21 research outputs found
Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals
In the field of electronic fetal health monitoring, computerized analysis of fetal heart rate
(FHR) signals has emerged as a valid decision-support tool in the assessment of fetal wellbeing.
Despite the availability of several approaches to analyze the variability of FHR signals (namely
the FHRV), there are still shadows hindering a comprehensive understanding of how linear and
nonlinear dynamics are involved in the control of the fetal heart rhythm. In this study, we propose
a straightforward processing and modeling route for a deeper understanding of the relationships
between the characteristics of the FHR signal. A multiparametric modeling and investigation of the
factors influencing the FHR accelerations, chosen as major indicator of fetal wellbeing, is carried out
by means of linear and nonlinear techniques, blockwise dimension reduction, and artificial neural
networks. The obtained results show that linear features are more influential compared to nonlinear
ones in the modeling of HRV in healthy fetuses. In addition, the results suggest that the investigation
of nonlinear dynamics and the use of predictive tools in the field of FHRV should be undertaken
carefully and limited to defined pregnancy periods and FHR mean values to provide interpretable
and reliable information to clinicians and researchers
A Comprehensive Review of Techniques for Processing and Analyzing Fetal Heart Rate Signals
The availability of standardized guidelines regarding the use of electronic fetal monitoring
(EFM) in clinical practice has not effectively helped to solve the main drawbacks of fetal heart rate
(FHR) surveillance methodology, which still presents inter- and intra-observer variability as well
as uncertainty in the classification of unreassuring or risky FHR recordings. Given the clinical
relevance of the interpretation of FHR traces as well as the role of FHR as a marker of fetal wellbeing
autonomous nervous system development, many different approaches for computerized processing
and analysis of FHR patterns have been proposed in the literature. The objective of this review is to
describe the techniques, methodologies, and algorithms proposed in this field so far, reporting their
main achievements and discussing the value they brought to the scientific and clinical community.
The review explores the following two main approaches to the processing and analysis of FHR
signals: traditional (or linear) methodologies, namely, time and frequency domain analysis, and less
conventional (or nonlinear) techniques. In this scenario, the emerging role and the opportunities
offered by Artificial Intelligence tools, representing the future direction of EFM, are also discussed
with a specific focus on the use of Artificial Neural Networks, whose application to the analysis of
accelerations in FHR signals is also examined in a case study conducted by the authors
First evidence that intrinsic fetal heart rate variability exists and is affected by hypoxic pregnancy.
KEY POINTS: We introduce a technique to test whether intrinsic fetal heart rate variability (iFHRV) exists and we show the utility of the technique by testing the hypothesis that iFHRV is affected by chronic fetal hypoxia, one of the most common adverse outcomes of human pregnancy complicated by fetal growth restriction. Using an established late gestation ovine model of fetal development under chronic hypoxic conditions, we identify iFHRV in isolated fetal hearts and show that it is markedly affected by hypoxic pregnancy. Therefore, the isolated fetal heart has intrinsic variability and carries a memory of adverse intrauterine conditions experienced during the last third of pregnancy. ABSTRACT: Fetal heart rate variability (FHRV) emerges from influences of the autonomic nervous system, fetal body and breathing movements, and from baroreflex and circadian processes. We tested whether intrinsic heart rate variability (iHRV), devoid of any external influences, exists in the fetal period and whether it is affected by chronic fetal hypoxia. Chronically catheterized ewes carrying male singleton fetuses were exposed to normoxia (n = 6) or hypoxia (10% inspired O2 , n = 9) for the last third of gestation (105-138 days of gestation (dG); term âŒ145 dG) in isobaric chambers. At 138 dG, isolated hearts were studied using a Langendorff preparation. We calculated basal intrinsic FHRV (iFHRV) indices reflecting iFHRV's variability, predictability, temporal symmetry, fractality and chaotic behaviour, from the systolic peaks within 15 min segments in each heart. Significance was assumed at P < 0.05. Hearts of fetuses isolated from hypoxic pregnancy showed approximately 4-fold increases in the Grid transformation as well as the AND similarity index (sgridAND) and a 4-fold reduction in the scale-dependent Lyapunov exponent slope. We also detected a 2-fold reduction in the Recurrence quantification analysis, percentage of laminarity (pL) and recurrences, maximum and average diagonal line (dlmax, dlmean) and the Multiscale time irreversibility asymmetry index. The iHRV measures dlmax, dlmean, pL and sgridAND correlated with left ventricular end-diastolic pressure across both groups (average R2  = 0.38 ± 0.03). This is the first evidence that iHRV originates in fetal life and that chronic fetal hypoxia significantly alters it. Isolated fetal hearts from hypoxic pregnancy exhibit a time scale-dependent higher complexity in iFHRV.British Heart Foundatio
Symbolic Dynamics Analysis: a new methodology for foetal heart rate variability analysis
Cardiotocography (CTG) is a widespread foetal diagnostic methods. However, it lacks of objectivity and reproducibility since its dependence on observer's expertise. To overcome these limitations, more objective methods for CTG interpretation have been proposed. In particular, many developed techniques aim to assess the foetal heart rate variability (FHRV). Among them, some methodologies from nonlinear systems theory have been applied to the study of FHRV. All the techniques have proved to be helpful in specific cases. Nevertheless, none of them is more reliable than the others. Therefore, an in-depth study is necessary. The aim of this work is to deepen the FHRV analysis through the Symbolic Dynamics Analysis (SDA), a nonlinear technique already successfully employed for HRV analysis. Thanks to its simplicity of interpretation, it could be a useful tool for clinicians.
