and 46 cosmopolitan bacterial infections), 3 concomitant arboviral-bacterial infections, and 4 malaria infections. The IMS detected inflammation in all but two participants. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the IMS for arboviral infections were 69.7%, 97.9%, 96.9%, and 77.3%, respectively, and for bacterial infections 77.7%, 93.3%, 92.4%, and 79.8%. Inflammation remained unclassified in 19.1% and 22.5% of patients with a proven bacterial or arboviral infection. When cases of unclassified inflammation were grouped in the bacterial etiology group, the NPV for bacterial infection was 95.5%. IMS performed comparable to CRP and outperformed PCT in this cohort.

CONCLUSIONS/SIGNIFICANCE

The IMS is an automated, easy to use, novel diagnostic tool that allows rapid differentiation between common causes of febrile illness in Southeast Asia.

Adjusted Intensive Care Infection Score (ICISΔ)-A new approach for prediction of ascitic fluid infection in patients with cirrhosis

BACKGROUND

Early and accurate diagnosis is the key to improving survival in cirrhotic patients with ascitic fluid infection.

AIMS

To investigate the usefulness of adjusted Intensive Care Infection Score (ICIS_Δ) for diagnosis of ascites infection in cirrhotic patients.

METHODS

Cirrhotic patients with ascites (n = 125) were enrolled, and the efficacy of ICIS and ICIS_Δ for predicting ascites infection was evaluated. ICIS_Δ was created by using the weighted variation of each ICIS parameter.

RESULTS

The area under the curves (AUCs) of ICIS for the diagnosis of ascites infection were 0.90 (95% CI: 0.84-0.95), 0.85 (95% CI: 0.79-0.90), and 0.87 (95% CI: 0.81-0.93), for SBP, culture-negative SBP, and combined SBP/culture-negative SBP, respectively. ICIS was optimized and diagnostic accuracy was obviously improved. ICIS_Δ had high AUCs of 0.99 (95% CI: 0.93-1.00) for SBP, 0.98 (95% CI: 0.83-1.00) for culture-negative SBP, and 0.98 (95% CI: 0.94-1.00) for the combination group. The optimal cutoff was identified as ICIS_Δ > 2, which had >97.8% sensitivity and 100% specificity for diagnosis of both SBP and culture-negative SBP. The ICIS_Δ had significantly higher AUCs than PCT and CPR in both groups (P = 0.002-0.008). ICIS_Δ kinetics could differentiate between SBP and culture-negative SBP patients. From sterile ascites, through culture-negative SBP to SBP, three ICIS_Δ parameters showed an increasing trend.

CONCLUSIONS

ICIS and ICIS_Δ are simple, rapid, accurate and cost-effective methods for the diagnosis of ascites infection in cirrhotic patients.

Improvement in detecting sepsis using leukocyte cell population data (CPD)

Background

The cell population data (CPD) parameters reported by XN analyzers (Sysmex Corporation, Kobe, Japan) reflect the size and internal structure of leukocytes. We explored whether CPD values could contribute to recognize those patients with fever at risk to develop sepsis. A profile of sepsis was developed combining CPD parameters and other markers.

Methods

We recruited 295 patients at the onset of fever, with infection confirmed by positive cultures. We studied the diagnostic performance of the CPD parameters in the differential diagnosis of sepsis vs. non-systemic bacterial infection using receiver operating characteristic (ROC) curve analysis. Additionally, the K-means unsupervised clustering method was applied. Once the clusters had been defined, the relationship between them and the CPD parameter values was assessed with the non-parametric Wilcoxon test. Lastly, the relationship between the clusters obtained and the categorical variables was examined with the χ2-test (or Fisher’s exact test).

Results

ROC analysis demonstrated that NE-FSL, NE-WY, NE-WZ and MO-WZ had areas under the curve (AUCs) >0.700 for predicting sepsis. Using the K-means clustering algorithm, 80 patients (66.67%) were assigned to Cluster 1 and the others to Cluster 2. Out of 80 of patients in Cluster 1, 45 (56.25%) presented a PCT value ≥2 ng/mL, whereas almost 80% of Cluster 2 patients had a PCT <2 ng/mL. Cluster 1 was characterized by high NE-SFL, NE-WY, MO-X, MO-WX and MO-Z values (p<0.05).

Conclusions

CPD related to monocyte complexity and neutrophil activation were found to be significant, with high values suggesting sepsis.

Role of leucocytes cell population data in the early detection of sepsis

AIMS

The cell population data (CPD) parameters reported by XN analyser (Sysmex, Kobe, Japan) reflect the size and internal structure of leucocytes. We aimed to assess the clinical utility of these parameters as biomarkers for the early diagnosis of sepsis.

METHODS

The study group (G1) included 586 controls (no quantitative or morphological alterations in the complete blood count) and 137 patients diagnosed with sepsis. The reliability of the model was evaluated using a validation group (G2) of 212 controls and 60 patients with sepsis. The optimal cut-off for the diagnosis of sepsis and the OR for CPD were established using a univariate logistic regression. A multivariate logistic regression model was then created. The OR and area under the curve were recorded. A risk stratification scale (neutrophils and monocytes (NEMO)) for diagnosing sepsis was established on the basis of the coefficients of the multivariate model.

RESULTS

MO-X and neutrophils fluorescence intensity (NE-SFL) were found to be the most relevant of the CPD in predicting sepsis applying multivariate analysis to G1.NEMO score was composed using the above-mentioned CPD and subsequently stratified into three risk groups: mild (≤3), moderate (4≤NEMO≤5) and high (≥6). The OR for patients with a score of 4-5 was 10 and 249 for a score of ≥6. When applied to G2, the positive predictive value was 84.8 % and the negative predictive value was 96.0%.

