Impact of COVID-19 on Intracranial Meningioma Resection: Results from California State Inpatient Database
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Design and Data Source
2.2. Study Population
2.3. Study Variables and Outcomes
2.4. Statistical Analysis
3. Results
4. Discussion
Strengths and Limitations
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Tsermoulas, G.; Zisakis, A.; Flint, G.; Belli, A. Challenges to neurosurgery during the coronavirus disease 2019 (COVID-19) pandemic. World Neurosurg. 2020, 139, 519–525. [Google Scholar] [CrossRef] [PubMed]
- Saad, H.; Alawieh, A.; Oyesiku, N.; Barrow, D.L.; Olson, J. Sheltered neurosurgery during COVID-19: The Emory experience. World Neurosurg. 2020, 144, e204–e209. [Google Scholar] [CrossRef] [PubMed]
- Cantor, J.; Sood, N.; Bravata, D.M.; Pera, M.; Whaley, C. The impact of the COVID-19 pandemic and policy response on health care utilization: Evidence from county-level medical claims and cellphone data. J. Health Econ. 2022, 82, 102581. [Google Scholar] [CrossRef] [PubMed]
- Hartnett, K.P.; Kite-Powell, A.; DeVies, J.; Coletta, M.A.; Boehmer, T.K.; Adjemian, J.; Gundlapalli, A.V. National Syndromic Surveillance Program Community of Practice. Impact of the COVID-19 pandemic on emergency department visits—United States, 1 January 2019–30 May 2020. Morb. Mortal. Wkly. Rep. 2020, 69, 699. [Google Scholar] [CrossRef]
- Ali, M.; Shah, S.T.H.; Imran, M.; Khan, A. The role of asymptomatic class, quarantine and isolation in the transmission of COVID-19. J. Biol. Dyn. 2020, 14, 389–408. [Google Scholar] [CrossRef]
- Wells, C.R.; Townsend, J.P.; Pandey, A.; Moghadas, S.M.; Krieger, G.; Singer, B.; McDonald, R.H.; Fitzpatrick, M.C.; Galvani, A.P. Optimal COVID-19 quarantine and testing strategies. Nat. Commun. 2021, 12, 356. [Google Scholar] [CrossRef]
- Findling, M.G.; Blendon, R.J.; Benson, J.M. Delayed care with harmful health consequences—Reported experiences from national surveys during coronavirus disease 2019. JAMA Health Forum 2020, 12, e201463. [Google Scholar] [CrossRef]
- Dyer, C. Covid-19: Doctors working outside their expertise are unlikely to face GMC charges. BMJ 2020, 370, m3572. [Google Scholar] [CrossRef]
- Devereaux, A.; Yang, H.; Seda, G.; Sankar, V.; Maves, R.C.; Karanjia, N.; Parrish, J.S.; Rosenberg, C.; Goodman-Crews, P.; Cederquist, L.; et al. Optimizing scarce resource allocation during COVID-19: Rapid creation of a regional health-care coalition and triage teams in San Diego County, California. Disaster Med. Public Health Prep. 2020, 16, 321–327. [Google Scholar] [CrossRef]
- Robert, R.; Kentish-Barnes, N.; Boyer, A.; Laurent, A.; Azoulay, E.; Reignier, J. Ethical dilemmas due to the Covid-19 pandemic. Ann. Intensive Care 2020, 10, 84. [Google Scholar] [CrossRef]
- Nguyen, L.H.; Drew, D.A.; Graham, M.S.; Joshi, A.D.; Guo, C.G.; Ma, W.; Mehta, R.S.; Warner, E.T.; Sikavi, D.R.; Lo, C.H.; et al. Coronavirus Pandemic Epidemiology Consortium. Risk of COVID-19 among front-line health-care workers and the general community: A prospective cohort study. Lancet Public Health 2020, 5, e475–e483. [Google Scholar] [CrossRef]
