Variability analysis of discrete event series and wavefront patterns in surface electrocardiogram: contributions to psychophysiological and clinical research

The surface electrocardiogram (ECG) is an established diagnostic tool for the detection of abnormalities in the electrical activity of the heart. The interest of the ECG, however, extends beyond the diagnostic purpose. In recent years, studies in cognitive psychophysiology have related heart rate variability (HRV) to memory performance and mental workload. The aim of this thesis was to analyze the variability of surface ECG derived rhythms, at two different time scales: the discrete-event time scale, typical of beat-related features (Objective I), and the “continuous” time scale of separated sources in the ECG (Objective II), in selected scenarios relevant to psychophysiological and clinical research, respectively. Objective I) Joint time-frequency and non-linear analysis of HRV was carried out, with the goal of assessing psychophysiological workload (PPW) in response to working memory engaging tasks. Results from fourteen healthy young subjects suggest the potential use of the proposed indices in discriminating PPW levels in response to varying memory-search task difficulty. Objective II) A novel source-cancellation method based on morphology clustering was proposed for the estimation of the atrial wavefront in atrial fibrillation (AF) from body surface potential maps. Strong direct correlation between spectral concentration (SC) of atrial wavefront and temporal variability of the spectral distribution was shown in persistent AF patients, suggesting that with higher SC, shorter observation time is required to collect spectral distribution, from which the fibrillatory rate is estimated. This could be time and cost effective in clinical decision-making. The results held for reduced leads sets, suggesting that a simplified setup could also be considered, further reducing the costs. In designing the methods of this thesis, an online signal processing approach was kept, with the goal of contributing to real-world applicability. An algorithm for automatic assessment of ambulatory ECG quality, and an automatic ECG delineation algorithm were designed and validated.

Apnea e reflusso gastroesofageo nel neonato pretermine

Objective: To document the existence of a relationship between apnea of prematurity (AOP) and gastroesophageal reflux (GER) in preterm infants. Setting: One Neonatal Intensive Care Unit Patients: Twenty-six preterm infants (gestational age<32 weeks) with recurrent apneas. Intervention: Simultaneous and synchronized recording of polysomnography and pH-impedance monitoring (pH-MII). Polysomnography detects and characterizes apneas, by recording of breathing movement, nasal airflow, electrocardiogram, pulse oximeter saturation. pH-MII is the state-of-theart methodology for GER detection in preterm newborns. Main outcome measures: Relationship between AOP and GER, which were considered temporally related if both started within 30 seconds of each other. Results: One-hundred-fifty-four apneas out of 1136 were temporally related to GER. The frequency of apnea during the one-minute time around the onset of GER was significantly higher than the one detected in the GER-free period (p=0.03). Furthermore, the frequency of apnea in the 30 seconds after GER (GER-triggered apneas) was greater than that detected in the 30 seconds before (p=0.01). A great inter-individual variability was documented in the proportion of GERtriggered apneas. A strong correlation between total number of apneas and the difference between apneas detected 30 seconds after and before GER was found (p=0.034). Conclusions: Our data show that a variable rate of apneas can be triggered by GER in very preterm infant. Further studies are needed to recognise clinical features which identify those patients who are more susceptible to GER-triggered apneas.

Ruolo dell'elettrocardiogramma standard nella stratificazione prognostica della cardiomiopatia ipertrofica. Studio multicentrico

Lo scopo di questo studio è di valutare il significato prognostico dell'elettrocardiogramma standard in un'ampia casistica di pazienti affetti da cardiomiopatia ipertrofica. In questo studio multicentrico sono stati considerati 841 pazienti con cardiomiopatia ipertrofica (66% uomini, età media 48±17 anni) per un follow-up di 7.1±7.1 anni, per ognuno è stato analizzato il primo elettrocardiogramma disponibile. I risultati hanno dimostrato come fattori indipendentemente correlati a morte cardiaca improvvisa la sincope inspiegata (p 0.004), il sopraslivellamento del tratto ST e/o la presenza di onde T positive giganti (p 0.048), la durata del QRS >= 120 ms (p 0.017). Sono stati costruiti due modelli per predire il rischio di morte improvvisa: il primo basato sui fattori di rischio universalmente riconosciuti (spessore parietale >= 30 mm, tachicardie ventricolari non sostenute all'ECG Holter 24 ore, sincope e storia familiare di morte improvvisa) e il secondo con l'aggiunta delle variabili sopraslivellamento del tratto ST/onde T positive giganti e durata del QRS >= 120 ms. Entrambi i modelli stratificano i pazienti in base al numero dei fattori di rischio, ma il secondo modello risulta avere un valore predittivo maggiore (chi-square da 12 a 22, p 0.002). In conclusione nella cardiomiopatia ipertrofica l'elettrocardiogramma standard risulta avere un valore prognostico e migliora l'attuale modello di stratificazione per il rischio di morte improvvisa.