Skip to main content

Advertisement

SpringerLink
Log in

Factors influencing self-reported anxiety or depression following stroke or TIA using linked registry and hospital data

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

Purpose

Approximately 30–50% of survivors experience problems with anxiety or depression post-stroke. It is important to understand the factors associated with post-stroke anxiety or depression to identify effective interventions.

Methods

Patient-level data from the Australian Stroke Clinical Registry (years 2009–2013), from participating hospitals in Queensland (n = 23), were linked with Queensland Hospital Emergency and Admission datasets. Self-reported anxiety or depression was assessed using the EQ-5D-3L, obtained at 90–180 days post-stroke. Multivariable multilevel logistic regression, with manual stepwise elimination of variables, was used to investigate the association between self-reported anxiety or depression, patient factors and acute stroke processes of care. Comorbidities, including prior mental health problems (e.g. anxiety, depression and dementia) coded in previous hospital admissions or emergency presentations using ICD-10 diagnosis codes, were identified from 5 years prior to stroke event.

Results

2853 patients were included (median age 74; 45% female; 72% stroke; 24% transient ischaemic attack). Nearly half (47%) reported some level of anxiety or depression post-stroke. The factors most strongly associated with anxiety or depression were a prior diagnosis of anxiety or depression [Adjusted Odds Ratio (aOR) 2.37, 95% confidence interval (95% CI) 1.66–3.39; p < 0.001], dementia (aOR 1.91, 95% CI 1.24–2.93; p = 0.003), being at home with support (aOR 1.41, 95% CI 1.12–1.69; p = < 0.001), and low socioeconomic advantage compared to high (aOR 1.59, 95% CI 1.21–2.10; p = 0.001). Acute stroke processes of care were not independently associated with anxiety or depression.

Conclusions

Identification of those with prior mental health problems for early intervention and support may help reduce the prevalence of post-stroke anxiety or depression.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Andrew, N. E., Kilkenny, M., Naylor, R., Purvis, T., Lalor, E., Moloczij, N., & Cadilhac, D. A. (2014). Understanding long-term unmet needs in Australian survivors of stroke. International Journal of Stroke, 9, 106–112.

    Article  Google Scholar 

  2. Chrichton, S. L., Bray, B. D., McKevitt, C., Rudd, A. G., & Wolfe, C. D. A. (2016). Patient outcomes up to 15 years after stroke: Survival, disability, quality of life, cognition and mental health. Journal of Neurology, Neurosurgery and Psychiatry, 87, 1091–1098.

    Article  Google Scholar 

  3. Broomfield, N. M., Quinn, T. J., Abdul-Rahim, A. H., Walters, M. R., & Evans, J. J. (2014). Depression and anxiety symptoms post-stroke/TIA: Prevalence and associations in cross-sectional data from a regional stroke registry. BMC Neurology, 14, 198.

    Article  Google Scholar 

  4. Berg, A., Palomaki, H., Lehtihalmes, M., Lonnqvist, J., & Kaste, M. (2003). Poststroke depression: An 18-month follow-up. Stroke, 34, 138–143.

    Article  Google Scholar 

  5. Shi, Y., Yang, D., Zeng, Y., & Wu, W. (2017) Risk factors for post-stroke depression: A meta-analysis. Frontiers in Aging Neuroscience. https://doi.org/10.3389/fnagi.2017.00218.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Cadilhac, D. A., Kilkenny, M. F., Longworth, M., Pollack, M. R. P., & Levi, C. R., on behalf of Greater Metropolitan Clinical T, Stroke Services New South Wales Coordinating C (2011). Metropolitan–rural divide for stroke outcomes: do stroke units make a difference? Internal Medicine Journal, 41, 321–326.

    Article  CAS  Google Scholar 

  7. National Stroke Foundation.(2010). Clinical guidelines for stroke management 2010. Melbourne.

  8. Stroke Unit Trialists C. (2007). Organised inpatient (stroke unit) care for stroke. Cochrane Database of Systematic Reviews, 4, 4.