- Ostrom, Q.T.; Cioffi, G.; Gittleman, H.; Patil, N.; Waite, K.; Kruchko, C.; Barnholtz-Sloan, J.S. CBTRUS statistical report: Primary brain and other central nervous system tumors diagnosed in the United States in 2012–2016. Neurooncology 2019, 21 (Suppl. 5), v1–v100. [Google Scholar] [CrossRef] [PubMed]
- Vernooij, M.W.; Ikram, M.A.; Tanghe, H.L.; Vincent, A.J.; Hofman, A.; Krestin, G.P.; Niessen, W.J.; Breteler, M.M.; van der Lugt, A. Incidental findings on brain MRI in the general population. N. Engl. J. Med. 2007, 357, 1821–1828. [Google Scholar] [CrossRef] [PubMed]
- Bhala, S.; Stewart, D.R.; Kennerley, V.; Petkov, V.I.; Rosenberg, P.S.; Best, A.F. Incidence of benign meningiomas in the United States: Current and future trends. JNCI Cancer Spectr. 2021, 5, pkab035. [Google Scholar] [CrossRef] [PubMed]
- Goldbrunner, R.; Minniti, G.; Preusser, M.; Jenkinson, M.D.; Sallabanda, K.; Houdart, E.; von Deimling, A.; Stavrinou, P.; Lefranc, F.; Lund-Johansen, M.; et al. EANO guidelines for the diagnosis and treatment of meningiomas. Lancet Oncol. 2016, 17, e383–e391. [Google Scholar] [CrossRef]
- Ildan, F.; Erman, T.; Göçer, A.I.; Tuna, M.; Bağdatoğlu, H.; Cetinalp, E.; Burgut, R. Predicting the probability of meningioma recurrence in the preoperative and early postoperative period: A multivariate analysis in the midterm follow-up. Skull Base 2007, 17, 157–171. [Google Scholar] [CrossRef] [PubMed]
- Hasseleid, B.F.; Meling, T.R.; Rønning, P.; Scheie, D.; Helseth, E. Surgery for convexity meningioma: Simpson Grade I resection as the goal. J. Neurosurg. 2012, 117, 999–1006. [Google Scholar] [CrossRef] [PubMed]
- Agency for Healthcare Research and Quality (AHRQ). Overview of the State Inpatient Databases (SID). Available online: https://www.hcup-us.ahrq.gov/sidoverview.jsp (accessed on 23 June 2022).
- Vandenbroucke, J.P.; von Elm, E.; Altman, D.G.; Gøtzsche, P.C.; Mulrow, C.D.; Pocock, S.J.; Poole, C.; Schlesselman, J.J.; Egger, M.; STROBE Initiative. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and elaboration. PLoS Med. 2007, 4, e297. [Google Scholar] [CrossRef]
- Clavien, P.A.; Barkun, J.; de Oliveira, M.L.; Vauthey, J.N.; Dindo, D.; Schulick, R.D.; de Santibañes, E.; Pekolj, J.; Slankamenac, K.; Bassi, C.; et al. The Clavien-Dindo classification of surgical complications: Five-year experience. Ann. Surg. 2009, 250, 187–196. [Google Scholar] [CrossRef]
- Abt, N.B.; Richmon, J.D.; Koch, W.M.; Eisele, D.W.; Agrawal, N. Assessment of the predictive value of the modified frailty index for Clavien-Dindo grade IV critical care complications in major head and neck cancer operations. JAMA Otolaryngol. Head Neck Surg. 2016, 142, 658–664. [Google Scholar] [CrossRef] [Green Version]
- Hall, E.C.; Boyarsky, B.J.; Deshpande, N.A.; Garonzik-Wang, J.M.; Berger, J.C.; Dagher, N.N.; Segev, D.L. Perioperative complications after live-donor hepatectomy. JAMA Surg. 2014, 149, 288–291. [Google Scholar] [CrossRef] [PubMed]
- Meyer, C.P.; Sun, M.; Karam, J.A.; Leow, J.J.; de Velasco, G.; Pal, S.K.; Chang, S.L.; Trinh, Q.D.; Choueiri, T.K. Complications after metastasectomy for renal cell carcinoma—A population-based assessment. Eur. Urol. 2017, 72, 171–174. [Google Scholar] [CrossRef] [PubMed]
