Study design
The study was conducted from July 2020 to December 2021 at the Shanghai General Hospital, Shanghai Jiaotong University, Shanghai, China. Its design and procedures followed the guidelines of the Helsinki Declaration on human experimentation. The ethics committee of the research institute approved this study, and informed consent forms from participants or their next of kin had been obtained prior to their inclusions in the study.
Case and control recruitment
Figure 1 shows the study flowchart. 36 healthy controls (age 32–95 years) were recruited from subjects who participated in annual health screenings at the Shanghai General Hospital, Shanghai Jiaotong University. 124 inpatients (age 20–97 years) with suspected respiratory tract infections or bloodstream infections from the intensive care unit (ICU) or respiratory ward were recruited. The suspected infection was defined as inpatients with one or several clinical symptoms (fever, chill, cough, sneeze, tachypnea, respiratory distress, chest wheezing), inflammatory markers and microbiological cultures were requested by attending physicians, and empirical antibiotic therapy was initiated [13]. We excluded patients: (1) age < 18 years old, (2) with infections at other sites besides respiratory tract infections and bloodstream infections, and (3) who had taken antibiotics before enrollment. All enrolled patients were classified into three groups based on the results of blood or sputum cultures:
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Negative Bacterial Culture Group (n = 34): patients with no evidence of infection by negative blood and sputum cultures. This group includes some patients with no infection and others having bacterial infections but with negative bacterial culture results.
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Respiratory Tract Infection Group (n = 56): patients with respiratory tract infection proven by positive sputum culture and negative blood culture.
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Bloodstream Infection Group (n = 34): patients with bloodstream infection proven by positive blood culture.
The Bloodstream Infection Group was further divided into two subgroups based on the results of sputum cultures: (1) Simple Bloodstream Infection Subgroup: patients with bloodstream infection only proven by positive blood culture and negative sputum culture (n = 21); (2) Mixed Bloodstream Infection Subgroup: patients with both bloodstream and respiratory tract infection proven by positive blood and sputum cultures (n = 13).
In addition, we followed up with the infected patients above and recorded their bacterial culture results after administering antibiotic therapy. During the study period, we recorded a total of 24 infected patients (age 23–83 years) whose blood and sputum cultures turned negative and had no clinical symptoms of infection after effective antibiotic therapy. Amongst these 24 patients, 15 were from the Respiratory Tract Infection Group, 6 were from the Simple Bloodstream Infection Subgroup, and 3 were from the Mixed Bloodstream Infection Subgroup. At the same time, we also recorded 19 infected patients (age 23–95 years) whose blood and sputum cultures remained positive after antibiotic therapy. Amongst these 19 patients, 11 were from the Respiratory Tract Infection Group, 3 were from the Simple Bloodstream Infection Subgroup, and 5 were from the Mixed Bloodstream Infection Subgroup. Moreover, we followed up with 10 patients randomly from the Negative Bacterial Culture Group who received antibiotic therapy and had no clinical symptoms of infection after antibiotic therapy, and recorded the changes in their indicators before and after antibiotic therapy. We also randomly selected 10 infected patients and monitored their nCD64 index, PCT, and temperature changes daily. Amongst these 10 patients, 4 were from the Respiratory Tract Infection Group, 3 were from the Simple Bloodstream Infection Subgroup, and 3 were from the Mixed Bloodstream Infection Subgroup.
Samples collection
Patients’ peripheral blood samples, blood cultures, and sputum cultures were collected simultaneously and examined before antibiotic therapy. Sterile blood culture bottles (BD BACTEC™ Plus Aerobic/F and BD BACTEC™ Lytic/10 Anaerobic/F) containing 10 mL of fresh blood were incubated in the automated BD BACTEC™ FX system at 37ºC for 7 days, after which it was considered negative. The blood culture, sputum culture, and the identification of pathogens were performed by the Clinical Microbiology Laboratory of the Department of Laboratory Medicine. The distribution of bacteria strains in patients is presented in Additional file 3: Table S1.
