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Combining patient-specific, digital 3D models with tele-education for adolescents with CHD

Published online by Cambridge University Press:  16 August 2021

David Liddle*
Affiliation:
Department of Cardiology, Boston Children’s Hospital, 300 Longwood Avenue, Boston, MA02115, USA
Sheri Balsara
Affiliation:
Department of Cardiology, Children’s Hospital of Philadelphia, 3401 Civic Center Boulevard, Philadelphia, PA19104, USA
Karin Hamann
Affiliation:
Department of Cardiology, Children’s National Hospital, 111 Michigan Avenue NW, Washington, DC20010, USA
Adam Christopher
Affiliation:
Department of Cardiology, Children’s Hospital of Pittsburgh, 4401 Penn Avenue, Pittsburgh, PA15224, USA
Laura Olivieri
Affiliation:
Department of Cardiology, Children’s National Hospital, 111 Michigan Avenue NW, Washington, DC20010, USA
Yue-Hin Loke
Affiliation:
Department of Cardiology, Children’s National Hospital, 111 Michigan Avenue NW, Washington, DC20010, USA
*
Author for correspondence: D. Liddle, MD, Pediatric Cardiology, Boston Children’s Hospital, 300 Longwood Avenue, Boston, MA02115, USA. Tel: +617 355 7830; Fax: +617 730 0710. E-mail: david.liddle@cardio.chboston.org

Abstract

Introduction:

Adolescents with CHD require transition to specialised adult-centred care. Previous studies have shown that adolescents’ knowledge of their medical condition is correlated with transition readiness. Three-dimensional printed models of CHD have been used to educate medical trainees and patients, although no studies have focused on adolescents with CHD. This study investigates the feasibility of combining patient-specific, digital 3D heart models with tele-education interventions to improve the medical knowledge of adolescents with CHD.

Methods:

Adolescent patients with CHD, aged between 13 and 18 years old, were enrolled and scheduled for a tele-education session. Patient-specific digital 3D heart models were created using images from clinically indicated cardiac magnetic resonance studies. The tele-education session was performed using commercially available, web-conferencing software (Zoom, Zoom Video Communications Inc.) and a customised software (Cardiac Review 3D, Indicated Inc.) incorporating an interactive display of the digital 3D heart model. Medical knowledge was assessed using pre- and post-session questionnaires that were scored by independent reviewers.

Results:

Twenty-two adolescents completed the study. The average age of patients was 16 years old (standard deviation 1.5 years) and 56% of patients identified as female. Patients had a variety of cardiac defects, including tetralogy of Fallot, transposition of great arteries, and coarctation of aorta. Post-intervention, adolescents’ medical knowledge of their cardiac defects and cardiac surgeries improved compared to pre-intervention (p < 0.01).

Conclusions:

Combining patient-specific, digital 3D heart models with tele-education sessions can improve adolescents’ medical knowledge and may assist with transition to adult-centred care.

