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Predicting depressed patients with suicidal ideation from ECG recordings

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Abstract

Globally suicidal behavior is the third most common cause of death among patients with major depressive disorder (MDD). This study presents multi-lag tone–entropy (T–E) analysis of heart rate variability (HRV) as a screening tool for identifying MDD patients with suicidal ideation. Sixty-one ECG recordings (10 min) were acquired and analyzed from control subjects (29 CONT), 16 MDD subjects with (MDDSI+) and 16 without suicidal ideation (MDDSI−). After ECG preprocessing, tone and entropy values were calculated for multiple lags (m: 1–10). The MDDSI+ group was found to have a higher mean tone value compared to that of the MDDSI− group for lags 1–8, whereas the mean entropy value was lower in MDDSI+ than that in CONT group at all lags (1–10). Leave-one-out cross-validation tests, using a classification and regression tree (CART), obtained 94.83 % accuracy in predicting MDDSI+ subjects by using a combination of tone and entropy values at all lags and including demographic factors (age, BMI and waist circumference) compared to results with time and frequency domain HRV analysis. The results of this pilot study demonstrate the usefulness of multi-lag T–E analysis in identifying MDD patients with suicidal ideation and highlight the change in autonomic nervous system modulation of the heart rate associated with depression and suicidal ideation.

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References

  1. Beck AT, Steer RA, Ranieri WF (1988) Scale for suicide ideation: psychometric properties of a self-report version. J Clin Psychology 44(4):499–505

    Article  CAS  Google Scholar 

  2. Berk M, Kapczinski F, Andreazza AC, Dean OM, Giorlando F, Maes M, Yücel M, Gama CS, Dodd S, Dean B, Magalhães PVS, Amminger P, Mcgorry P, Malhi GS (2011) Pathways underlying neuroprogression in bipolar disorder: focus on inflammation, oxidative stress and neurotrophic factors. Neurosci Biobehav Rev 35:804–817

    Article  CAS  PubMed  Google Scholar 

  3. Booij L, Swenne CA, Brosschot JF, Haffmans PJ, Thayer JF, Van der Does AW (2006) Tryptophan depletion affects heart rate variability and impulsivity in remitted depressed patients with a history of suicidal ideation. Biol Psychiatry 60(5):507–514

    Article  CAS  PubMed  Google Scholar 

  4. Bootsma MARIANNE, Swenne CA, Van Bolhuis HH, Chang PC, Cats VM, Bruschke AV (1994) Heart rate and heart rate variability as indexes of sympathovagal balance. Am J Physiol Heart Circ Physiol 266(4):H1565–H1571

    CAS  Google Scholar 

  5. Breiman L, Friedman J, Stone CJ, Olshen RA (1984) Classification and regression trees. CRC Press, New York

    Google Scholar 

  6. Bush DE, Ziegelstein RC, Tayback M, Richter D, Stevens S, Zahalsky H, Fauerbach JA (2001) Even minimal symptoms of depression increase mortality risk after acute myocardial infarction. Am J Cardiol 88(4):337–341

    Article  CAS  PubMed  Google Scholar 

  7. Butler IJ, Lankford JE, Hashmi SS, Numan MT (2014) Biogenic amine metabolism in juvenile neurocardiogenic syncope with dysautonomia. Ann Clin Transl Neurol 1(4):251–257

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Camm AJ, Malik M, Bigger JT, Günter B, Cerutti S, Choen R (1996) Task force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation 93(5):1043–1065

    Article  Google Scholar 

  9. Carney RM, Freedland KE (2009) Depression and heart rate variability in patients with coronary artery disease. Clevel Clin J Med 76(2):S13–S17

    Article  Google Scholar 

  10. Cavalcanti S, Belardinelli E (1996) Modeling of cardiovascular variability using a differential delay equation. IEEE Trans Biomed Eng 43(10):982–989

    Article  CAS  PubMed  Google Scholar 

  11. Chang HA, Chang CC, Chen CL, Kuo TB, Lu RB, Huang SY (2012) Major depression is associated with cardiac autonomic dysregulation. Acta Neuropsychiatr 24(6):318–327

