Socio-Demographic Characteristics of the Patients with a Post Stroke Depression from the Municipality of Tetovo, Republic of Macedonia

Authors

  • Danijela Vojtikiv-Samoilovska Clinical Hospital, Tetovo http://orcid.org/0000-0002-7331-2262
  • Anita Arsovska Clinic of Neurology, Faculty of Medicine, Ss Cyril and Methodius University of Skopje, Skopje

DOI:

https://doi.org/10.3889/oamjms.2018.201

Keywords:

PSD, age, education, gender, nationality, occupational status

Abstract

BACKGROUND: Although post-stroke depression (PSD) is the most common neuro-psychiatric consequence after a stroke there is still some obscurity regarding its aetiology and risk factors, which complicates its management. A better knowledge of the predictors will enable better prevention and treatment.

AIM: The aim of this work was the identification of the risk factors for PSD, typical for the Macedonian population, which will help in early prediction, timely diagnosis and treatment of the disease.

MATERIALS AND METHODS:  We carried out a prospective study at the Clinical Hospital in Tetovo, the Republic of Macedonia to determine the prevalence of PSD and to analyse the socio-demographic characteristics as possible risk factors in 100 patients on discharge and after 5 months. The depression symptoms were quantified using the Hamilton Depression Ranking Scale (HAM-d) and the Geriatric Depression Scale (GDS).

RESULTS: The average age of the patients with PSD on the first examination is 65.0 ± 8.3, whereas on the second examination is 64.5 ± 9.2. According to the Mann-Whitney U test, the difference between the average ages on both examinations is statistically insignificant for p > 0.05. On both examinations, the statistically significant dependence of p > 0.05 between PSD and the occupational status and PSD and education is not recorded. On both examinations, the PSD in male patients was 78.0% and 62.7%, while in female patients it was 85.4% and 68.3% not recording the statistically significant dependence of p < 0.05 between PSD and the gender.

CONCLUSION: The socio-demographic characteristics of the patients with PSD cannot be considered as predictors of the disease.

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References

Ayerbe L, Ayis S, Crichton S, Wolfe CD, Rudd AG. The long-term outcomes of depression up to 10 years after stroke; the South London Stroke Register. J Neurol Neurosurg Psychiatry. 2014; 85(5):514-21. https://doi.org/10.1136/jnnp-2013-306448 PMid:24163430

Srivastava A, Taly AB, Gupta A, Murali T. Post-stroke depression: prevalence and relationship with disability in chronic stroke survivors. Annals of Indian Academy of Neurology. 2010; 13(2):123. https://doi.org/10.4103/0972-2327.64643 PMid:20814496 PMCid:PMC2924510

De Ryck A, Brouns R, Fransen E, et al. A prospective study on the prevalence and risk factors of poststroke depression. Cerebrovasc dis extra. 2013; 3(1):1-13. https://doi.org/10.1159/000345557 PMid:23626594 PMCid:PMC3567876

Maree L. Hackett, Ma (hons), Craig S. Anderson. Predictors of depression after stroke. A systematic review of observational studie. Stroke. 2005; 36:2296-2301s. https://doi.org/10.1161/01.STR.0000183622.75135.a4 PMid:16179565

Robert G. Robinson, Ricardo E. Jorge. Post-stroke depression: a review. Am J psychiatry. 2016; 173:221–231. https://doi.org/10.1176/appi.ajp.2015.15030363 PMid:26684921

Allan LM, Rowan EN, Thomas AJ, Polvikoski TM, O'Brien JT, Kalaria RN. Long-term incidence of depression and predictors of depressive symptoms in older stroke survivors. The British Journal of Psychiatry. 2013; 203(6):453-60. https://doi.org/10.1192/bjp.bp.113.128355 PMid:24158880

Ayerbe L, Ayis S, Rudd AG, Heuschmann PU, Wolfe CD. Natural history, predictors, and associations of depression 5 years after stroke: the South London Stroke Register. Stroke. 2011; 42(7):1907-11. https://doi.org/10.1161/STROKEAHA.110.605808 PMid:21566241

Schepers V, Post M, Visser-Meily A, van de Port I, Akhmouch M, Lindeman E. Prediction of depressive symptoms up to three years post-stroke. Journal of rehabilitation medicine. 2009; 41(11):930-5. https://doi.org/10.2340/16501977-0446 PMid:19841846

Cojocaru GR, Popa-Wagner A, Stanciulescu EC, Babadan L, Buga AM. Post-stroke depression and the aging brain. Journal of molecular psychiatry. 2013; 1(1):14. https://doi.org/10.1186/2049-9256-1-14 PMid:25408907 PMCid:PMC4223891

Terroni L, Amaro Jr E, Iosifescu DV, Tinone G, Sato JR, Leite CC, Sobreiro MF, Lucia MC, Scaff M, Fráguas R. Stroke lesion in cortical neural circuits and post-stroke incidence of major depressive episode: a 4-month prospective study. The world journal of biological psychiatry. 2011; 12(7):539-48. https://doi.org/10.3109/15622975.2011.562242 PMid:21486107 PMCid:PMC3279135

Hama S, Yamashita H, Yamawaki S, Kurisu K. Postâ€stroke depression and apathy: Interactions between functional recovery, lesion location, and emotional response. Psychogeriatrics. 2011; 11(1):68-76. https://doi.org/10.1111/j.1479-8301.2011.00358.x PMid:21447112

Published

2018-05-14

How to Cite

1.
Vojtikiv-Samoilovska D, Arsovska A. Socio-Demographic Characteristics of the Patients with a Post Stroke Depression from the Municipality of Tetovo, Republic of Macedonia. Open Access Maced J Med Sci [Internet]. 2018 May 14 [cited 2024 Apr. 19];6(5):782-5. Available from: https://oamjms.eu/index.php/mjms/article/view/oamjms.2018.201

Issue

Section

B - Clinical Sciences