- Oseran, A.S.; Nash, D.; Kim, C.; Moisuk, S.; Lai, P.Y.; Pyhtila, J.; Sequist, T.D.; Wasfy, J.H. Changes in hospital admissions for urgent conditions during COVID-19 pandemic. Am. J. Manag. Care 2020, 26, 327–328. [Google Scholar] [PubMed]
- Birkmeyer, J.D.; Barnato, A.; Birkmeyer, N.; Bessler, R.; Skinner, J. The impact of the COVID-19 pandemic on hospital admissions in the United States: Study examines trends in US hospital admissions during the COVID-19 pandemic. Health Aff. 2020, 39, 2010–2017. [Google Scholar] [CrossRef]
- Noureldine, M.H.A.; Pressman, E.; Krafft, P.R.; Greenberg, M.S.; Agazzi, S.; van Loveren, H.; Alikhani, P. Impact of the COVID-19 pandemic on neurosurgical practice at an academic tertiary referral center: A comparative study. World Neurosurg. 2020, 139, e872–e876. [Google Scholar] [CrossRef]
- Aldujeli, A.; Hamadeh, A.; Briedis, K.; Tecson, K.M.; Rutland, J.; Krivickas, Z.; Stiklioraitis, S.; Briede, K.; Aldujeili, M.; Unikas, R.; et al. Delays in presentation in patients with acute myocardial infarction during the COVID-19 pandemic. Cardiol. Res. 2020, 11, 386. [Google Scholar] [CrossRef]
- Gale, R.; Eberlein, S.; Fuller, G.; Khalil, C.; Almario, C.V.; Spiegel, B.M. Public Perspectives on Decisions About Emergency Care Seeking for Care Unrelated to COVID-19 During the COVID-19 Pandemic. JAMA Netw. Open 2021, 4, e2120940. [Google Scholar] [CrossRef]
- Mahmud, N.; Hubbard, R.A.; Kaplan, D.E.; Serper, M. Declining cirrhosis hospitalizations in the wake of the COVID-19 pandemic: A national cohort study. Gastroenterology 2020, 159, 1134–1136.e3. [Google Scholar] [CrossRef]
- Kilgore, M.D.; Scullen, T.; Mathkour, M.; Dindial, R.; Carr, C.; Zeoli, T.; Werner, C.; Kahn, L.; Bui, C.J.; Keen, J.R.; et al. Effects of the COVID-19 pandemic on operative volume and residency training at two academic neurosurgery centers in New Orleans. World Neurosurg. 2021, 151, e68–e77. [Google Scholar] [CrossRef]
- Khalafallah, A.M.; Jimenez, A.E.; Lee, R.P.; Weingart, J.D.; Theodore, N.; Cohen, A.R.; Tamargo, R.J.; Huang, J.; Brem, H.; Mukherjee, D. Impact of COVID-19 on an Academic Neurosurgery Department: The Johns Hopkins Experience. Impact of COVID-19 on an academic neurosurgery department: The Johns Hopkins experience. World Neurosurg. 2020, 139, e877–e884. [Google Scholar] [CrossRef]
- Kuzemko, C.; Bradshaw, M.; Bridge, G.; Goldthau, A.; Jewell, J.; Overland, I.; Scholten, D.; Van de Graaf, T.; Westphal, K. Covid-19 and the politics of sustainable energy transitions. Energy Res. Soc. Sci. 2020, 68, 101685. [Google Scholar] [CrossRef] [PubMed]
- Lenzen, M.; Li, M.; Malik, A.; Pomponi, F.; Sun, Y.Y.; Wiedmann, T.; Faturay, F.; Fry, J.; Gallego, B.; Geschke, A.; et al. Global socio-economic losses and environmental gains from the Coronavirus pandemic. PLoS ONE 2020, 15, e0235654. [Google Scholar]
- Aljuboori, Z.S.; Young, C.C.; Srinivasan, V.M.; Kellogg, R.T.; Quon, J.L.; Alshareef, M.A.; Chen, S.H.; Ivan, M.; Grant, G.A.; McEvoy, S.D.; et al. Early effects of COVID-19 pandemic on neurosurgical training in the United States: A case volume analysis of 8 programs. World Neurosurg. 2021, 145, e202–e208. [Google Scholar] [CrossRef]