We performed a literature study involving about 200 references on HRV and FHRV analysis; approximately 100 works were focused on non-linear techniques. Then, in order to compare linear and non-linear methods, we carried out a multiparametric study. 580 antepartum recordings of healthy fetuses were examined. Signals were processed using an updated software for CTG analysis and a new developed software for generating simulated CTG traces. Finally, statistical tests and regression analyses were carried out for estimating relationships among extracted indexes and other clinical information. Results confirm that none of the employed techniques is more reliable than the others. Moreover, in agreement with the literature, each analysis should take into account two relevant parameters, the foetal status and the week of gestation. Regarding the SDA, results show its promising capabilities in FHRV analysis. It allows recognizing foetal status, gestation week and global variability of FHR signals, even better than other methods. Nevertheless, further studies, which should involve even pathological cases, are necessary to establish its reliability.La Cardiotocografia (CTG) Ăš una diffusa tecnica di diagnostica fetale. Nonostante ciĂČ, la sua interpretazione soffre di forte variabilitĂ intra- e inter- osservatore. Per superare tali limiti, sono stati proposti piĂč oggettivi metodi di analisi. Particolare attenzione Ăš stata rivolta alla variabilitĂ della frequenza cardiaca fetale (FHRV). Nel presente lavoro abbiamo suddiviso le tecniche di analisi della FHRV in tradizionali, o lineari, e meno convenzionali, o non-lineari. Tutte si sono rivelate efficaci in casi specifici ma nessuna si Ăš dimostrata piĂč utile delle altre. Pertanto, abbiamo ritenuto necessario effettuare unâindagine piĂč dettagliata. In particolare, scopo della tesi Ăš stato approfondire una specifica metodologia non-lineare, la Symbolic Dynamics Analysis (SDA), data la sua notevole semplicitĂ di interpretazione che la renderebbe un potenziale strumento di ausilio allâattivitĂ clinica. Sono stati esaminati allâincirca 200 riferimenti bibliografici sullâanalisi di HRV e FHRV; di questi, circa 100 articoli specificamente incentrati sulle tecniche non-lineari. Eâ stata condotta unâanalisi multiparametrica su 580 tracciati CTG di feti sani per confrontare le metodologie adottate. Sono stati realizzati due software, uno per lâanalisi dei segnali CTG reali e lâaltro per la generazione di tracciati CTG simulati. Infine, sono state effettuate analisi statistiche e di regressione per esaminare le correlazioni tra indici calcolati e parametri di interesse clinico.
