Influence of anxiety on the heart rate variability of patients in preoperative orthopedic surgery

Authors

DOI:

https://doi.org/10.33448/rsd-v10i8.17237

Keywords:

Heart Rate Variability; Preoperative Orthopedic Surgery; Anxiety; Nonlinear analysis; Decision tree algorithm.

Abstract

Anxiety is a negative emotional response to situations that threaten the subject. Objective: The present study aims to verify the influence of anxiety on heart rate variability, considering two specific times: hospitalization and before surgery. In this analytical and cross-sectional study, the Hospital Anxiety and Depression Scale (HADS) was used to classify anxiety levels. Methodology: The time series of RR intervals were collected by Polar® monitor. Nonlinear methods and decision tree algorithm were combined with HADS scale to analyze the influence of the preoperative period on heart rate variability. The nonlinear methods used detrended fluctuation analysis (DFA), recurrence quantification analysis (RQA), and central tendency measure (CTM). Results: Among the 42 study participants, 13 (31%) were classified as anxious at hospital admission. The applied time domain methods found an increase in the heart rate variability (HRV) values in all features analyzed (p < 0.05). CTM method showed HRV reduction for the values considering radius between 6 and 20 milliseconds (p < 0.05). Conclusion: The anxiety identified at admission is directly related to the reduction in heart rate variability demonstrated by nonlinear methods, such as the central tendency measure.

References

Associação Brasileira para o Estudo da Obesidade e da Síndrome Metabólica. (2016). Diretrizes Brasileiras de Obesidade. https://abeso.org.br/wp-content/uploads/2019/12/Diretrizes-Download-Diretrizes-Brasileiras-de-Obesidade-2016.pdf

Albuquerque, A. L. M. de., Sousa Filho, P. G. T. de., Braga Junior, M. B., Cavalcante Neto, J. de S., Medeiros, B. B. L. de., & Lopes, M. B. G. (2012). Epidemiologia das fraturas em pacientes do interior do Ceará tratadas pelo SUS. Acta Ortopédica Brasileira, 20(2), 66–69. https://doi.org/10.1590/S1413-78522012000200001

Albuquerque, R. P., Hara, R., Prado, J., Schiavo, L., Giordano, V., & Amaral, N. P. do. (2013). Estudo epidemiológico das fraturas do planalto tibial em hospital de trauma nível I. Acta Ortopédica Brasileira. https://doi.org/10.1590/s1413-78522013000200008

Aubert, A. E., Seps, B., & Beckers, F. (2003). Heart Rate Variability in Athletes. In Sports Medicine. https://doi.org/10.2165/00007256-200333120-00003

Billman, G. E. (2009). Cardiac autonomic neural remodeling and susceptibility to sudden cardiac death: effect of endurance exercise training. American Journal of Physiology-Heart and Circulatory Physiology, 297(4), H1171–H1193. https://doi.org/10.1152/ajpheart.00534.2009

Brunetto, A. F., Silva, B. M., Roseguini, B. T., Hirai, D. M., & Guedes, D. P. (2005). Limiar ventilatório e variabilidade da freqüência cardíaca em adolescentes. Revista Brasileira de Medicina Do Esporte, 11(1), 22–27. https://doi.org/10.1590/S1517-86922005000100003

Cambri, L. T., Fronchetti, L., De-Oliveira, F. R., Gevaerd, M. S., & Oliveira, F. R. (2008). Variabilidade da frequência cardíaca e controlo metabólico. Arq Sanny Pesq Saúde. https://doi.org/10.1017/CBO9781107415324.004

Caumo, W., Schmidt, A. P., Schneider, C. N., Bergmann, J., Iwamoto, C. W., Adamatti, L. C., Bandeira, D., & Ferreira, M. B. C. (2001). Risk factors for postoperative anxiety in adults. Anaesthesia. https://doi.org/10.1046/j.1365-2044.2001.01842.x

Chalmers, J. A., Quintana, D. S., Abbott, M. J. A., & Kemp, A. H. (2014). Anxiety disorders are associated with reduced heart rate variability: A meta-analysis. Frontiers in Psychiatry. https://doi.org/10.3389/fpsyt.2014.00080

Christóforo, B. E. B., & Carvalho, D. S. (2009). Cuidados de enfermagem realizados ao paciente cirúrgico no período pré-operatório. Revista Da Escola de Enfermagem Da USP, 43(1), 14–22. https://doi.org/10.1590/S0080-62342009000100002

Cohen, M. E., Hudson, D. L., & Deedwania, P. Ć. (1996). Applying continuous chaotic modeling to cardiac signal analysis. In IEEE Engineering in Medicine and Biology Magazine. https://doi.org/10.1109/51.537065

DATASUS. (2019). DataSUS/TABNET. Ministério Da Saúde. Available in http://www2.datasus.gov.br/DATASUS.

