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DOI: 10.4103/0976-3147.188627
Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach
Publication History
Publication Date:
26 September 2019 (online)
ABSTRACT
An aneurysmal subarachnoid hemorrhage (aSAH) carries a high disability burden. The true impact of rurality as a predictor of outcome severity is unknown. Our aim is to clarify the relationship between the proposed explanations of regional and rural health disparities linked to severity of outcome following an aSAH. An initial literature search identified limited data directly linking geographical location, rurality, rural vulnerability, and aSAH. A further search noting parallels with ischemic stroke and acute myocardial infarct literature presented a number of diverse and interrelated predictors. This a priori knowledge informed the development of a conceptual framework that proposes the relationship between rurality and severity of outcome following an aSAH utilizing structural equation modeling. The presented conceptual framework explores a number of system, environmental, and modifiable risk factors. Socioeconomic characteristics, modifiable risk factors, and timely treatment that were identified as predictors of severity of outcome following an aSAH and within each of these defined predictors a number of contributing specific individual predictors are proposed. There are considerable gaps in the current knowledge pertaining to the impact of rurality on the severity of outcome following an aSAH. Absent from the literature is any investigation of the cumulative impact and multiplicity of risk factors associated with rurality. The proposed conceptual framework hypothesizes a number of relationships between both individual level and system level predictors, acknowledging that intervening predictors may mediate the effect of one variable on another.
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References
- 1 Al-Khindi T, Macdonald RL, Schweizer TA. Cognitive and functional outcome after aneurysmal subarachnoid hemorrhage. Stroke 2010; 41: e519-36
- 2 Khan M, Ahmed B, Ahmed M, Najeeb M, Raza E, Khan F. et al. Functional, cognitive and psychological outcomes, and recurrent vascular events in Pakistani stroke survivors: A cross sectional study. BMC Res Notes 2012; 5: 89
- 3 Togha M, Sahraian MA, Khorram M, Khashayar P. Warning signs and symptoms of subarachnoid hemorrhage. South Med J 2009; 102: 21-4
- 4 Nichols LJ, Smith L, Allen PL. Pathways to enhancing the quality of stroke care through national data monitoring systems for hospitals. Med J Aust 2014; 200: 392-3
- 5 Godley J, McLaren L. Socioeconomic status and body mass index in Canada: Exploring measures and mechanisms. Can Rev Sociol 2010; 47: 381-403
- 6 Kim AS, Johnston SC. Global variation in the relative burden of stroke and ischemic heart disease. Circulation 2011; 124: 314-23
- 7 Stevenson CE, Mannan H, Peeters A, Walls H, Magliano DJ, Shaw JE. et al. The effect of modifiable risk factors on geographic mortality differentials: A modelling study. BMC Public Health 2012; 12: 79
- 8 Beseoglu K, Holtkamp K, Steiger HJ, Hänggi D. Fatal aneurysmal subarachnoid haemorrhage: Causes of 30-day in-hospital case fatalities in a large single-centre historical patient cohort. Clin Neurol Neurosurg 2013; 115: 77-81
- 9 Zhang J, Liu G, Arima H, Li Y, Cheng G, Shiue I. et al. Incidence and risks of subarachnoid hemorrhage in China. Stroke 2013; 44: 2891-3
- 10 Davis S, Bartlett H. Healthy ageing in rural Australia: Issues and challenges. Australas J Ageing 2008; 27: 56-60
- 11 Jackson JE, Doescher MP, Jerant AF, Hart LG. A national study of obesity prevalence and trends by type of rural county. J Rural Health 2005; 21: 140-8
- 12 Connolly Jr ES, Rabinstein AA, Carhuapoma JR, Derdeyn CP, Dion J, Higashida RT. et al. Guidelines for the management of aneurysmal subarachnoid hemorrhage: A guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 2012; 43: 1711-37
- 13 Boscoe FP, Henry KA, Zdeb MS. A nationwide comparison of driving distance versus straight-line distance to hospitals. Prof Geogr 2012; 64: 1-12
