Chronic Q fever diagnosis—consensus guideline versus expert opinion

Chronic Q fever, caused by Coxiella burnetii, has high mortality and morbidity rates if left untreated. Controversy about the diagnosis of this complex disease has emerged recently. We applied the guideline from the Dutch Q Fe­ver Consensus Group and a set of diagnostic criteria pro­posed by Didier Raoult to all 284 chronic Q fever patients included in the Dutch National Chronic Q Fever Database during 2006–2012. Of the patients who had proven cas­es of chronic Q fever by the Dutch guideline, 46 (30.5%) would not have received a diagnosis by the alternative cri­teria designed by Raoult, and 14 (4.9%) would have been considered to have possible chronic Q fever. Six patients with proven chronic Q fever died of related causes. Until results from future studies are available, by which current guidelines can be modified, we believe that the Dutch lit­erature-based consensus guideline is more sensitive and easier to use in clinical practice

The value of the neutrophil-lymphocyte count ratio in the diagnosis of sepsis in patients admitted to the Intensive Care Unit: A retrospective cohort study

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Hypophosphatemia, fever and prolonged length of hospital stay in seronegative PCR positive patients as compared to seropositive patients with early acute Q fever pneumonia

Background: Query fever (Q fever) is a zoonotic infection, caused by the intracellular Gram-negative coccobacillus Coxiella burnetii. From 2007 until 2010, a large Q fever outbreak has occurred in the Netherlands. We studied traditional and less common inflammation markers in seronegative and seropositive patients with acute Q fever pneumonia to identify markers that distinguish different disease stages and predict disease severity. Methods: A total of 443 adult patients presenting at the Emergency Department with community-acquired pneumonia were included in a prospective etiologic study. Patients with acute Q fever pneumonia were identified by PCR and/or serology. Patient characteristics, clinical symptoms, pneumonia severity and inflammation markers were assessed upon presentation. Duration of symptoms, prior therapy and length of hospital stay were retrieved from the hospital information system. Results: In all, 40 patients with acute Q fever pneumonia were identified. Of these, 29 were seronegative and 11 seropositive at presentation. C-reactive protein (CRP) was the only inflammation marker increased in all seronegative and seropositive patients but no significant difference was observed between groups. In seronegative patients, hypophosphatemia was more common (p=0.01), and length of hospital stay was longer (p=0.02). However, there was no significant difference in pneumonia severity index. Furthermore, phosphate levels were inversely correlated with body temperature (p=0.003). Conclusions: In acute Q fever pneumonia, CRP is the only traditional inflammation marker adequately reflecting disease activity. Patients with seronegative acute Q fever pneumonia present with hypophosphatemia and have prolonged length of hospital stay when compared to seropositive patients, suggesting an increased disease severity

Noise pollution in the ICU: time to look into the mirror

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Biomarkers and Molecular Analysis to Improve Bloodstream Infection Diagnostics in an Emergency Care Unit

Molecular pathogen detection from blood is still expensive and the exact clinical value remains to be determined. The use of biomarkers may assist in preselecting patients for immediate molecular testing besides blood culture. In this study, 140 patients with ≥ 2 SIRS criteria and clinical signs of infection presenting at the emergency department of our hospital were included. C-reactive protein (CRP), neutrophil-lymphocyte count ratio (NLCR), procalcitonin (PCT) and soluble urokinase plasminogen activator receptor (suPAR) levels were determined. One ml EDTA blood was obtained and selective pathogen DNA isolation was performed with MolYsis (Molzym). DNA samples were analysed for the presence of pathogens, using both the MagicPlex Sepsis Test (Seegene) and SepsiTest (Molzym), and results were compared to blood cultures. Fifteen patients had to be excluded from the study, leaving 125 patients for further analysis. Of the 125 patient samples analysed, 27 presented with positive blood cultures of which 7 were considered to be contaminants. suPAR, PCT, and NLCR values were significantly higher in patients with positive blood cultures compared to patients without (p < 0.001). Receiver operating characteristic curves of the 4 biomarkers for differentiating bacteremia from non-bacteremia showed the highest area under the curve (AUC) for PCT (0.806 (95% confidence interval 0.699–0.913)). NLCR, suPAR and CRP resulted in an AUC of 0.770, 0.793, and 0.485, respectively. When compared to blood cultures, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for SepsiTest and MagicPlex Sepsis Test were 11%, 96%, 43%, 80%, and 37%, 77%, 30%, 82%, respectively. In conclusion, both molecular assays perform poorly when one ml whole blood is used from emergency care unit patients. NLCR is a cheap, fast, easy to determine, and rapidly available biomarker, and therefore seems most promising in differentiating BSI from non-BSI patients for subsequent pathogen identification using molecular diagnostics

