The effect of cognitive dysfunction on mid- and long-term mortality after vascular surgery

András Szabó, Krisztina Tóth, Ádám Nagy, Dominika Domokos, Nikoletta Czobor, Csaba Eke, Ágnes Sándor, Béla Merkely, Éva Susánszky, János Gál, Andrea Székely, András Szabó, Krisztina Tóth, Ádám Nagy, Dominika Domokos, Nikoletta Czobor, Csaba Eke, Ágnes Sándor, Béla Merkely, Éva Susánszky, János Gál, Andrea Székely

Abstract

Background: In recent decades, previous studies have noted the importance of frailty, which is a frequently used term in perioperative risk evaluations. Psychological and socioeconomical domains were investigated as part of frailty syndrome. The aim of this study was to assess the importance of these factors in mortality after vascular surgery.

Methods: In our prospective, observational study (ClinicalTrials.gov Identifier: NCT02224222), we examined 164 patients who underwent elective vascular surgery between 2014 and 2017. At the outpatient anaesthesiology clinic, patients completed a questionnaire about cognitive functions, depression and anxiety, social support and self-reported quality of life were assessed using a comprehensive frailty index, in addition to medical variables. Propensity score matching was performed to analyse the difference between patients and controls in a nationwide population cohort. The primary outcome was 4 year mortality. The Kaplan-Meier method and Cox regression analysis were used for statistical analyses.

Results: The patients' mean age was 67.05 years (SD: 9.49 years). Mini-Mental State Examination scores of less than 27 points were recorded for 41 patients. Overall mortality rates were 22.4 and 47.6% in the control and cognitive impairment groups, respectively (p = 0.013). In the univariate Cox regression analysis, cognitive impairment measured using age- and education-adjusted MMSE scores increased the risk of mortality (AHR: 2.842, 95% CI: 1.389-5.815, p = 0.004).

Conclusion: Even mild cognitive dysfunction measured preoperatively using the MMSE represents a potentially important risk factor for mortality after vascular surgery.

Keywords: Cognitive dysfunction; Mini mental state examination; Perioperative risk factors; Psychosocial factors; Social support; Vascular surgery.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
KM curve for MMSE categories and mortality: a. MMSE groups: 27 points and higher, 24–26 points, 23 points and lower. b. MMSE groups: age and education adjusted normal cognitive function and cognitive impairment. c. MMSE groups: 27 points and higher, 26 points and lower (modified cut-off value). Legend: In Fig. 1/A log-rank pairwise comparison was performed: an MMSE score of 27 points or higher vs. 24–26 points, p = 0.531; 27 points or higher vs. 23 or fewer points, p = 0.007; 24–26 points and 23 points and below, p = 0.120
Fig. 2
Fig. 2
Effects of variables on overall mortality in the multivariate Cox regression model

