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INTRODUCTION: Recurrence plots have been increasingly used to evaluate complex dynamic systems of which the human body is an excellent model. The different quantitative and qualitative elements of recurrence plots in health, disease, and death were analysed. A time series of normal heartbeats were collected in healthy newborns, healthy children, healthy young adults, healthy middle-aged adults, elderly individuals living in nursing homes, individuals with advanced chronic kidney disease, and individuals with declared brain death or in a state of imminent death. Healthy young adults showed the best homeostasis (lower recurrence). Healthy newborns and individuals with declared brain death or in a state of imminent death had higher recurrence values. At the qualitative visual level, healthy young adults showed a more diffuse and uniform distribution, indicative of better homeostasis; for individuals with declared brain death or in a state of imminent death this was totally linear - the worst condition. A parabolic pattern was clearly evidenced. In conclusion, it was possible, using the correlation of only two variables (SDNN and TT), to easily differentiate states of health, disease, and death using recurrence plots
Gráficos de recorrência (GR) têm sido utilizados para avaliar sistemas dinâmicos complexos, sendo o corpo humano um excelente modelo. Foram analisados os elementos quantitativos e qualitativos do GR na diferenciação de Saúde, Doença e Morte. Séries temporais de batimentos cardíacos normais foram coletadas em recém-nascidos saudáveis (Grupo A1), crianças saudáveis (Grupo A2), adultos jovens saudáveis (Grupo A3), adultos saudáveis de meia-idade (Grupo A4), idosos residentes em casas de repouso (Grupo B ), indivíduos com doença renal crônica avançada (Grupo C) e indivíduos com morte encefálica declarada ou em estado de morte iminente (Grupo D). O grupo A3 apresentou a melhor homeostase (menor recorrência). Os grupos A1 e D apresentaram os maiores valores de recorrência. Em termos visuais qualitativos, o Grupo A3 apresentou distribuição mais difusa e uniforme, um indicativo de melhor homeostase e o Grupo D foi totalmente linear, a pior condição. Um padrão parabólico foi claramente evidenciado. Em conclusão, foi possível, utilizando a correlação de apenas duas variáveis (SDNN e TT), diferenciar tanto de modo quantitativo como qualitativo os estados de Saúde, Doença e Morte usando GR.
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Abstract Introduction The temporal behavior of atrial electrograms (AEGs) collected during persistent atrial fibrillation (persAF) directly affects ablative treatment outcomes. We investigated different durations of AEGs collected during persAF using recurrence quantification analysis (RQA). Methods 797 bipolar AEGs with different durations (from 0.5 s to 8 s) from 18 patients were investigated. Four RQA-based attributes were evaluated based on AEG durations: determinism (DET); recurrence rate (RR); laminarity (LAM); and diagonal lines' entropy (ENTR). The Spearman correlation (ρ) between each duration versus 8 s was calculated. AEG classification was performed following the CARTO criteria (Biosense Webster) and receiving operating characteristic (ROC) curves were created for the RQA variables. Results The RQA variables successfully discriminated the AEGs: the area under the ROC curves were as high as 0.70 for AEGs with 3.5 s or greater. Three types of AEGs were found using these variables: normal, fractionated and temporally unstable. The number of unstable AEGs decreased with longer AEG segments. Different AEG durations significantly affected the RQA variables (P<0.0001), with no statistical difference between the durations 6 s, 7 s and 8 s for DET, LAM and ENTR, and no difference between 7 s and 8 s for RR (P<0.0001). AEGs with 3 s or longer have shown ρ ≥ 80% for all variables. Conclusion The RQA variables have been shown effective in the characterization of AEGs collected during persAF with a shorter duration than current recommendations, which motivates their use for the characterization of atrial substrate during persAF ablation.