A Clinical Prediction Rule for the Severe Acute Respiratory Syndrome
Authors: Matthew H.M. Ma, Shey-Ying Chen, Wen-Chu Chiang, Chan-Ping Su, Wen-Jone Chen
Journal: Annals of Internal Medicine (2005)

Letters1 February 2005A Clinical Prediction Rule for the Severe Acute Respiratory SyndromeFREEMatthew H.M. Ma, MD, PhD, Shey-Ying Chen, MD, Wen-Chu Chiang, MD, Chan-Ping Su, MD, and Wen-Jone Chen, MD, PhDMatthew H.M. Ma, MD, PhDFrom National Taiwan University Hospital, Taipei, Taiwan.Search for more papers by this author, Shey-Ying Chen, MDFrom National Taiwan University Hospital, Taipei, Taiwan.Search for more papers by this author, Wen-Chu Chiang, MDFrom National Taiwan University Hospital, Taipei, Taiwan.Search for more papers by this author, Chan-Ping Su, MDFrom National Taiwan University Hospital, Taipei, Taiwan.Search for more papers by this author, and Wen-Jone Chen, MD, PhDFrom National Taiwan University Hospital, Taipei, Taiwan.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-142-3-200502010-00019 SectionsAboutVisual AbstractPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR:We read with great interest the article by Leung and colleagues (1) on their clinical prediction rule for emergency department diagnosis of the severe acute respiratory syndrome (SARS). During the early period of the 2003 SARS epidemics in Taiwan, we prospectively developed a clinical decision rule from a cohort of febrile patients (2, 3), consisting of a 4-item symptom score and a 6-item clinical score (2). The prediction rule was adopted in our institution and became part of an integrated decision-making process for sorting incoming febrile patients during the epidemic. When validated by a second cohort, our rule showed a sensitivity of 90.2%, a specificity of 80.1%, and an area under the receiver-operating characteristic curve of 0.89 (3). We applied Leung and colleagues' rule to our cohort of 299 febrile patients, including 79 with laboratory-confirmed SARS and 220 without SARS. The sensitivity, specificity, positive predictive value, and negative predictive value were 98.8%, 52.0%, 43.6%, and 99.1%, respectively.The authors should be congratulated for a well-conducted study. However, some aspects of their prediction rule warrant further elaboration.First, the study cohort had a higher proportion of nonfebrile patients with SARS than has been reported elsewhere (4, 5). Because of the study's retrospective design, it is possible that some of these patients might not have had SARS to begin with but were instead cross-infected in hospital settings. This might introduce some misclassification bias and threaten the study's validity. Second, the clinical utility of the rule, if applied as suggested, may be limited in a large outbreak. More than 80% of patients still need hospitalization after triage by the rule. Housing patients with a 21% risk for SARS, quartile 1 in the high-risk group, in a communal isolation ward can be a dangerous practice.Triage of SARS during epidemics depends on the prevalence of the disease in the community and on local policies. Three pieces of information—contact history, fever, and pulmonary infiltrate—need to be considered. Patients with contact history and pulmonary infiltrates should be admitted regardless of body temperature. Afebrile patients without pulmonary infiltrates could be discharged home and receive daily follow-up of body temperature. Clinical decision rules are not needed for these patients. Febrile patients without pulmonary infiltrates are the most challenging for emergency department staff and should be the focus of a prediction rule. Whether to admit patients with pulmonary infiltrates but no contact history, however, is a policy issue. Well-thought-out clinical prediction rules, along with sound policies, would help communities tackle future SARS epidemics or similar outbreaks.Matthew H.M. Ma, MD, PhDShey-Ying Chen, MDWen-Chu Chiang, MDChan-Ping Su, MDWen-Jone Chen, MD, PhDNational Taiwan University Hospital; Taipei, TaiwanReferences1. Leung GM, Rainer TH, Lau FL, Wong IO, Tong A, Wong TW, et al. A clinical prediction rule for diagnosing severe acute respiratory syndrome in the emergency department. Ann Intern Med. 2004;141:333-42. [PMID: 15326019] LinkGoogle Scholar2. Chen SY, Su CP, Ma MH, Chiang WC, Hsu CY, Ko PC, et al. Predictive model of diagnosing probable cases of severe acute respiratory syndrome in febrile patients with exposure risk. Ann Emerg Med. 2004;43:1-5. [PMID: 14707932] CrossrefMedlineGoogle Scholar3. Su CP, Chiang WC, Ma MH, Chen SY, Hsu CY, Ko PC, et al. Validation of a novel severe acute respiratory syndrome scoring system. Ann Emerg Med. 2004;43:34-42. [PMID: 14707938] CrossrefMedlineGoogle Scholar4. Chen SY, Chiang WC, Ma MH, Su CP, Hsu CY, Ko PC, et al. Sequential symptomatic analysis in probable severe acute respiratory syndrome cases. Ann Emerg Med. 2004;43:27-33. [PMID: 14707937] CrossrefMedlineGoogle Scholar5. Peiris JS, Yuen KY, Osterhaus AD, Stohr K. The severe acute respiratory syndrome. N Engl J Med. 2003;349:2431-41. [PMID: 14681510] CrossrefMedlineGoogle Scholar Comments 0 Comments Sign In to Submit A Comment Author, Article, and Disclosure InformationAuthors: Matthew H.M. Ma, MD, PhD; Shey-Ying Chen, MD; Wen-Chu Chiang, MD; Chan-Ping Su, MD; Wen-Jone Chen, MD, PhDAffiliations: From National Taiwan University Hospital, Taipei, Taiwan. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetailsSee AlsoA Clinical Prediction Rule for Diagnosing Severe Acute Respiratory Syndrome in the Emergency Department Gabriel M. Leung , Timothy H. Rainer , Fei-Lung Lau , Irene O.L. Wong , Anna Tong , Tai-Wai Wong , James H.B. Kong , Anthony J. Hedley , and Tai-Hing Lam , for the Hospital Authority SARS Collaborative GroupA Clinical Prediction Rule for the Severe Acute Respiratory Syndrome Timothy H. Rainer , Irene O.L. Wong , and Gabriel M. Leung Metrics Cited byThermogenesis-based interventions for obesity and Type 2 diabetes mellitusA comparative epidemiologic analysis of SARS in Hong Kong, Beijing and Taiwan 1 February 2005Volume 142, Issue 3 Page: 225 Keywords Emergency department Forecasting Hospitalizations Negative predictive value Positive predictive value Retrospective studies SARS coronavirus Specificity Temperature Triage ePublished: 1 February 2005 Issue Published: 1 February 2005 Copyright & PermissionsCopyright © 2005 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...