- Shannon, C. A Timeline of California in the Coronavirus Pandemic. ABC10 News, 11 March 2021. [Google Scholar]
- Sander, C.; Dercks, N.V.; Fehrenbach, M.K.; Wende, T.; Stehr, S.; Winkler, D.; Meixensberger, J.; Arlt, F. Neurosurgical Care during the COVID-19 Pandemic in Central Germany: A Retrospective Single Center Study of the Second Wave. Int. J. Environ. Res. Public Health 2021, 18, 12034. [Google Scholar] [CrossRef] [PubMed]
- Anzalone, C.L.; Glasgow, A.E.; Van Gompel, J.J.; Carlson, M.L. Racial differences in disease presentation and management of intracranial meningioma. J. Neurol. Surg. Part B Skull Base 2019, 80, 555–561. [Google Scholar] [CrossRef] [PubMed]
- Mendoza, J.; Pangal, D.J.; Cardinal, T.; Bonney, P.A.; Lechtholz-Zey, E.; Strickland, B.A.; Giannotta, S.; Zada, G. Systematic Review of Racial, Socioeconomic, and Insurance Status Disparities in Neurosurgical Care for Intracranial Tumors. World Neurosurg. 2022, 158, 38–64. [Google Scholar] [CrossRef]
Characteristic | 2019 n = 921 (53.9%) | 2020 n = 788 (46.1%) | p Value |
---|---|---|---|
Age, n (%) | 0.858 | ||
18–44 years | 139 (15.1%) | 124 (15.7%) | |
45–64 years | 416 (45.2%) | 346 (43.9%) | |
≥65 years | 366 (39.7%) | 318 (40.4%) | |
Sex, n (%) | 0.750 | ||
Male | 274 (29.8%) | 240 (30.5%) | |
Female | 647 (70.2%) | 548 (69.5%) | |
Race/ethnicity, n (%) | 0.216 | ||
White | 459 (51.0%) | 372 (47.6%) | |
Black | 60 (6.7%) | 42 (5.4%) | |
Hispanic | 203 (22.6%) | 187 (23.9%) | |
Asian or Pacific Islander and Native American | 127 (14.1%) | 120 (15.3%) | |
Other | 51 (5.7%) | 61 (7.8%) | |
Insurance status, n (%) | 0.427 | ||
Medicare | 354 (38.4%) | 301 (38.2%) | |
Medicaid | 141 (15.3%) | 136 (17.3%) | |
Private insurance | 388 (42.1%) | 327 (41.6%) | |
Other | 38 (4.1%) | 23 (2.9%) | |
Clinical risk profile, n (%) | |||
Hypertension | 472 (51.2%) | 405 (51.4%) | 0.951 |
Diabetes mellitus | 92 (10.0%) | 79 (10.0%) | 0.980 |
Obesity | 181 (19.7%) | 153 (19.4%) | 0.902 |
Coagulation disorder | 50 (5.4%) | 41 (5.2%) | 0.835 |
Peripheral vascular disease | 47 (5.1%) | 43 (5.5%) | 0.744 |
Liver disease | 17 (1.8%) | 26 (3.3%) | 0.055 |
Chronic renal failure | 53 (5.8%) | 51 (6.5%) | 0.536 |
Alcohol abuse | 13 (1.4%) | 11 (1.3%) | 0.798 |
Drug abuse | 27 (2.9%) | 16 (2.0%) | 0.235 |
Elixhauser comorbidity index, n (%) | 0.482 | ||
0 | 197 (21.4%) | 169 (21.4%) | |
1 or 2 | 426 (46.3%) | 344 (43.7%) | |
≥3 | 298 (32.4%) | 275 (34.9%) |
Characteristic | 2019 n = 1165 (66.8%) | 2020 n = 575 (33.2%) | p Value |
---|---|---|---|
Clavien–Dindo grade IV complications | |||
Severe sepsis or septic shock | 13 (1.4%) | 13 (1.6%) | 0.688 |
Acute renal failure requiring dialysis | NR | NR | --- |
Pulmonary embolism | NR | NR | --- |
Acute myocardial infarction or cardiac arrest requiring cardiopulmonary resuscitation | NR | NR | --- |
Prolonged requirement of mechanical ventilation | 30 (3.3%) | 34 (4.3%) | 0.251 |
Unplanned intubation/reintubation | NR | NR | --- |
Any grade IV complication | 41 (4.5%) | 42 (5.3%) | 0.399 |
In-hospital mortality | NR | 12 (1.5%) | --- |