References

    1. Alvarez-Nebreda ML, et al. Recommendations for Preoperative Management of Frailty from the Society for Perioperative Assessment and Quality Improvement (SPAQI) J Clin Anesthesia. 2018;47:33–42. doi: 10.1016/j.jclinane.2018.02.011.
    1. Ambler GK, et al. Effect of frailty on short- and mid-term outcomes in vascular surgical patients. Br J Surg. 2015;102(6):638–645. doi: 10.1002/bjs.9785.
    1. Graham A, Brown CH. Frailty, aging, and cardiovascular surgery. Anesth Analg. 2017;124(4):1053–1060. doi: 10.1213/ANE.0000000000001560.
    1. Morley JE, et al. Frailty consensus: a call to action. J Am Med Dir Assoc. 2013;14(6):392–397. doi: 10.1016/j.jamda.2013.03.022.
    1. Bandeen-Roche K, et al. Frailty in Older Adults: A Nationally Representative Profile in the United States. J Gerontol A Biol Sci Med Sci. 2015;70(11):1427–1434. doi: 10.1093/gerona/glv133.
    1. Cawthon PM, et al. Frailty in older men: prevalence, progression, and relationship with mortality. J Am Geriatr Soc. 2007;55(8):1216–1223. doi: 10.1111/j.1532-5415.2007.01259.x.
    1. Evenhuis HM, et al. Frailty and disability in older adults with intellectual disabilities: results from the healthy ageing and intellectual disability study. J Am Geriatr Soc. 2012;60(5):934–938. doi: 10.1111/j.1532-5415.2012.03925.x.
    1. Lakey SL, et al. Antidepressant use, depressive symptoms, and incident frailty in women aged 65 and older from the Women's Health Initiative Observational Study. J Am Geriatr Soc. 2012;60(5):854–861. doi: 10.1111/j.1532-5415.2012.03940.x.
    1. Haynes SR, Lawler PG. An assessment of the consistency of ASA physical status classification allocation. Anaesthesia. 1995;50(3):195–199. doi: 10.1111/j.1365-2044.1995.tb04554.x.
    1. Golubovic M, et al. Potential New Approaches in Predicting Adverse Cardiac Events One Month after Major Vascular Surgery. Med Princ Pract. 2019;28(1):63–69. doi: 10.1159/000495079.
    1. Golubovic M, et al. A Risk Stratification Model for Cardiovascular Complications during the 3-Month Period after Major Elective Vascular Surgery. Biomed Res Int. 2018;2018:4381527. doi: 10.1155/2018/4381527.
    1. Lima DFT, et al. Outcome prediction with Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity score system in elderly patients submitted to elective surgery. Saudi J Anaesth. 2019;13(1):46–51.
    1. Reis P, et al. Predicting mortality in patients admitted to the intensive care unit after open vascular surgery. Surg Today. 2019;49(10):836–842. doi: 10.1007/s00595-019-01805-w.
    1. Crum RM, et al. Population-based norms for the Mini-Mental State Examination by age and educational level. JAMA. 1993;269(18):2386–2391. doi: 10.1001/jama.1993.03500180078038.
    1. Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–198. doi: 10.1016/0022-3956(75)90026-6.
    1. Bartos A, Raisova M. The Mini-Mental State Examination: Czech Norms and Cutoffs for Mild Dementia and Mild Cognitive Impairment due to Alzheimer's Disease. Dement Geriatr Cogn Disord. 2016;42(1–2):50–57. doi: 10.1159/000446426.
    1. Xu G, et al. Screening for mild cognitive impairment (MCI) utilizing combined mini-mental-cognitive capacity examinations for identifying dementia prodromes. Int J Geriatr Psychiatry. 2002;17(11):1027–1033. doi: 10.1002/gps.744.
    1. Tang-Wai DF, et al. Comparison of the short test of mental status and the mini-mental state examination in mild cognitive impairment. Arch Neurol. 2003;60(12):1777–1781. doi: 10.1001/archneur.60.12.1777.
    1. Koivumaa-Honkanen H, et al. Self-reported life satisfaction and 20-year mortality in healthy Finnish adults. Am J Epidemiol. 2000;152(10):983–991. doi: 10.1093/aje/152.10.983.
    1. Guillen-Riquelme A, Buela-Casal G. Meta-analysis of group comparison and meta-analysis of reliability generalization of the State-Trait Anxiety Inventory Questionnaire (STAI) Rev Esp Salud Publica. 2014;88(1):101–112. doi: 10.4321/S1135-57272014000100007.
    1. Kvaal K, Laake K, Engedal K. Psychometric properties of the state part of the Spielberger State-Trait Anxiety Inventory (STAI) in geriatric patients. Int J Geriatr Psychiatry. 2001;16(10):980–986. doi: 10.1002/gps.458.
    1. Kopp MS. Psychophysiological characteristics of anxiety patients and controls. Psychother Psychosom. 1989;52(1–3):74–79. doi: 10.1159/000288302.
    1. Beck AT, et al. An inventory for measuring depression. Arch Gen Psychiatry. 1961;4:561–571. doi: 10.1001/archpsyc.1961.01710120031004.
    1. Beck AT, et al. Comparison of Beck Depression Inventories -IA and -II in psychiatric outpatients. J Pers Assess. 1996;67(3):588–597. doi: 10.1207/s15327752jpa6703_13.
    1. Robinson BE, Kelley L. Concurrent validity of the Beck Depression Inventory as a measure of depression. Psychol Rep. 1996;79(3 Pt 1):929–930. doi: 10.2466/pr0.1996.79.3.929.
    1. Palinkas A, et al. Associations between untreated depression and secondary health care utilization in patients with hypertension and/or diabetes. Soc Psychiatry Psychiatr Epidemiol. 2019;54(2):255–276. doi: 10.1007/s00127-018-1545-7.
    1. Yesavage JA, et al. Development and validation of a geriatric depression screening scale: a preliminary report. J Psychiatr Res. 1982;17(1):37–49. doi: 10.1016/0022-3956(82)90033-4.
