Download PDF
J Neurol Surg B Skull Base 2022; 83(S 02): e31-e39
DOI: 10.1055/s-0040-1722664
Original Article

Effect of Household Income on Short-Term Outcomes Following Cerebellopontine Angle Tumor Resection

Vincent Huang
1   Department of Neurosurgery, Perelman School of Medicine University of Pennsylvania, Philadelphia, Pennsylvania, United States
,
Stephen P. Miranda
1   Department of Neurosurgery, Perelman School of Medicine University of Pennsylvania, Philadelphia, Pennsylvania, United States
,
Ryan Dimentberg
1   Department of Neurosurgery, Perelman School of Medicine University of Pennsylvania, Philadelphia, Pennsylvania, United States
,
Kaitlyn Shultz
2   Department of Mathematics, West Chester University of Pennsylvania, West Chester, Pennsylvania, United States
,
Scott D. McClintock
2   Department of Mathematics, West Chester University of Pennsylvania, West Chester, Pennsylvania, United States
,
Neil R. Malhotra
1   Department of Neurosurgery, Perelman School of Medicine University of Pennsylvania, Philadelphia, Pennsylvania, United States
› Author Affiliations
› Further Information
    Permissions and Reprints

Abstract

Objectives The objective of this study is to elucidate the impact of income on short-term outcomes in a cerebellopontine angle (CPA) tumor resection population.

Design This is a retrospective regression analysis.

Setting This study was done at a single, multihospital, urban academic medical center.

Participants Over 6 years (from June 7, 2013, to April 24, 2019), 277 consecutive CPA tumor cases were reviewed.

Main Outcome Measures Outcomes studied included readmission, emergency department evaluation, unplanned return to surgery, return to surgery after index admission, and mortality. Univariate analysis was conducted among the entire population with significance set at a p-value <0.05. The population was divided into quartiles based on median household income and univariate analysis conducted between the lowest (quartile 1 [Q1]) and highest (quartile 4 [Q4]) socioeconomic quartiles, with significance set at a p-value <0.05. Stepwise regression was conducted to determine the correlations among study variables and to identify confounding factors.

Results Regression analysis of 273 patients demonstrated decreased rates of unplanned reoperation (p = 0.015) and reoperation after index admission (p = 0.035) at 30 days with higher standardized income. Logistic regression between the lowest (Q1) and highest (Q4) socioeconomic quartiles demonstrated decreased unplanned reoperation (p = 0.045) and decreasing but not significant reoperation after index admission (p = 0.15) for Q4 patients. No significant difference was observed for other metrics of morbidity and mortality.

Conclusion Higher socioeconomic status is associated with decreased risk of unplanned reoperation following CPA tumor resection.

Keywords

cerebellopontine angle tumors - socioeconomic - outcome disparities - readmissions