Markers of infection in inpatients and outpatients with acute Q-fever

Background: Query-fever (Q-fever) is a zoonotic infection caused by the intracellular Gram-negative coccobacillus Coxiella burnetii. A large ongoing outbreak of Q-fever has been reported in the Netherlands. We studied various markers of infection in inpatients (hospitalised) and outpatients (treated by a general physician) with acute Q-fever in relation to disease severity. Methods: Leukocyte counts, C-reactive protein (CRP) and procalcitonin (PCT) concentrations were measured in 25 inpatients and 40 outpatients upon presentation with acute Q-fever. Chest X-rays, if available, were analysed and confusion, urea, respiratory rate, blood pressure-age 65 (CURB-65) scores, indicating severity of pneumonia, were calculated. Results: CRP was the only marker that significantly differentiated between inpatients and outpatients. It was increased in all patients from both groups. Leukocyte counts and PCT concentrations did not differ between inpatients and outpatients. Overall, only 13/65 patients had an increased leukocyte count and only 11/65 patients presented with PCT concentrations indicative of possible bacterial respiratory tract infection. Infiltrative changes on the chest X-ray were observed in the majority of patients. CURB-65 score was 0±1 (mean±SD). Conclusions: Acute Q-fever, a relatively mild pneumonia with low CURB-65 scores, specifically induces a response in CRP, while PCT concentrations and leukocytes are within the normal range or increased only marginally

Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records

Purpose : To assess, validate and compare the predictive performance of models for in-hospital mortality of COVID-19 patients admitted to the intensive care unit (ICU) over two different waves of infections. Our models were built with high-granular Electronic Health Records (EHR) data versus less-granular registry data. Methods : Observational study of all COVID-19 patients admitted to 19 Dutch ICUs participating in both the national quality registry National Intensive Care Evaluation (NICE) and the EHR-based Dutch Data Warehouse (hereafter EHR). Multiple models were developed on data from the first 24 h of ICU admissions from February to June 2020 (first COVID-19 wave) and validated on prospective patients admitted to the same ICUs between July and December 2020 (second COVID-19 wave). We assessed model discrimination, calibration, and the degree of relatedness between development and validation population. Coefficients were used to identify relevant risk factors. Results : A total of 1533 patients from the EHR and 1563 from the registry were included. With high granular EHR data, the average AUROC was 0.69 (standard deviation of 0.05) for the internal validation, and the AUROC was 0.75 for the temporal validation. The registry model achieved an average AUROC of 0.76 (standard deviation of 0.05) in the internal validation and 0.77 in the temporal validation. In the EHR data, age, and respiratory-system related variables were the most important risk factors identified. In the NICE registry data, age and chronic respiratory insufficiency were the most important risk factors. Conclusion : In our study, prognostic models built on less-granular but readily-available registry data had similar performance to models built on high-granular EHR data and showed similar transportability to a prospective COVID-19 population. Future research is needed to verify whether this finding can be confirmed for upcoming waves

Rapid Evaluation of Coronavirus Illness Severity (RECOILS) in intensive care: Development and validation of a prognostic tool for in-hospital mortality

Background The prediction of in-hospital mortality for ICU patients with COVID-19 is fundamental to treatment and resource allocation. The main purpose was to develop an easily implemented score for such prediction. Methods This was an observational, multicenter, development, and validation study on a national critical care dataset of COVID-19 patients. A systematic literature review was performed to determine variables possibly important for COVID-19 mortality prediction. Using a logistic multivariable model with a LASSO penalty, we developed the Rapid Evaluation of Coronavirus Illness Severity (RECOILS) score and compared its performance against published scores. Results Our development (validation) cohort consisted of 1480 (937) adult patients from 14 (11) Dutch ICUs admitted between March 2020 and April 2021. Median age was 65 (65) years, 31% (26%) died in hospital, 74% (72%) were males, average length of ICU stay was 7.83 (10.25) days and average length of hospital stay was 15.90 (19.92) days. Age, platelets, PaO2/FiO2 ratio, pH, blood urea nitrogen, temperature, PaCO2, Glasgow Coma Scale (GCS) score measured within +/−24 h of ICU admission were used to develop the score. The AUROC of RECOILS score was 0.75 (CI 0.71–0.78) which was higher than that of any previously reported predictive scores (0.68 [CI 0.64–0.71], 0.61 [CI 0.58–0.66], 0.67 [CI 0.63–0.70], 0.70 [CI 0.67–0.74] for ISARIC 4C Mortality Score, SOFA, SAPS-III, and age, respectively). Conclusions Using a large dataset from multiple Dutch ICUs, we developed a predictive score for mortality of COVID-19 patients admitted to ICU, which outperformed other predictive scores reported so far.ISSN:0001-5172ISSN:1399-657