    Google Scholar 

  9. Cadilhac, D. A., Andrew, N. E., Kilkenny, M. F., Hill, K., Grabsch, B., Lannin, N. A., Thrift, A. G., Anderson, C. S., Donnan, G. A., Middleton, S., & Grimley, R. (2017). Improving quality and outcomes of stroke care in hospitals: Protocol and statistical analysis plan for the Stroke123 implementation study. International Journal of Stroke, 13, 96–106.

    Article  Google Scholar 

  10. Andrew, N. E., Sundararajan, V., Thrift, A. G., Kilkenny, M. F., Katzenellenbogen, J., Flack, F., Gattellari, M., Boyd, J. H., Anderson, P., Grabsch, B., et al. (2016). Addressing the challenges of cross-jurisdictional data linkage between a national clinical quality registry and government-held health data. Australian and New Zealand Journal of Public Health, 40, 436–442.

    Article  Google Scholar 

  11. Lannin, N. A., Anderson, C., Lim, J., Paice, K., Price, C., Faux, S., Levi, C., Donnan, G., & Cadilhac, D. (2013). Telephone follow-up was more expensive but more efficient than postal in a national stroke registry. Journal of Clinical Epidemiology, 66, 896–902.

    Article  Google Scholar 

  12. Preen, D. B., Holman, C. D. A. J., Spilsbury, K., Semmens, J. B., & Brameld, K. J. (2006). Length of comorbidity lookback period affected regression model performance of administrative health data. Journal of Clinical Epidemiology, 59, 940–946.

    Article  Google Scholar 

  13. WHO (World Health Organization) (2007). International statistical classification of diseases and related health problems. Retrieved April 16, 2017. 10th Revision, Version for 2010.

  14. Cadilhac, D. A., Lannin, N. A., Anderson, C. S., Levi, C. R., Faux, S., Price, C., Middleton, S., Lim, J., Thrift, A. G., & Donnan, G. A. (2010). Protocol and pilot data for establishing the Australian Stroke Clinical Registry. International Journal of Stroke, 5, 217–226.

    Article  Google Scholar 

  15. Rabin, R., & de Charro, F. (2001). EQ-5D: A measure of health status from the EuroQol Group. Annals of Medicine, 33, 337–343.

    Article  CAS  Google Scholar 

  16. Dorman, P. J., Waddell, F., Slattery, J., Dennis, M., & Sandercock, P. (1997). Is the EuroQol a valid measure of health-related quality of life after stroke? Stroke, 28, 1876–1882.

    Article  CAS  Google Scholar 

  17. Hunger, M., Sabariego, C., Stollenwerk, B., Cieza, A., & Leidl, R. (2012). Validity, reliability and responsiveness of the EQ-5D in German stroke patients undergoing rehabilitation. Quality of Life Research, 21, 1205–1216.

    Article  Google Scholar 

  18. Konig, H. H., Bernert, S., Angermeyer, M. C., Matschinger, H., Martinez, M., Vilagut, G., Haro, J. M., de Girolamo, G., de Graaf, R., Kovess, V., & Alonso, J. (2009). Comparison of population health status in six european countries: Results of a representative survey using the EQ-5D questionnaire. Medical Care, 47, 255–261.

    Article  Google Scholar 

  19. McCaffrey, N., Kaambwa, B., Currow, D. C., & Ratcliffe, J. (2016). Health-related quality of life measured using the EQ-5D-5L: South Australian population norms. Health and Quality of Life Outcomes, 14, 133.

    Article  Google Scholar 

  20. Jorgensen, T. S., Turesson, C., Kapetanovic, M., Englund, M., Turkiewicz, A., Christensen, R., Bliddal, H., Geborek, P., & Kristensen, L. E. (2017). EQ-5D utility, response and drug survival in rheumatoid arthritis patients on biologic monotherapy: A prospective observational study of patients registered in the south Swedish SSATG registry. PLoS ONE, 12, e0169946.

    Article  Google Scholar 

  21. Christensen, M. C., Mayer, S., & Ferran, J. M. (2009). Quality of life after intracerebral hemorrhage: Results of the factor seven for acute hemorrhagic stroke (FAST) trial. Stroke, 40, 1677–1682.

    Article  Google Scholar 

  22. Lindgren, P., Glader, E. L., & Jonsson, B. (2008). Utility loss and indirect costs after stroke in Sweden. European Journal of Cardiovascular Prevention and Rehabilitation, 15, 230–233.

