PATTERN OF COMPUTED TOMOGRAPHY FINDINGS IN ADULT PATIENTS PRESENTING WITH STROKE IN NNEWI, SOUTHEAST NIGERIA
Abstract
The incidence of stroke in developing countries like Nigeria is expected to rise in the future as the population undergoes a “health transition”, from less of infectious diseases, and diseases related to poverty and malnutrition to more of non-communicable diseases. This study sort to evaluate the pattern of computed tomography findings in adult patients presenting with stroke in Nnewi, Southeast Nigeria in order to provide the baseline data that will enable accurate diagnosis in patients affected by stroke. This was a retrospective cross-sectional review. A convenient sampling technique was used to recruit patients’ data with clinical suspected CVA and retrieve records/cases of CT examination findings from this population at Waves diagnostics Nnewi, Anambra state. Statistical package for social science (SPSS) V.20.0 was used to analyse the data include descriptive statistics such as mean, frequency and percentage was used to summarize the data. Data was categorized according to age group and gender. Majority of the participant where in the age range of 51-60years (25%) followed closely by 61-70years (22%) and then 71-80years (19.0%) making age range 51-80years the most stroke affected population (66%). Majority of the participants where males (51%). Result also showed that majority of the participants were diagnosed with right ischaemic CVA (72%) whereas the least was bilateral haemorrhagic CVA (1.0%). In general, ischaemic CVA had the highest prevalence (74.7%). Ischaemic stroke was prevalent in this population, more men had stroke than women especial bilateral CVA (multiple affectation). CVA was more prevalent in the older age group than in the younger population. While basal ganglia lacunar was common feature in ischaemic CVA, intracerebral/subdural haemorrhage and subarachnoid haemorrhage were common features in haemorrhage CVA.
Downloads
References
[2] Adeloye D. (2014) An Estimate of the Incidence and Prevalence of Stroke in Africa: A Systematic Review and Meta-Analysis. PLoS ONE; 9(6): 1007 24.
[3] American Stroke Association (ASA) (2023). Stroke symptoms. https://www.stroke.org/en/about-stroke/stroke-symptoms Accessed 18/052023
[4] Birenbaum D., Bancroft L. W., Felsberg G. J. (2011). Imaging in acute stroke. The Western Journal of Emergency Medicine; 12(1):67-76.
[5] Chen, R., Ovbiagele, B. and Feng, W. (2016). Diabetes and Stroke: Epidemiology, Pathophysiology, Pharmaceuticals and Outcomes. American Journal Medical Sciences; 351(4): 380–386.
[6] Chugh, C. (2019). Acute Ischemic Stroke: Management Approach. Indian Journal Critical Care Medicine; 23(2): 140–146.
[7] Danesi M., Okubadejo N., Ojini F. (2007). Prevalence of stroke in an urban, mixed-income community in Lagos, Nigeria. Neuroepidemiology; 28(4):216-23.
[8] Danziger A. (2018). https://emedicine.medscape.com/article/338385- overview?reg=1&icd=login_success_email_match_norm#a1 Accessed on 18/05/2023
[9] Donnan, G. A., Fisher, M.,Macleod,M. and Davis,S. M.(2008). Stroke. Lancet;371:1612–23.
[10] Ekeh, B., Ogunniyi, A., Isamade, E. and Ekrikpo, U. (2015). Stroke mortality and its predictors in a Nigerian teaching hospital. African Health Science; 15(1): 74–81.
[11] Elugwu, C. H., Idigo, F. U., Makata, N. E., Ugwu, A. C., Ohagwu, C. C., Eze, J. C., and Ikegwuonu, N. (2023). Interprofessional learning impacts on professional dynamics among health professionals in Southeastern Nigeria. IJRDO -Journal of Health Sciences and Nursing; 9(1), 1-8. https://doi.org/10.53555/hsn.v9i1.5564.
[12] Gkantzios, A., Kokkotis, C., Tsiptsios, D., Moustakidis, S., Gkartzonika, E., Avramidis, T., Aggelousis, N. and Vadikolias, K. (2023). Evaluation of Blood Biomarkers and Parameters for the Prediction of Stroke Survivors’ Functional Outcome upon Discharge Utilizing Explainable Machine Learning. Diagnostics; 13, 532- 50.
