PREDICTION OF THE RISK OF NEUROLOGICAL DISORDERS AND DISORDERS OF THE MUSCULOSKELETAL SYSTEM IN POST-STROKE PATIENTS

Authors

  • N. T. Shalabai I. Horbachevsky Ternopil National Medical University
  • S. I. Shkrobot I. Horbachevsky Ternopil National Medical University
  • D. O. Kovalchuk I. Horbachevsky Ternopil National Medical University
  • L. P. Mazur I. Horbachevsky Ternopil National Medical University
  • A. S. Sverstiuk I. Horbachevsky Ternopil National Medical University

DOI:

https://doi.org/10.11603/2411-1597.2023.3-4.14548

Keywords:

stroke, diseases of the nervous system, disorders of the musculoskeletal system, multivariate regression prediction model

Abstract

Introduction. Stroke is a severe somatic disease characterised by impaired cerebral circulation, nervous system and musculoskeletal system functions. Stroke is one of the leading causes of death and a serious global threat to public health worldwide. That is why it is an urgent task to predict the risk of nervous system and musculoskeletal disorders.

The aim of the study – to develop a multivariate regression model for predicting the risk of diseases of the nervous system and musculoskeletal system in post-stroke patients.

The main part. Were examined 107 patients who suffered a stroke and were undergoing inpatient treatment in the stroke department of the Ternopil Regional Clinical Psychoneurological Hospital of Ternopil Regional Council. The study involved post-stroke patients aged 35 to 83 years with various risk symptoms of neurological and locomotor disorders, as well as localization of brain damage. The paper proposes risk criteria for nervous disorders and diseases of the musculoskeletal system. The initial data for the study were localization of damage to the left and right hemispheres, occipital and parietal-occipital areas, symptoms of damage to the musculoskeletal system, dizziness, numbness of the limbs, paresis, hemihypesthesia, movement disorders. According to the results of multivariate regression analysis in the Statistica 10.0 program for predicting the risk of damage to the nervous system and musculoskeletal system, localization of damage in the occipital region, symptoms of damage to the musculoskeletal system, dizziness, numbness of the limbs, paresis were the most significant with a significance level of less than 0.05. The coefficient of determination (R2) was used to test the quality of the predictive model, and ANOVA was used to assess model acceptability.

Conclusions. The proposed multivariate regression model for predicting the risk of developing disorders of the nervous and musculoskeletal systems will allow timely monitoring and assessment of the condition of post-stroke patients, as well as contribute to the creation of effective adapted rehabilitation programs for patients with impaired cerebral circulation.

References

Diegoli, H., Magalhães Pedro, S.C., Makdisse Márcia, R.P., Moro Carla, H.C., França Paulo, H.C., Lange, M.C., & Longo, A.L. (2023). Real-World Populational-Based Quality of Life and Functional Status After Stroke. Value in Health Regional Issues, 36, 76-82. DOI: 10.1016/j.vhri.2023.02.005. DOI: https://doi.org/10.1016/j.vhri.2023.02.005

Yang, L., Huang, X., Wang, J., Yang, X., Ding, L., Li, Z., & Li, J. (2023). Identifying stroke-related quantified evidence from electronic health records in real-world studies. Artificial Intelligence in Medicine, 140, 102552. DOI: 10.1016/j.artmed.2023.102552. DOI: https://doi.org/10.1016/j.artmed.2023.102552

Biswas, N., Uddin Khandaker, M.М., Rikta, S.T., & Dey, S.K. (2022). A comparative analysis of machine learning classifiers for stroke prediction: A predictive analytics approach. Healthcare Analytics, 2, 100116. DOI: 10.1016/j.health.2022.100116. DOI: https://doi.org/10.1016/j.health.2022.100116

Schwartz, L., Anteby, R., Klang, E., & Soffer, S. (2023). Stroke mortality prediction using machine learning: systematic review. Journal of the Neurological Sciences, 444, 120529. DOI: 10.1016/j.jns.2022.120529. DOI: https://doi.org/10.1016/j.jns.2022.120529

Huijberts, I., Pinckaers Florentina, M.E., H. van Zwam, W., Boogaarts, H.D., J. van Oostenbrugge, R., & Alida, A.P. (2023). Cerebral arterial air emboli on immediate post-endovascular treatment CT are associated with poor short- and long-term clinical outcomes in acute ischaemic stroke patients. Journal of Neuroradiology, 50(5), 530-536. DOI: 10.1016/j.neurad.2023.06.001. DOI: https://doi.org/10.1016/j.neurad.2023.06.001

Basheti, I.A., Ayasrah, S.M., & Muayyad, A. (2019). Identifying treatment related problems and associated factors among hospitalized post-stroke patients through medication management review: a multi-center study. Saudi Pharmaceutical Journal, 27(2), 208-219. DOI: 10.1016/j.jsps.2018.10.005. DOI: https://doi.org/10.1016/j.jsps.2018.10.005

