Introduction: Absolute lymphocytopenia has been reported as a predictor of bacteremia in medical emergencies. Likewise, the neutrophil-lymphocyte count ratio (NLCR) has been shown a simple promising method to evaluate systemic inflammation in critically ill patients. Methods: We retrospectively evaluated the ability of conventional infection markers, lymphocyte count and NLCR to predict bacteremia in adult patients admitted to the Emergency Department with suspected community-acquired bacteremia. The C-reactive protein (CRP) level, white blood cell (WBC) count, neutrophil count, lymphocyte count and NLCR were compared between patients with positive blood cultures (n = 92) and age-matched and gender-matched patients with negative blood cultures (n = 92) obtained upon Emergency Department admission. Results: Significant differences between patients with positive and negative blood cultures were detected with respect to the CRP level (mean ± standard deviation 176 ± 138 mg/l vs. 116 ± 103 mg/l; P = 0.042), lymphocyte count (0.8 ± 0.5 × 10⁹/l vs. 1.2 ± 0.7 × 10⁹/l; P < 0.0001) and NLCR (20.9 ± 13.3 vs. 13.2 ± 14.1; P < 0.0001) but not regarding WBC count and neutrophil count. Sensitivity, specificity, positive and negative predictive values were highest for the NLCR (77.2%, 63.0%, 67.6% and 73.4%, respectively). The area under the receiver operating characteristic curve was highest for the lymphocyte count (0.73; confidence interval: 0.66 to 0.80) and the NLCR (0.73; 0.66 to 0.81). Conclusions: In an emergency care setting, both lymphocytopenia and NLCR are better predictors of bacteremia than routine parameters like CRP level, WBC count and neutrophil count. Attention to these markers is easy to integrate in daily practice and without extra costs.

Background: Lymphocytopenia has frequently been described in patients with malaria, but studies on its association with disease severity have yielded conflicting results. The neutrophil/lymphocyte count ratio (NLCR) has been introduced as a parameter for systemic inflammation in critically ill patients and was found, together with lymphocytopenia, to be a better predictor of bacteraemia than routine parameters like C-reactive protein and total leukocyte count. In the present study, the predictive value of the NLCR and lymphocytopenia for severe disease was evaluated in patients with imported malaria. Methods: All patients diagnosed with malaria at the Harbour Hospital between January 1^st 1999 and January 1^st 2012 with differential white cell counts determined within the first 24 hours after admission were included in this retrospective study. Severe malaria was defined according to the WHO criteria. The performance of the NLCR and lymphocytopenia as a marker of severe malarial disease was compared back-to-back with that of C-reactive protein as a reference biomarker. Results: A total of 440 patients (severe falciparum malaria n = 61, non-severe falciparum malaria n = 259, non-falciparum malaria n=120) were included in the study. Lymphocytopenia was present in 52% of all patients and the median NLCR of all patients was 3.2. Total lymphocyte counts and NLCR did not differ significantly between groups. A significant correlation of total leukocyte count and NLCR, but not lymphocyte count, with parasitaemia was found. ROC analysis revealed a good negative predictive value but a poor positive predictive value of both lymphocytopenia and NLCR and performance was inferior to that of C-reactive protein. After complete parasite clearance a significant rise in total leukocyte count and lymphocyte count and a significant decrease in NLCR was observed. Conclusion: The NLCR was found to correlate with parasitaemia, but both lymphocytopenia and the NLCR were inferior to C-reactive protein as markers for severe disease in patients with imported malaria. The NLCR and lymphocytopenia are not useful as predictive markers for severe disease in imported malaria in the acute care setting.

The extracellular domains of cytokine receptors are released during inflammation, but little is known about the shedding of Toll-like receptors (TLR) and whether they can be used as diagnostic biomarkers. The release of sTLR2 and sTLR4 was studied in in-vitro stimulations, as well as in-vivo during experimental human endotoxemia (n = 11, 2 ng/kg LPS), and in plasma of 394 patients with infections (infectious mononucleosis, measles, respiratory tract infections, bacterial sepsis and candidemia) or non-infectious inflammation (Crohn’s disease, gout, rheumatoid arthritis, autoinflammatory syndromes and pancreatitis). Using C-statistics, the value of sTLR2 and sTLR4 levels for discrimination between infections and non-infectious inflammatory diseases, as well as between viral and bacterial infections was analyzed. In-vitro, peripheral blood mononuclear cells released sTLR2 and sTLR4 by exposure to microbial ligands. During experimental human endotoxemia, plasma concentrations peaked after 2 hours (sTLR4) and 4 hours (sTLR2). sTLR4 did not correlate with cytokines, but sTLR2 correlated positively with TNFα (rs = 0.80, P < 0.05), IL-6 (rs = 0.65, P < 0.05), and IL-1Ra (rs = 0.57, P = 0.06), and negatively with IL-10 (rs = -0.58, P = 0.06), respectively. sTLR4 had a similar area under the ROC curve [AUC] for differentiating infectious and non-infectious inflammation compared to CRP: 0.72 (95% CI 0.66-0.79) versus 0.74 (95% CI 0.69-0.80) [P = 0.80], while sTLR2 had a lower AUC: 0.60 (95% CI 0.54-0.66) [P = 0.0004]. CRP differentiated bacterial infections better from viral infections than sTLR2 and sTLR4: AUC 0.94 (95% CI 0.90-0.96) versus 0.58 (95% CI 0.51-0.64) and 0.75 (95% CI 0.70-0.80), respectively [P < 0.0001 for both]. sTLRs are released into the circulation, and suggest the possibility to use sTLRs as diagnostic tool in inflammatory conditions.

