Linear and nonlinear analyses of heart rate variability following orthostatism in subclinical hypothyroidism

Hoshi, Rosângela Akemi; Andreão, Rodrigo Varejão; Santos, Itamar S; Dantas, Eduardo Miranda; Mill, José Geraldo; Lotufo, Paulo A

doi:10.1097/md.0000000000014140

Cited by 15 publications

(25 citation statements)

References 52 publications

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“…35 In another investigation from our research group, we detected impaired autonomic regulation in SCH at rest and following orthostatic manoeuver, but using nonlinear HRV analysis. 14 Galetta et al 13 and Sahin et al 12 found an association between low global variability (SDNN) and TSH levels in SCH patients compared with controls. However, in the referred studies, the mean TSH levels were much higher than those observed in our sample.…”

Section: Discussionmentioning

confidence: 97%

“…Separately, DM and SCH associate with impaired cardiac autonomic modulation and electrophysiological changes 7‐13 . Our previous studies detected lower heart rate variability (HRV) as a predictor for diabetes development and blunted sympathetic autonomic responses to active postural change in SCH patients compared with euthyroid subjects 14,15 …”

Section: Introductionmentioning

confidence: 97%

“…[7][8][9][10][11][12][13] Our previous studies detected lower heart rate variability (HRV) as a predictor for diabetes development and blunted sympathetic autonomic responses to active postural change in SCH patients compared with euthyroid subjects. 14,15 The isolated effects of DM and SCH on cardiovascular outcomes and reduced cardio autonomic modulation are wellknown separately. Although they are commonly claimed as coexistent, the significance of this apparent association has not been fully settled.…”

Section: Introductionmentioning

confidence: 99%

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Diabetes and subclinical hypothyroidism on heart rate variability

Hoshi

Santos

Dantas

et al. 2020

Eur J Clin Investigation

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Background: We aimed to analyse if the effects of coexistent diabetes and subclinical hypothyroidism extend to the cardio autonomic nervous system, using heart rate variability baseline data from the Brazilian Longitudinal Study of Adult Health. Materials and Methods: Heart rate variability analyses were performed by linear time and frequency domains in 5-minute time series collected in the supine position. The associations of diabetes and subclinical hypothyroidism with the lowest quartile group for heart rate and the highest quartile group for each heart rate variability parameter were analysed using additive and multiplicative terms in logistic models. For the first approach, the subsample was categorized into four groups: subjects without diabetes and normal thyroid function (controls); subjects without diabetes and subclinical hypothyroidism; patients with diabetes and normal thyroid function; and patients with diabetes and subclinical hypothyroidism. For the interaction alnalysis, diabetes and subclinical hypothyroidism diagnoses were included in separate, along with a multiplicative interaction term between them. Results: Point odds ratio estimates for the 4th quartiles of heart rate, and 1st quartiles of all heart rate variability measurements were higher for subjects with combined diabetes and subclinical hypothyroidism than for diabetes only, independently of main sociodemographic and clinical variables (HR: 8.33 vs 2.63; SDNN: 2.59 vs 1.61; RMSSD: 2.37 vs 1.42; LF: 2.83 vs 1.71; HF: 3.06 vs 1.39), but not independently of HbA1c and TSH. Only the interaction term for the association with heart rate, adjusted for sociodemographic and clinical variables, had borderline statistical significance. Conclusion: Diabetes and subclinical hypothyroidism exert a potential joint impact on cardiac autonomic control, showed by additive effects between diabetes and subclinical hypothyroidism, as well as a significant interaction term for the association with heart rate.

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Section: Discussionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

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Diabetes and subclinical hypothyroidism on heart rate variability

Hoshi

Santos

Dantas

et al. 2020

Eur J Clin Investigation

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“…An increase of HRV has been recognized as one of the important physiological indicators of positive therapeutic effects of slow breathing techniques on the cardiovascular system (Bruton and Lewith, 2005;Dick et al, 2014;Russo et al, 2017) and the physiological indicator of cardiovagal function (Shields, 2009). Also, the research on the orthostasis effect on HRV has been well-documented (De Souza et al, 2014;Zaidi and Collins, 2016;Valente et al, 2018) and is routinely used as a sensitive test for the evaluation of "physiological adaptive mechanisms" generated by the autonomic nervous system (head up tilt, Zygmunt and Stanczyk, 2010;Hoshi et al, 2019). Most of the studies that evaluate HRV in these physiological conditions (supine position, standing, supine position with 0.1 Hz breathing and standing with 0.1 Hz) focused on linear properties of HRV (Kabir et al, 2011;de Paula Vidigal et al, 2016;Javorka et al, 2018;Jha et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Slow 0.1 Hz Breathing and Body Posture Induced Perturbations of RRI and Respiratory Signal Complexity and Cardiorespiratory Coupling

