Relationship between trajectories of post-stroke disability and self-rated health (NeuroAdapt): protocol for a prospective observational study

Sarah K Schäfer, Robert Fleischmann, Bettina von Sarnowski, Dominic Bläsing, Agnes Flöel, Susanne Wurm, Sarah K Schäfer, Robert Fleischmann, Bettina von Sarnowski, Dominic Bläsing, Agnes Flöel, Susanne Wurm

Abstract

Introduction: Stroke is the leading neurological cause of adult long-term disability in Europe. Even though functional consequences directly related to neurological impairment are well studied, post-stroke trajectories of functional health according to the International Classification of Functioning, Disability and Health are poorly understood. Particularly, no study investigated the relationship between post-stroke trajectories of activities of daily living (ADL) and self-rated health (SRH). However, such knowledge is of major importance to identify patients at risk of unfavourable courses. This prospective observational study aims to investigate trajectories of ADL and SRH, and their modifying factors in the course of the first year after stroke.

Methods and analysis: The study will consecutively enrol 300 patients admitted to a tertiary care hospital with acute ischaemic stroke or transient ischaemic attack (TIA; Age, Blood Pressure, Clinical Features, Duration of symptoms, Diabetes score ≥3). Patient inclusion is planned from May 2021 to September 2022. All participants will complete an interview assessing ADL, SRH, mental health, views on ageing and resilience-related concepts. Participants will be interviewed face-to-face 1-5 days post-stroke/TIA in the hospital; and will be followed up after 6 weeks, 3 months, 6 months and 12 months via telephone. The 12-month follow-up will also include a neurological assessment. Primary endpoints are ADL operationalised by modified Rankin Scale scores and SRH. Secondary outcomes are further measures of ADL, functional health, physical activity, falls and fatigue. Views on ageing, social support, resilience-related concepts, affect, frailty, illness perceptions and loneliness will be examined as modifying factors. Analyses will investigate the bidirectional relationship between SRH and ADL using bivariate latent change score models.

Ethics and dissemination: The study has been approved by the institutional review board of the University Medicine Greifswald (Ref. BB 237/20). The results will be disseminated through scientific publications, conferences and media. Moreover, study results and potential implications will be discussed with patient representatives.

Trial registration number: NCT04704635.

Keywords: stroke; stroke medicine.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Figures

Figure 1
Figure 1
Conceptual framework of the International Classification of Functioning, Health and Disability (World Health Organization, 2001) including an illustrating example for stroke.
Figure 2
Figure 2
SPIRIT flow chart.

