Daily patterns of fatigue after subarachnoid haemorrhage: an ecological momentary assessment study

Authors

  • Elisabeth A. de Vries Department of Rehabilitation Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Rijndam Rehabilitation, Rotterdam, The Netherlands
  • Majanka H. Heijenbrok-Kal Department of Rehabilitation Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Rijndam Rehabilitation, Rotterdam, The Netherlands
  • Fop van Kooten Department of Neurology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
  • Marco Giurgiu Mental mHealth lab, Karlsruhe Institute of Technology, Germany
  • Ulrich W. Ebner-Priemer Mental mHealth lab, Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe; mHealth Methods in Psychiatry, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
  • Gerard M. Ribbers Department of Rehabilitation Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Rijndam Rehabilitation, Rotterdam, The Netherlands
  • Rita J.G. van den Berg-Emons Department of Rehabilitation Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
  • Johannes B. J. Bussmann Department of Rehabilitation Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands

DOI:

https://doi.org/10.2340/jrm.v55.6486

Keywords:

Subarachnoid Hemorrhage, Fatigue, Stroke, Ecological Momentary Assessment, Latent Class Analysis

Abstract

Objective: To examine the daily course of, and factors associated with, momentary fatigue after subarachnoid haemorrhage, and to explore subgroups of patients with distinct diurnal patterns of fatigue.

Design: Observational study using ecological momentary assessment.

Subjects: A total of 41 participants with subarachnoid haemorrhage.

Methods: Patients with fatigue were included within one year post-onset. Momentary fatigue (scale 1–7) was assessed with repeated measurements (10–11 times/day) during 7 consecutive days. Multilevel-mixed-model analyses and latent-class trajectory modelling were conducted.

Results: Mean (standard deviation; SD) age of the group was 53.9 (13.0) years, 56% female, and mean (SD) time post-subarachnoid haemorrhage onset was 9.3 (3.2) months. Mean (SD) momentary fatigue over all days was 3.22 (1.47). Fatigue increased significantly (p <0.001) over the day, and experiencing more burden of fatigue and day type (working day vs weekend day) were significantly (p < 0.05) associated with higher momentary fatigue. Three subgroups could be distinguished based on diurnal patterns of fatigue. The largest group (n = 17, 41.5%) showed an increasing daily pattern of fatigue.

Conclusion: Momentary fatigue in patients with subarachnoid haemorrhage increases over the day, and diurnal patterns of fatigue differ between  participants. In addition to conventional measures, momentary measures of fatigue might provide valuable information for physicians to optimize personalized management of fatigue after subarachnoid haemorrhage.

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References

Macdonald RL, Schweizer TA. Spontaneous subarachnoid haemorrhage. Lancet 2017; 389: 655-666.

https://doi.org/10.1016/S0140-6736(16)30668-7 DOI: https://doi.org/10.1016/S0140-6736(16)30668-7

de Rooij NK, Linn FH, van der Plas JA, Algra A, Rinkel GJ. Incidence of subarachnoid haemorrhage: a systematic review with emphasis on region, age, gender and time trends. J Neurol Neurosurg Psychiatry 2007; 78: 1365-1372.

https://doi.org/10.1136/jnnp.2007.117655 DOI: https://doi.org/10.1136/jnnp.2007.117655

Rinkel GJ, Algra A. Long-term outcomes of patients with aneurysmal subarachnoid haemorrhage. Lancet Neurol 2011; 10: 349-356.

https://doi.org/10.1016/S1474-4422(11)70017-5 DOI: https://doi.org/10.1016/S1474-4422(11)70017-5

Al-Khindi T, Macdonald RL, Schweizer TA. Cognitive and functional outcome after aneurysmal subarachnoid hemorrhage. Stroke 2010; 41: 519-536.

https://doi.org/10.1161/STROKEAHA.110.581975 DOI: https://doi.org/10.1161/STROKEAHA.110.581975

Kutlubaev MA, Barugh AJ, Mead GE. Fatigue after subarachnoid haemorrhage: a systematic review. J Psychosom Res 2012; 72: 305-310.