I risultati dimostrano che nessuno degli indici calcolati risulta piĂč vantaggioso rispetto agli altri. Inoltre, in accordo con la letteratura, lo stato del feto e le settimane di gestazione sono parametri di riferimento da tenere sempre in considerazione per ogni analisi effettuata. Riguardo la SDA, essa risulta utile allâanalisi della FHRV, permettendo di distinguere â meglio o al pari di altre tecniche â lo stato del feto, la settimana di gestazione e la variabilitĂ complessiva del segnale. Tuttavia, sono necessari ulteriori studi, che includano anche casi di feti patologici, per confermare queste evidenze
Monitoring Fetal Heart Rate during Pregnancy: Contributions from Advanced Signal Processing and Wearable Technology
Monitoring procedures are the basis to evaluate the clinical state of patients and to assess changes in their conditions, thus providing necessary interventions in time. Both these two objectives can be achieved by integrating technological development with methodological tools, thus allowing accurate classification and extraction of useful diagnostic information. The paper is focused on monitoring procedures applied to fetal heart rate variability (FHRV) signals, collected during pregnancy, in order to assess fetal well-being. The use of linear time and frequency techniques as well as the computation of non linear indices can contribute to enhancing the diagnostic power and reliability of fetal monitoring. The paper shows how advanced signal processing approaches can contribute to developing new diagnostic and classification indices. Their usefulness is evaluated by comparing two selected populations: normal fetuses and intra uterine growth restricted (IUGR) fetuses. Results show that the computation of different indices on FHRV signals, either linear and nonlinear, gives helpful indications to describe pathophysiological mechanisms involved in the cardiovascular and neural system controlling the fetal heart. As a further contribution, the paper briefly describes how the introduction of wearable systems for fetal ECG recording could provide new technological solutions improving the quality and usability of prenatal monitoring. © 2014 Maria G. Signorini et al
Surveillance non invasive de la rĂ©ponse neuroimmunitaire fĆtale Ă lâinfection
Introduction. In utero, lâinfection des membranes maternelles et fĆtales, la chorioamniotite, passe souvent inaperçue et, en particulier lorsque associĂ©e Ă une acidĂ©mie, due Ă lâocclusion du cordon ombilical (OCO), comme il se produirait au cours du travail, peut entrainer des lĂ©sions cĂ©rĂ©brales et avoir des rĂ©percussions neurologiques pĂ©ri - et postnatales Ă long terme chez le fĆtus. Il n'existe actuellement aucun moyen de dĂ©tecter prĂ©cocement ces conditions pathologiques in utĂ©ro afin de prĂ©venir ou de limiter ces atteintes.
HypothĂšses. 1)lâĂ©lectroencĂ©phalogramme (EEG) fĆtal obtenu du scalp fĆtal pourrait servir dâoutil auxiliaire Ă la surveillance Ă©lectronique fĆtale du rythme cardiaque fĆtal (RCF) pour la dĂ©tection prĂ©coce d'acidĂ©mie fĆtale et d'agression neurologique; 2) la frĂ©quence dâĂ©chantillonnage de lâECG fĆtal (ECGf) a un impact important sur le monitoring continu de la VariabilitĂ© du Rythme Cardiaque (VRCf) dans la prĂ©diction de lâacidĂ©mie fĆtale ; 3) les patrons de la corrĂ©lation de la VRCf aux cytokines pro-inflammatoires reflĂ©teront les Ă©tats de rĂ©ponses spontanĂ©es versus inflammatoires de la Voie Cholinergique Anti-inflammatoire (VCA); 4) grĂące au dĂ©veloppement dâun modĂšle de prĂ©dictions mathĂ©matiques, la prĂ©diction du pH et de lâexcĂšs de base (EB) Ă la naissance sera possible avec seulement une heure de monitoring dâECGf.
MĂ©thodes. Dans une sĂ©rie dâĂ©tudes fondamentales et cliniques, en utilisant respectivement le mouton et une cohorte de femmes en travail comme modĂšle expĂ©rimental et clinique , nous avons modĂ©lisĂ© 1) une situation dâhypoxie cĂ©rĂ©brale rĂ©sultant de sĂ©quences dâocclusion du cordon ombilical de sĂ©vĂ©ritĂ© croissante jusquâĂ atteindre un pH critique limite de 7.00 comme mĂ©thode expĂ©rimentale analogue au travail humain pour tester les premiĂšre et deuxiĂšme hypothĂšses 2) un inflammation fĆtale modĂ©rĂ©e en administrant le LPS Ă une autre cohorte animale pour vĂ©rifier la troisiĂšme hypothĂšse et 3) un modĂšle mathĂ©matique de prĂ©dictions Ă partir de paramĂštres et mesures validĂ©s cliniquement qui permettraient de dĂ©terminer les facteurs de prĂ©diction dâune dĂ©tresse fĆtale pour tester la derniĂšre hypothĂšse.