    Article  Google Scholar 

  23. Brooks, R. (1996). EuroQol: The current state of play. Health Policy, 37, 53–72.

    Article  CAS  Google Scholar 

  24. Kim, S.-K., Kim, S.-H., Jo, M.-W., & Lee, S. (2015). Estimation of minimally important differences in the EQ-5D and SF-6D indices and their utility in stroke. Health and Quality of Life Outcomes, 13, 32.

    Article  Google Scholar 

  25. Pickard, A. S., Neary, M. P., & Cella, D. (2007). Estimation of minimally important differences in EQ-5D utility and VAS scores in cancer. Health and Quality of Life Outcomes, 5, 70.

    Article  Google Scholar 

  26. Quan, H., Li, B., Couris, C. M., Fushimi, K., Graham, P., Hider, P., Januel, J.-M., & Sundararajan, V. (2011). Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. American Journal of Epidemiology, 173, 676–682.

    Article  Google Scholar 

  27. Charlson, M., Szatrowski, T. P., Peterson, J., & Gold, J. (1994). Validation of a combined comorbidity index. Journal of Clinical Epidemiology, 47, 1245–1251.

    Article  CAS  Google Scholar 

  28. Australian Bureau of Stastistics. (2006). Socio-economic indexes for areas (SEIFA). Canberra: Australian Bureau of Stastistics.

    Google Scholar 

  29. Counsell, C., Dennis, M., McDowall, M., & Warlow, C. (2002). Predicting outcome after acute and subacute stroke. Stroke, 33, 1041.

    Article  Google Scholar 

  30. Royston, P., Moons, K. G. M., Altman, D. G., & Vergouwe, Y. (2009). Prognosis and prognostic research: Developing a prognostic model. British Medical Journal, 338, b604.

    Article  Google Scholar 

  31. Spiegelhalter, D. J., Best, N. G., Carlin, B. P., & van der Linde, A. (2002). Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society Series B, 64, 583–639.

    Article  Google Scholar 

  32. Cadilhac, D. A., Pearce, D. C., Levi, C. R., & Donnan, G. A. (2008). Improvements in the quality of care and health outcomes with new stroke care units following implementation of a clinician-led, health system redesign programme in New South Wales, Australia. Quality and Safety in Health Care, 17, 329–333.

    Article  CAS  Google Scholar 

  33. Cadilhac, D. A., Kim, J., Lannin, N. A., Levi, C. R., Dewey, H. M., Hill, K., Faux, S., Andrew, N. E., Kilkenny, M. F., Grimley, R., et al. (2016). Better outcomes for hospitalized patients with TIA when in stroke units: An observational study. Neurology, 86, 2042–2048.

    Article  CAS  Google Scholar 

  34. Hackett, M. L., Yapa, C., Parag, V., & Anderson, C. S. (2005). Frequency of depression after stroke: A systematic review of observational studies. Stroke, 36, 1330–1340.

    Article  Google Scholar 

  35. Kutlubaev, M. A., & Hackett, M. L. (2014). Part II: Predictors of depression after stroke and impact of depression on stroke outcome: An updated systematic review of observational studies. International Journal of Stroke, 9, 1026–1036.

    Article  Google Scholar 

  36. Hackett, M. L., & Anderson, C. S. (2005). Predictors of depression after stroke. Stroke, 36, 2296.

    Article  Google Scholar 

  37. Stroke Foundation. National stroke audit—rehabilitation services report 2016. Melbourne, Australia.

  38. Cameron, J. I., O’Connell, C., Foley, N., Salter, K., Booth, R., Boyle, R., Cheung, D., Cooper, N., Corriveau, H., Dowlatshahi, D., et al. (2016). Canadian stroke best practice recommendations: Managing transitions of care following Stroke, Guidelines Update 2016. International Journal of Stroke, 11, 807–822.

    Article  Google Scholar 

  39. Eng, J. J., & Reime, B. (2014). Exercise for depressive symptoms in stroke patients: A systematic review and meta-analysis. Clinical Rehabilitation, 28, 731–739.