De Castro, R. R. M., Ribeiro, N. F., De Andrade, A. M., & Jaques, B. D. (2013). Orthopedics nursing patients’ profile of a public hospital in Salvador-Bahia. Acta Ortopedica Brasileira. https://doi.org/10.1590/S1413-78522013000400001

Dos Santos, L., Barroso, J. J., De Godoy, M. F., Macau, E. E. N., & Freitas, U. S. (2014). Recurrence quantification analysis as a tool for discrimination among different dynamics classes: The heart rate variability associated to different age groups. Springer Proceedings in Mathematics and Statistics, 103. https://doi.org/10.1007/978-3-319-09531-8_8

Dos Santos, L., Barroso, J. J., Macau, E. E. N., & de Godoy, M. F. (2015). Assessment of heart rate variability by application of central tendency measure. Medical and Biological Engineering and Computing, 53(11). https://doi.org/10.1007/s11517-015-1390-8

Dos Santos, L., Barroso, J. J., Macau, E. E. N., & de Godoy, M. F. (2013). Application of an automatic adaptive filter for Heart Rate Variability analysis. Medical Engineering & Physics. https://doi.org/10.1016/j.medengphy.2013.07.009

Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. In Emotion. https://doi.org/10.1037/1528-3542.7.2.336

Härter, M. C., Conway, K. P., & Merikangas, K. R. (2003). Associations between anxiety disorders and physical illness. European Archives of Psychiatry and Clinical Neuroscience. https://doi.org/10.1007/s00406-003-0449-y

Hayashi, J. M., & Garanhani, M. L. (2012). Perioperatory care of the orthopaedic patient from the nursing team perspective. Revista Mineira de Enfermagem.

Homma, I., & Masaoka, Y. (2008). Breathing rhythms and emotions. In Experimental Physiology. https://doi.org/10.1113/expphysiol.2008.042424

Huikuri, H. V., Mäkikallio, T. H., & Perkiömäki, J. (2003). Measurement of Heart Rate Variability by Methods Based on Nonlinear Dynamics. Journal of Electrocardiology. https://doi.org/10.1016/j.jelectrocard.2003.09.021

Javorka, M., Trunkvalterova, Z., Tonhajzerova, I., Lazarova, Z., Javorkova, J., & Javorka, K. (2008). Recurrences in heart rate dynamics are changed in patients with diabetes mellitus. Clinical Physiology and Functional Imaging, 28(5), 326–331. https://doi.org/10.1111/j.1475-097X.2008.00813.x

Jeong, J., Gore, J. C., & Peterson, B. S. (2002). A method for determinism in short time series, and its application to stationary EEG. IEEE Transactions on Biomedical Engineering. https://doi.org/10.1109/TBME.2002.804581

Jorge, M. H. P. de M., Laurenti, R., Lima-Costa, M. F., Gotlieb, S. L. D., & Filho, A. D. P. C. (2008). A mortalidade de idosos no Brasil: a questão das causas mal definidas. Epidemiologia e Serviços de Saúde, 17(4). https://doi.org/10.5123/S1679-49742008000400004

Kamath, M. V., Watanabe, M. A., & Upton, A. R. M. (2016). Heart rate variability (HRV) signal analysis: Clinical applications. In Heart Rate Variability (HRV) Signal Analysis: Clinical Applications.