[13] Hsia A. W, Castle A., Wing J. J, Edwards D. F, Brown N. C, Higgins T. M, Wallace J. L, Koslosky S. S, Gibbons M. C, Sánchez B. N, Fokar A., Shara N., Morgenstern L. B., Kidwell C. S. (2011). Understanding reasons for delay in seeking acute stroke care in an underserved urban population. Stroke; 42(6):1697-701.
[14] Kelly-Hayes M. (2010). Influence of age and health behaviors on stroke risk: lessons from longitudinal studies. Journal of American Geriatrics Society. 2(2): S325.
[15] Kissela B. M., Khoury J. C., Alwell K., Moomaw C. J., Woo D., Adeoye O., Flaherty M. L., Khatri P., Ferioli S., De Los Rios La Rosa F., Broderick J. P., Kleindorfer D. O. (2012). Age at stroke: temporal trends in stroke incidence in a large, biracial population. Neurology. 23;79(17):1781-7
[16] Kuriakose, D. and Xiao, Z. (2020). Pathophysiology and Treatment of Stroke: Present Status and Future Perspectives. International Journal Molecular Science; 21(20): 7609.
[17] Mehndiratta P., Wasay M., Mehndiratta M. M. (2015). Implications of female sex on stroke risk factors, care, outcome and rehabilitation: an Asian perspective. Cerebrovascular Disease. 39, 302–308.
[18] Nor A. M, Davis J., Sen B. (2005). The Recognition of Stroke in the Emergency Room (ROSIER) scale: development and validation of a stroke recognition instrument. Lancet Neurology; 4:727-734.
[19] Nwosu M. C. (2001). Epidemiology of stroke an overview. Journal of Medical Investigation and Practice; 3:14-22.
[20] Owolabi M. O. (2013). Consistent determinants of poststroke health-related quality of life across diverse cultures: Berlin-Ibadan study. Acta Neurologica Scandinavica; 128(5):311- 320.
[21] Paul S. L, Srikanth V. K., and Thrift A. G. (2007). The large and growing burden of stroke. Current Drug Targets; 8:786-93.
[22] Reeves M. J., Bushnell C. D., Howard G., Gargano J. W., Duncan P. W., Lynch G., Khatiwoda A., Lisabeth L. (2008) Sex differences in stroke: epidemiology, clinical presentation, medical care, and outcomes. Lancet Neurology; 7(10):915-26.
[23] Sacco R. L., Kasner S. E., Broderick J. P. (2013). An updated definition of stroke for the 21st century: a statement for healthcare professionals from the American Heart Association /American Stroke Association. Stroke; 44:2064-2089.
[24] Salvadori E., Papi G., Insalata G., Rinnoci V.., Donnini I., Martini M., Falsini C., Hakiki B., Romoli A., Barbato C., Polcaro P., Casamorata F., Macchi C., Cecchi F., Poggesi A. (2020). Comparison between Ischemic and Hemorrhagic Strokes in Functional Outcome at Discharge from an Intensive Rehabilitation Hospital. Diagnostics (Basel);11(1):38.
[25] Ugwuanyi, D. C., Sibeudu, T. F., Irole, C. P., Ogolodom, M. P., Nwagbara, C. T., Ibekwe, A. M. and Mbaba, A. N. (2020). Evaluation of common findings in brain computerized tomography (CT) scan: A single center study. AIMS Neuroscience; 7( 3): 311–318.
[26] Yu C., An Z., Zhao W., Wang W., Gao C., Liu S., Wang J., Wu J. (2015). Sex Differences in Stroke Subtypes, Severity, Risk Factors, and Outcomes among Elderly Patients with Acute Ischemic Stroke. Front Aging Neuroscience; 7:174.
Copyright (c) 2023 IJRDO -JOURNAL OF HEALTH SCIENCES AND NURSING
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Author(s) and co-author(s) jointly and severally represent and warrant that the Article is original with the author(s) and does not infringe any copyright or violate any other right of any third parties, and that the Article has not been published elsewhere. Author(s) agree to the terms that the IJRDO Journal will have the full right to remove the published article on any misconduct found in the published article.
