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Eisblume - Ewig lyrics + English translation (Version #2)
Paper Back Publishing Date: Submit Review Submit Review. Pick Of The Day. One point is given for each parameter present which results in CRB scores of 0—4.
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For each patient the CRB score was calculated with patient data ascertained at first presentation. We performed statistical analysis with Graph Pad Prism 4. Two group comparisons of nonparametric data were performed by the Mann-Whitney U-test. For multigroup comparisons, Kruskal-Wallis one-way analysis of variance test was used. The causative pathogen was identified in patients A PCT cut-off level of 0. The scatterplots represent all data.
Median values with interquartile ranges are shown. The severity of pneumonia was assessed using the CRB score. Overall, the mean CRB score was 0. Median PCT value was 0. These patients were classified into lower CRB classes mean 0. Only a moderate increase with the severity of CAP could be observed. Results of Kruskal-Wallis one-way analysis of variance are shown. At a cut-off level of 0. Outpatients were classified into lower CRB classes mean 0.
In ROC curve analysis where sensitivity was calculated among those patients who were hospitalised and specificity was assessed among patients who were treated as outpatients the AUC for CRB was 0. In the study population we identified 48 patients with Legionella pneumophila , with Mycoplasma pneumoniae and only two patients with Chlamydia pneumoniae.
In CAP it is essential to assess disease severity to optimise therapeutic decisions, e.
Different scoring systems have been developed for a more objective assessment of CAP severity. In a primary care setting blood urea results are not directly available. CAP patients with a CRB score of 0—1 have a very low mortality risk and can be treated as outpatients [ 20 ].
In our study, CRB score was significantly lower in outpatients but was not influenced by the microbiological etiology of CAP. A detailed analysis of the correlation of these inflammatory markers with CRB score has not been performed in a larger CAP population before. In a recently published study, Masia et al. The authors described no differences in PCT levels between major etiologic groups when the whole sample of patients with CAP was considered.
CRP values were not reported in this study. In contrast to the study by Masia et al. This might be explained by the higher number of patients that were evaluated in our study vs. Our study confirms the findings of previous studies that PCT is a good predictor of severity of pneumonia [ 8 , 10 , 11 , 21 ]. CRP and WBC were not helpful for the discrimination of low risk and high risk patients and the prediction of hospitalisation. CAP can have various etiologies. In our study, classical and atypical bacteria were the most frequent pathogens in CAP.
The distribution of pathogens in our study was comparable to a previous study including patients with severe CAP [ 22 ]. In contrast to CRP and WBC, PCT may have one very important potential — it might be a marker for clinically relevant infections and could be used to decide if antibiotic treatment should be initiated or not [ 23 , 24 ]. Antibiotic use might be discouraged in patients with low PCT levels e. In a second randomised trial, Christ-Crain et al.
As a result, PCT guided therapy significantly reduced total antibiotic exposure, antibiotic prescription on admission and antibiotic treatment duration compared to treatment according to current guidelines. The important effect of this study on clinical management of CAP patients, treatment costs and development of microbiological resistance has to be taken into account.
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The results of the study by Christ-Crain et al. In conclusion, patients with lower severity of disease might probably need less intensive antibiotic therapy. However, it was not possible to definitively differentiate between CAP due to S. CAP with viral or atypical etiology showed comparable levels of inflammatory biomarkers, so that a differentiation of both etiologies and the consecutive choice to start antibiotic therapy was not possible in the individual patient.
Furthermore, there is the dilemma that higher PCT levels are indicative of S.
PCT levels in our study are lower than those reported in other studies including patients with lower respiratory tract infections [ 23 ] or CAP [ 10 , 25 ]. This could be explained by the fact, that these previous studies included hospitalised patients in contrast to our study with a percentage of The severity of disease in outpatients is usually lower, which could be demonstrated by a lower CRB score in this group.
In other studies that also included CAP outpatients, PCT levels were lower and comparable with our results [ 8 , 26 ]. CRP is an early sensitive but non-specific marker of inflammation. Long ago, CRP was initially discovered as a test for patients with pneumococcal pneumonia [ 27 ]. In one small study with 28 patients it could be demonstrated that serial CRP measurements are helpful for the prediction of antibiotic treatment failure or the development of infective complications [ 28 ]. Patients with high CRP levels show a longer duration of fever, longer hospital stay, and recover less often after discharge, but CRP is not associated with a higher mortality [ 29 ].
In pediatric patients, serum CRP was not useful to distinguish between classical bacterial, atypical or viral pneumonia [ 2 , 31 ]. In contrast, Almirall et al.
Ewig (English translation)
In our study group, CRP levels of outpatients were lower compared to inpatients, too. The present study has some limitations. Despite intensive microbiological diagnostics, the etiology remained unknown in This low sensitivity of microbiological tests is well known from other pneumonia studies. The etiology of CAP has been studied in various patient populations, regions, settings and with different diagnostic methodologies.
There are several factors that may reduce the diagnostic yield in our study as well as in the previous ones. First, ambulatory antimicrobial pre-treatment is very important. Nearly one third of patients are pre-treated with antibiotics on hospital admission. Many cases of unknown etiology may be caused by Streptococcus pneumoniae , a pathogen which is easily missed after one single dose of antimicrobial treatment [ 36 ].
A second factor might be that Mycoplasma pneumoniae and Chlamydia pneumoniae might be often not recognised due to diagnostic problems, but represent important causes of CAP. Third, another point that could explain the low number of patients with a microbiological diagnosis is the fact that Outpatients are usually less severely ill. The percentage of outpatients that present with representative sputum or bacteraemia that increase diagnostic yield is lower compared to patients that are hospitalized. An important confounder which may have accounted for a large part of the undiagnosed cases is incomplete diagnostic work-up, especially in outpatients.
A more extensive and aggressive diagnostic approach may have increased the diagnostic yield.
The application of more invasive procedures such as bronchoscopy including bronchial washing and brushing is not feasible and realistic in such a study and was therefore omitted. Interestingly, it was previously shown that mortality is not different between patients with and without known etiology of CAP [ 37 ]. In conclusion, appropriate tools for establishing microbial diagnosis and assessing severity of disease in CAP would be helpful for optimal management of this disease.
Measurement of PCT, CRP, and WBC may be useful to predict typical bacterial pneumonia, since elevated levels were observed in comparison to atypical bacterial and viral pneumonia. However, the inflammatory markers do not allow an individual prediction of microbial etiology of CAP. PCT might be a valuable tool helping clinicians — in combination with scoring systems- to identify clinically relevant infections, to assess a patient's risk profile, and to improve therapeutic decision making as well as decisions about hospitalisation and ICU admission. JP and JK do not own stock or options in the company.
SK helped planning the study, performed data processing and interpretation and wrote the manuscript. SE helped with data interpretation and with the manuscript. JP and JK helped planning the study, performed data processing and interpretation and helped with the manuscript.