- 14 Jordan H, Roderick P, Martin D, Barnett S. Distance, rurality and the need for care: Access to health services in South West England. Int J Health Geogr 2004; 3: 21
- 15 Kupek E. Beyond logistic regression: Structural equations modelling for binary variables and its application to investigating unobserved confounders. BMC Med Res Methodol 2006; 6: 13
- 16 Wu JR, Moser DK, Riegel B, McKinley S, Doering LV. Impact of prehospital delay in treatment seeking on in-hospital complications after acute myocardial infarction. J Cardiovasc Nurs 2011; 26: 184-93
- 17 Beran TN, Violato C. Structural equation modeling in medical research: A primer. BMC Res Notes 2010; 3: 267
- 18 Fox-Wasylyshyn SM, El-Masri M, Artinian NT. Testing a model of delayed care-seeking for acute myocardial infarction. Clin Nurs Res 2010; 19: 38-54
- 19 Jakovljevic D, Sivenius J, Sarti C, Torppa J, Mähönen M, Immonen-Räihä P. et al. Socioeconomic inequalities in the incidence, mortality and prognosis of subarachnoid hemorrhage: The FINMONICA stroke register. Cerebrovasc Dis 2001; 12: 7-13
- 20 Schievink WI, Riedinger M, Jhutty TK, Simon P. Racial disparities in subarachnoid hemorrhage mortality: Los Angeles County, California, 1985-1998. Neuroepidemiology 2004; 23: 299-305
- 21 Kapral MK, Wang H, Mamdani M, Tu JV. Effect of socioeconomic status on treatment and mortality after stroke. Stroke 2002; 33: 268-73
- 22 Strong K, Mathers C, Bonita R. Preventing stroke: Saving lives around the world. Lancet Neurol 2007; 6: 182-7
- 23 Heeley EL, Wei JW, Carter K, Islam MS, Thrift AG, Hankey GJ. et al. Socioeconomic disparities in stroke rates and outcome: Pooled analysis of stroke incidence studies in Australia and New Zealand. Med J Aust 2011; 195: 10-4
- 24 Humphreys JS. Delimiting ’rural’: Implications of an agreed ’rurality’ index for healthcare planning and resource allocation. Aust J Rural Health 1998; 6: 212-6
- 25 James R. Participation disadvantage in Australian higher education: An analysis of some effects of geographical location and socioeconomic status. High Educ 2001; 42: 455-72
- 26 Eberhardt MS, Pamuk ER. The importance of place of residence: Examining health in rural and nonrural areas. Am J Public Health 2004; 94: 1682-6
- 27 Australian Institute of Health and Welfare. Rural, Regional and Remote Health: Indicators of Health System Performance. Canberra: Australian Institute of Health and Welfare; 2008
- 28 Zahnd WE, Scaife SL, Francis ML. Health literacy skills in rural and urban populations. Am J Health Behav 2009; 33: 550-7
- 29 Alkadry MG, Wilson C, Nicholson D. Stroke awareness among rural residents: The case of West Virginia. Soc Work Health Care 2005; 42: 73-92
- 30 Larsen CC, Eskesen V, Hauerberg J, Olesen C, Romner B, Astrup J. Considerable delay in diagnosis and acute management of subarachnoid haemorrhage. Dan Med Bull 2010; 57: A4139
- 31 Langagergaard V, Palnum KH, Mehnert F, Ingeman A, Krogh BR, Bartels P. et al. Socioeconomic differences in quality of care and clinical outcome after stroke: A nationwide population-based study. Stroke 2011; 42: 2896-902
- 32 Jaja BN, Saposnik G, Nisenbaum R, Schweizer TA, Reddy D, Thorpe KE. et al. Effect of socioeconomic status on inpatient mortality and use of postacute care after subarachnoid hemorrhage. Stroke 2013; 44: 2842-7
- 33 Addo J, Ayerbe L, Mohan KM, Crichton S, Sheldenkar A, Chen R. et al. Socioeconomic status and stroke: An updated review. Stroke 2012; 43: 1186-91
- 34 Hartley D. Rural health disparities, population health, and rural culture. Am J Public Health 2004; 94: 1675-8
- 35 Kerr GD, Slavin H, Clark D, Coupar F, Langhorne P, Stott DJ. Do vascular risk factors explain the association between socioeconomic status and stroke incidence: A meta-analysis. Cerebrovasc Dis 2011; 31: 57-63
- 36 Thorogood M, Connor M, Tollman S, Lewando Hundt G, Fowkes G, Marsh J. A cross-sectional study of vascular risk factors in a rural South African population: Data from the Southern African stroke prevention initiative (SASPI). BMC Public Health 2007; 7: 326
