Abstract

Alerts based on abnormal maternal vital signs may allow clinicians to identify clinical deterioration prior to critical illness; however, optimal thresholds in pregnancy are not well-established. This study examined the relationship between abnormal oxygen saturation (O2 sat), systolic (SBP) and diastolic blood pressure (DBP) parameters and maternal morbidity. This retrospective cohort study analyzed all pregnant patients >18 years old at any gestational age admitted to the obstetric service of a large academic hospital system in 2018. Vital signs and clinical data were extracted from the electronic medical record. O2 sat cutoffs of < 95% and < 90%, SBP cutoffs of < 90, < 80, and >160 mmHg, and DBP cutoffs of < 50, < 40, and >110 mmHg were analyzed. The primary outcome was significant maternal morbidity including hemorrhage, infection, cardiac dysfunction, and respiratory distress ascertained by clinical criteria and diagnosis codes. Test characteristics of each vital sign threshold were assessed. Of 14,597 obstetric admissions, 2,451 patients experienced morbidity (16.8%) including 980 cases of hemorrhage (6.7%), 1,337 of infection (9.2%), 362 of cardiac dysfunction (2.5%), and 275 of respiratory distress (1.9%). 41% and 12% of patients with morbidity had O2 sat < 95 and < 90, compared to 26% and 8% of patients without morbidity, respectively. 40% of patients who experienced morbidity had SBP < 90, 15% < 80, and 18% >160, compared to 29%, 8%, and 11% of patients without morbidity. 53% of patients with morbidity had DBP < 50, 17% < 40, and 14% >110, compared to 41%, 10%, and 9% in patients without morbidity (Table 1). Sensitivity was higher for less stringent parameters while positive predictive (PPV) and negative predictive values (NPV) were similar across parameters (Table 2). O2 sat and BP had similar PPV and NPV for morbidity at varying cutoffs. The relatively high prevalence of O2 sat < 95%, SBP < 90, and DBP < 50, and low sensitivity of other, more stringent cutoffs supports relatively poor discrimination of obstetric risk prediction based on these parameters.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

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