Diagnostic properties of C-reactive protein for detecting pneumonia in children

SummaryBackgroundThe diagnostic value of C-reactive protein (CRP) level for pneumonia in children is unknown. As a first step in the assessment of the value of CRP, a diagnostic study was performed in children at an emergency department (ED).MethodsIn this cross-sectional study, data were retrospectively collected from children presenting with suspected pneumonia at the ED of Antonius Hospital Nieuwegein in The Netherlands between January 2007 and January 2012. Diagnostic outcome was pneumonia yes/no according to independent radiologist. (Un)adjusted association between CRP level and pneumonia and diagnostic value of CRP were calculated.ResultsOf 687 presenting children, 286 underwent both CRP measurement and chest radiography. 148 had pneumonia (52%). The proportion of pneumonia increased with CRP level. Negative predictive values declined, but positive predictive values increased with higher CRP thresholds. Univariable odds ratio for the association between CRP level and pneumonia was 1.2 (95% CI 1.11–1.21) per 10 mg/L increase. After adjustment for baseline characteristics CRP level remained associated with pneumonia.ConclusionsCRP level has independent diagnostic value for pneumonia in children presenting at the ED with suspected pneumonia, but low levels do not exclude pneumonia in this setting. These results prompt evaluation of CRP in primary care children with LRTI

External validation of prediction models for pneumonia in primary care patients with lower respiratory tract infection: an individual patient data meta-analysis

Pneumonia remains difficult to diagnose in primary care. Prediction models based on signs and symptoms (S&S) serve to minimize the diagnostic uncertainty. External validation of these models is essential before implementation into routine practice. In this study all published S&S models for prediction of pneumonia in primary care were externally validated in the individual patient data (IPD) of previously performed diagnostic studies

Ancient coastlines of the Black Sea and conditions for human presence – Black Sea expedition 2011

Project DO 02-337, an expedition on the RV Akademik, took place during June 2011 with financial support from the Bulgarian Science Fund. The location for this expedition was the Western Black Sea. 17 core and 8 grapple organic seabed samples were taken. The initial core samples were extracted from the submerged shorelines with subsequent ones taken from deeper water. So submerged shoreline was mapped, samples for dating, isotope analysis and pollen sampling were taken.Проект ДО 02-337, експедиція у східну частину Чорного моря на н/с «Академік» відбулася в червні 2011 року за фінансової підтримки Болгарського наукового фонду. Відібрано 17 проб трубкою і 8 проб драгою. Зразки відбиралися із затопленої берегової лінії, відібрано зразки для датування, ізотопного і пилкового аналізів.Проект ДО 02-337, экспедиция в восточную часть Черного моря на н/с «Академик» состоялась в июне 2011 г. при финансовой поддержке Болгарского научного фонда. Отобраны 17 проб трубкой и 8 проб драгой. Образцы отбирались из затопленной береговой линии, отобраны образцы для датирования, изотопного и пыльцевого анализов

C-reactive protein point-of-care testing and associated antibiotic prescribing

Background. In clinical trials, the potential of point-of-care (POC) C-reactive protein (CRP) tests was demonstrated in decreasing antibiotic prescribing in adults with acute cough in general practice, but effects of implementation are unknown. Objective. To determine the overall effect of POC CRP testing on antibiotic prescribing rate in general practice. Methods. In an observational study, GPs were instructed to use POC CRP in adults with acute cough following current guidelines. After routine history taking and physical examination, they reported whether they intended to prescribe antibiotics (‘pre-test decision’). They reported their revised decision after receiving the POC CRP test result (‘post-test decision’). Primary outcome was the percentage of patients in whom the GP changed his or her decision to prescribe antibiotics. Secondary outcome was the difference between ‘pre-test’ and ‘post-test’ antibiotic prescribing % at group level. Results. A total of 40 GPs enrolled 939 patients, 78% of whom were tested for CRP. GPs changed their decision after POC CRP testing in 200 patients (27%). Antibiotic prescribing before and after CRP testing did not differ (‘pre-test’ 31%, ‘post-test’ 28%; 95% confidence interval of difference −7 to 1). In 41% of the tested patients, the indication for testing was in accordance with the guidelines. Conclusion. POC CRP influenced GPs to change their decision about antibiotic prescribing in patients with acute cough. POC CRP testing does not reduce overall antibiotic prescribing by GPs who already have a low antibiotic prescribing rate