Kemp, A. H., Brunoni, A. R., Nunes, M. A., Santos, I. S., Goulart, A. C., Ribeiro, A. L., Bensenor, I. M., & Lotufo, P. A. (2015). The association between mood and anxiety disorders, and coronary heart disease in Brazil: a cross-sectional analysis on the Brazilian longitudinal study of adult health (ELSA-Brasil). Frontiers in Psychology, 6. https://doi.org/10.3389/fpsyg.2015.00187

Kemp, A. H., Quintana, D. S., Felmingham, K. L., Matthews, S., & Jelinek, H. F. (2012). Depression, comorbid anxiety disorders, and heart rate variability in physically healthy, unmedicated patients: Implications for cardiovascular risk. PLoS ONE. https://doi.org/10.1371/journal.pone.0030777

Kessler, R. C., Angermeyer, M., Anthony, J. C., DE Graaf, R., Demyttenaere, K., Gasquet, I., DE Girolamo, G., Gluzman, S., Gureje, O., Haro, J. M., Kawakami, N., Karam, A., Levinson, D., Medina Mora, M. E., Oakley Browne, M. A., Posada-Villa, J., Stein, D. J., Adley Tsang, C. H., Aguilar-Gaxiola, S., & Ustün, T. B. (2007). Lifetime prevalence and age-of-onset distributions of mental disorders in the World Health Organization’s World Mental Health Survey Initiative. World Psychiatry: Official Journal of the World Psychiatric Association (WPA).

Kfuri Junior, M. (2011). O trauma ortopédico no Brasil. Revista Brasileira de Ortopedia, 46, 0–0. https://doi.org/10.1590/S0102-36162011000700003

Lake, D. E., Richman, J. S., Griffin, M. P., & Moorman, J. R. (2002). Sample entropy analysis of neonatal heart rate variability. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology, 283(3), R789–R797. https://doi.org/10.1152/ajpregu.00069.2002

Lima, A. L. L. M., Zumiotti, A. V., Uip, D. E., & Silva, J. dos S. (2004). Fatores preditivos de infecção em pacientes com fraturas expostas nos membros inferiores. Acta Ortopédica Brasileira. https://doi.org/10.1590/s1413-78522004000100005

Maciel, T. V., Seus, V. D. R., Machado, K. D. S., & Borges, E. N. (2015). Mineração de dados em triagem de risco de saúde. Revista Brasileira de Computação Aplicada. https://doi.org/10.5335/rbca.2015.4651

Malpas, S. C. (2010). Sympathetic Nervous System Overactivity and Its Role in the Development of Cardiovascular Disease. Physiological Reviews, 90(2), 513–557. https://doi.org/10.1152/physrev.00007.2009

Marães, V. R. F. S. (2010). Heart rate and its variability: Analysis and applications. Heart Rate and Its Variability: Analysis and Applications.

Marcolino, J. A. M., Mathias, L. A. da S. T., Piccinini Filho, L., Guaratini, A. A., Suzuki, F. M., & Alli, L. A. C. (2007). Hospital Anxiety and Depression Scale: a study on the validation of the criteria and reliability on preoperative patients. Revista Brasileira de Anestesiologia. https://doi.org/10.1590/S0034-70942007000100006

Marwan, N., Carmen Romano, M., Thiel, M., & Kurths, J. (2007). Recurrence plots for the analysis of complex systems. In Physics Reports. https://doi.org/10.1016/j.physrep.2006.11.001

Marwan, N., Wessel, N., Meyerfeldt, U., Schirdewan, A., & Kurths, J. (2002). Recurrence-plot-based measures of complexity and their application to heart-rate-variability data. Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. https://doi.org/10.1103/PhysRevE.66.026702

Masetic, Z., & Subasi, A. (2016). Congestive heart failure detection using random forest classifier. Computer Methods and Programs in Biomedicine, 130, 54–64. https://doi.org/10.1016/j.cmpb.2016.03.020

Melillo, P., Bracale, M., & Pecchia, L. (2011). Nonlinear Heart Rate Variability features for real-life stress detection. Case study: Students under stress due to university examination. BioMedical Engineering Online. https://doi.org/10.1186/1475-925X-10-96

Melione, L. P. R., & De Mello-Jorge, M. H. P. (2008). Unified national health system costs in São José dos Campos, São Paulo State, Brazil, for hospital admissions due to external causes. Cadernos de Saude Publica. https://doi.org/10.1590/s0102-311x2008000800010