    Article  PubMed  Google Scholar 

  12. Chowdhury N (2016) Integration between mental health-care providers and traditional spiritual healers: contextualising Islam in the twenty-first century. J Relig Health. doi:10.1007/s10943-016-0234-7

    PubMed  Google Scholar 

  13. Claudia L, Oscar I, Héctor PG, Marco VJ (2003) Poincaré plot indexes of heart rate variability capture dynamic adaptations after haemodialysis in chronic renal failure patients. Clin Physiol Funct Imaging 23(2):72–80

    Article  Google Scholar 

  14. Coryell W, Schlesser M (2001) The dexamethasone suppression test and suicide prediction. Am J Psychiatry 158:748–753

    Article  CAS  PubMed  Google Scholar 

  15. Denollet J, Brutsaert DL (1998) Personality, disease severity, and the risk of long-term cardiac events in patients with a decreased ejection fraction after myocardial infarction. Circulation 97(2):167–173

    Article  CAS  PubMed  Google Scholar 

  16. Depression looms as global crisis (2009) http://news.bbc.co.uk/2/hi/health/8230549.stm

  17. Ernst C, Mechawar N, Turecki G (2009) Suicide neurobiology. Prog Neurobiol 89(4):315–333

    Article  CAS  PubMed  Google Scholar 

  18. Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G et al (2013) Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010. PLoS Med 10(11):e1001547. doi:10.1371/journal.pmed.1001547

    Article  PubMed  PubMed Central  Google Scholar 

  19. Flynn AC, Jelinek HF, Smith M (2005) Heart rate variability analysis: a useful assessment tool for diabetes associated cardiac dysfunction in rural and remote areas. Aust J Rural Health 13(2):77–82

    Article  PubMed  Google Scholar 

  20. Frasure-Smith N, Lespérance F, Juneau M, Talajic M, Bourassa MG (1999) Gender, depression, and one-year prognosis after myocardial infarction. Psychosom Med 61(1):26–37

    Article  CAS  PubMed  Google Scholar 

  21. Frasure-Smith N, Lespérance F, Gravel G, Masson A, Juneau M, Talajic M, Bourassa MG (2000) Social support, depression, and mortality during the first year after myocardial infarction. Circulation 101(16):1919–1924

    Article  CAS  PubMed  Google Scholar 

  22. Friedman RA, Leon AC (2007) Expanding the black box—depression, antidepressants, and the risk of suicide. N Engl J Med 356:2343–2346

    Article  CAS  PubMed  Google Scholar 

  23. Goldberger AL, Amaral LA, Hausdorff JM, Ivanov PC, Peng CK, Stanley HE (2002) Fractal dynamics in physiology: alterations with disease and aging. Proc Natl Acad Sci 99(suppl 1):2466–2472

    Article  PubMed  PubMed Central  Google Scholar 

  24. Hanley JA, McNeil BJ (1983) A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 148(3):839–843

    Article  CAS  PubMed  Google Scholar 

  25. Jokinen J, Nordstrom AL, Nordstrom P (2008) ROC analysis of dexamethasone suppression test threshold in suicide prediction after attempted suicide. J Affect Disorders 106:145–152

    Article  CAS  PubMed  Google Scholar 

  26. Jokinen J, Nordstrom AL, Nordstrom P (2009) CSF 5-HIAA and DST non-suppression orthogonal biologic risk factors for suicide in male mood disorder inpatients. Psychiatry Res 165:96–102

    Article  CAS  PubMed  Google Scholar 

  27. Karmakar CK, Khandoker AH, Jelinek HF, Palaniswami M (2013) Risk stratification of cardiac autonomic neuropathy based on multi-lag tone-entropy. Med Biol Eng Comput 51(5):537–546

    Article  CAS  PubMed  Google Scholar 

  28. Kemp AH, Quintana DS, Felmingham KL, Matthews S, Jelinek HF (2012) Depression, comorbid anxiety disorders, and heart rate variability in physically healthy, unmedicated patients: implications for cardiovascular risk. PLoS ONE 7(2):e30777