References

    1. Catanese L, Tarsia J, Fisher M. Acute ischemic stroke therapy overview. Circ Res 2017;120:541–58. 10.1161/CIRCRESAHA.116.309278
    1. Feigin VL, Norrving B, Mensah GA. Global burden of stroke. Circ Res 2017;120:439–48. 10.1161/CIRCRESAHA.116.308413
    1. Deuschl G, Beghi E, Fazekas F, et al. . The burden of neurological diseases in Europe: an analysis for the global burden of disease study 2017. Lancet Public Health 2020;5:e551–67. 10.1016/S2468-2667(20)30190-0
    1. Dhamoon MS, Moon YP, Paik MC, et al. . Trajectory of functional decline before and after ischemic stroke: the Northern Manhattan study. Stroke 2012;43:2180–4. 10.1161/STROKEAHA.112.658922
    1. Dhamoon MS, Moon YP, Paik MC, et al. . Quality of life declines after first ischemic stroke. The Northern Manhattan study. Neurology 2010;75:328–34. 10.1212/WNL.0b013e3181ea9f03
    1. Chen R-L, Balami JS, Esiri MM, et al. . Ischemic stroke in the elderly: an overview of evidence. Nat Rev Neurol 2010;6:256–65. 10.1038/nrneurol.2010.36
    1. Benjamin EJ, Blaha MJ, Chiuve SE, et al. . Heart disease and stroke Statistics-2017 update: a report from the American heart association. Circulation 2017;135:e146–603. 10.1161/CIR.0000000000000485
    1. Dhamoon MS, Longstreth WT, Bartz TM, et al. . Disability trajectories before and after stroke and myocardial infarction: the cardiovascular health study. JAMA Neurol 2017;74:1439–45. 10.1001/jamaneurol.2017.2802
    1. Wondergem R, Pisters MF, Wouters EJ, et al. . The course of activities in daily living: who is at risk for decline after first ever stroke? Cerebrovasc Dis 2017;43:1–8. 10.1159/000451034
    1. Cassidy JM, Cramer SC, Spontaneous CSC. Spontaneous and Therapeutic-Induced mechanisms of functional recovery after stroke. Transl Stroke Res 2017;8:33–46. 10.1007/s12975-016-0467-5
    1. Edwards JD, Kapral MK, Fang J, et al. . Trends in long-term mortality and morbidity in patients with no early complications after stroke and transient ischemic attack. J Stroke Cerebrovasc Dis 2017;26:1641–5. 10.1016/j.jstrokecerebrovasdis.2016.09.038
    1. World Health Organization . International classification of functioning, disability, and health. World Health Organization, 2001.
    1. Levine DA, Davydow DS, Hough CL, et al. . Functional disability and cognitive impairment after hospitalization for myocardial infarction and stroke. Circ Cardiovasc Qual Outcomes 2014;7:863–71. 10.1161/HCQ.0000000000000008
    1. Engel-Yeger B, Tse T, Josman N, et al. . Scoping review: the trajectory of recovery of participation outcomes following stroke. Behav Neurol 2018;2018:5472018. 10.1155/2018/5472018
    1. de Graaf JA, van Mierlo ML, Post MWM, et al. . Long-term restrictions in participation in stroke survivors under and over 70 years of age. Disabil Rehabil 2018;40:637–45. 10.1080/09638288.2016.1271466
    1. van Mierlo M, van Heugten C, Post MWM, et al. . Trajectories of health-related quality of life after stroke: results from a one-year prospective cohort study. Disabil Rehabil 2018;40:997–1006. 10.1080/09638288.2017.1292320
    1. Spuling SM, Wolff JK, Wurm S. Response shift in self-rated health after serious health events in old age. Soc Sci Med 2017;192:85–93. 10.1016/j.socscimed.2017.09.026
    1. Araújo Érika de Freitas, Viana RT, Teixeira-Salmela LF, et al. . Self-rated health after stroke: a systematic review of the literature. BMC Neurol 2019;19:221. 10.1186/s12883-019-1448-6
    1. Au N, Johnston DW. Self-assessed health: what does it mean and what does it hide? Soc Sci Med 2014;121:21–8. 10.1016/j.socscimed.2014.10.007
    1. Arnadottir SA, Gunnarsdottir ED, Stenlund H, et al. . Determinants of self-rated health in old age: a population-based, cross-sectional study using the International classification of functioning. BMC Public Health 2011;11:670. 10.1186/1471-2458-11-670
    1. DeSalvo KB, Bloser N, Reynolds K, et al. . Mortality prediction with a single General self-rated health question. A meta-analysis. J Gen Intern Med 2006;21:267. 10.1111/j.1525-1497.2005.00291.x
    1. Connor KM, Davidson JRT. Development of a new resilience scale: the Connor-Davidson resilience scale (CD-RISC). Depress Anxiety 2003;18:76–82. 10.1002/da.10113
    1. Antonovsky A. Health, Stress, and Coping. Jossey-Bass, 1979.
    1. Antonovsky A. Unraveling the mystery of health: How people manage stress and stay well. San Francisco, CA, US: Jossey-Bass, 1987.
    1. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychol Rev 1977;84:191–215. 10.1037//0033-295x.84.2.191
    1. Wurm S, Diehl M, Kornadt AE, et al. . How do views on aging affect health outcomes in adulthood and late life? explanations for an established connection. Dev Rev 2017;46:27–43. 10.1016/j.dr.2017.08.002
    1. American Psychological Association . The road to resilience, 2014. Available: [Accessed 28 Aug 2019].
    1. Wurm S, Tesch-Römer C, Tomasik MJ. Longitudinal findings on aging-related cognitions, control beliefs, and health in later life. J Gerontol B Psychol Sci Soc Sci 2007;62:P156–64. 10.1093/geronb/62.3.p156
    1. Stephan Y, Sutin AR, Wurm S, et al. . Subjective aging and incident cardiovascular disease. J Gerontol B Psychol Sci Soc Sci 2021;76:910–9. 10.1093/geronb/gbaa106