Melo, R. C., Santos, M. D. B., Silva, E., Quitério, R. J., Moreno, M. A., Reis, M. S., Verzola, I. A., Oliveira, L., Martins, L. E. B., Gallo-Junior, L., & Catai, A. M. (2005). Effects of age and physical activity on the autonomic control of heart rate in healthy men. Brazilian Journal of Medical and Biological Research, 38(9), 1331–1338. https://doi.org/10.1590/S0100-879X2005000900007

Millar, P. J., Rakobowchuk, M., Adams, M. M., Hicks, A. L., McCartney, N., & MacDonald, M. J. (2009). Effects of short-term training on heart rate dynamics in individuals with spinal cord injury. Autonomic Neuroscience, 150(1–2), 116–121. https://doi.org/10.1016/j.autneu.2009.03.012

Montano, N., Porta, A., Cogliati, C., Costantino, G., Tobaldini, E., Casali, K. R., & Iellamo, F. (2009). Heart rate variability explored in the frequency domain: A tool to investigate the link between heart and behavior. Neuroscience & Biobehavioral Reviews, 33(2), 71–80. https://doi.org/10.1016/j.neubiorev.2008.07.006

Noteboom, J. T., Barnholt, K. R., & Enoka, R. M. (2001). Activation of the arousal response and impairment of performance increase with anxiety and stressor intensity. Journal of Applied Physiology. https://doi.org/10.1152/jappl.2001.91.5.2093

Peng, C. ‐K., Havlin, S., Stanley, H. E., & Goldberger, A. L. (1995). Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos: An Interdisciplinary Journal of Nonlinear Science, 5(1), 82–87. https://doi.org/10.1063/1.166141

Pereira, B. R. R., Mendoza, I. Y. Q., Couto, B. R. G. M., Ercole, F. F., & Goveia, V. R. (2014). Artroplastia do quadril: prevenção de infecção do sítio cirúrgico. Revista Sobecc, 19(4), 181–187. https://doi.org/10.5327/Z1414-4425201400040002

Physical status: The use and interpretation of anthropometry. (1995). In World Health Organization - Technical Report Series. https://doi.org/10.1093/ajcn/64.5.830

Power, M., & Dalgleish, T. (2007). Cognition and Emotion. In Cognition and Emotion: From Order to Disorder: Second Edition. Psychology Press. https://doi.org/10.4324/9780203934487

Rajendra, A. U., Paul Joseph, K., Kannathal, N., Lim, C. M., & Suri, J. S. (2006). Heart rate variability: a review. Medical & Biological Engineering & Computing, 44(12), 1031–1051. https://doi.org/10.1007/s11517-006-0119-0

Roest, A. M., Martens, E. J., de Jonge, P., & Denollet, J. (2010). Anxiety and Risk of Incident Coronary Heart Disease. A Meta-Analysis. Journal of the American College of Cardiology. https://doi.org/10.1016/j.jacc.2010.03.034

Safavian, S. R., & Landgrebe, D. (1991). A survey of decision tree classifier methodology. IEEE Transactions on Systems, Man, and Cybernetics, 21(3), 660–674. https://doi.org/10.1109/21.97458

Sakaki, M. H., Matsumura, B. A. R., Dotta, T. D. A. G., Pontin, P. A., Santos, A. L. G. dos, & Fernandes, T. D. (2014). Epidemiologic study of ankle fractures in a tertiary hospital. Acta Ortopédica Brasileira, 22(2), 90–93. https://doi.org/10.1590/1413-78522014220200874

Sakakibara, M. (2018). Clinical application of heart rate variability. The Proceedings of the Annual Convention of the Japanese Psychological Association. https://doi.org/10.4992/pacjpa.82.0_tws-011

Shibeshi, W. A., Young-Xu, Y., & Blatt, C. M. (2007). Anxiety Worsens Prognosis in Patients With Coronary Artery Disease. Journal of the American College of Cardiology. https://doi.org/10.1016/j.jacc.2007.03.007

Tarvainen, M. P., Niskanen, J. P., Lipponen, J. A., Ranta-aho, P. O., & Karjalainen, P. A. (2014). Kubios HRV - Heart rate variability analysis software. Computer Methods and Programs in Biomedicine. https://doi.org/10.1016/j.cmpb.2013.07.024

