[A predictive model of mortality in the ICU of a Mexico City hospital].
OBJECTIVE
To explore the associations of mortality with routine logbook information as a preliminary to developing a quality control system in an ICU.


METHODS
The ICU logbook contained seven variables of 2,745 consecutive cases hospitalized from Jan-01-1998 to Dec-31-2002. The univariate association of ICU mortality with five predictive and two non-predictive variables was explored. Gender was the only one unassociated. A logistic regression predictive model of mortality of three variables was generated (cause of hospitalization, age and type of patient).


RESULTS
The global mortality was 27%. The highest risk was for non-surgery patients aged 80+ years with multiple organic failure, sepsis and/or pneumonia. They had a relative risk of 18.1 versus the reference group (surgical cases aged 20-39 with less severe illnesses). Three additional simple predictors were identified as potentially useful and are to be included in an updated logbook.


CONCLUSIONS
1. The logbook information appeared to be useful in monitoring ICU quality of service as six logbook variables were associated to mortality. 2. Our predictive model has the potential to operate as an index of severity of disease and may improve by the inclusion of additional information. 3. Its usefulness is to be compared prospectively with well-established predictors (Apache II and others).
Rosel-Ramírez
Roberto
R
Unidad de Cuidados Intensivos, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Tlalpan, México, DF.
Loría
Alvar
A
Domínguez-Cherit
Guillermo
G
Gutiérrez-Sougarret
Bernardo
B
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D017052:Hospital Mortality / Q000639:trends*; D006801:Humans; D007362:Intensive Care Units / Q000706:statistics & numerical data*; D008297:Male; D008800:Mexico; D008875:Middle Aged; D015233:Models, Statistical; D015999:Multivariate Analysis; D011379:Prognosis; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*; D014505:Urban Population