RĂ©sultats. Les sĂ©ries dâOCO rĂ©pĂ©titives se sont soldĂ©s par une acidose marquĂ©e (pH artĂ©riel 7.35±0.01 Ă 7.00±0.01), une diminution des amplitudes Ă l'Ă©lectroencĂ©phalogramme( EEG) synchronisĂ© avec les dĂ©cĂ©lĂ©rations du RCF induites par les OCO accompagnĂ©es d'une baisse pathologique de la pression artĂ©rielle (PA) et une augmentation marquĂ©e de VRCf avec hypoxie-acidĂ©mie aggravante Ă 1000 Hz, mais pas Ă 4 Hz, frĂ©quence dâĂ©chantillonnage utilisĂ©e en clinique. Lâadministration du LPS entraĂźne une inflammation systĂ©mique chez le fĆtus avec les IL-6 atteignant un pic 3 h aprĂšs et des modifications de la VRCf retraçant prĂ©cisĂ©ment ce profil temporel des cytokines. En clinique, avec nos cohortes originale et de validation, un modĂšle statistique basĂ©e sur une matrice de 103 mesures de VRCf (R2 = 0,90, P < 0,001) permettent de prĂ©dire le pH mais pas lâEB, avec une heure dâenregistrement du RCF avant la poussĂ©e.
Conclusions. La diminution de l'amplitude Ă l'EEG suggĂšre un mĂ©canisme d'arrĂȘt adaptatif neuroprotecteur du cerveau et suggĂšre que l'EEG fĆtal puisse ĂȘtre un complĂ©ment utile Ă la surveillance du RCF pendant le travail Ă haut risque chez la femme. La VRCf Ă©tant capable de dĂ©tecter une hypoxie-acidĂ©mie aggravante tĂŽt chez le fĆtus Ă 1000Hz vs 4 Hz Ă©voque quâun mode d'acquisition dâECG fĆtal plus sensible pourrait constituer une solution. Des profils distinctifs de mesures de la VRCf, identifiĂ©s en corrĂ©lation avec les niveaux de l'inflammation, ouvre une nouvelle voie pour caractĂ©riser le profil inflammatoire de la rĂ©ponse fĆtale Ă lâinfection. En clinique, un monitoring de chevet de prĂ©diction du pH et EB Ă la naissance, Ă partir de mesures de VRCf permettrait des interprĂ©tations visuelles plus explicites pour des prises de dĂ©cision plus exactes en obstĂ©trique au cours du travail.Introduction. In utero, the infection of maternal and fetal membranes, chorioamnionitis, goes frequently unnoticed and, especially when combined with acidemia due to occlusions of the umbilical cord as they occur during labour, can result in brain damage and long term neurological sequelae peri- and postnatally. Currently, there is no way to early detect these pathological conditions to prevent or limit lasting neurological deficits.
Hypotheses. (1) the fetal electroencephalogram (EEG), obtained from the scalp could serve as a useful ancillary tool to the existing fetal heart rate (FHR) monitoring for early detection of fetal acidemia and neurological injury; (2) the sampling rate of fetal ECG has a significant impact on the continuous FHR monitoring in the prediction of fetal acidemia; 3) patterns of FHR variability will reflect fetal baseline and inflammatory states; (4) FHR variability analysis should permit prediction of pH and base excess (BE) at birth.
Methods. In a series of studies using the chronically instrumented unanesthetized fetal sheep and clinical cohort, we modeled 1) worsening fetal acidemia with intermittent hypoxia resulting from umbilical cord occlusions (UCO) of increasing severity as experimental model of human labour to test the 1st and 2nd hypotheses; 2) moderate fetal inflammation by administering lipopolysaccharide (LPS) to test the 3rd hypothesis and 3) prediction of pH and BE status at birth using clinically validated FHR variability measures in a clinical cohort of laboring women to test the 4th hypothesis.
Results. Repetitive UCO resulted in marked acidosis (pH arterial 7.35±0.01 to 7.00±0.01), decreased EEG amplitudes synchronized with UCO-induced FHR decelerations and pathological arterial blood pressure decreases; in addition, we detected a significant increase in FHR variability with worsening acidemia when sampled at 1000 but not at 4 Hz, the sampling rate used clinically. LPS administration resulted in systemic fetal inflammation with IL-6 peaking at 3 h and FHR variability changes tracking this temporal cytokine profile precisely. In the clinical cohort, a statistical model based on a matrix of 103 FHR variability measures predicted pH (R2 = 0.90, P < 0.001), but not BE, from one hour of FHR recording prior to pushing stage.
