Characteristics of preeclampsia- and eclampsia-related maternal death in rural Haiti.
OBJECTIVE
The maternal mortality ratio in Haiti remains one of the highest in the world at 600/100 000 live births. Preeclampsia- and eclampsia-related complications are one of the leading causes of maternal death. In this resource-limited setting, effective, efficient hospital-based interventions are necessary to reduce this risk. Our objective was to assess the utility of common laboratory and clinical admission data for the determination of preeclampsia- and eclampsia-related maternal death.


METHODS
We performed an analysis of women presenting to the Hôpital Albert Schweitzer with preeclampsia and eclampsia during a 3-year period. Factors analyzed were: maternal age, parity, gestational age, hematocrit, serum creatinine, urine protein, systolic and diastolic blood pressure, intrauterine fetal death (IUFD), coma on arrival, and address (residence within or outside hospital catchment area). Stepwise logistic regression identified factors predictive of maternal mortality.


RESULTS
Preeclampsia/eclampsia affected 423 of 2295 deliveries (18%) and resulted in 19 deaths. Multivariate analysis identified the following predictors of maternal mortality: IUFD (RR 7.57; 95% CI 2.76-12.69), eclampsia (RR 6.91; 95% CI 2.08-12.64), and oliguria (RR 5.39; 95% CI 1.80-10.69).


CONCLUSIONS
In this setting, traditional admission laboratory and clinical tests were not useful in maternal mortality prediction. The analysis highlights clinical characteristics of women at highest risk for maternal death.
Small
Maria J
MJ
Yale University School of Medicine, Yale University School of Public Health, Division of Maternal Fetal Medicine, New Haven, CT 06520-8063, USA. mjs93@email.med.yale.edu
Kershaw
Trace
T
Frederic
Rikerdy
R
Blanc
Christian
C
Neale
Donna
D
Copel
Joshua
J
Williams
Keith P
KP
D000328:Adult; D004461:Eclampsia / Q000401:mortality*; D005260:Female; D005313:Fetal Death / Q000453:epidemiology; D006205:Haiti / Q000453:epidemiology; D006801:Humans; D016015:Logistic Models; D008428:Maternal Mortality; D015999:Multivariate Analysis; D009846:Oliguria / Q000453:epidemiology; D011225:Pre-Eclampsia / Q000401:mortality*; D011247:Pregnancy; D012306:Risk; D012424:Rural Population