Publication History

Received: 09 June 2020

Accepted: 01 November 2020

Article published online:
04 February 2021

© 2021. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Taylor LA, Tan AX, Coyle CE. et al. Leveraging the social determinants of health: what works?. PLoS One 2016; 11 (08) e0160217
    CrossrefPubMedGoogle Scholar
  • 2 Thornton RLJ, Glover CM, Cené CW, Glik DC, Henderson JA, Williams DR. Evaluating strategies for reducing health disparities by addressing the social determinants of health. Health Aff (Millwood) 2016; 35 (08) 1416-1423
    CrossrefPubMedGoogle Scholar
  • 3 Preda A, Voigt K. The social determinants of health: why should we care?. Am J Bioeth 2015; 15 (03) 25-36
    CrossrefPubMedGoogle Scholar
  • 4 Robeznieks A. New ICD-10 codes will help physicians tackle social barriers to care | American Medical Association. Published 2019. Accessed April 21, 2020 at: https://www.ama-assn.org/practice-management/digital/new-icd-10-codes-will-help-physicians-tackle-social-barriers-care
    Google Scholar
  • 5 Ultee KHJ, Tjeertes EKM, Bastos Gonçalves F. et al. The relation between household income and surgical outcome in the Dutch setting of equal access to and provision of healthcare. PLoS One 2018; 13 (01) e0191464
    CrossrefPubMedGoogle Scholar
  • 6 Hsieh N, Ruther M. Despite increased insurance coverage, nonwhite sexual minorities still experience disparities in access to care. Health Aff (Millwood) 2017; 36 (10) 1786-1794
    CrossrefPubMedGoogle Scholar
  • 7 Gattamorta KA, Salerno JP, Castro AJ. Intersectionality and health behaviors among US high school students: examining race/ethnicity, sexual identity, and sex. J Sch Health 2019; 89 (10) 800-808
    CrossrefPubMedGoogle Scholar
  • 8 Wilson Y, White A, Jefferson A, Danis M. Intersectionality in clinical medicine: the need for a conceptual framework. Am J Bioeth 2019; 19 (02) 8-19
    CrossrefPubMedGoogle Scholar
  • 9 Jackson JW, Williams DR, VanderWeele TJ. Disparities at the intersection of marginalized groups. Soc Psychiatry Psychiatr Epidemiol 2016; 51 (10) 1349-1359
    CrossrefPubMedGoogle Scholar
  • 10 Kapilashrami A, Marsden S. Examining intersectional inequalities in access to health (enabling) resources in disadvantaged communities in Scotland: advancing the participatory paradigm. Int J Equity Health 2018; 17 (01) 83
    CrossrefPubMedGoogle Scholar
  • 11 Ioannidou E. The sex and gender intersection in chronic periodontitis. Front Public Health 2017; 5: 189
    CrossrefPubMedGoogle Scholar
  • 12 Hahm HC, Cook BL, Ault-Brutus A, Alegría M. Intersection of race-ethnicity and gender in depression care: screening, access, and minimally adequate treatment. Psychiatr Serv 2015; 66 (03) 258-264
    CrossrefPubMedGoogle Scholar
  • 13 Agénor M, Abboud S, Delgadillo JG, Pérez AE, Peitzmeier SM, Borrero S. Intersectional nativity and racial/ethnic disparities in human papillomavirus vaccination initiation among U.S. women: a national population-based study. Cancer Causes Control 2018; 29 (10) 927-936
    CrossrefPubMedGoogle Scholar
  • 14 Mallucci CL, Ward V, Carney AS, O'Donoghue GM, Robertson I. Clinical features and outcomes in patients with non-acoustic cerebellopontine angle tumours. J Neurol Neurosurg Psychiatry 1999; 66 (06) 768-771
    CrossrefPubMedGoogle Scholar
  • 15 Briggs RJ, Fabinyi G, Kaye AH. Current management of acoustic neuromas: review of surgical approaches and outcomes. J Clin Neurosci 2000; 7 (06) 521-526
    CrossrefPubMedGoogle Scholar
  • 16 He X, Liu W, Wang Y, Zhang J, Liang B, Huang JH. Surgical management and outcome experience of 53 cerebellopontine angle meningiomas. Cureus 2017; 9 (08) e1538
    PubMedGoogle Scholar
  • 17 Agarwal V, Babu R, Grier J. et al. Cerebellopontine angle meningiomas: postoperative outcomes in a modern cohort. Neurosurg Focus 2013; 35 (06) E10
    CrossrefPubMedGoogle Scholar
  • 18 Memari F, Hassannia F, Abtahi SHR. Surgical outcomes of cerebellopontine angle tumors in 50 cases. Iran J Otorhinolaryngol 2015; 27 (78) 29-34
    PubMedGoogle Scholar
  • 19 Gawande A. Why Doctors Hate Their Computers. New Yorker. November 2018. Accessed December 30, 2019 at: https://www.newyorker.com/magazine/2018/11/12/why-doctors-hate-their-computers?verso=true
    Google Scholar