et al. 2020

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Objective: We explored the physiological background of the non-linear operating mode of cardiorespiratory oscillators as the fundamental question of cardiorespiratory homeodynamics and as a prerequisite for the understanding of neurocardiovascular diseases. We investigated 20 healthy human subjects for changes using electrocardiac RR interval (RRI) and respiratory signal (Resp) Detrended Fluctuation Analysis (DFA, α 1RRI , α 2RRI , α 1Resp , α 2Resp), Multiple Scaling Entropy (MSE RRI1−4 , MSE RRI5−10 , MSE Resp1−4 , MSE Resp5−10), spectral coherence (Coh RRI−Resp), cross DFA (ρ 1 and ρ 2) and cross MSE (X MSE1−4 and X MSE5−10) indices in four physiological conditions: supine with spontaneous breathing, standing with spontaneous breathing, supine with 0.1 Hz breathing and standing with 0.1 Hz breathing. Main results: Standing is primarily characterized by the change of RRI parameters, insensitivity to change with respiratory parameters, decrease of Coh RRI−Resp and insensitivity to change of in ρ 1 , ρ 2 , X MSE1−4 , and X MSE5−10. Slow breathing in supine position was characterized by the change of the linear and non-linear parameters of both signals, reflecting the dominant vagal RRI modulation and the impact of slow 0.1 Hz breathing on Resp parameters. Coh RRI−Resp did not change with respect to supine position, while ρ 1 increased. Slow breathing in standing reflected the qualitatively specific state of autonomic regulation with striking impact on both cardiac and respiratory parameters, with specific patterns of cardiorespiratory coupling. Significance: Our results show that cardiac and respiratory short term and long term complexity parameters have different, state dependent patterns. Sympathovagal non-linear interactions are dependent on the pattern of their activation, having different scaling properties when individually activated with respect to the state of their joint activation. All investigated states induced a change of α 1 vs. α 2 relationship, which can be accurately expressed by the proposed measure-inter-fractal angle θ. Short scale (α 1 vs. MSE 1−4) and long scale (α 2 vs. MSE 5−10) complexity measures had reciprocal interrelation in standing with 0.1 Hz breathing, with specific cardiorespiratory coupling pattern (ρ 1 vs. X MSE1−4). These results support the hypothesis of hierarchical organization Matić et al. RRI-Respiratory Complexity and Cardiorespiratory Coupling of cardiorespiratory complexity mechanisms and their recruitment in ascendant manner with respect to the increase of behavioral challenge complexity. Specific and comprehensive cardiorespiratory regulation in standing with 0.1 Hz breathing suggests this state as the potentially most beneficial maneuver for cardiorespiratory conditioning.

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“…Logo, é lícita a reflexão que os estressores contemporâneos apresentem a capacidade de estimular reações neuroendócrinas, que, em última instância, podem contribuir para o surgimento de fenótipos ansiosos e/ou depressivos. Alterações emocionais podem, deste modo, provocar respostas autonômicas, e dentre elas está o estudo da modulação autonômica cardíaca, em que os dados oriundos dos batimentos cardíacos consecutivos podem ser analisados por meio de modelos lineares e/ou não lineares (Byun et al, 2019;Hoshi et al, 2019).…”

Section: Controle Cardiovascular Pelo Sistema Nervoso Autônomounclassified

Ansiedade, Depressão E Análise Não Linear Da Variabilidade Da Frequência Cardíaca Em Ingressantes No Ensino Superior

et al. 2020

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The non-linear analysis of the heart rate variability (HRV) is a potential correlation tool between physiological and emotional states. The aim of this study was correlate changes in non-linear parameters of the HRV with anxiety and depression indices in higher education entrants from Federal University of Goiás (UFG). To record HRV, the Polar Frequency Metermodel Polar® RS800cx (Electro Oi, Finland) was used. To analyze the levels of depression, the Beck Depression Inventory-I (BDI) was used, and for analysis of anxiety, the Inventories of State and Trace (IDATE T and E). Altogether, 50 (19.4±2.48 years) volunteers participated in the study. The scores of the depression and anxiety inventories indicated that the public had low and moderate indices of both conditions, respectively. Statistically significant correlations were found between the SD2 parameter (from the Poincaré plot in the HRV analysis), entropy data (ApEn and SampEn) and fractal property (DFA: α1) and trait and state anxiety levels. Although ApEn e SampEn still do not have well-defined physiological correspondences, DFA: α1 has been associated with parasympathetic modulation of heart rate. Therefore, it is concluded that chronic negative emotional states, such as anxiety and humor disorders, can be accompanied by parasympathetic increase in HRV, so the organism would be able to not wear out against long-term stressors. New studies are necessary to understand the physiological and evolutional bases of depression and anxiety.

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Linear and nonlinear analyses of heart rate variability following orthostatism in subclinical hypothyroidism

Abstract: Supplemental Digital Content is available in the text

Cited by 15 publications

References 52 publications

Diabetes and subclinical hypothyroidism on heart rate variability

Diabetes and subclinical hypothyroidism on heart rate variability

Slow 0.1 Hz Breathing and Body Posture Induced Perturbations of RRI and Respiratory Signal Complexity and Cardiorespiratory Coupling

Ansiedade, Depressão E Análise Não Linear Da Variabilidade Da Frequência Cardíaca Em Ingressantes No Ensino Superior

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