Background: During the coronavirus disease 2019 (COVID-19) pandemic in the Netherlands it was noticed that very few blood cultures from COVID-19 patients turned positive with clinically relevant bacteria. This was particularly evident in comparison to the number of positive blood cultures during previous seasonal epidemics of influenza. This observation raised questions about the occurrence and causative microorganisms of bacteraemia in COVID-19 patients, especially in the perspective of the widely reported overuse of antibiotics and the rising rate of antibiotic resistance. Methods: We conducted a retrospective cohort study on blood culture results in influenza A, influenza B and COVID-19 patients presenting to two hospitals in the Netherlands. Our main outcome consisted of the percentage of positive blood cultures. The percentage of clinically relevant blood cultures, isolated bacteria and 30-day all-cause mortality served as our secondary outcomes. Results: A total of 1331 viral episodes were analysed in 1324 patients. There was no statistically significant difference (p = 0.47) in overall occurrence of blood culture positivity in COVID-19 patients (9.0, 95% CI 6.8–11.1) in comparison to influenza A (11.4, 95% CI 7.9–14.8) and influenza B patients (10.4, 95% CI 7.1–13.7,). After correcting for the high rate of contamination, the occurrence of clinically relevant bacteraemia in COVID-19 patients amounted to 1.0% (95% CI 0.3–1.8), which was statistically significantly lower (p = 0.04) compared to influenza A patients (4.0, 95% CI 1.9–6.1) and influenza B patients (3.0, 95% CI 1.2–4.9). The most frequently identified bacterial isolates in COVID-19 patients were Escherichia coli (n = 2) and Streptococcus pneumoniae (n = 2). The overall 30-day all-cause mortality for COVID-19 patients was 28.3% (95% CI 24.9–31.7), which was statistically significantly higher (p = <.001) when compared to patients with influenza A (7.1, 95% CI 4.3–9.9) and patients with influenza B (6.4, 95% CI 3.8–9.1). Conclusions: We report a very low occurrence of community-acquired bacteraemia amongst COVID-19 patients in comparison to influenza patients. These results reinforce current clinical guidelines on antibiotic management in COVID-19, which only advise utilization of antibiotics when a bacterial co-infection is suspected.

In the peak of the 2009 Q fever outbreak in the Netherlands, we introduced a diagnostic algorithm for acute Q fever with an enzyme-linked immunosorbent assay for immunoglobulin M antibodies toCoxiella burnetiiphase II antigens (MII screen) as an initial step. Subsequently, an immunofluorescence assay or PCR was performed depending on the MII screen outcome, date of onset of disease, and inpatient or outpatient setting. The impact of MII screen on the number of immunofluorescence assays performed and the contribution of PCR to diagnosis were retrospectively evaluated in 825 patients referred in a 17-day period. Acute Q fever was diagnosed in 256 patients. The introduction of MII screen reduced the number of immunofluorescence assays performed by more than 80%. In 103 patients, PCR analysis contributed to the diagnosis of acute Q fever. Q fever diagnostics were hampered by the fact that for a high number of patients the date of onset of disease was not provided and the requested follow-up serum samples were not received.

Little is known about the effect of timing of antibiotic treatment on development of IgG antibodies following acute Q fever. We studied IgG antibody responses in symptomatic patients diagnosed either before or during development of the serologic response toCoxiella burnetii. Between 15 and 31 May 2009, 186 patients presented with acute Q fever, of which 181 were included in this retrospective study: 91 early-diagnosed (ED) acute Q fever patients, defined as negative IgM phase II enzyme-linked immunosorbent assay (ELISA) and positive PCR, and 90 late-diagnosed (LD) acute Q fever patients, defined as positive/dubious IgM phase II ELISA and positive immunofluorescence assay (IFA). Follow-up serology at 3, 6, and 12 months was performed using IFA (IgG phase I and II). High IgG antibody titers were defined as IgG phase II titers of ≥1:1,024 together with IgG phase I titers of ≥1:256. At 12 months, 28.6% of ED patients and 19.5% of LD patients had high IgG antibody titers (P= 0.17). No statistically significant differences were found in frequencies of IgG phase I and IgG phase II antibody titers at all follow-up appointments for adequately and inadequately treated patients overall, as well as for ED and LD patients analyzed separately. Additionally, no significant difference was found in frequencies of high antibody titers and between early (treatment started within 7 days after seeking medical attention) and late timing of treatment. This study indicates that early diagnosis and antibiotic treatment of acute Q fever do not prohibit development of the IgG antibody response.