  • 20 Bonaventura A, Leale I, Carbone F. et al. Pre-surgery age-adjusted Charlson comorbidity index is associated with worse outcomes in acute cholecystitis. Dig Liver Dis 2019; 51 (06) 858-863
    CrossrefPubMedGoogle Scholar
  • 21 Chang C-M, Yin W-Y, Wei C-K. et al. Adjusted age-adjusted Charlson comorbidity index score as a risk measure of perioperative mortality before cancer surgery. PLoS One 2016; 11 (02) e0148076
    CrossrefPubMedGoogle Scholar
  • 22 Grossman R, Mukherjee D, Chang DC. et al. Preoperative Charlson comorbidity score predicts postoperative outcomes among older intracranial meningioma patients. World Neurosurg 2011; 75 (02) 279-285
    CrossrefPubMedGoogle Scholar
  • 23 Rueth NM, Parsons HM, Habermann EB. et al. Surgical treatment of lung cancer: predicting postoperative morbidity in the elderly population. J Thorac Cardiovasc Surg 2012; 143 (06) 1314-1323
    CrossrefPubMedGoogle Scholar
  • 24 Genther DJ, Gourin CG. Effect of comorbidity on short-term outcomes and cost of care after head and neck cancer surgery in the elderly. Head Neck 2015; 37 (05) 685-693
    CrossrefPubMedGoogle Scholar
  • 25 Smits A, Lopes A, Das N. et al. Surgical morbidity and clinical outcomes in ovarian cancer - the role of obesity. BJOG 2016; 123 (02) 300-308
    CrossrefPubMedGoogle Scholar
  • 26 Wilson JR, Tetreault LA, Schroeder G. et al. Impact of elevated body mass index and obesity on long-term surgical outcomes for patients with degenerative cervical myelopathy: analysis of a combined prospective dataset. Spine 2017; 42 (03) 195-201
    CrossrefPubMedGoogle Scholar
  • 27 Ri M, Miyata H, Aikou S. et al. Effects of body mass index (BMI) on surgical outcomes: a nationwide survey using a Japanese web-based database. Surg Today 2015; 45 (10) 1271-1279
    CrossrefPubMedGoogle Scholar
  • 28 Lio A, Bovio E, Nicolò F. et al. Influence of body mass index on outcomes of patients undergoing surgery for acute aortic dissection: a propensity-matched analysis. Tex Heart Inst J 2019; 46 (01) 7-13
    CrossrefPubMedGoogle Scholar
  • 29 Turan A, Mascha EJ, Roberman D. et al. Smoking and perioperative outcomes. Anesthesiology 2011; 114 (04) 837-846
    CrossrefPubMedGoogle Scholar
  • 30 Gajdos C, Hawn MT, Campagna EJ, Henderson WG, Singh JA, Houston T. Adverse effects of smoking on postoperative outcomes in cancer patients. Ann Surg Oncol 2012; 19 (05) 1430-1438
    CrossrefPubMedGoogle Scholar
  • 31 Kim JYS, Khavanin N, Rambachan A. et al. Surgical duration and risk of venous thromboembolism. JAMA Surg 2015; 150 (02) 110-117
    Google Scholar
  • 32 Chu D, Bakaeen FG, Wang XL, LeMaire SA, Coselli JS, Huh J. Does the duration of surgery affect outcomes in patients undergoing coronary artery bypass grafting?. Am J Surg 2008; 196 (05) 652-656
    CrossrefPubMedGoogle Scholar
  • 33 Phan K, Kim JS, Lee NJ, Kothari P, Cho SK. Relationship between ASA scores and 30-day readmissions in patients undergoing anterior cervical discectomy and fusion. Spine 2017; 42 (02) 85-91
    CrossrefPubMedGoogle Scholar
  • 34 Sauvanet A, Mariette C, Thomas P. et al. Mortality and morbidity after resection for adenocarcinoma of the gastroesophageal junction: predictive factors. J Am Coll Surg 2005; 201 (02) 253-262
    CrossrefPubMedGoogle Scholar
  • 35 Martsolf GR, Barrett ML, Weiss AJ. et al. Impact of race/ethnicity and socioeconomic status on risk-adjusted hospital readmission rates following hip and knee arthroplasty. J Bone Joint Surg Am 2016; 98 (16) 1385-1391
    CrossrefPubMedGoogle Scholar
  • 36 Seicean A, Seicean S, Neuhauser D, Benzel EC, Weil RJ. The influence of race on short-term outcomes after laminectomy and/or fusion spine surgery. Spine 2017; 42 (01) 34-41
    CrossrefPubMedGoogle Scholar
  • 37 LaPar DJ, Bhamidipati CM, Harris DA. et al. Gender, race, and socioeconomic status affects outcomes after lung cancer resections in the United States. Ann Thorac Surg 2011; 92 (02) 434-439
    CrossrefPubMedGoogle Scholar
  • 38 Lemaire A, Cook C, Tackett S, Mendes DM, Shortell CK. The impact of race and insurance type on the outcome of endovascular abdominal aortic aneurysm (AAA) repair. J Vasc Surg 2008; 47 (06) 1172-1180
    CrossrefPubMedGoogle Scholar
  • 39 Alosh H, Riley III LH, Skolasky RL. Insurance status, geography, race, and ethnicity as predictors of anterior cervical spine surgery rates and in-hospital mortality: an examination of United States trends from 1992 to 2005. Spine 2009; 34 (18) 1956-1962