CONCLUSIONS

CPD are potentially useful for the early diagnosis of sepsis. Their values were used to compose in NEMO score can help in rapid and reliable decision making.

The intensive care infection score - a novel marker for the prediction of infection and its severity

Background

The prediction of infection and its severity remains difficult in the critically ill. A novel, simple biomarker derived from five blood-cell derived parameters that characterize the innate immune response in routine blood samples, the intensive care infection score (ICIS), could be helpful in this respect. We therefore compared the predictive value of the ICIS with that of the white blood cell count (WBC), C-reactive protein (CRP) and procalcitonin (PCT) for infection and its severity in critically ill patients.

Methods

We performed a multicenter, cluster-randomized, crossover study in critically ill patients between January 2013 and September 2014. Patients with a suspected infection for which blood cultures were taken by the attending intensivist were included. Blood was taken at the same time for WBC, ICIS, CRP and PCT measurements in the control study periods. Results of imaging and cultures were collected. Patients were divided into groups of increasing likelihood of infection and invasiveness: group 1 without infection or with possible infection irrespective of cultures, group 2 with probable or microbiologically proven local infection without blood stream infection (BSI) and group 3 with BSI irrespective of local infection. Septic shock was assessed.

Results

In total, 301 patients were enrolled. CRP, PCT and ICIS were higher in groups 2 and 3 than group 1. The area under the receiver operating characteristic curve (AUROC) for the prediction of infection was 0.70 for CRP, 0.71 for PCT and 0.73 for ICIS (P < 0.001). For the prediction of septic shock the AUROC was 0.73 for CRP, 0.85 for PCT and 0.76 for ICIS. These AUROC did not differ from each other.

Conclusion

The data suggest that the ICIS is potentially useful for the prediction of infection and its severity in critically ill patients, non-inferiorly to CRP and PCT. In contrast to CRP and PCT, the ICIS can be determined routinely without extra blood sampling and lower costs, yielding results within 15 minutes.

Trial registration

ClinicalTrials.gov identifier: ID NCT01847079. Registered on 24 April 2013.

Improvement in detecting bacterial infection in lower respiratory tract infections using the Intensive Care Infection Score (ICIS)

Immediate treatment of lower respiratory tract infections (LRTI) caused by bacteria is important to reduce pneumonia and other complications such as systemic inflammatory response syndrome and sepsis. Nowadays procalcitonin (PCT) is the gold standard to differentiate between bacterial and non-bacterial infections in LRTI. The aim of this study was to evaluate if the new Intensive Care Infection Score (ICIS) which is a combination of various cellular measurements made on hematology analyzers could be a potential method to differentiate between bacterial and non-bacterial infections in LRTI.

The ICIS is composed of five blood-cell derived parameters characterizing the early innate immune response; (1) mean fluorescence intensity of mature (segmented) neutrophils; (2) the difference in hemoglobin concentration between newly formed red blood cells and the mature ones; (3) absolute number of segmented neutrophils; (4) absolute count of antibody secreting lymphocytes and (5) absolute count of number of granulocytes.

The discriminative power of ICIS to differentiate between patients with LRTI of bacterial and non-bacterial origin is as good or even better as the commonly used infection biomarkers PCT, CRP and IL-6.

Beside PCT, CRP and IL-6, ICIS could be used as infection marker in LRTI.

Influence of Granulocyte-Macrophage Colony-Stimulating Factor or Influenza Vaccination on HLA-DR, Infection and Delirium Days in Immunosuppressed Surgical Patients: Double Blind, Randomised Controlled Trial

PURPOSE

Surgical patients are at high risk for developing infectious complications and postoperative delirium. Prolonged infections and delirium result in worse outcome. Granulocyte-macrophage colony-stimulating factor (GM-CSF) and influenza vaccination are known to increase HLA-DR on monocytes and improve immune reactivity. This study aimed to investigate whether GM-CSF or vaccination reverses monocyte deactivation. Secondary aims were whether it decreases infection and delirium days after esophageal or pancreatic resection over time.

METHODS

In this prospective, randomized, placebo-controlled, double-blind, double dummy trial setting on an interdisciplinary ICU of a university hospital 61 patients with immunosuppression (monocytic HLA-DR [mHLA-DR] <10,000 monoclonal antibodies [mAb] per cell) on the first day after esophageal or pancreatic resection were treated with either GM-CSF (250 μg/m2/d), influenza vaccination (Mutagrip 0.5 ml/d) or placebo for a maximum of 3 consecutive days if mHLA-DR remained below 10,000 mAb per cell. HLA-DR on monocytes was measured daily until day 5 after surgery. Infections and delirium were followed up for 9 days after surgery. Primary outcome was HLA-DR on monocytes, and secondary outcomes were duration of infection and delirium.

RESULTS

mHLA-DR was significantly increased compared to placebo (p < 0.001) and influenza vaccination (p < 0.001) on the second postoperative day. Compared with placebo, GM-CSF-treated patients revealed shorter duration of infection (p < 0.001); the duration of delirium was increased after vaccination (p = 0.003).

CONCLUSION

Treatment with GM-CSF in patients with postoperative immune suppression was safe and effective in restoring monocytic immune competence. Furthermore, therapy with GM-CSF reduced duration of infection in immune compromised patients. However, influenza vaccination increased duration of delirium after major surgery.

TRIAL REGISTRATION

www.controlled-trials.com ISRCTN27114642.