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Objective Vital sign scoring systems that alert providers of clinical deterioration prior to critical illness have been proposed as a means of reducing maternal risk. This study examined the predictive ability of established maternal early warning systems (MEWS)—as well as their component vital sign thresholds—for different types of maternal morbidity, to discern an optimal early warning system. Study Design This retrospective cohort study analyzed all patients admitted to the obstetric services of a four-hospital urban academic system in 2018. Three sets of published MEWS criteria were evaluated. Maternal morbidity was defined as a composite of hemorrhage, infection, acute cardiac disease, and acute respiratory disease ascertained from the electronic medical record data warehouse and administrative data. The test characteristics of each MEWS, as well as for heart rate, blood pressure, and oxygen saturation were compared. Results Of 14,597 obstetric admissions, 2,451 patients experienced the composite morbidity outcome (16.8%) including 980 cases of hemorrhage (6.7%), 1,337 of infection (9.2%), 362 of acute cardiac disease (2.5%), and 275 of acute respiratory disease (1.9%) (some patients had multiple types of morbidity). The sensitivities (15.3–64.8%), specificities (56.8–96.1%), and positive predictive values (22.3–44.5%) of the three MEWS criteria ranged widely for overall morbidity, as well as for each morbidity subcategory. Of patients with any morbidity, 28% met criteria for the most liberal vital sign combination, while only 2% met criteria for the most restrictive parameters, compared with 14 and 1% of patients without morbidity, respectively. Sensitivity for all combinations was low (maximum 28.2%), while specificity for all combinations was high, ranging from 86.1 to 99.3%. Conclusion Though all MEWS criteria demonstrated poor sensitivity for maternal morbidity, permutations of the most abnormal vital signs have high specificity, suggesting that MEWS may be better implemented as a trigger tool for morbidity reduction strategies in the highest risk patients, rather than a general screen. Key Points |