https://doi.org/10.1016/j.jpsychores.2011.12.008 DOI: https://doi.org/10.1016/j.jpsychores.2011.12.008

Alghamdi I, Ariti C, Williams A, Wood E, Hewitt J. Prevalence of fatigue after stroke: a systematic review and meta-analysis. Eur Stroke J 2021; 6: 319-332.

https://doi.org/10.1177/23969873211047681 DOI: https://doi.org/10.1177/23969873211047681

Buunk AM, Groen RJ, Veenstra WS, Spikman JM. Leisure and social participation in patients 4-10 years after aneurysmal suba-rachnoid haemorrhage. Brain Inj 2015; 29: 1589-1596.

https://doi.org/10.3109/02699052.2015.1073789 DOI: https://doi.org/10.3109/02699052.2015.1073789

Boerboom W, van Zandvoort MJ, van Kooten F, Khajeh L, Visser-Meily JM, Ribbers GM, et al. Long-term fatigue after peri-mesencephalic subarachnoid haemorrhage in relation to cognitive functioning, mood and comorbidity. Disabil Rehabil 2017; 39: 928-933.

https://doi.org/10.3109/09638288.2016.1172671 DOI: https://doi.org/10.3109/09638288.2016.1172671

de Vries EA, Boerboom W, van den Berg-Emons R, van Kooten F, Ribbers GM, Heijenbrok-Kal MH. Fatigue in relation to long-term participation outcome in aneurysmal subarachnoid haemorrhage survivors. J Rehabil Med 2021; 53: jrm00173.

https://doi.org/10.2340/16501977-2800 DOI: https://doi.org/10.2340/16501977-2800

Powell J, Kitchen N, Heslin J, Greenwood R. Psychosocial outcomes at 18 months after good neurological recovery from aneu-rysmal subarachnoid haemorrhage. J Neurol Neurosurg Psychiatry 2004; 75: 1119-1124.

https://doi.org/10.1136/jnnp.2002.000414 DOI: https://doi.org/10.1136/jnnp.2002.000414

Dulhanty LH, Hulme S, Vail A, Patel HC, Tyson SF. The self-reported needs of patients following subarachnoid hemorrhage (SAH). Disabil Rehabil 2019; 42: 3450-3456.

https://doi.org/10.1080/09638288.2019.1595748 DOI: https://doi.org/10.1080/09638288.2019.1595748

Su Y, Yuki M, Otsuki M. Non-pharmacological interventions for post-stroke fatigue: systematic review and network meta-analysis. J Clin Med 2020; 9: 621.

https://doi.org/10.3390/jcm9030621 DOI: https://doi.org/10.3390/jcm9030621

Wu S, Kutlubaev MA, Chun HY, Cowey E, Pollock A, Macleod MR, et al. Interventions for post-stroke fatigue. Cochrane Data-base Syst Rev 2015;2015: CD007030.

https://doi.org/10.1002/14651858.CD007030.pub3 DOI: https://doi.org/10.1002/14651858.CD007030.pub3

Elbers RG, Verhoef J, van Wegen EE, Berendse HW, Kwakkel G. Interventions for fatigue in Parkinson's disease. Cochrane Data-base Syst Rev 2015; 2015: CD010925.

https://doi.org/10.1002/14651858.CD010925.pub2 DOI: https://doi.org/10.1002/14651858.CD010925.pub2

Ali A, Morfin J, Mills J, Pasipanodya EC, Maas YJ, Huang E, et al. Fatigue after traumatic brain injury: a systematic review. J Head Trauma Rehabil 2022; 37: 249-257.

https://doi.org/10.1097/HTR.0000000000000710 DOI: https://doi.org/10.1097/HTR.0000000000000710

Kluger BM, Krupp LB, Enoka RM. Fatigue and fatigability in neurologic illnesses: proposal for a unified taxonomy. Neurology 2013; 80: 409-416.

https://doi.org/10.1212/WNL.0b013e31827f07be DOI: https://doi.org/10.1212/WNL.0b013e31827f07be

