Relationship between Deceleration Areas in the Second Stage of Labor and Neonatal Acidemia

Agostinelli, Angela; Palmieri, Flavio; Biagini, Alessandra; Sbrollini, Agnese; Burattini, Luca; Nardo, Francesco Di; Fioretti, Sandro; Burattini, Laura

doi:10.22489/cinc.2016.260-352

Cited by 7 publications

(1 citation statement)

References 15 publications

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“…For example, high BLV and high #AC, AAC and DAC indicate fetal well-being, while low BLV and high #DC, ADC and DDC are associated with fetal distress [18,19].…”

Section: Discussionmentioning

confidence: 99%

Extraction of Digital Cardiotocographic Signals from Digital Cardiotocographic Images: Robustness of eCTG Procedure

et al. 2019

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A recently developed software application, eCTG, extracts cardiotocographic (CTG) signals from digital CTG images, possibly obtained by scanning paper CTG reports. The aim of this study was to evaluate eCTG robustness across varying image formats, resolution and screw. Using 552 digital CTG signals from the “CTU-UHB Intrapartum Cardiotocography Database” of Physionet, seven sets of digital CTG images were created, differing in format (.TIFF, .PNG and .JPEG), resolution (96 dpi, 300 dpi and 600 dpi) and screw (0.0°, 0.5°, and 1.0°). All created images were submitted to eCTG for CTG signals extraction. Quality of extracted signals was statistically evaluated based 1) on signal morphology, by computation of the correlation coefficient (ρ) and of the mean signal error percent (MSE%), and 2) on signal clinical content, by assessment of 18 standard CTG variables. For all sets of images, ρ was high (ρ ≥ 0.81) and MSE% was small (MSE% ≤ 2%). However, significant changes occurred in median values of four, four and five standard CTG variables in image sets with 96 dpi resolution, 0.5° screw and 1.0° screw, respectively. In conclusion, for an optimal eCTG performance, digital images should be saved in lossless formats, have a resolution of at least 300 dpi and not be affected by screw.

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“…For example, high BLV and high #AC, AAC and DAC indicate fetal well-being, while low BLV and high #DC, ADC and DDC are associated with fetal distress [18,19].…”

Section: Discussionmentioning

confidence: 99%

Extraction of Digital Cardiotocographic Signals from Digital Cardiotocographic Images: Robustness of eCTG Procedure

et al. 2019

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CTG Analyzer: A graphical user interface for cardiotocography

Sbrollini

Agostinelli

Burattini

et al. 2017

2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Cardiotocography (CTG) is the most commonly used test for establishing the good health of the fetus during pregnancy and labor. CTG consists in the recording of fetal heart rate (FHR; bpm) and maternal uterine contractions (UC; mmHg). FHR is characterized by baseline, baseline variability, tachycardia, bradycardia, acceleration and decelerations. Instead, UC signal is characterized by presence of contractions and contractions period. Such parameters are usually evaluated by visual inspection. However, visual analysis of CTG recordings has a well-demonstrated poor reproducibility, due to the complexity of physiological phenomena affecting fetal heart rhythm and being related to clinician's experience. Computerized tools in support of clinicians represents a possible solution for improving correctness in CTG interpretation. This paper proposes CTG Analyzer as a graphical tool for automatic and objective analysis of CTG tracings. CTG Analyzer was developed under MATLAB®; it is a very intuitive and user friendly graphical user interface. FHR time series and UC signal are represented one under the other, on a grid with reference lines, as usually done for CTG reports printed on paper. Colors help identification of FHR and UC features. Automatic analysis is based on some unchangeable features definitions provided by the FIGO guidelines, and other arbitrary settings whose default values can be changed by the user. Eventually, CTG Analyzer provides a report file listing all the quantitative results of the analysis. Thus, CTG Analyzer represents a potentially useful graphical tool for automatic and objective analysis of CTG tracings.

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Statistical baseline assessment in cardiotocography

Agostinelli

Braccili

Marchegiani

et al. 2017

2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Cardiotocography (CTG) is the most common non-invasive diagnostic technique to evaluate fetal well-being. It consists in the recording of fetal heart rate (FHR; bpm) and maternal uterine contractions. Among the main parameters characterizing FHR, baseline (BL) is fundamental to determine fetal hypoxia and distress. In computerized applications, BL is typically computed as mean FHR±ΔFHR, with ΔFHR=8 bpm or ΔFHR=10 bpm, both values being experimentally fixed. In this context, the present work aims: to propose a statistical procedure for ΔFHR assessment; to quantitatively determine ΔFHR value by applying such procedure to clinical data; and to compare the statistically-determined ΔFHR value against the experimentally-determined ΔFHR values. To these aims, the 552 recordings of the "CTU-UHB intrapartum CTG database" from Physionet were submitted to an automatic procedure, which consisted in a FHR preprocessing phase and a statistical BL assessment. During preprocessing, FHR time series were divided into 20-min sliding windows, in which missing data were removed by linear interpolation. Only windows with a correction rate lower than 10% were further processed for BL assessment, according to which ΔFHR was computed as FHR standard deviation. Total number of accepted windows was 1192 (38.5%) over 383 recordings (69.4%) with at least an accepted window. Statistically-determined ΔFHR value was 9.7 bpm. Such value was statistically different from 8 bpm (P<;10) but not from 10 bpm (P=0.16). Thus, ΔFHR=10 bpm is preferable over 8 bpm because both experimentally and statistically validated.

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Relationship between Deceleration Areas in the Second Stage of Labor and Neonatal Acidemia

Abstract: Understanding the fetal heart rate (FHR) (ρ=-0.23, P<10 -6

Cited by 7 publications

References 15 publications

Extraction of Digital Cardiotocographic Signals from Digital Cardiotocographic Images: Robustness of eCTG Procedure

Extraction of Digital Cardiotocographic Signals from Digital Cardiotocographic Images: Robustness of eCTG Procedure

CTG Analyzer: A graphical user interface for cardiotocography

Statistical baseline assessment in cardiotocography

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