Measurement of conventional indicators
We used the Mindray BC-5390 hematology analyzer (Mindray Bio-Medical Electronics Co., Ltd., Shenzhen, China) and corresponding diagnostic kits to measure routine blood counts and CRP. The WBC and NLR were calculated based on routine blood counts. We measured serum PCT levels by electro-chemiluminescence immunoassay in Roche Cobas e601 automatic analyzer with the Elecsys BRAHMS PCT assay reagent (Roche Diagnostics GmbH, Mannheim, Germany). All operations were strictly conducted according to the instructions provided by the instrument and reagent manufacturers.
Measurement of nCD64 index and T lymphocyte subsets via flow cytometry
Whole peripheral blood samples were stained with anti-human CD64 fluorescein isothiocyanate (CD64-FITC, Beckman Coulter, USA), anti-human CD14 phycoerythrin (CD14-PE, Beckman Coulter, USA), and anti-human CD45 phycoerythrin-cyanine5 (CD45-PE-Cy5, Beckman Coulter, USA). After staining, red blood cells were lysed with Erythrocyte Lysis Buffer (BD Biosciences, USA) to obtain peripheral blood nucleated cells. We used full-spectrum flow cytometry Cytek Northern Lights-CLC (NL-CLC, Cytekbios, China) to examine nucleated cells stained with fluorescent. The scatter plot was drawn with side scatter (SSC) and pan-leucocyte marker CD45 to gate nucleated cells (Fig. 2 A). Then, neutrophils (NEO), lymphocytes (LYM), and monocytes (MON) were gated from nucleated cells according to CD14 distribution (Fig. 2B). The mean fluorescence intensity (MFI) of CD64 in neutrophils (NEO), lymphocytes (LYM), and monocytes (MON) were acquired, respectively (Fig. 2 C). The nCD64 index was calculated with the following formula: nCD64 index= (MFINEO CD64/MFILYM CD64)/ (MFIMON CD64/MFINEO CD64) (Fig. 2D). In the calculation, the MFI of CD64 on LYM and MON served as the internal negative and positive controls.
T lymphocyte subsets were measured with a similar approach. We stained whole peripheral blood samples with anti-human CD3 fluorescein isothiocyanate (CD3-FITC, Beckman Coulter, USA), anti-human CD4 phycoerythrin (CD4-PE, Beckman Coulter, USA), anti-human CD8 phycoerythrin-cyanine5 (CD8-PE-Cy5, Beckman Coulter, USA), and anti-human CD45 phycoerythrin-cyanine7 (CD45-PE-Cy7, Beckman Coulter, USA). Afterwards, red blood cells were lysed with Erythrocyte Lysis Buffer (BD Biosciences, USA) to obtain peripheral blood nucleated cells. We detected nucleated cells stained with fluorescent via flow cytometry (NL-CLC, Cytekbios, China) and calculated counts of CD3+ T cell, CD4+ T cell, and CD8+ T cell using the volume method.
Statistical analysis
Data were analyzed using SPSS for Windows version 24.0 software (SPSS, Chicago, IL, USA). We calculated numbers and proportions for qualitative data and presented results as the mean ± standard deviation (SD) for quantitative data. The Kolmogorov-Smirnoff test assessed the normality of the data. We then used paired t-test, independent Student’s t-test, and one-way ANOVA followed by Bonferroni multiple comparison tests to assess normal distribution data. In addition, to assess non-normal distribution data and qualitative data, we used the χ2 test, the Mann-Whitney U test, Wilcoxon signed ranks test, and Kruskal-Wallis followed by Bonferroni multiple comparison tests. The stepwise multivariable logistic regression analysis was performed to identify the association between the nCD64 index and bacterial infections. And receiver operating characteristic (ROC) curves were plotted to explore the significance of PCT and nCD64 index for differentiating infected patients from culture-negative patients. We calculated the predicted probabilities of combining PCT and nCD64 index through logistic regression analysis and plotted ROC curves based on the predicted probabilities. At the same time, we calculated and compared the areas under the curve (AUC), the cutoff value, the sensitivity and the specificity of different indicators. In all cases, differences were statistically significant with p < 0.05.