- 37 Korja M, Silventoinen K, Laatikainen T, Jousilahti P, Salomaa V, Hernesniemi J. et al. Risk factors and their combined effects on the incidence rate of subarachnoid hemorrhage – a population-based cohort study. PLoS One 2013; 8: e73760
- 38 Larrew T, Pryor 3rd W, Weinberg J, Webb S, Battenhouse H, Turk AS. et al. Aneurysmal subarachnoid hemorrhage: A statewide assessment of outcome based on risk factors, aneurysm characteristics, and geo-demography. J Neurointerv Surg 2015; 7: 855-60
- 39 Murthy SB, Moradiya Y, Shah S, Naval NS. In-hospital outcomes of aneurysmal subarachnoid hemorrhage associated with cocaine use in the USA. J Clin Neurosci 2014; 21: 2088-91
- 40 Ruigrok YM, Buskens E, Rinkel GJ. Attributable risk of common and rare determinants of subarachnoid hemorrhage. Stroke 2001; 32: 1173-5
- 41 Yamada S, Koizumi A, Iso H, Wada Y, Watanabe Y, Date C. et al. Risk factors for fatal subarachnoid hemorrhage: The Japan collaborative cohort study. Stroke 2003; 34: 2781-7
- 42 De Marchis GM, Lantigua H, Schmidt JM, Lord AS, Velander AJ, Fernandez A. et al. Impact of premorbid hypertension on haemorrhage severity and aneurysm rebleeding risk after subarachnoid haemorrhage. J Neurol Neurosurg Psychiatry 2014; 85: 56-9
- 43 Tang C, Zhang TS, Zhou LF. Risk factors for rebleeding of aneurysmal subarachnoid hemorrhage: A meta-analysis. PLoS One 2014; 9: e99536
- 44 Chotai S, Ahn SY, Moon HJ, Kim JH, Chung HS, Chung YG. et al. Prediction of outcomes in young adults with aneurysmal subarachnoid hemorrhage. Neurol Med Chir (Tokyo) 2013; 53: 157-62
- 45 McLaughlin D, Hockey R, Mishra G. Heart disease in women in remote Australia: Urban-rural differences after adjusting for lifestyle behaviours and socio-demographic factors. Aust N Z J Public Health 2013; 37: 90
- 46 Janus ED, Bunker SJ, Kilkkinen A, McNamara K, Philpot B, Tideman P. et al. Prevalence, detection and drug treatment of hypertension in a rural Australian population: The greater green triangle risk factor study 2004-2006. Intern Med J 2008; 38: 879-86
- 47 de Rooij NK, Rinkel GJ, Dankbaar JW, Frijns CJ. Delayed cerebral ischemia after subarachnoid hemorrhage: A systematic review of clinical, laboratory, and radiological predictors. Stroke 2013; 44: 43-54
- 48 Isaksen J, Egge A, Waterloo K, Romner B, Ingebrigtsen T. Risk factors for aneurysmal subarachnoid haemorrhage: The Tromsø study. J Neurol Neurosurg Psychiatry 2002; 73: 185-7
- 49 Dalbjerg SM, Larsen CC, Romner B. Risk factors and short-term outcome in patients with angiographically negative subarachnoid hemorrhage. Clin Neurol Neurosurg 2013; 115: 1304-7
- 50 Inagawa T, Yahara K, Ohbayashi N. Risk factors associated with cerebral vasospasm following aneurysmal subarachnoid hemorrhage. Neurol Med Chir (Tokyo) 2014; 54: 465-73
- 51 Hillbom M, Saloheimo P, Juvela S. Alcohol consumption, blood pressure, and the risk of stroke. Curr Hypertens Rep 2011; 13: 208-13
- 52 Leppälä JM, Paunio M, Virtamo J, Fogelholm R, Albanes D, Taylor PR. et al. Alcohol consumption and stroke incidence in male smokers. Circulation 1999; 100: 1209-14
- 53 Inder KJ, Handley TE, Fitzgerald M, Lewin TJ, Coleman C, Perkins D. et al. Individual and district-level predictors of alcohol use: Cross sectional findings from a rural mental health survey in Australia. BMC Public Health 2012; 12: 586
- 54 Catalano AR, Winn HR, Gordon E, Frontera JA. Impact of interhospital transfer on complications and outcome after intracranial hemorrhage. Neurocrit Care 2012; 17: 324-33
- 55 Nuño M, Patil CG, Lyden P, Drazin D. The effect of transfer and hospital volume in subarachnoid hemorrhage patients. Neurocrit Care 2012; 17: 312-23
- 56 Drazin D, Rosner J, Nuño M, Alexander MJ, Schievink WI, Palestrant D. et al. Type of admission is associated with outcome of spontaneous subarachnoid hemorrhage. Int J Stroke 2015; 10: 529-33
- 57 Edlow JA, Malek AM, Ogilvy CS. Aneurysmal subarachnoid hemorrhage: Update for emergency physicians. J Emerg Med 2008; 34: 237-51
- 58 Lorenzi L, Kerr ME, Yonas H, Alexander S, Crago E. Influence of delaying treatment after symptoms develop from subarachnoid hemorrhage: A preliminary analysis. J Neurosci Nurs 2003; 35: 210-4