Analysis of recruitment in a pragmatic observational study on C-reactive protein point-of-care testing in primary care

NTRODUCTION: Failure to recruit all eligible study patients can lead to biased results. Little is known on selective patient recruitment in studies on implementation of diagnostic devices. OBJECTIVES: The aim of this observational study was to measure recruitment of patients in an implementation study in primary care on use of point-of-care (POC) C-reactive protein (CRP) and to evaluate recruitment bias and its impact on the study endpoint. METHODS: In a cross-sectional observational study on POC CRP implementation and related antibiotics prescribing, we compared included patients with all eligible patients to assess the representativeness of the included subjects. Eligible patients were adults presenting with acute cough in primary care between March and September 2012. The frequency of POC CRP testing and the proportion of prescribed antibiotics were compared between recruited and non-recruited patients. As measure of bias, odds ratios (ORs) with accompanying 95% confidence intervals (CIs) for the association between CRP level (<20 mg/l or not) and antibiotic prescribing were computed. RESULTS: Of all 1473 eligible patients 348 (24%) were recruited. In recruited patients, POC CRP tests were conducted and antibiotics prescribed more frequently as compared to non-recruited patients (81% versus 6% and 44% versus 29%, respectively). The ORs were 18.2 (95%CI: 9.6-34.3), 30.5 (95%CI: 13.2-70.3) and 3.8 (95%CI: 0.9-14.8) respectively in all eligible patients, the recruited and the non-recruited patients. CONCLUSION: Selective recruitment resulted in an overestimation of POC CRP test use and antibiotic prescribing

External Validation of Prediction Models for Pneumonia in Primary Care Patients with Lower Respiratory Tract Infection: An Individual Patient Data Meta-Analysis.

BackgroundPneumonia remains difficult to diagnose in primary care. Prediction models based on signs and symptoms (S&amp;S) serve to minimize the diagnostic uncertainty. External validation of these models is essential before implementation into routine practice. In this study all published S&amp;S models for prediction of pneumonia in primary care were externally validated in the individual patient data (IPD) of previously performed diagnostic studies.Methods and findingsS&amp;S models for diagnosing pneumonia in adults presenting to primary care with lower respiratory tract infection and IPD for validation were identified through a systematical search. Six prediction models and IPD of eight diagnostic studies (N total = 5308, prevalence pneumonia 12%) were included. Models were assessed on discrimination and calibration. Discrimination was measured using the pooled Area Under the Curve (AUC) and delta AUC, representing the performance of an individual model relative to the average dataset performance. Prediction models by van Vugt et al. and Heckerling et al. demonstrated the highest pooled AUC of 0.79 (95% CI 0.74-0.85) and 0.72 (0.68-0.76), respectively. Other models by Diehr et al., Singal et al., Melbye et al., and Hopstaken et al. demonstrated pooled AUCs of 0.65 (0.61-0.68), 0.64 (0.61-0.67), 0.56 (0.49-0.63) and 0.53 (0.5-0.56), respectively. A similar ranking was present based on the delta AUCs of the models. Calibration demonstrated close agreement of observed and predicted probabilities in the models by van Vugt et al. and Singal et al., other models lacked such correspondence. The absence of predictors in the IPD on dataset level hampered a systematical comparison of model performance and could be a limitation to the study.ConclusionsThe model by van Vugt et al. demonstrated the highest discriminative accuracy coupled with reasonable to good calibration across the IPD of different study populations. This model is therefore the main candidate for primary care use