Simple triage scoring system predicting death and the need for critical care resources for use during epidemics.
OBJECTIVE
In the event of pandemic influenza, the number of critically ill victims will likely overwhelm critical care capacity. To date, no standardized method for allocating scarce resources when the number of patients in need far exceeds capacity exists. We sought to derive and validate such a triage scheme.


METHODS
: Retrospective analysis of prospectively collected data.


METHODS
Emergency departments of two urban tertiary care hospitals.


METHODS
Three separate cohorts of emergency department patients with suspected infection, comprising a total of 5,133 patients.


METHODS
None.


METHODS
A triage decision rule for use in an epidemic was developed using only those vital signs and patient characteristics that were readily available at initial presentation to the emergency department. The triage schema was derived from a cohort at center 1, validated on a second cohort from center 1, and then validated on a third cohort of patients from center 2. The primary outcome for the analysis was in-hospital mortality. Secondary outcomes were intensive care unit admission and use of mechanical ventilation.


RESULTS
Multiple logistic regression demonstrated the following as independent predictors of death: a) age of >65 yrs, b) altered mental status, c) respiratory rate of >30 breaths/min, d) low oxygen saturation, and e) shock index of >1 (heart rate > blood pressure). This model had an area under the receiver operating characteristic curve of 0.80 in the derivation set and 0.74 and 0.76 in the validation sets. When converted to a simple rule assigning 1 point per covariate, the discrimination of the model remained essentially unchanged. The model was equally effective at predicting need for intensive care unit admission and mechanical ventilation.


CONCLUSIONS
If, as expected, patient demand far exceeds the capability to provide critical care services in an epidemic, a fair and just system to allocate limited resources will be essential. The triage rule we have developed can serve as an initial guide for such a process.
Talmor
Daniel
D
Trauma Anesthesia and Critical Care, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA. dtalmor@bidmc.harvard.edu
Jones
Alan E
AE
Rubinson
Lewis
L
Howell
Michael D
MD
Shapiro
Nathan I
NI
D019540:Area Under Curve; D015897:Comorbidity; D003422:Critical Care / Q000592:standards*; D004196:Disease Outbreaks; D005260:Female; D015276:Health Care Rationing / Q000379:methods; D017052:Hospital Mortality; D006801:Humans; D053124:Influenza A Virus, H5N1 Subtype; D007251:Influenza, Human / Q000401:mortality*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D012189:Retrospective Studies; D014218:Triage / Q000379:methods* / Q000592:standards; D000078329:Workforce