Clinical prognostic rules for severe acute respiratory syndrome in low- and high-resource settings

被引:13
作者
Cowling, Benjamin J.
Muller, Matthew P.
Wong, Irene O. L.
Ho, Lai-Ming
Lo, Su-Vui
Tsang, Thomas
Lam, Tai Hing
Louie, Marie
Leung, Gabriel M.
机构
[1] Univ Hong Kong, Dept Community Med, Hong Kong, Hong Kong, Peoples R China
[2] Univ Hong Kong, Sch Publ Hlth, Hong Kong, Hong Kong, Peoples R China
[3] Govt Hong Kong Special Adm Res, Hlth Welf & Food But, Hong Kong, Hong Kong, Peoples R China
[4] Govt Hong Kong Special Adm Res, Ctr Hlth Protect, Dept Hlth, Hong Kong, Hong Kong, Peoples R China
[5] Mt Sinai Hosp, Toronto, ON M5G 1X5, Canada
关键词
D O I
10.1001/archinte.166.14.1505
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: An accurate prognostic model for patients with severe acute respiratory syndrome (SARS) could provide a practical clinical decision aid. We developed and validated prognostic rules for both high- and low-resource settings based on data available at the time of admission. Methods: We analyzed data on all 1755 and 291 patients with SARS in Hong Kong (derivation cohort) and Toronto (validation cohort), respectively, using a multivariable logistic scoring method with internal and external validation. Scores were assigned on the basis of patient history in a basic model, and a full model additionally incorporated radiological and laboratory results. The main outcome measure was death. Results: Predictors for mortality in the basic model included older age, male sex, and the presence of comorbid conditions. Additional predictors in the full model included haziness or infiltrates on chest radiography, less than 95% oxygen saturation on room air, high lactate dehydrogenase level, and high neutrophil and low platelet counts. The basic model had an area under the receiver operating characteristic (ROC) curve of 0.860 in the derivation cohort, which was maintained on external validation with an area under the ROC curve of 0.882. The full model improved discrimination with areas under the ROC curve of 0.877 and 0.892 in the derivation and validation cohorts, respectively. Conclusion: The model performs well and could be useful in assessing prognosis for patients who are infected with re-emergent SARS.
引用
收藏
页码:1505 / 1511
页数:7
相关论文
共 48 条
[31]   SARS-CoV antibody prevalence in all Hong Kong patient contacts [J].
Leung, GM ;
Chung, PH ;
Tsang, T ;
Lim, W ;
Chan, SKK ;
Chau, P ;
Donnelly, CA ;
Ghani, AC ;
Fraser, C ;
Riley, S ;
Ferguson, NM ;
Anderson, RM ;
Law, YI ;
Mok, T ;
Ng, T ;
Fu, A ;
Leung, PY ;
Peiris, JSM ;
Lam, TH ;
Hedley, AJ .
EMERGING INFECTIOUS DISEASES, 2004, 10 (09) :1653-1656
[32]   A clinical prediction rule for diagnosing severe acute respiratory syndrome in the emergency department [J].
Leung, GM ;
Rainer, TH ;
Lau, FL ;
Wong, IOL ;
Tong, A ;
Wong, TW ;
Kong, JHB ;
Hedley, AJ ;
Lam, TH .
ANNALS OF INTERNAL MEDICINE, 2004, 141 (05) :333-342
[33]   Bats are natural reservoirs of SARS-like coronaviruses [J].
Li, WD ;
Shi, ZL ;
Yu, M ;
Ren, WZ ;
Smith, C ;
Epstein, JH ;
Wang, HZ ;
Crameri, G ;
Hu, ZH ;
Zhang, HJ ;
Zhang, JH ;
McEachern, J ;
Field, H ;
Daszak, P ;
Eaton, BT ;
Zhang, SY ;
Wang, LF .
SCIENCE, 2005, 310 (5748) :676-679
[34]  
Little R.J.A., 2002, STAT ANAL MISSING DA, DOI DOI 10.1002/9781119013563
[35]   Critics slam treatment for SARS as ineffective and perhaps dangerous [J].
Oyranoski, D .
NATURE, 2003, 423 (6935) :4-4
[36]   Early diagnosis of SARS Coronavirus infection by real time RT-PCR [J].
Poon, LLM ;
Chan, KH ;
Wong, OK ;
Yam, WC ;
Yuen, KY ;
Guan, Y ;
Lo, YMD ;
Peiris, JSM .
JOURNAL OF CLINICAL VIROLOGY, 2003, 28 (03) :233-238
[37]  
R Core Team, 2016, R LANG ENV STAT COMP
[38]   Multiple imputation: a primer [J].
Schafer, JL .
STATISTICAL METHODS IN MEDICAL RESEARCH, 1999, 8 (01) :3-15
[39]   Prognostic modeling with logistic regression analysis: In search of a sensible strategy in small data sets [J].
Steyerberg, EW ;
Eijkemans, MJC ;
Harrell, FE ;
Habbema, JDF .
MEDICAL DECISION MAKING, 2001, 21 (01) :45-56
[40]  
Tang P, 2004, CAN MED ASSOC J, V170, P47