Fetal heart rate patterns in labor and the risk of neonatal encephalopathy: A case control study. (June 2022) - Reynolds, Adam J.; Murray, Michelle L.; Geary, Michael P.; Ater, Stewart B.; Hayes, Breda C.
Highlights: The power of NICE (UK) FHR analysis criteria to predict HIE is described. Their overall accuracy is modest. Assessing the total duration of abnormalities increases accuracy. In retrospect, ¼ of cases were detected with 95% specificity >1 h before delivery. Abstract: Objective: To describe the accuracy of intrapartum fetal heart rate abnormalities as defined by National Institute of Health and Care Excellence guidelines to predict moderate-severe neonatal encephalopathy of apparent hypoxic-ischemic etiology. Study design: A case-control study of HIE risk factors was conducted. Eligible babies were born in a single maternity hospital in Dublin, Ireland between September 2006, and November 2017 at ≥35 + 0 weeks' gestational age. Cases were eligible babies with moderate-severe neonatal encephalopathy of definite or apparent hypoxic-ischemic etiology. Controls were eligible babies born before and after each case with normal Apgar scores. The included subjects who had intrapartum fetal heart rate recordings were identified. Pattern features (baseline rate, variability, accelerations, decelerations [early, late, variable, prolonged], bradycardia, sinusoidal pattern) were manually identified blind to all clinical details by one of the authors. Each 15-minute segment was then algorithmically categorized (uninterpretable, normal, suspicious, pathological). Results: Of 88 cases and 176 controls, 71 cases (81%) and 146 controls (83%) were admitted to the delivery suite in labor. From that group, intrapartum FHR traces longer than 15 min were available for 52 (73%) cases and 118 (83%) controls. The FHR pattern feature with the largest area under the receiver operating characteristic curve was the maximum number of consecutive segments in which the baseline was >160 bpm (0.71 [95% confidence interval: 0.62–0.80]). The category variable with the highest area under the curve was the number of suspicious segments (0.76 [95% confidence interval: 0.67–0.84]). A tri-variate logistic regression model incorporating the total number of segments, the number of "suspicious" segments classed, and the number of "pathological" segments achieved an area under the curve of 0.78 (95% confidence interval: 0.70–0.86). With 95% specificity, this model correctly identified 17 cases (33%) at a median time before delivery of 2 h and 18 min (interquartile range: 01:19–04:40). Conclusions: The power of fetal heart rate analysis to predict neonatal encephalopathy is hampered by poor specificity given the rarity of the outcome. When analyzing a suspicious trace, it is beneficial to consider the overall duration of the suspicious pattern.