Enoka RM, Almuklass AM, Alenazy M, Alvarez E, Duchateau J. Distinguishing between fatigue and fatigability in multiple scle-rosis. Neurorehabil Neural Repair 2021; 35: 960-973.

https://doi.org/10.1177/15459683211046257 DOI: https://doi.org/10.1177/15459683211046257

Dittner AJ, Wessely SC, Brown RG. The assessment of fatigue: a practical guide for clinicians and researchers. J Psychosom Res 2004; 56: 157-170.

https://doi.org/10.1016/S0022-3999(03)00371-4 DOI: https://doi.org/10.1016/S0022-3999(03)00371-4

Nadarajah M, Mazlan M, Abdul-Latif L, Goh HT. Test-retest reliability, internal consistency and concurrent validity of Fatigue Severity Scale in measuring post-stroke fatigue. Eur J Phys Rehabil Med 2016.

https://doi.org/10.23736/S1973-9087.16.04388-4 DOI: https://doi.org/10.23736/S1973-9087.16.04388-4

De Doncker W, Dantzer R, Ormstad H, Kuppuswamy A. Mechanisms of poststroke fatigue. J Neurol Neurosurg Psychiatry 2018; 89: 287-293.

https://doi.org/10.1136/jnnp-2017-316007 DOI: https://doi.org/10.1136/jnnp-2017-316007

Enoka RM, Duchateau J. Translating fatigue to human performance. Med Sci Sports Exerc 2016; 48: 2228-2238.

https://doi.org/10.1249/MSS.0000000000000929 DOI: https://doi.org/10.1249/MSS.0000000000000929

Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annu Rev Clin Psychol 2008; 4: 1-32.

https://doi.org/10.1146/annurev.clinpsy.3.022806.091415 DOI: https://doi.org/10.1146/annurev.clinpsy.3.022806.091415

Lenaert B, van Kampen N, van Heugten C, Ponds R. Real-time measurement of post-stroke fatigue in daily life and its relations-hip with the retrospective Fatigue Severity Scale. Neuropsychol Rehabil 2020; 32: 1-15.

https://doi.org/10.1080/09602011.2020.1854791 DOI: https://doi.org/10.1080/09602011.2020.1854791

Heine M, van den Akker LE, Blikman L, Hoekstra T, van Munster E, Verschuren O, et al. Real-time assessment of fatigue in pa-tients with multiple sclerosis: how does it relate to commonly used self-report fatigue questionnaires? Arch Phys Med Rehabil 2016; 97: 1887-1894.

https://doi.org/10.1016/j.apmr.2016.04.019 DOI: https://doi.org/10.1016/j.apmr.2016.04.019

Juengst SB, Terhorst L, Nabasny A, Wallace T, Weaver JA, Osborne CL, et al. Use of mHealth technology for patient-reported outcomes in community-dwelling adults with acquired brain injuries: a scoping review. Int J Environ Res Public Health 2021; 18: 2173.

https://doi.org/10.3390/ijerph18042173 DOI: https://doi.org/10.3390/ijerph18042173

Kratz AL, Murphy SL, Braley TJ. Ecological momentary assessment of pain, fatigue, depressive, and cognitive symptoms reve-als significant daily variability in multiple sclerosis. Arch Phys Med Rehabil 2017; 98: 2142-2150.

https://doi.org/10.1016/j.apmr.2017.07.002 DOI: https://doi.org/10.1016/j.apmr.2017.07.002

Juengst SB, Terhorst L, Kew CL, Wagner AK. Variability in daily self-reported emotional symptoms and fatigue measured over eight weeks in community dwelling individuals with traumatic brain injury. Brain Inj 2019; 33: 567-573.

https://doi.org/10.1080/02699052.2019.1584333 DOI: https://doi.org/10.1080/02699052.2019.1584333

Powell DJH, Liossi C, Schlotz W, Moss-Morris R. Tracking daily fatigue fluctuations in multiple sclerosis: ecological momentary assessment provides unique insights. J Behav Med 2017; 40: 772-783.

https://doi.org/10.1007/s10865-017-9840-4 DOI: https://doi.org/10.1007/s10865-017-9840-4

Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol 1989; 46: 1121-1123.

https://doi.org/10.1001/archneur.1989.00520460115022 DOI: https://doi.org/10.1001/archneur.1989.00520460115022

Ebner-Priemer UW, Eid M, Kleindienst N, Stabenow S, Trull TJ. Analytic strategies for understanding affective (in)stability and other dynamic processes in psychopathology. J Abnorm Psychol 2009; 118: 195-202.

https://doi.org/10.1037/a0014868 DOI: https://doi.org/10.1037/a0014868

Proust-Lima C, Philipps V, Liquet B. Estimation of extended mixed models using latent classes and latent processes: the R Package lcmm. J Stat Software 2017; 78: 1-56.

https://doi.org/10.18637/jss.v078.i02 DOI: https://doi.org/10.18637/jss.v078.i02

Lennon H, Kelly S, Sperrin M, Buchan I, Cross AJ, Leitzmann M, et al. Framework to construct and interpret latent class trajectory modelling. BMJ Open 2018; 8: e020683.

https://doi.org/10.1136/bmjopen-2017-020683 DOI: https://doi.org/10.1136/bmjopen-2017-020683

Chaudhuri A, Behan PO. Fatigue in neurological disorders. Lancet 2004; 363: 978-988.

https://doi.org/10.1016/S0140-6736(04)15794-2 DOI: https://doi.org/10.1016/S0140-6736(04)15794-2

Penner IK, Paul F. Fatigue as a symptom or comorbidity of neurological diseases. Nat Rev Neurol 2017; 13: 662-675.

https://doi.org/10.1038/nrneurol.2017.117 DOI: https://doi.org/10.1038/nrneurol.2017.117

Lenaert B, Neijmeijer M, van Kampen N, van Heugten C, Ponds R. Poststroke fatigue and daily activity patterns during outpati-ent rehabilitation: an experience sampling method study. Arch Phys Med Rehabil 2020; 101: 1001-1008.

https://doi.org/10.1016/j.apmr.2019.12.014 DOI: https://doi.org/10.1016/j.apmr.2019.12.014

Harmsen WJ, Ribbers GM, Zegers B, Sneekes EM, Heijenbrok-Kal MH, Khajeh L, et al. Impaired cardiorespiratory fitness after aneurysmal subarachnoid hemorrhage. J Rehabil Med 2016; 48: 769-775.

https://doi.org/10.2340/16501977-2127 DOI: https://doi.org/10.2340/16501977-2127

Harmsen WJ, Ribbers GM, Heijenbrok-Kal MH, Khajeh L, Sneekes EM, van Kooten F, et al. Fatigue after aneurysmal suba-rachnoid hemorrhage is highly prevalent in the first-year postonset and related to low physical fitness: a longitudinal study. Am J Phys Med Rehabil 2019; 98: 7-13.

https://doi.org/10.1097/PHM.0000000000000976 DOI: https://doi.org/10.1097/PHM.0000000000000976

Passier PE, Post MW, van Zandvoort MJ, Rinkel GJ, Lindeman E, Visser-Meily JM. Predicting fatigue 1 year after aneurysmal subarachnoid hemorrhage. J Neurol 2011; 258: 1091-1097.

https://doi.org/10.1007/s00415-010-5891-y DOI: https://doi.org/10.1007/s00415-010-5891-y

Boerboom W, Heijenbrok-Kal MH, Khajeh L, van Kooten F, Ribbers GM. Differences in cognitive and emotional outcomes between patients with perimesencephalic and aneurysmal subarachnoid haemorrhage. J Rehabil Med 2014; 46: 28-32.

https://doi.org/10.2340/16501977-1236 DOI: https://doi.org/10.2340/16501977-1236

Kratz AL, Murphy SL, Braley TJ. Pain, fatigue, and cognitive symptoms are temporally associated within but not across days in multiple sclerosis. Arch Phys Med Rehabil 2017; 98: 2151-2159.

https://doi.org/10.1016/j.apmr.2017.07.003 DOI: https://doi.org/10.1016/j.apmr.2017.07.003