    1. Wurm S, Wiest M, Wolff JK, et al. . Changes in views on aging in later adulthood: the role of cardiovascular events. Eur J Ageing 2020;17:457–67. 10.1007/s10433-019-00547-5
    1. Hu T, Zhang D, Wang J. A meta-analysis of the trait resilience and mental health. Pers Individ Dif 2015;76:18–27. 10.1016/j.paid.2014.11.039
    1. Eriksson M, Lindström B. Antonovsky's sense of coherence scale and the relation with health: a systematic review. J Epidemiol Community Health 2006;60:376–81. 10.1136/jech.2005.041616
    1. Bergh C, Udumyan R, Fall K, et al. . Stress resilience in male adolescents and subsequent stroke risk: cohort study. J Neurol Neurosurg Psychiatry 2014;85:1331. 10.1136/jnnp-2013-307485
    1. Zhang W, Liu Z, Zhou X, et al. . Resilience among stroke survivors: A cohort study of the first 6 months. J Adv Nurs 2020;76:504–13. 10.1111/jan.14247
    1. Wolff JK, Warner LM, Ziegelmann JP, et al. . What do targeting positive views on ageing add to a physical activity intervention in older adults? results from a randomised controlled trial. Psychol Health 2014;29:915–32. 10.1080/08870446.2014.896464
    1. Beyer A-K, Wolff JK, Freiberger E, et al. . Are self-perceptions of ageing modifiable? examination of an exercise programme with vs. without a self-perceptions of ageing-intervention for older adults. Psychol Health 2019;34:661–76. 10.1080/08870446.2018.1556273
    1. Joyce S, Shand F, Tighe J, et al. . Road to resilience: a systematic review and meta-analysis of resilience training programmes and interventions. BMJ Open 2018;8:e017858. 10.1136/bmjopen-2017-017858
    1. Chmitorz A, Kunzler A, Helmreich I, et al. . Intervention studies to foster resilience - A systematic review and proposal for a resilience framework in future intervention studies. Clin Psychol Rev 2018;59:78–100. 10.1016/j.cpr.2017.11.002
    1. Chan A-W, Tetzlaff JM, Gøtzsche PC, et al. . Spirit 2013 explanation and elaboration: guidance for protocols of clinical trials. BMJ 2013;346:e7586. 10.1136/bmj.e7586
    1. von Elm E, Altman DG, Egger M, et al. . The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. PLoS Med 2007;4:e296. 10.1371/journal.pmed.0040296
    1. Ahmadi M, Laumeier I, Ihl T, et al. . A support programme for secondary prevention in patients with transient ischaemic attack and minor stroke (INSPiRE-TMS): an open-label, randomised controlled trial. Lancet Neurol 2020;19:49–60. 10.1016/S1474-4422(19)30369-2
    1. Khanevski AN, Kvistad CE, Novotny V, et al. . Incidence and etiologies of stroke mimics after incident stroke or transient ischemic attack. Stroke 2019;50:2937–40. 10.1161/STROKEAHA.119.026573
    1. Rankin J. Cerebral vascular accidents in patients over the age of 60. II. prognosis. Scott Med J 1957;2:200–15. 10.1177/003693305700200504
    1. Mahoney FI, Barthel DW. Functional evaluation: the Barthel index: a simple index of independence useful in scoring improvement in the rehabilitation of the chronically ill. Maryland State Medical Journal 1965;14:61–5.
    1. Duncan PW, Lai SM, Bode RK, et al. . Stroke impact Scale-16: a brief assessment of physical function. Neurology 2003;60:291–6. 10.1212/01.WNL.0000041493.65665.D6
    1. Kim S-Y. Sample size requirements in single- and multiphase growth mixture models: a Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal 2012;19:457–76. 10.1080/10705511.2012.687672
    1. Kievit RA, Brandmaier AM, Ziegler G, et al. . Developmental cognitive neuroscience using latent change score models: a tutorial and applications. Dev Cogn Neurosci 2018;33:99–117. 10.1016/j.dcn.2017.11.007
    1. Kasner SE. Clinical interpretation and use of stroke scales. Lancet Neurol 2006;5:603–12. 10.1016/S1474-4422(06)70495-1
    1. Magidson J, Vermunt JK. Latent class models. In: The SAGE Handbook of quantitative methodology for the social sciences, 2004: 175–98.
    1. Meyer C, Rumpf HJ, Hapke U, et al. . Prevalence of alcohol consumption, abuse and dependence in a country with high per capita consumption: findings from the German TACOS study. transitions in alcohol consumption and smoking. Soc Psychiatry Psychiatr Epidemiol 2000;35:539–47. 10.1007/s001270050277
    1. Mavaddat N, Sadler E, Lim L, et al. . Perceptions of self-rated health among stroke survivors: a qualitative study in the United Kingdom. BMC Geriatr 2018;18:81. 10.1186/s12877-018-0765-8
    1. World Medical Association . World Medical association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 2013;310:2191–4. 10.1001/jama.2013.281053
    1. Fong JH, Kok Z-C. Does subjective health matter? Predicting overall and specific ADL disability incidence. Arch Gerontol Geriatr 2020;90:104169. 10.1016/j.archger.2020.104169
    1. Falconer J, Quesnel-Vallée A. Pathway from poor self-rated health to mortality: explanatory power of disease diagnosis. Soc Sci Med 2017;190:227–36. 10.1016/j.socscimed.2017.08.008
    1. Janssen PM, Visser NA, Dorhout Mees SM, et al. . Comparison of telephone and face-to-face assessment of the modified Rankin scale. Cerebrovasc Dis 2010;29:137–9. 10.1159/000262309
    1. Powers JR, Mishra G, Young AF. Differences in mail and telephone responses to self-rated health: use of multiple imputation in correcting for response bias. Aust N Z J Public Health 2005;29:149–54. 10.1111/j.1467-842x.2005.tb00065.x

Source: PubMed

3
Tilaa