- 著者
- Hajime Fukuyama Tadashi Ishida Hiromasa Tachibana Hiroaki Nakagawa Masahiro Iwasaku Mika Saigusa Hiroshige Yoshioka Machiko Arita Toru Hashimoto
- 出版者
- The Japanese Society of Internal Medicine
- 雑誌
- Internal Medicine (ISSN:09182918)
- 巻号頁・発行日
- vol.50, no.18, pp.1917-1922, 2011 (Released:2011-09-15)
- 参考文献数
- 22
- 被引用文献数
- 3 12
Objective Several scoring systems have been derived to identify patients with severe community-acquired pneumonia (CAP). Recently, España et al (Am J Respir Crit Care Med 174:1249-1256, 2006) developed a clinical prediction rule that predicts hospital mortality, the need for mechanical ventilation, and risk for septic shock. We assessed the performance of this rule and compared it with other published scoring systems. Methods A prospective study was conducted of patients with CAP who were hospitalized at our hospital from April 2007 till May 2009. Clinical and laboratory features at presentation were recorded and used in order to calculate España rule, the pneumonia severity index (PSI), CURB-65, A-DROP, the 2007 Infectious Diseases Society of America/American Thoracic Society (IDSA/ATS) prediction rule and SMART-COP. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were compared for adverse outcomes. We also assessed the association of the España rule criteria and adverse outcomes. Results A total of 505 patients were enrolled in the study. The overall in-hospital mortality rate was 6.5%, and 6.3% of patients were admitted to the intensive care unit (ICU). Sixty-two (12.3%) patients were defined as having severe CAP (in-hospital death or need for mechanical ventilation or septic shock). España rule achieved highest sensitivity and NPV in predicting severe CAP. When ICU admission was the outcome measure, the IDSA/ATS rule and SMART-COP were regarded to be good predictors. Conclusion España rule performed well in identifying patients with severe CAP. As a result, each of the severity scores has advantages and limitations for predicting adverse outcomes.