- 59 Singh A, Soares WE. Management strategies for acute headache in the emergency department. Emerg Med Pract 2012; 14: 1-23
- 60 Miyazaki T, Ohta F, Moritake K, Nagase A, Kagawa T. The key to improving prognosis for aneurysmal subarachnoid hemorrhage remains in the pre-hospitalization period. Surg Neurol 2006; 65: 360-5
- 61 Newman-Toker DE, Moy E, Valente E, Coffey R, Hines AL. Missed diagnosis of stroke in the emergency department: A cross-sectional analysis of a large population-based sample. Diagnosis 2014; 1: 155-66
- 62 Murata A, Matsuda S. Association between ambulance distance to hospitals and mortality from acute diseases in Japan: National database analysis. J Public Health Manag Pract 2013; 19: E23-8
- 63 Sharma S, Gomez D, de Mestral C, Hsiao M, Rutka J, Nathens AB. Emergency access to neurosurgical care for patients with traumatic brain injury. J Am Coll Surg 2014; 218: 51-7
- 64 Leira EC, Hess DC, Torner JC, Adams Jr HP. Rural-urban differences in acute stroke management practices: A modifiable disparity. Arch Neurol 2008; 65: 887-91
- 65 Lovelock CE, Rinkel GJ, Rothwell PM. Time trends in outcome of subarachnoid hemorrhage: Population-based study and systematic review. Neurology 2010; 74: 1494-501
- 66 Sarmiento JM, Mukherjee D, Nosova K, Schievink WI, Alexander MJ, Patil CG. et al. Predictors of treatment delay in aneurysmal subarachnoid hemorrhage patients. J Neurol Surg A Cent Eur Neurosurg 2015; 76: 46-55
- 67 Smith KB, Humphreys JS, Wilson MG. Addressing the health disadvantage of rural populations: How does epidemiological evidence inform rural health policies and research?. Aust J Rural Health 2008; 16: 56-66
- 68 Guly HR. Diagnostic errors in an accident and emergency department. Emerg Med J 2001; 18: 263-9
- 69 Kowalski RG, Claassen J, Kreiter KT, Bates JE, Ostapkovich ND, Connolly ES. et al. Initial misdiagnosis and outcome after subarachnoid hemorrhage. JAMA 2004; 291: 866-9
- 70 Vermeulen MJ, Schull MJ. Missed diagnosis of subarachnoid hemorrhage in the emergency department. Stroke 2007; 38: 1216-21
- 71 Bø SH, Davidsen EM, Gulbrandsen P, Dietrichs E. Acute headache: A prospective diagnostic work-up of patients admitted to a general hospital. Eur J Neurol 2008; 15: 1293-9
- 72 Bardach NS, Olson SJ, Elkins JS, Smith WS, Lawton MT, Johnston SC. Regionalization of treatment for subarachnoid hemorrhage: A cost-utility analysis. Circulation 2004; 109: 2207-12
- 73 Cong W, Zhongxin Z, Tiangui L, Zhang Y, Min H, Chao Y. Risk factors for rebleeding of aneurysmal subarachnoid hemorrhage based on the analysis of on-admission information. Turk Neurosurg 2012; 22: 675-81
- 74 Algra AM, Klijn CJ, Helmerhorst FM, Algra A, Rinkel GJ. Female risk factors for subarachnoid hemorrhage: A systematic review. Neurology 2012; 79: 1230-6
- 75 Schöller K, Massmann M, Markl G, Kunz M, Fesl G, Brückmann H. et al. Aneurysmal subarachnoid hemorrhage in elderly patients: Long-term outcome and prognostic factors in an interdisciplinary treatment approach. J Neurol 2013; 260: 1052-60
- 76 Claassen J, Carhuapoma JR, Kreiter KT, Du EY, Connolly ES, Mayer SA. Global cerebral edema after subarachnoid hemorrhage: Frequency, predictors, and impact on outcome. Stroke 2002; 33: 1225-32
- 77 Naidech AM, Janjua N, Kreiter KT, Ostapkovich ND, Fitzsimmons BF, Parra A. et al. Predictors and impact of aneurysm rebleeding after subarachnoid hemorrhage. Arch Neurol 2005; 62: 410-6
- 78 Wostrack M, Sandow N, Vajkoczy P, Schatlo B, Bijlenga P, Schaller K. et al. Subarachnoid haemorrhage WFNS grade V: Is maximal treatment worthwhile?. Acta Neurochir (Wien) 2013; 155: 579-86
- 79 Bollen KA, Bauldry S. Three Cs in measurement models: Causal indicators, composite indicators, and covariates. Psychol Methods 2011; 16: 265-84
- 80 Sharma B, Satija V, Dubey P, Panagariya A. Subarachnoid hemorrhage with transient ischemic attack: Another masquerader in cerebral venous thrombosis. Indian J Med Sci 2010; 64: 85-9
- 81 Hays RD, Revicki D, Coyne KS. Application of structural equation modeling to health outcomes research. Eval Health Prof 2005; 28: 295-309