    CrossrefPubMedGoogle Scholar
  • 40 Herrera-Escobar JP, Seshadri AJ, Rivero R. et al. Lower education and income predict worse long-term outcomes after injury. J Trauma Acute Care Surg 2019; 87 (01) 104-110
    CrossrefPubMedGoogle Scholar
  • 41 Blackburn GL. Metabolic considerations in management of surgical patients. Surg Clin North Am 2011; 91 (03) 467-480
    CrossrefPubMedGoogle Scholar
  • 42 Correia MITD, Waitzberg DL. The impact of malnutrition on morbidity, mortality, length of hospital stay and costs evaluated through a multivariate model analysis. Clin Nutr 2003; 22 (03) 235-239
    CrossrefPubMedGoogle Scholar
  • 43 Thomas MN, Kufeldt J, Kisser U. et al. Effects of malnutrition on complication rates, length of hospital stay, and revenue in elective surgical patients in the G-DRG-system. Nutrition 2016; 32 (02) 249-254
    CrossrefPubMedGoogle Scholar
  • 44 Kassin MT, Owen RM, Perez SD. et al. Risk factors for 30-day hospital readmission among general surgery patients. J Am Coll Surg 2012; 215 (03) 322-330
    CrossrefPubMedGoogle Scholar
  • 45 Kirkpatrick S, Tarasuk V. The relationship between low income and household food expenditure patterns in Canada. Public Health Nutr 2003; 6 (06) 589-597
    CrossrefPubMedGoogle Scholar
  • 46 Mark S, Lambert M, O'Loughlin J, Gray-Donald K. Household income, food insecurity and nutrition in Canadian youth. Can J Public Health 2012; 103 (02) 94-99
    CrossrefPubMedGoogle Scholar
  • 47 French SA, Tangney CC, Crane MM, Wang Y, Appelhans BM. Nutrition quality of food purchases varies by household income: the SHoPPER study. BMC Public Health 2019; 19 (01) 231
    CrossrefPubMedGoogle Scholar
  • 48 Blok DJ, de Vlas SJ, Bakker R, van Lenthe FJ. Reducing income inequalities in food consumption: explorations with an agent-based model. Am J Prev Med 2015; 49 (04) 605-613
    CrossrefPubMedGoogle Scholar
  • 49 Lopez Ramos C, Brandel MG, Steinberg JA. et al. The impact of traveling distance and hospital volume on post-surgical outcomes for patients with glioblastoma. J Neurooncol 2019; 141 (01) 159-166
    CrossrefPubMedGoogle Scholar
  • 50 Xia L, Taylor BL, Mamtani R, Christodouleas JP, Guzzo TJ. Associations between travel distance, hospital volume, and outcomes following radical cystectomy in patients with muscle-invasive bladder cancer. Urology 2018; 114: 87-94
    CrossrefPubMedGoogle Scholar
  • 51 Beal EW, Mehta R, Merath K. et al. Outcomes after resection of hepatocellular carcinoma: intersection of travel distance and hospital volume. J Gastrointest Surg 2019; 23 (07) 1425-1434
    CrossrefPubMedGoogle Scholar
  • 52 Etzioni DA, Fowl RJ, Wasif N, Donohue JH, Cima RR. Distance bias and surgical outcomes. Med Care 2013; 51 (03) 238-244
    CrossrefPubMedGoogle Scholar
  • 53 Ma X, Sharpe PA, Bell BA, Liu J, White K, Liese AD. Food acquisition and shopping patterns among residents of low-income and low-access communities in South Carolina. J Acad Nutr Diet 2018; 118 (10) 1844-1854
    CrossrefPubMedGoogle Scholar
  • 54 Kangovi S, Barg FK, Carter T. et al. Challenges faced by patients with low socioeconomic status during the post-hospital transition. J Gen Intern Med 2014; 29 (02) 283-289
    CrossrefPubMedGoogle Scholar
  • 55 Camacho EM, Verstappen SMM, Symmons DPM. Association between socioeconomic status, learned helplessness, and disease outcome in patients with inflammatory polyarthritis. Arthritis Care Res (Hoboken) 2012; 64 (08) 1225-1232
    CrossrefPubMedGoogle Scholar
  • 56 Algren MH, Ekholm O, Nielsen L, Ersbøll AK, Bak CK, Andersen PT. Associations between perceived stress, socioeconomic status, and health-risk behaviour in deprived neighbourhoods in Denmark: a cross-sectional study. BMC Public Health 2018; 18 (01) 250
    CrossrefPubMedGoogle Scholar
  • 57 Baum A, Garofalo JP, Yali AM. Socioeconomic status and chronic stress. Does stress account for SES effects on health?. Ann N Y Acad Sci 1999; 896 (01) 131-144
    CrossrefPubMedGoogle Scholar
  • 58 Grzywacz JG, Almeida DM, Neupert SD, Ettner SL. Socioeconomic status and health: a micro-level analysis of exposure and vulnerability to daily stressors. J Health Soc Behav 2004; 45 (01) 1-16
    CrossrefPubMedGoogle Scholar