    Article  Google Scholar 

  40. Thayabaranathan, T., Andrew, N. E., Immink, M. A., Hillier, S., Stevens, P., Stolwyk, R., Kilkenny, M., & Cadilhac, D. A. (2017). Determining the potential benefits of yoga in chronic stroke care: a systematic review and meta-analysis. Topics in Stroke Rehabilitation, 24, 279–287.

    Article  Google Scholar 

  41. Ayerbe, L., Ayis, S., Rudd, A. G., Heuschmann, P. U., & Wolfe, C. D. (2011). Natural history, predictors, and associations of depression 5 years after stroke: The South London Stroke Register. Stroke, 42, 1907–1911.

    Article  Google Scholar 

  42. Spuling, S. M., Wolff, J. K., & Wurm, S. (2017). Response shift in self-rated health after serious health events in old age. Social Science and Medicine, 192, 85–93.

    Article  Google Scholar 

  43. Kapral, M. K., Wang, H., Mamdani, M., & Tu, J. V. (2002). Effect of socioeconomic status on treatment and mortality after stroke. Stroke, 33, 268.

    Article  Google Scholar 

  44. Broomfield, N. M., Quinn, T. J., Abdul-Rahim, A. H., Walters, M. R., & Evans, J. J. (2014). Depression and anxiety symptoms post-stroke/TIA: Prevalence and associations in cross-sectional data from a regional stroke registry. BioMed Central Neurology, 14, 198.

    PubMed  Google Scholar 

Download references

Acknowledgements

We acknowledge members of the Australian Stroke Clinical Registry (AuSCR) Steering Committee, staff from the George Institute for Global Health and the Florey Institute of Neuroscience and Mental Health who manage the AuSCR (Online-Only Data Supplement). We also thank the hospital clinicians (Online-Only Data Supplement) and patients who contribute data to AuSCR. We also acknowledge the data linkage team in Queensland Health (Data Linkage Queensland) who undertook the linkage of data that this study is based on.

Funding

The Australian Stroke Clinical Registry (AuSCR) was supported by grants from the National Health and Medical Research Council (NHMRC: 1034415), Monash University, Queensland Health, Victorian Department of Health and Human Services, the Stroke Foundation, Allergan Australia, Ipsen, Boehringer Ingelheim, and consumer donations. TT is supported by the Australian Government Research Training Program Scholarship. The following authors receive Research Fellowship support from the NHMRC: NEA (1072053), MFK (1109426), AGT (1042600), NAL (1112158) and DAC (1063761 co-funded by Heart Foundation).

Author information

Authors and Affiliations

  1. Stroke and Ageing Research, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia

    Tharshanah Thayabaranathan, Nadine E. Andrew, Monique F. Kilkenny, Amanda G. Thrift, Rohan Grimley & Dominique A. Cadilhac

  2. Department of Medicine, Peninsula Clinical School, Central Clinical School, Monash University, Frankston, VIC, Australia

    Nadine E. Andrew

  3. Stroke Division, The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Heidelberg, VIC, Australia

    Monique F. Kilkenny & Dominique A. Cadilhac

  4. Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Clayton, VIC, Australia

    Rene Stolwyk

  5. Sunshine Coast Clinical School, The University of Queensland, Birtinya, QLD, Australia

    Rohan Grimley

  6. Statistical Services Branch, Queensland Department of Health, Brisbane, QLD, Australia

    Trisha Johnston

  7. St Vincent’s Hospital, University of Melbourne, Melbourne, VIC, Australia

    Vijaya Sundararajan

  8. School of Allied Health, La Trobe University, Bundoora, VIC, Australia

    Natasha A. Lannin

Authors
  1. Tharshanah Thayabaranathan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nadine E. Andrew
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Monique F. Kilkenny
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rene Stolwyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Amanda G. Thrift
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Rohan Grimley
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Trisha Johnston
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Vijaya Sundararajan
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Natasha A. Lannin
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Dominique A. Cadilhac
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tharshanah Thayabaranathan.

Ethics declarations

Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study as part of the registry.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 35 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thayabaranathan, T., Andrew, N.E., Kilkenny, M.F. et al. Factors influencing self-reported anxiety or depression following stroke or TIA using linked registry and hospital data. Qual Life Res 27, 3145–3155 (2018). https://doi.org/10.1007/s11136-018-1960-y

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-018-1960-y

Keywords

Search

Navigation