Conclusions. The decrease in the EEG amplitude suggests an adaptive and neuroprotective brain shut-down; fetal EEG may complement the FHR monitoring during labour to improve early detection of incipient acidemia. FHR variability changes can detect early developing hypoxic-acidemia when sampled at 1000 Hz, but not when sampled at 4 Hz suggesting that a more sensitive mode of fetal ECG acquisition will improve early acidemia detection. Distinctive subsets of FHR variability measures permit online monitoring of fetal inflammation from ECG opening a new approach to characterizing the fetal inflammatory profile. Clinical bedside prediction of pH and BE monitoring at birth using FHR variability monitoring will allow more accurate decision making in obstetrics during labou
OSAS severity is associated to decreased heart rate turbulence slope
Obstructive sleep apnea syndrome (OSAS) has been associated to impaired baroreflex sensitivity (BRS) which has recently been shown to be non-invasively assessed by heart rate turbulence (HRT) analysis. Although HRT seems to be better suited than traditional heart rate variability indexes for autonomic assessment in presence of respiratory and arrhythmic disorders, very few papers addressed its evaluation in OSAS. Aim of the study is to find out whether and to which extend HRT is associated to OSAS severity. We studied HRT in polysomnographic recordings of 221 mild to severe OSAS pts. Results showed that, while HRT onset values did not significantly differ between mild (-0,78±1,50), moderate (-0,89±1,78) and severe (-0,70±1,28) pts., HRT slope significantly decreases (Kruskal-Wallis P value <0.05) from mild (3,27±2,7) to moderate (2,6±2,6) and severe (1,98±2,5) pts., with a significant Dunn's multiple comparisons post test only between mild vs. severe OSAS pts. Data indicate that the main BRS alterations do not appear in the early HRT phase triggered by transient vagal inhibition, but during the slow one, due to the sympathetic hyperactivity affecting the heart rate recovery. These findings support the conclusion that HRT assessment could have a prognostic value related to the development of cardiovascular disease in OSAS
Predictive Analysis of Healthcare-Associated Blood Stream Infections in the Neonatal Intensive Care Unit Using Artificial Intelligence: A Single Center Study
Background: Neonatal infections represent one of the six main types of healthcare-associated infections and have resulted in increasing mortality rates in recent years due to preterm births or problems arising from childbirth. Although advances in obstetrics and technologies have minimized the number of deaths related to birth, different challenges have emerged in identifying the main factors affecting mortality and morbidity. Dataset characterization: We investigated healthcare-associated infections in a cohort of 1203 patients at the level III Neonatal Intensive Care Unit (ICU) of the âFederico IIâ University Hospital in Naples from 2016 to 2020 (60 months). Methods: The present paper used statistical analyses and logistic regression to identify an association between healthcare-associated blood stream infection (HABSIs) and the available risk factors in neonates and prevent their spread. We designed a supervised approach to predict whether a patient suffered from HABSI using seven different artificial intelligence models. Results: We analyzed a cohort of 1203 patients and found that birthweight and central line catheterization days were the most important predictors of suffering from HABSI. Conclusions: Our statistical analyses showed that birthweight and central line catheterization days were significant predictors of suffering from HABSI. Patients suffering from HABSI had lower gestational age and birthweight, which led to longer hospitalization and umbilical and central line catheterization days than non-HABSI neonates. The predictive analysis achieved the highest Area Under Curve (AUC), accuracy and F1-macro score in the prediction of HABSIs using Logistic Regression (LR) and Multi-layer Perceptron (MLP) models, which better resolved the imbalanced dataset (65 infected and 1038 healthy)
Multiple regression model to analyze the total LOS for patients undergoing laparoscopic appendectomy
The rapid growth in the complexity of services and stringent quality requirements present a challenge to all healthcare facilities, especially from an economic perspective. The goal is to implement different strategies that allows to enhance and obtain health processes closer to standards. The Length Of Stay (LOS) is a very useful parameter for the management of services within the hospital and is an index evaluated for the management of costs. In fact, a patient's LOS can be affected by a number of factors, including their particular condition, medical history, or medical needs. To reduce and better manage the LOS it is necessary to be able to predict this value