Subscribe to RSS
DOI: 10.1055/s-0031-1273765
© Georg Thieme Verlag KG Stuttgart · New York
Comparison of Pre-episode and Pre-remission States Using Mood Ratings from Patients with Bipolar Disorder
Publication History
Publication Date:
04 May 2011 (online)
Abstract
Daily self-reported mood ratings from patients with bipolar disorder were analyzed to see if the 60 days before an episode of hypomania or depression (pre-episode state) could be distinguished from the 60 days before a month of euthymia (pre-remission state), and if a pre-hypomanic state could be distinguished from a pre-depressed state. Data were available from 98 outpatients with bipolar disorder, who returned about one year of daily data, and received treatment as usual. The approximate entropy (ApEn), mean mood and mood variability (standard deviation) were determined for 53 pre-hypomanic states, 42 pre-depressive states, and 65 pre-remission states.There was greater serial irregularity (ApEn) and greater variability in mood in the pre-episode than the pre-remission state. There was greater serial irregularity (ApEn) but no difference in variability in mood in the pre-hypomanic state when compared to the pre-depressed state. ApEn can distinguish between the pre-episode, pre-remission, pre-hypomanic and pre-depressive states. Using daily mood ratings, pre-episode changes were detected before the episode onset. Further investigation to relate the pre-episode and pre-remission states to other clinical and biological data is indicated.
References
- 1 Bauer M, Grof P, Gyulai L. et al . Using technology to improve longitudinal studies: self-reporting with chronoRecord in bipolar disorder. Bipolar Disord. 2004; 6 67-74
- 2 Bauer M, Grof P, Rasgon N. et al . Temporal relation between sleep and mood in patients with bipolar disorder. Bipolar Disord. 2006; 8 160-167
- 3 Bauer M, Wilson T, Neuhaus K. et al . Self-reporting software for bipolar disorder: validation of ChronoRecord by patients with mania. Psychiatry Res. 2008; 159 359-366
- 4 Bauer M, Glenn T, Grof P. et al . Frequency of subsyndromal symptoms and employment status in patients with bipolar disorder. Soc Psychiatry Psychiatr Epidemiol. 2009; 44 515-522
- 5 Bauer M, Glenn T, Grof P. et al . Subsyndromal mood symptoms: a useful concept for maintenance studies of bipolar disorder?. Psychopathology. 2010; 43 1-7
- 6 Bhattacharya J. Complexity analysis of spontaneous EEG. Acta Neurobiol Exp (Wars). 2000; 60 495-501
- 7 Bhattacharya J. Reduced degree of long-range phase synchrony in pathological human brain. Acta Neurobiol Exp (Wars). 2001; 61 309-318
- 8 David AS. Insight and psychosis. Br J Psychiatry. 1990; 156 798-808
- 9 Denicoff KD, Smith-Jackson EE, Disney ER. et al . Preliminary evidence of the reliability and validity of the prospective life-chart methodology (LCM-p). J Psychiatr Res. 1997; 31 593-603
- 10 Engle R. Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica. 1982; 50 987-1007
- 11 Fischer JE, Bachmann LM, Jaeschke R. A readers’ guide to the interpretation of diagnostic test properties: clinical example of sepsis. Intensive Care Med. 2003; 29 1043-1051
- 12 Glenn T, Whybrow PC, Rasgon N. et al . Approximate entropy of self-reported mood prior to episodes. Bipolar Disord. 2006; 8 424-429
- 13 Gottschalk A, Bauer MS, Whybrow PC. Evidence of chaotic mood variation in bipolar disorder. Arch Gen Psychiatry. 1995; 52 947-959
- 14 Jackson A, Cavanagh J, Scott J. A systematic review of manic and depressive prodromes. J Affect Disord. 2003; 74 209-217
- 15 Judd LL, Akiskal HS, Schettler PJ. et al . The long-term natural history of the weekly symptomatic status of bipolar I disorder. Arch Gen Psychiatry. 2002; 59 530-537
- 16 Mantere O, Suominen K, Valtonen HM. et al . Only half of bipolar I and II patients report prodromal symptoms. J Affect Disord. 2008; 111 366-371
- 17 O’Donnell BF, Hetrick WP, Vohs JL. et al . Neural synchronization deficits to auditory stimulation in bipolar disorder. Neuroreport. 2004; 15 1369-1372
- 18 Pincus SM. Approximate entropy as a measure of system complexity. Proc Natl Acad Sci USA. 1991; 88 2297-2301
- 19 Pincus SM, Gladstone IM, Ehrenkranz RA. A regularity statistic for medical data analysis. J Clin Monit. 1991; 7 335-345
- 20 Pincus SM, Viscarello RR. Approximate entropy: a regularity measure for fetal heart rate analysis. Obstet Gynecol. 1992; 79 249-255
- 21 Pincus SM, Gevers E, Robinson ICAF. et al . Females secrete growth hormone with more process irregularity than males in both human and rat. Am J Physiol. 1996; 270 E107-E115
- 22 Pincus SM, Hartman ML, Roelfsema F. et al . Hormone pulsatility discrimination via coarse and short time sampling. Am J Physiol. 1999; 277 E948-E957
- 23 Pincus SM. Irregularity and asynchrony in biologic network signals. Methods Enzymol. 2000; 321 149-182
- 24 Tretter F, Gebicke-Haerter PJ. Philosophy of neuroscience and options of systems science. Pharmacopsychiatry. 2009; 42 (S 01) S2-S10
- 25 Tschacher W, Scheier C, Hashimoto Y. Dynamical analysis of schizophrenia courses. Biol Psychiatry. 1997; 41 428-437
- 26 Vaillancourt DE, Newell KM. Changing complexity in human behavior and physiology through aging and disease. Neurobiol Aging. 2002; 23 1-11
- 27 Veldhuis JD, Keenan DM, Pincus SM. Motivations and methods for analyzing pulsatile hormone secretion. Endocr Rev. 2008; 29 823-864
- 28 Vikman S, Mäkikallio TH, Yli-Mäyry S. et al . Altered complexity and correlation properties of R-R interval dynamics before the spontaneous onset of paroxysmal atrial fibrillation. Circulation. 1999; 100 2079-2084
- 29 Yen CF, Chen CS, Ko CH. et al . Changes in insight among patients with bipolar I disorder: a 2-year prospective study. Bipolar Disord. 2007; 9 238-242
- 30 Zweig MH, Campbell G. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clinical Chemistry. 1993; 39 561-577
Correspondence
Prof. Dr. Dr. M. Bauer
Department of Psychiatry and
Psychotherapy
Universitätsklinikum Carl
Gustav Carus
Technische Universität Dresden
Fetscherstraße 74
01307 Dresden
Germany
Phone: +49/351/45 80
Fax: +49/30/450 51 79 62
Email: michael.bauer@uniklinikum-dresden.de