Task Force of the ESC-NASPE. (1996). Heart Rate Variability: Standards of Measurement, Physiological Interpretation, and Clinical Use. Circulation. https://doi.org/10.1161/01.CIR.93.5.1043

Tulppo, M. P., Hughson, R. L., Mäkikallio, T. H., Airaksinen, K. E. J., Seppänen, T., & Huikuri, H. V. (2001). Effects of exercise and passive head-up tilt on fractal and complexity properties of heart rate dynamics. American Journal of Physiology-Heart and Circulatory Physiology, 280(3), H1081–H1087. https://doi.org/10.1152/ajpheart.2001.280.3.H1081

Tulppo, M. P., Kiviniemi, A. M., Hautala, A. J., Kallio, M., Seppänen, T., Mäkikallio, T. H., & Heikki, H. V. (2005). Physiological background of the loss of fractal heart rate dynamics. Circulation. https://doi.org/10.1161/CIRCULATIONAHA.104.523712

Vanderlei, L. C. M., Pastre, C. M., Júnior, I. F. F., & de Godoy, M. F. (2010). Fractal correlation of heart rate variability in obese children. Autonomic Neuroscience, 155(1–2), 125–129. https://doi.org/10.1016/j.autneu.2010.02.002

Vanderlei, L. C. M., Silva, R. A., Pastre, C. M., Azevedo, F. M., & Godoy, M. F. (2008). Comparison of the Polar S810i monitor and the ECG for the analysis of heart rate variability in the time and frequency domains. Brazilian Journal of Medical and Biological Research, 41(10), 854–859. https://doi.org/10.1590/S0100-879X2008005000039

Vargas, T. V. P., Maia, E. M., & Dantas, R. A. S. (2006). Patient feelings during the preoperative period for cardiac surgery. Revista Latino-Americana de Enfermagem, 14(3), 383–388. https://doi.org/10.1590/S0104-11692006000300012

Webber, C. L., & Zbilut, J. P. (1994). Dynamical assessment of physiological systems and states using recurrence plot strategies. Journal of Applied Physiology, 76(2), 965–973. https://doi.org/10.1152/jappl.1994.76.2.965

Wessel, N., Marwan, N., Meyerfeldt, U., Schirdewan, A., & Kurths, J. (2001). Recurrence quantification analysis to characterise the heart rate variability before the onset of ventricular tachycardia. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). https://doi.org/10.1007/3-540-45497-7_45

Wijngaarden, M. A., Pijl, H., van Dijk, K. W., Klaassen, E. S., & Burggraaf, J. (2013). Obesity is associated with an altered autonomic nervous system response to nutrient restriction. Clinical Endocrinology, n/a-n/a. https://doi.org/10.1111/cen.12100

Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2011). Data Mining: Practical Machine Learning Tools and Techniques. In Data Mining: Practical Machine Learning Tools and Techniques. Elsevier. https://doi.org/10.1016/C2009-0-19715-5

Yeh, R. G., Chen, G. Y., Shieh, J. S., & Kuo, C. D. (2010). Parameter investigation of detrended fluctuation analysis for short-term human heart rate variability. Journal of Medical and Biological Engineering. https://doi.org/10.5405/jmbe.30.5.02

Zbilut, J. P., & Webber, C. L. (1992). Embeddings and delays as derived from quantification of recurrence plots. Physics Letters A, 171(3–4), 199–203. https://doi.org/10.1016/0375-9601(92)90426-M

Zigmond, A. S., & Snaith, R. P. (1983). The Hospital Anxiety and Depression Scale. Acta Psychiatrica Scandinavica. https://doi.org/10.1111/j.1600-0447.1983.tb09716.x

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09/07/2021

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CORREA, F. V.; MENESES, A. M. D.; CARVALHO, S. P.; MENDES, A. P.; SANTOS, L. dos . Influence of anxiety on the heart rate variability of patients in preoperative orthopedic surgery. Research, Society and Development, [S. l.], v. 10, n. 8, p. e14410817237, 2021. DOI: 10.33448/rsd-v10i8.17237. Disponível em: https://www.rsdjournal.org/index.php/rsd/article/view/17237. Acesso em: 28 apr. 2024.

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Health Sciences