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Khandoker AH, Jelinek HF, Moritani T, Palaniswami M (2010) Association of cardiac autonomic neuropathy with alteration of sympatho-vagal balance through heart rate variability analysis. Med Eng Phys 32(2):161–167

    Article  PubMed  Google Scholar 

  30. Kop WJ, Stein PK, Tracy RP, Barzilay JI, Schulz R, Gottdiener JS (2010) Autonomic nervous system dysfunction and inflammation contribute to the increased cardiovascular mortality risk associated with depression. Psychosom Med 72(7):626–635

    Article  PubMed  PubMed Central  Google Scholar 

  31. Kroenke K, Spitzer R, Williams W (2001) The PHQ-9: validity of a brief depression severity measure. JGIM 16:606–616

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Lerma C, Infante O, Perez-Grovas H, Jose MV (2003) Poincaré plot indexes of heart rate variability capture dynamic adaptations after haemodialysis in chronic renal failure patients. Clin Physiol Funct Imaging 23(2):72–80

    Article  PubMed  Google Scholar 

  33. Lespérance F, Frasure-Smith N, Talajic M, Bourassa MG (2002) Five-year risk of cardiac mortality in relation to initial severity and one-year changes in depression symptoms after myocardial infarction. Circulation 105(9):1049–1053

    Article  PubMed  Google Scholar 

  34. Licht CMM, De Geus EJC, Zitman FG, Hoogendijk WJG, Van Dyck R, Penninx BWJH (2008) Association between major depressive disorder and heart rate variability in the Netherlands study of depression and anxiety (NESDA). Arch Gen Psychiatry 65:1358–1367

    Article  PubMed  Google Scholar 

  35. Malpas SC (2002) Neural influences on cardiovascular variability: possibilities and pitfalls. Am J Physiol Heart Circ Physiol 282(1):H6–H20

    CAS  PubMed  Google Scholar 

  36. Nemeroff CB, Musselman DL, Evans DL (1998) Depression and cardiac disease. Depress Anxiety 8(1):71–79

    Article  Google Scholar 

  37. Oida E, Moritani T, Yamori Y (1997) Tone-entropy analysis on cardiac recovery after dynamic exercise. J Appl Physiol 82(6):1794–1801

    CAS  PubMed  Google Scholar 

  38. Oida E, Kannagi T, Moritani T, Yamori Y (1999) Aging alteration of cardiac vagosympathetic balance assessed through the tone-entropy analysis. J Gerontol Ser A: Biol Sci Med Sci 54(5):M219–M224

    Article  CAS  Google Scholar 

  39. Olesen J, Gustavsson A, Svensson M, Wittchen HU, Jönsson B (2012) The economic cost of brain disorders in Europe. Eur J Neurol 19(1):155–162

    Article  CAS  PubMed  Google Scholar 

  40. Pan J, Tompkins WJ (1985) A real-time QRS detection algorithm. IEEE Trans Biomed Eng 3:230–236

    Article  Google Scholar 

  41. Pan LA, Hassel S, Segreti AM, Nau SA, Brent DA, Phillips ML (2013) Differential patterns of activity and functional connectivity in emotion processing neural circuitry to angry and happy faces in adolescents with and without suicide attempt. Psychol Med 43(10):2129–2142

    Article  CAS  PubMed  Google Scholar 

  42. Penninx BW, Milaneschi Y, Lamers F, Vogelzangs N (2013) Understanding the somatic consequences of depression: biological mechanisms and the role of depression symptom profile. BMC Med 11(1):1

    Article  Google Scholar 

  43. Pitchot W, Reggers J, Pinto E, Hansenne M, Ansseau M (2003) Catecholamine and HPA axis dysfunction in depression: relationship with suicidal behavior. Neuropsychobiology 47:152–157

    Article  CAS  PubMed  Google Scholar 

  44. Quilliot D, Fluckiger L, Zannad F, Drouin P, Ziegler O (2001) Impaired autonomic control of heart rate and blood pressure in obesity: role of age and of insulin-resistance. Clin Auton Res 11:79–86