Lau SCL, Connor LT, Skidmore ER, King AA, Lee JM, Baum CM. The moderating role of motivation in the real-time associations of fatigue, cognitive complaints, and pain with depressed mood among stroke survivors: an ecological momentary assessment study. Arch Phys Med Rehabil 2023; 104: 761-768.

https://doi.org/10.1016/j.apmr.2022.11.012 DOI: https://doi.org/10.1016/j.apmr.2022.11.012

Schuiling WJ, Rinkel GJ, Walchenbach R, de Weerd AW. Disorders of sleep and wake in patients after subarachnoid hemorrhage. Stroke 2005; 36: 578-582.

https://doi.org/10.1161/01.STR.0000154862.33213.73 DOI: https://doi.org/10.1161/01.STR.0000154862.33213.73

Byun E, McCurry SM, Opp M, Liu D, Becker KJ, Thompson HJ. Self-efficacy is associated with better sleep quality and sleep ef-ficiency in adults with subarachnoid hemorrhage. J Clin Neurosci 2020; 73: 173-178.

https://doi.org/10.1016/j.jocn.2019.12.010 DOI: https://doi.org/10.1016/j.jocn.2019.12.010

Forster SD, Gauggel S, Petershofer A, Völzke V, Mainz V. Ecological momentary assessment in patients with an acquired brain injury: a pilot study on compliance and fluctuations. Front Neurol 2020; 11: 115.

https://doi.org/10.3389/fneur.2020.00115 DOI: https://doi.org/10.3389/fneur.2020.00115

Claassen J, Park S. Spontaneous subarachnoid haemorrhage. Lancet 2022; 400: 846-862.

https://doi.org/10.1016/S0140-6736(22)00938-2 DOI: https://doi.org/10.1016/S0140-6736(22)00938-2

Western E, Sorteberg A, Brunborg C, Nordenmark TH. Prevalence and predictors of fatigue after aneurysmal subarachnoid hemorrhage. Acta Neurochir 2020; 162: 3107-3116.

https://doi.org/10.1007/s00701-020-04538-9 DOI: https://doi.org/10.1007/s00701-020-04538-9

Huenges Wajer IMC, Hendriks ME, Witkamp TD, Hendrikse J, Rinkel GJE, Visser-Meily JMA, et al. The relationship between ischaemic brain lesions and cognitive outcome after aneurysmal subarachnoid haemorrhage. J Neurol 2019; 266: 2252-2257.

https://doi.org/10.1007/s00415-019-09408-8 DOI: https://doi.org/10.1007/s00415-019-09408-8

Band R, Barrowclough C, Caldwell K, Emsley R, Wearden A. Activity patterns in response to symptoms in patients being trea-ted for chronic fatigue syndrome: an experience sampling methodology study. Health Psychol 2017; 36: 264-269.

https://doi.org/10.1037/hea0000422 DOI: https://doi.org/10.1037/hea0000422

Kruisheer EM, Huenges Wajer IMC, Visser-Meily JMA, Post MWM. Course of participation after subarachnoid hemorrhage. J Stroke Cerebrovasc Dis 2017; 26: 1000-1006.

https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.11.124 DOI: https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.11.124

Buunk AM, Spikman JM, Metzemaekers JDM, van Dijk JMC, Groen RJM. Return to work after subarachnoid hemorrhage: the in-fluence of cognitive deficits. PloS One 2019; 14 e0220972.

https://doi.org/10.1371/journal.pone.0220972 DOI: https://doi.org/10.1371/journal.pone.0220972

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Published

2023-10-18

How to Cite

de Vries, E. A., Heijenbrok-Kal, M. H., van Kooten, F., Giurgiu, M., Ebner-Priemer, U. W., Ribbers, G. M., van den Berg-Emons, R. J., & Bussmann, J. B. J. (2023). Daily patterns of fatigue after subarachnoid haemorrhage: an ecological momentary assessment study. Journal of Rehabilitation Medicine, 55, jrm6486. https://doi.org/10.2340/jrm.v55.6486

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