Intensive Care Medicine

, Volume 22, Issue 12, pp 1294–1300

A predictive model for the treatment approach to community-acquired pneumonia in patients needing ICU admission

  • P. M. Olaechea
  • J. M. Quintana
  • M. S. Gallardo
  • J. Insausti
  • E. Maraví
  • B. Alvarez
Original

DOI: 10.1007/BF01709541

Cite this article as:
Olaechea, P.M., Quintana, J.M., Gallardo, M.S. et al. Intensive Care Med (1996) 22: 1294. doi:10.1007/BF01709541

Abstract

Objective

To create a predictive model for the treatment approach to community-acquired pneumonia (CAP) in patients needing Intensive Care Unit (ICU) admission.

Design

Multicenter prospective study

Setting

Twenty-six Spanish ICUs.

Patients

One hundred seven patients with CAP, all of them with accurate etiological diagnosis, divided in three groups according to their etiology in typical (bacterial pneumonia),Legionella and other atypical (Mycoplasma, Chlamydia spp. and virus). For the multivariate analysis we groupedLegionella and other atypical etiologies in the same category.

Methods

We recorded 34 variables including clinical characteristics, risk factors and radiographic pattern. We used a multivariate logistic regression analysis to find out a predictive model.

Results

We have the complete data in 70 patients. Four variables: APACHE II, (categorized as a dummy variable) serum sodium and phosphorus and “length of symptoms” gave an accurate predictive model (c=0.856). From the model we created a score that predicts typical pneumonia with a sensitivity of 90.2% and specificity 72.4%.

Conclusion

Our model is an attempt to help in the treatment approach to CAP in ICU patients based on a predictive model of basic clinical and laboratory information. Further studies, including larger numbers of patients, should validate and investigate the utility of this model in different clinical settings.

Key words

Community-acquired infectionsBacterial pneumoniaIntensive Care UnitsLogistic models

Copyright information

© Springer-Verlag 1996

Authors and Affiliations

  • P. M. Olaechea
    • 1
  • J. M. Quintana
    • 1
  • M. S. Gallardo
    • 1
  • J. Insausti
    • 2
  • E. Maraví
    • 3
  • B. Alvarez
    • 4
  1. 1.Hospital de GaldakaoGaldakao, VizcayaSpain
  2. 2.Hospital de NavarraPamplona, NavarraSpain
  3. 3.Hospital Virgen del CaminoPamplona, NavarraSpain
  4. 4.Hospital General de AlicanteAlicanteSpain