PT - JOURNAL ARTICLE AU - J. Bont AU - E. Hak AU - A. W. Hoes AU - M. Schipper AU - F. G. Schellevis AU - T. J. M. Verheij TI - A prediction rule for elderly primary-care patients with lower respiratory tract infections AID - 10.1183/09031936.00129706 DP - 2007 May 01 TA - European Respiratory Journal PG - 969--975 VI - 29 IP - 5 4099 - http://erj.ersjournals.com/content/29/5/969.short 4100 - http://erj.ersjournals.com/content/29/5/969.full SO - Eur Respir J2007 May 01; 29 AB - Prognostic scores for lower respiratory tract infections (LRTI) have been mainly derived in a hospital setting. The current authors have developed and validated a prediction rule for the prognosis of acute LRTI in elderly primary-care patients. Data including demographics, medication use, healthcare use and comorbid conditions from 3,166 episodes of patients aged ≥65 yrs visiting the general practitioner (GP) with LRTI were collected. Multiple logistic regression analysis was used to construct a predictive model. The main outcome measure was 30-day hospitalisation or death. The Second Dutch Survey of GPs was used for validation. The following were independent predictors of 30-day hospitalisation or death: increasing age; previous hospitalisation; heart failure; diabetes; use of oral glucocorticoids; previous use of antibiotics; a diagnosis of pneumonia; and exacerbation of chronic obstructive pulmonary disease. A prediction rule based on these variables showed that the outcome increased directly with increasing scores: 3, 10 and 31% for scores of <2 points, 3–6 and ≥7 points, respectively. Corresponding figures for the validation cohort were 3, 11 and 26%, respectively. This simple prediction rule can help the primary-care physician to differentiate between high- and low-risk patients. As a possible consequence, low-risk patients may be suitable for home treatment, whereas high-risk patients might be monitored more closely in a homecare or hospital setting. Future studies should assess whether information on signs and symptoms can further improve this prediction rule.