Fernández PM, Sarmiento HAP, Briones GJC

Language: Spanish
References: 11
Page: 28-31
PDF size: 294.40 Kb.

ABSTRACT

Introduction: hypertensive disorders of pregnancy represent the most common complication during gestation, occurring in up to 15% of cases. They are considered one of the leading causes of maternal mortality, and in Latin America, preeclampsia is responsible for 25.7% of these deaths. The importance of timely diagnosis lies in the high rate of maternal and fetal complications. In this context, the FullPIERS model emerged as a scale to predict maternal complications within the first 48 hours of patient admission. Objective: to determine the usefulness of the FullPIERS scale in predicting adverse maternal outcomes in patients diagnosed with severe preeclampsia at the "Dr. Maximiliano Ruiz Castañeda" General Hospital. Material and methods: a descriptive relational analysis was conducted. The necessary information was identified in the records of patients who met the inclusion criteria. For qualitative variables, frequency and percentage calculations were performed, while for quantitative variables, measures of central tendency and dispersion were calculated. Probability measures included sensitivity, specificity, positive predictive value, and negative predictive value. To evaluate the diagnostic performance of the scale, prevalence ratios and confidence intervals were used, with a statistical power of 95 and 5% margin of error, accepting a significant difference at p < 0.05. Results: sensitivity of 38.9% and a specificity of 98.8%. Additionally, the positive predictive value was 93.33%, and the negative predictive value was 78.64%. The area under the curve was 0.849 and an accuracy of 80.5%. Conclusions: the FullPIERS scale is useful for predicting adverse maternal outcomes in patients diagnosed with severe preeclampsia. A low result on the scale is related to low probability of developing adverse maternal outcomes with a high specificity (98.8%). The model found an accuracy 80.5% which indicates that it classifies correctly 4 out of 5 patients.

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