    1. Hinz A, et al. Frequency of somatic symptoms in the general population: Normative values for the Patient Health Questionnaire-15 (PHQ-15) J Psychosom Res. 2017;96:27–31. doi: 10.1016/j.jpsychores.2016.12.017.
    1. Kroenke K, Spitzer RL, Williams JB. The PHQ-15: validity of a new measure for evaluating the severity of somatic symptoms. Psychosom Med. 2002;64(2):258–266. doi: 10.1097/00006842-200203000-00008.
    1. Kroenke K, et al. The Patient Health Questionnaire Somatic, Anxiety, and Depressive Symptom Scales: a systematic review. Gen Hosp Psychiatry. 2010;32(4):345–359. doi: 10.1016/j.genhosppsych.2010.03.006.
    1. Devins GM. Using the illness intrusiveness ratings scale to understand health-related quality of life in chronic disease. J Psychosom Res. 2010;68(6):591–602. doi: 10.1016/j.jpsychores.2009.05.006.
    1. Devins GM, et al. The emotional impact of end-stage renal disease: importance of patients’ perception of intrusiveness and control. Int J Psychiatry Med. 1983;13(4):327–343. doi: 10.2190/5DCP-25BV-U1G9-9G7C.
    1. Sarason IG, et al. A Brief Measure of Social Support: Practical and Theoretical Implications. J Soc Person Relationships. 1987;4(4):497–510. doi: 10.1177/0265407587044007.
    1. Assari S, Caldwell CH. Low Family Support and Risk of Obesity among Black Youth: Role of Gender and Ethnicity. Children (Basel). 2017;4(5):36. 10.3390/children4050036.
    1. Kao TA, Caldwell CH. Family Efficacy within Ethnically Diverse Families: A Qualitative Study. Fam Process. 2017;56(1):217–233. doi: 10.1111/famp.12149.
    1. Xue Y, Zimmerman MA, Caldwell CH. Neighborhood residence and cigarette smoking among urban youths: the protective role of prosocial activities. Am J Public Health. 2007;97(10):1865–1872. doi: 10.2105/AJPH.2005.081307.
    1. Soldatos CR, Dikeos DG, Paparrigopoulos TJ, et al. J Psychosom Res. 2000;48(6):555–560. doi: 10.1016/S0022-3999(00)00095-7.
    1. Susányszky É., S.A., A Hungarostudy 2013 felmérés módszertana. Magyar Lelkiállapot, 2013. 2013: p. 13–21. ISSN - 206 437 21.
    1. Susanszky É., S.A., Hungarostudy 2013. Database - Accessed 25 Oct 2020.
    1. Shi S, et al. Comparative utility of frailty to a general prognostic score in identifying patients at risk for poor outcomes after aortic valve replacement. BMC Geriatrics. 2020;20(1):38. doi: 10.1186/s12877-020-1440-4.
    1. Richards SJG, et al. Frailty in surgical patients. Int J Colorectal Dis. 2018;33(12):1657–1666. doi: 10.1007/s00384-018-3163-y.
    1. Lee H, Lee E, Jang IY. Frailty and Comprehensive Geriatric Assessment. J Korean Med Sci. 2020;35(3):e16. doi: 10.3346/jkms.2020.35.e16.
    1. Partridge JS, et al. Frailty and poor functional status are common in arterial vascular surgical patients and affect postoperative outcomes. Int J Surg. 2015;18:57–63. doi: 10.1016/j.ijsu.2015.04.037.
    1. Ghaffarian AA, et al. Prognostic implications of diagnosing frailty and sarcopenia in vascular surgery practice. J Vasc Surg. 2019;70(3):892–900. doi: 10.1016/j.jvs.2018.11.025.
    1. Johnson RL, et al. Impact of Frailty on Outcomes After Primary and Revision Total Hip Arthroplasty. J Arthroplasty. 2019;34(1):56–64.e5. doi: 10.1016/j.arth.2018.09.078.
    1. Marshall L, Griffin R, Mundy J. Frailty assessment to predict short term outcomes after cardiac surgery. Asian Cardiovasc Thorac Ann. 2016;24(6):546–554. doi: 10.1177/0218492316653557.
    1. Skaar E, Øksnes A, Eide LSP, et al. Baseline frailty status and outcomes important for shared decision-making in older adults receiving transcatheter aortic valve implantation, a prospective observational study. Aging Clin Exp Res. 2020. 10.1007/s40520-020-01525-z.
    1. Mitchell AJ. A meta-analysis of the accuracy of the mini-mental state examination in the detection of dementia and mild cognitive impairment. J Psychiatr Res. 2009;43(4):411–431. doi: 10.1016/j.jpsychires.2008.04.014.
    1. Cserep Z, et al. Psychosocial factors and major adverse cardiac and cerebrovascular events after cardiac surgery. Interact Cardiovasc Thorac Surg. 2010;11(5):567–572. doi: 10.1510/icvts.2010.244582.
    1. Szekely A, et al. Anxiety predicts mortality and morbidity after coronary artery and valve surgery--a 4-year follow-up study. Psychosom Med. 2007;69(7):625–631. doi: 10.1097/PSY.0b013e31814b8c0f.
    1. Morin RT, Insel P, Bickford D, Nelson C, Mackin RS. Depression Severity, but Not Cognitive Impairment or Frailty, is Associated with Disability in Late-Life Depression. Clin Gerontol. 2020;43(4):411-19. 10.1080/07317115.2019.1699882. Epub 2019 Dec 21.
    1. Banik A, et al. Enabling, Not Cultivating: Received Social Support and Self-Efficacy Explain Quality of Life After Lung Cancer Surgery. Ann Behav Med. 2017;51(1):1–12. doi: 10.1007/s12160-016-9821-9.
    1. Colella TJ, King-Shier K. The effect of a peer support intervention on early recovery outcomes in men recovering from coronary bypass surgery: A randomized controlled trial. Eur J Cardiovasc Nurs. 2018;17(5):408–417. doi: 10.1177/1474515117725521.
    1. Neuling SJ, Winefield HR. Social support and recovery after surgery for breast cancer: frequency and correlates of supportive behaviours by family, friends and surgeon. Soc Sci Med. 1988;27(4):385–392. doi: 10.1016/0277-9536(88)90273-0.

Source: PubMed

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