BACKGROUND: Prediction rules based on clinical information have been developed to support the diagnosis of pneumonia and help limit the use of expensive diagnostic tests. However, these prediction rules need to be validated in the primary care setting. METHODS: Adults who met our definition of lower respiratory tract infection (LRTI) were recruited for a prospective study on the causes of LRTI, between November 15, 1998 and June 1, 2001 in the Leiden region of The Netherlands. Clinical information was collected and chest radiography was performed. A literature search was also done to find prediction rules for pneumonia. RESULTS: 129 patients--26 with pneumonia and 103 without--were included, and 6 prediction rules were applied. Only the model with the addition of a test for C-reactive protein had a significant area under the curve of 0.69 (95% confidence interval [CI], 0.58-0.80), with a positive predictive value of 47% (95% CI, 23-71) and a negative predictive value of 84% (95% CI, 77-91). The pretest probabilities for the presence and absence of pneumonia were 20% and 80%, respectively. CONCLUSIONS: Models based only on clinical information do not reliably predict the presence of pneumonia. The addition of an elevated C-reactive protein level seems of little value.
BACKGROUND: Prediction rules based on clinical information have been developed to support the diagnosis of pneumonia and help limit the use of expensive diagnostic tests. However, these prediction rules need to be validated in the primary care setting. METHODS: Adults who met our definition of lower respiratory tract infection (LRTI) were recruited for a prospective study on the causes of LRTI, between November 15, 1998 and June 1, 2001 in the Leiden region of The Netherlands. Clinical information was collected and chest radiography was performed. A literature search was also done to find prediction rules for pneumonia. RESULTS: 129 patients--26 with pneumonia and 103 without--were included, and 6 prediction rules were applied. Only the model with the addition of a test for C-reactive protein had a significant area under the curve of 0.69 (95% confidence interval [CI], 0.58-0.80), with a positive predictive value of 47% (95% CI, 23-71) and a negative predictive value of 84% (95% CI, 77-91). The pretest probabilities for the presence and absence of pneumonia were 20% and 80%, respectively. CONCLUSIONS: Models based only on clinical information do not reliably predict the presence of pneumonia. The addition of an elevated C-reactive protein level seems of little value.
Authors: M Woodhead; F Blasi; S Ewig; J Garau; G Huchon; M Ieven; A Ortqvist; T Schaberg; A Torres; G van der Heijden; R Read; T J M Verheij Journal: Clin Microbiol Infect Date: 2011-11 Impact factor: 8.067
Authors: Raymond Oppong; Mark Jit; Richard D Smith; Christopher C Butler; Hasse Melbye; Sigvard Mölstad; Joanna Coast Journal: Br J Gen Pract Date: 2013-07 Impact factor: 5.386
Authors: Margaretha C Minnaard; Joris A H de Groot; Rogier M Hopstaken; Alwin Schierenberg; Niek J de Wit; Johannes B Reitsma; Berna D L Broekhuizen; Saskia F van Vugt; Arie Knuistingh Neven; Aleida W Graffelman; Hasse Melbye; Timothy H Rainer; Johann Steurer; Anette Holm; Ralph Gonzales; Geert-Jan Dinant; Alma C van de Pol; Theo J M Verheij Journal: CMAJ Date: 2016-09-19 Impact factor: 8.262
Authors: A Willy Graffelman; Francois E J A Willemssen; Harmine M Zonderland; Arie Knuistingh Neven; Aloys C M Kroes; Peterhans J van den Broek Journal: Br J Gen Pract Date: 2008-02 Impact factor: 5.386
Authors: Saskia F van Vugt; Berna D L Broekhuizen; Christine Lammens; Nicolaas P A Zuithoff; Pim A de Jong; Samuel Coenen; Margareta Ieven; Chris C Butler; Herman Goossens; Paul Little; Theo J M Verheij Journal: BMJ Date: 2013-04-30