Chen, Y.-Ch., Chou, W., Hong, R.B., Lee, J.H., & Chang, J.H. (2023). Home-based rehabilitation versus hospital-based rehabilitation for stroke patients in post-acute care stage: Comparison on the quality of life. Journal of the Formosan Medical Association, 122(9), 862-871. DOI: 10.1016/j.jfma.2023.05.007. DOI: https://doi.org/10.1016/j.jfma.2023.05.007

Cogan, A.M., Weaver, J.A., Davidson, L.F., Khromouchkine, N., & Mallinson, T. (2021). Association of Therapy Time and Cognitive Recovery in Stroke Patients in Post-Acute Rehabilitation. Journal of the American Medical Directors Association, 22(2), 453-458. DOI: 10.1016/j.jamda.2020.06.031. DOI: https://doi.org/10.1016/j.jamda.2020.06.031

Mankoo, A., Roy S., Davies, A., Panerai, R.B., Robinson, T.G., Brassard, P., Beishon, L.C., & Minhas, J.S. (2023). The role of the autonomic nervous system in cerebral blood flow regulation in stroke: A review. Autonomic Neuroscience, 246, 103082. DOI: 10.1016/j.autneu.2023.103082. DOI: https://doi.org/10.1016/j.autneu.2023.103082

Kim, Ch.Y., Choi, S.B., & Lee, E.S. (2024). Prevalence and predisposing factors of post-stroke complex regional pain syndrome: Retrospective case-control study. Journal of Stroke and Cerebrovascular Diseases, 33(2), 107522. DOI: 10.1016/j.jstrokecerebrovasdis.2023.107522. DOI: https://doi.org/10.1016/j.jstrokecerebrovasdis.2023.107522

Adeniji, T., Nadasan, T., Olagbeg,i O.M., & Dada, O. (2023). Telerehabilitation-based exercises with or without transcranial direct current stimulation for pain, motor and cognitive function in older adults with mild cognitive impairments post-stroke: A multi-arm parallel-group randomized controlled trial study protocol. Brain Hemorrhages, 4(3), 122-128. DOI: 10.1016/j.hest.2023.01.004. DOI: https://doi.org/10.1016/j.hest.2023.01.004

Su, X., Pan, D., Meng, H., Lu, W., Wang, X., Liu, Z., Geng, Y., Ma, X., & Liang, P. (2023). Dementia increases the risk of death in stroke patients: A retrospective cohort-based risk score model study. Journal of Stroke and Cerebrovascular Diseases, 32(11), 107337. DOI: 10.1016/j.jstrokecerebrovasdis.2023.107337. DOI: https://doi.org/10.1016/j.jstrokecerebrovasdis.2023.107337

Chukur, O., Pasyechko, N., Bob, A., & Sverstiuk, A. (2022). Prediction of climacteric syndrome development in perimenopausal women with hypothyroidismи. Przeglad Menopauzalny, 21(4), 236-241. DOI: 10.5114/pm.2022.123522. DOI: https://doi.org/10.5114/pm.2022.123522

Musiienko, V., Marushchak, M., Sverstuik, A., Filipyuk, A., Krynytska, I. (2021). Prediction Factors for the Risk of Hypothyroidism Development in Type 2 Diabetic Patients. PharmacologyOnLine, 3, 585-594.

Musiienko, V., Sverstiuk, A., Lepyavko, A., Danchak, S., & Lisnianska, N. (2022). Prediction factors for the risk of diffuse non-toxic goiter development in type 2 diabetic patients. Polski merkuriusz lekarski: organ Polskiego Towarzystwa Lekarskiegothis, 296(50), 94-98. PMID: 35436270.

Nykytyuk, S.O., Sverstiuk, A.S., Pyvovarchuk, D.S., & Klymnyuk, S.I. (2023). A multifactorial model for predicting severe course and organ and systems damage in Lyme borreliosis in children. Modern pediatrics, 130(2), 6-16. DOI: 10.15574/SP.2023.130.6. DOI: https://doi.org/10.15574/SP.2023.130.6

Jaiswal, V., Ang, S.P., Suresh, V.J., Halder, A.A., Rajak, K., Nasir, Y. M., … Kainth, T. (2023) Association between baseline high-sensitive C-reactive protein, Homocysteine levels, and post-stroke depression among stroke patients: A Systematic Review, Meta-analysis, and Meta-regression. Current Problems in Cardiology, 102338. DOI: 10.1016/j.cpcardiol.2023.102338. DOI: https://doi.org/10.1016/j.cpcardiol.2023.102338

Published

2024-03-29

How to Cite

Shalabai, N. T., Shkrobot, S. I., Kovalchuk, D. O., Mazur, L. P., & Sverstiuk, A. S. (2024). PREDICTION OF THE RISK OF NEUROLOGICAL DISORDERS AND DISORDERS OF THE MUSCULOSKELETAL SYSTEM IN POST-STROKE PATIENTS. Nursing, (3-4), 86–92. https://doi.org/10.11603/2411-1597.2023.3-4.14548

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