Abstract
BACKGROUND AND OBJECTIVE: The temporal importance of prognostic indicators for severe acute respiratory syndrome (SARS) has not been studied. This study identified the various clinical prognostic factors for SARS and described the temporal evolution of these factors in the course of the SARS illness in Hong Kong in 2003. METHODS: A retrospective analysis of the entire Hong Kong cohort of 1312 laboratory-confirmed SARS patients aged 15-74 years was undertaken. Demographic, clinical and laboratory data at presentation and investigative data during the first 10 days of illness from the time of symptom onset were compiled. Two adverse outcomes were examined: hospital mortality and the development of oxygenation failure based on the estimated PaO(2)/FiO(2) ratio of <200 mm Hg. Logistic regression was used to identify the association between these prognostic factors and outcomes. RESULTS: Based on adjusted odds ratios with a P-value of <0.05, older age, male gender, elevated pulse rate and elevated neutrophil count were all predictive of oxygenation failure and death during the 10-day illness. Raised serum albumin and creatinine phosphokinase (CPK) levels were predictive of hospital mortality during this period. The presenting ALT and CPK level and the day 7 and day 10 platelet counts were predictive of oxygenation failure while the day 7 LDH was predictive of death. Contact exposure outside health-care institutions also appeared to carry higher risk of death. CONCLUSION: This large-scale analysis identified important discriminatory parameters related to the patients' demographic profile (age and gender), severity of illness (pulse rate and neutrophil count), and multisystem derangement (platelet count, CPK, ALT and LDH), all of which prognosticated adverse outcomes during the SARS episode. While age, pulse rate and neutrophil count consistently remained significant prognosticators during the first 10 days of illness, the prognostic impact of other derangements was more time-course dependent. Clinicians should be aware of the time-course evolution of these prognosticators.