Predicting Category II and III foetal heart rate patterns during epidural analgesia: a retrospective cohort study.
A predictive model for abnormal fetal heart rate patterns during labor epidural analgesia showed good discrimination and calibration, but further validation is needed.
Where it sits
this study against the rest of the oxytocin corpusSummary and findings
This study developed a prediction model for Category II and III fetal heart rate patterns in 237 parturients undergoing labor epidural analgesia. The model identified 11 predictors, including maternal temperature and oxytocin dosage, with an AUC of 0.800. The nomogram was internally validated and showed good discrimination and calibration.
Abstract
<h4>Background</h4>This study aimed to identify predictors and develop a multivariable prediction model for Category II and III foetal heart rate (FHR) patterns in parturients undergoing labour epidural analgesia (LEA).<h4>Methods</h4>A retrospective cohort study of 237 parturients receiving LEA was conducted. To address the multicollinearity of 18 intrapartum variables, least absolute shrinkage and selection operator (LASSO) regression and cross-validation were used for feature selection. A predictive nomogram was constructed and internally validated. Model performance was evaluated by the area under the receiver operating characteristic curve (AUC), calibration plots, and Decision Curve Analysis (DCA).<h4>Results</h4>Abnormal FHR patterns (Category II and III) occurred in 168 (70.9%) parturients. The LASSO algorithm identified 11 predictors. Multivariable logistic regression demonstrated that maternal intrapartum temperature (OR = 3.518), initial LEA bolus count (OR = 3.625), body mass index (BMI), and oxytocin dosage were independent predictors associated with abnormal FHR patterns. The constructed nomogram demonstrated good discrimination (AUC = 0.800) and good calibration. DCA demonstrated potential clinical net benefit across a wide range of threshold probabilities (0.02-0.99).<h4>Conclusions</h4>We developed and internally validated an 11-variable nomogram (AUC = 0.800) to predict abnormal FHR patterns during LEA. By integrating routinely available clinical variables, the nomogram facilitate early risk stratification and support individualised intrapartum management.<h4>Trial registration</h4>Clinical trial registration: (https://www.chictr.org.cn ChiCTR2300073493; registered 12th July 2023).
Background
The study addresses the challenge of predicting abnormal fetal heart rate patterns during labor epidural analgesia. Such patterns can indicate fetal distress, necessitating timely intervention. Prior research has identified various risk factors, but a comprehensive predictive model integrating multiple variables was lacking.
Methods
This was a retrospective cohort study involving 237 parturients receiving labor epidural analgesia. The study used LASSO regression and cross-validation to address multicollinearity among 18 intrapartum variables. A predictive nomogram was constructed and internally validated, with model performance assessed using AUC, calibration plots, and Decision Curve Analysis.
Results
Abnormal fetal heart rate patterns were observed in 168 parturients, accounting for 70.9% of the cohort. The LASSO algorithm identified 11 predictors, including maternal intrapartum temperature and oxytocin dosage, as significant. The nomogram demonstrated good discrimination with an AUC of 0.800 and was well-calibrated. Decision Curve Analysis indicated potential clinical net benefit across a wide range of threshold probabilities.
Interpretation
The study provides a predictive model with good discrimination and calibration for identifying abnormal fetal heart rate patterns during labor epidural analgesia. While statistically significant, the clinical significance of the findings depends on the model's application in diverse clinical settings. The retrospective design and lack of external validation limit the generalizability of the results.
Key findings
- 168 (70.9%) parturients experienced abnormal FHR patterns.
- Maternal intrapartum temperature had an OR of 3.518.
- Initial LEA bolus count had an OR of 3.625.
- The nomogram's AUC was 0.800.
- DCA showed potential clinical net benefit across threshold probabilities of 0.02-0.99.
Limitations
- Retrospective design
- Internal validation only
- Potential selection bias
- Single-site study