Prolonged length of stay, n (%) | 249 (27.0%) | 220 (27.9%) | 0.683 |
Characteristic | Odds Ratio (95% CI) |
---|---|
Year | |
2019 | Reference |
2020 | 1.23 (0.78–1.94) |
Age | |
18–44 years | Reference |
45–64 years | 1.61 (0.73–3.54) |
≥65 years | 1.61 (0.58–4.51) |
Sex | |
Male | Reference |
Female | 0.79 (0.48–1.28) |
Race | |
White | Reference |
Black | 3.56 (1.65–7.65) |
Hispanic | 1.57 (0.84–2.95) |
Asian or Pacific Islander and Native American | 1.92 (0.99–3.74) |
Other | 2.06 (0.90–4.72) |
Insurance status | |
Medicare | Reference |
Medicaid | 1.51 (0.64–3.59) |
Private insurance | 0.77 (0.34–1.76) |
Other | 1.49 (0.45–4.93) |
Hypertension | 0.81 (0.48–1.37) |
Diabetes mellitus | 0.56 (0.21–1.48) |
Obesity | 1.03 (0.57–1.86) |
Coagulation disorder | 5.22 (2.82–9.67) |
Peripheral vascular disease | 0.85 (0.33–2.15) |
Liver disease | 1.39 (0.43–4.50) |
Chronic renal failure | 5.52 (2.84–10.76) |
Alcohol abuse | 1.11 (0.22–5.53) |
Drug abuse | 2.81 (0.99–7.96) |
Characteristic | Odds Ratio (95% CI) |
---|---|
Year | |
2019 | Reference |
2020 | 1.05 (0.84–1.32) |
Age | |
18–44 years | Reference |
45–64 years | 1.25 (0.87–1.80) |
≥65 years | 1.29 (0.79–2.11) |
Sex | |
Male | Reference |
Female | 0.80 (0.62–1.02) |
Race | |
White | Reference |
Black | 1.21 (0.78–1.88) |
Hispanic | 1.62 (0.42–1.93) |
Asian or Pacific Islander and Native American | 1.03 (0.54–1.98) |
Other | 1.19 (0.89–1.76) |
Insurance status | |
Medicare | Reference |
Medicaid | 1.21 (0.78–1.88) |
Private insurance | 0.62 (0.42–0.93) |
Other | 1.03 (0.54–1.98) |
Hypertension | 1.59 (1.23–2.06) |
Diabetes mellitus | 0.65 (0.43–0.97) |
Obesity | 0.95 (0.71–1.27) |
Coagulation disorder | 4.24 (2.67–6.73) |
Peripheral vascular disease | 0.81 (0.50–1.33) |
Liver disease | 1.29 (0.64–2.60) |
Chronic renal failure | 1.85 (1.19–2.88) |
Alcohol abuse | 1.73 (0.71–4.24) |
Drug abuse | 1.03 (0.56–1.88) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Rubens, M.; Saxena, A.; Ramamoorthy, V.; Ahmed, M.A.; Zhang, Z.; McGranaghan, P.; Veledar, E.; McDermott, M. Impact of COVID-19 on Intracranial Meningioma Resection: Results from California State Inpatient Database. Cancers 2022, 14, 4785. https://doi.org/10.3390/cancers14194785
Rubens M, Saxena A, Ramamoorthy V, Ahmed MA, Zhang Z, McGranaghan P, Veledar E, McDermott M. Impact of COVID-19 on Intracranial Meningioma Resection: Results from California State Inpatient Database. Cancers. 2022; 14(19):4785. https://doi.org/10.3390/cancers14194785
Chicago/Turabian StyleRubens, Muni, Anshul Saxena, Venkataraghavan Ramamoorthy, Md Ashfaq Ahmed, Zhenwei Zhang, Peter McGranaghan, Emir Veledar, and Michael McDermott. 2022. "Impact of COVID-19 on Intracranial Meningioma Resection: Results from California State Inpatient Database" Cancers 14, no. 19: 4785. https://doi.org/10.3390/cancers14194785
APA StyleRubens, M., Saxena, A., Ramamoorthy, V., Ahmed, M. A., Zhang, Z., McGranaghan, P., Veledar, E., & McDermott, M. (2022). Impact of COVID-19 on Intracranial Meningioma Resection: Results from California State Inpatient Database. Cancers, 14(19), 4785. https://doi.org/10.3390/cancers14194785