ArticleJournal of clinical monitoring and computing2021
Fetal heart rate variability analysis for neonatal acidosis prediction.
Article in Journal of clinical monitoring and computing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 22 citations in OpenAlex.
- Development and validation of a machine learning-based early prediction model for fetal acidosis in vaginal deliveries.Scientific reports · 2026Article
- Predicting Intrapartum Acidemia: A Review of Approaches Based on Fetal Heart Rate.Bioengineering (Basel, Switzerland) · 2026Review
- Advancements in Fetal Heart Rate Monitoring: A Report on Opportunities and Strategic Initiatives for Better Intrapartum Care.BJOG : an international journal of obstetrics and gynaecology · 2025Review
- Hybrid-FHR: a multi-modal AI approach for automated fetal acidosis diagnosis.BMC medical informatics and decision making · 2024Article
- Conventional CardiotocographyMaedica · 2023Article
- Computerized cardiotocography analysis during labor - A state-of-the-art review.Acta obstetricia et gynecologica Scandinavica · 2023Review
- DeepCTG® 1.0: an interpretable model to detect fetal hypoxia from cardiotocography data during labor and delivery.Frontiers in pediatrics · 2023Article
- Classification of Cardiotocography Based on the Apriori Algorithm and Multi-Model Ensemble Classifier.Frontiers in cell and developmental biology · 2022Article
- A deep feature fusion network for fetal state assessment.Frontiers in physiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fetal well-being during labor is usually assessed by visual analysis of a fetal heart rate (FHR) tracing. Our primary objective was to evaluate the ability of automated heart rate variability (HRV) analysis methods, including our new fetal stress index (FSI), to predict neonatal acidosis. 552 intrapartum recordings were analyzed. The analysis occurred in the last 90 min before birth and was conducted during two 5-min intervals: (i) a stable period of FHR and (ii) the period corresponding to the maximum FSI value. For each period, we computed the mean FHR, FSI, short-term variability (STV), and long-term variability (LTV). Visual FHR interpretation was performed using the FIGO classification. The population was separated into two groups: (i) an acidotic group with an arterial pH at birth ≤ 7.10 and a control group. Prediction of a neonatal pH ≤ 7.10 was assessed by computing the receiver-operating characteristic area under the curve (AUC). FHR, FSI, STV, and LTV did not differ significantly between groups during the stable period. During the FSI max peak period, LTV and STV correlated significantly in the acidotic group (- 5.85 ± 2.19, p = 0.010 and - 0.62 ± 0.29, p = 0.037, respectively). The AUC values were 0.569 for FIGO classification, 0.595 for STV, and 0.622 for LTV. The multivariate model (FIGO, FSI, FC, STV, LTV) had the greatest accuracy for predicting acidosis (AUC = 0.719). FSI was not predictive of neonatal acidosis probably because of the low quality of the FHR signal in cardiotocography. When used separately, HRV indexes and visual FHR analysis were poor predictors of neonatal acidosis. Including all indexes in a multivariate model increased the predictive ability.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.