    Article  CAS  PubMed  Google Scholar 

  45. Ripley Brian D (1996) Pattern recognition and neural networks. Cambridge University Press, Cambridge

    Book  Google Scholar 

  46. Rottenberg J (2007) Cardiac vagal control in depression: a critical analysis. Biol Psychol 74(2):200–211

    Article  PubMed  Google Scholar 

  47. Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423

    Article  Google Scholar 

  48. Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E et al (1998) The mini-international neuropsychiatric interview (MINI): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry 59:22–33

    PubMed  Google Scholar 

  49. Slavich GM, Irwin MR (2014) From stress to inflammation and major depressive disorder: a social signal transduction theory of depression. Psychol Bull 140(3):774–815

    Article  PubMed  PubMed Central  Google Scholar 

  50. Swinson RP (2006) The GAD-7 scale was accurate for diagnosing generalised anxiety disorder. Evid Based Med. 11(6):184

    Article  PubMed  Google Scholar 

  51. Thayer JF, Fischer JE (2013) Heart rate variability, overnight urinary norepinephrine, and plasma cholesterol in apparently healthy human adults. Int J Cardiol 162(3):240–244

    Article  PubMed  Google Scholar 

  52. Umetani K, Singer DH, McCraty R, Atkinson M (1998) Twenty-four hour time domain heart rate variability and heart rate: relations to age and gender over nine decades. J Am Coll Cardiol 31:593–601

    Article  CAS  PubMed  Google Scholar 

  53. Wang Y, Zhao X, O’Neil A, Turner A, Liu X, Berk M (2013) Altered cardiac autonomic nervous function in depression. BMC Psychiatry 13(1):187

    Article  PubMed  PubMed Central  Google Scholar 

  54. Welch PD (1967) The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Trans Audio Electroacoust 15(2):70–73

    Article  Google Scholar 

  55. Wells CL (2008) A comparison of suicidal ideation between active duty military and military dependents outpatients: a retrospective study identifying treatment outcome using the outcome questionnaire-45.2. ProQuest

  56. Williams JB (1988) A structured interview guide for the Hamilton depression rating scale. Arch General Psychiatry 45(8):742–747

    Article  CAS  Google Scholar 

  57. Windham BG, Fumagalli S, Ble A et al (2012) The relationship between heart rate variability and adiposity differs for central and overall adiposity. J Obesity. doi:10.1155/2012/149516

    Google Scholar 

  58. Zahorska-Markiewicz B, Kuagowska E, Kucio C, Klin M (1993) Heart rate variability in obesity. Int J Obes Relat Metab Disord 17:21–23

    CAS  PubMed  Google Scholar 

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Acknowledgements

This work was partially supported by a Khalifa University Internal Fund (KUIRF) awarded to Ahsan Khandoker. The authors like to thank Ms Ola Ali and other psychiatric nurses of American Center for Psychiatry and Neurology for Patients' recruitment and experimental data collection from MDD patients.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Khalifa University, PO Box 127788, Abu Dhabi, UAE

    A. H. Khandoker & N. Chowdhury

  2. Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, VIC, 3010, Australia

    A. H. Khandoker

  3. American Center for Psychiatry and Neurology, Abu Dhabi, UAE

    V. Luthra & Y. Abouallaban

  4. United International University, Dhaka, Bangladesh

    S. Saha, K. I. Ahmed & R. Mostafa

  5. School of Community Health and Centre for Research in Complex Systems, Charles Sturt University, Albury, NSW, Australia

    H. F. Jelinek

  6. Australian School of Advanced Medicine, Macquarie University, Sydney, NSW, Australia

    H. F. Jelinek

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  1. A. H. Khandoker
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Correspondence to A. H. Khandoker.

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Khandoker, A.H., Luthra, V., Abouallaban, Y. et al. Predicting depressed patients with suicidal ideation from ECG recordings. Med Biol Eng Comput 55, 793–805 (2017). https://doi.org/10.1007/s11517-016-1557-y

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