Type
Original Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

Hoffman, JI, Kaplan, S, Liberthson, RR. Prevalence of congenital heart disease. Am Heart J 2004; 147: 425439. doi: 10.1016/j.ahj.2003.05.003 CrossRefGoogle ScholarPubMed
Webb, GD, Williams, RG. Care of the adult with congenital heart disease: introduction. J Am Coll Cardiol 2001; 37: 1166. doi: 10.1016/s0735-1097(01)01280-3 CrossRefGoogle ScholarPubMed
Hays, L. Transition to adult congenital heart disease care: a review. J Pediatr Nurs 2015; 30: e63e69. doi: 10.1016/j.pedn.2015.01.025 CrossRefGoogle ScholarPubMed
Yeung, E, Kay, J, Roosevelt, GE, Brandon, M, Yetman, AT. Lapse of care as a predictor for morbidity in adults with congenital heart disease. Int J Cardiol 2008; 125: 6265. doi: 10.1016/j.ijcard.2007.02.023 CrossRefGoogle Scholar
Reid, GJ, Irvine, MJ, McCrindle, BW, et al. Prevalence and correlates of successful transfer from pediatric to adult health care among a cohort of young adults with complex congenital heart defects. Pediatrics 2004; 113: e197e205. doi: 10.1542/peds.113.3.e197 CrossRefGoogle ScholarPubMed
Burström, Å, Bratt, EL, Frenckner, B, et al. Adolescents with congenital heart disease: their opinions about the preparation for transfer to adult care. Eur J Pediatr 2017; 176: 881889. doi: 10.1007/s00431-017-2917-9 CrossRefGoogle ScholarPubMed
Stewart, KT, Chahal, N, Kovacs, AH, et al. Readiness for transition to adult health care for young adolescents with congenital heart disease. Pediatr Cardiol 2017; 38: 778786. doi: 10.1007/s00246-017-1580-2 CrossRefGoogle ScholarPubMed
Uzark, K, Smith, C, Donohue, J, et al. Assessment of transition readiness in adolescents and young adults with heart disease. J Pediatr 2015; 167: 12331238. doi: 10.1016/j.jpeds.2015.07.043 CrossRefGoogle Scholar
Kappanayil, M, Koneti, NR, Kannan, RR, Kottayil, BP, Kumar, K. Three-dimensional-printed cardiac prototypes aid surgical decision-making and preoperative planning in selected cases of complex congenital heart diseases: Early experience and proof of concept in a resource-limited environment. Ann Pediatr Cardiol 2017; 10: 117125. doi: 10.4103/apc.APC_149_16 CrossRefGoogle Scholar
Kim, MS, Hansgen, AR, Wink, O, Quaife, RA, Carroll, JD. Rapid prototyping: a new tool in understanding and treating structural heart disease. Circulation 2008; 117: 23882394. doi: 10.1161/CIRCULATIONAHA.107.740977 CrossRefGoogle ScholarPubMed
Loke, YH, Harahsheh, AS, Krieger, A, Olivieri, LJ. Usage of 3D models of tetralogy of Fallot for medical education: impact on learning congenital heart disease. BMC Med Educ 2017; 17: 54. Published 2017 Mar 11. doi: 10.1186/s12909-017-0889-0 CrossRefGoogle ScholarPubMed
Loke, T., Krieger, A., Sable, C. et al. Novel uses for three-dimensional printing in congenital heart disease. Curr Pediatr Rep 4, 2834 (2016). doi: 10.1007/s40124-016-0099-y CrossRefGoogle Scholar
Biglino, G, Capelli, C, Wray, J, et al. 3D-manufactured patient-specific models of congenital heart defects for communication in clinical practice: feasibility and acceptability. BMJ Open 2015; 5: e007165. Published 2015 Apr 30. doi: 10.1136/bmjopen-2014-007165 CrossRefGoogle ScholarPubMed
Lau, I, Wong, YH, Yeong, CH, et al. Quantitative and qualitative comparison of low- and high-cost 3D-printed heart models. Quant Imaging Med Surg 2019; 9: 107114. doi: 10.21037/qims.2019.01.02 CrossRefGoogle ScholarPubMed
Jaglal, SB, Haroun, VA, Salbach, NM, et al. Increasing access to chronic disease self-management programs in rural and remote communities using telehealth. Telemed J E Health 2013; 19: 467473. doi: 10.1089/tmj.2012.0197 CrossRefGoogle ScholarPubMed
Mackie, AS, Rempel, GR, Kovacs, AH, et al. Transition intervention for adolescents with congenital heart disease. J Am Coll Cardiol 2018; 71: 17681777. doi: 10.1016/j.jacc.2018.02.043 CrossRefGoogle ScholarPubMed
Mackie, AS, Rempel, GR, Kovacs, AH, et al. A cluster randomized trial of a transition intervention for adolescents with congenital heart disease: rationale and design of the CHAPTER 2 study. BMC Cardiovasc Disord 2016; 16: 127. Published 2016 Jun 6. doi: 10.1186/s12872-016-0307-2 CrossRefGoogle ScholarPubMed
Pather, N, Blyth, P, Chapman, JA, et al. Forced disruption of anatomy education in Australia and New Zealand: an acute response to the COVID-19 pandemic. Anat Sci Educ 2020; 13: 284300. doi: 10.1002/ase.1968 CrossRefGoogle ScholarPubMed
Burke, BL Jr, Hall, RW, SECTION ON TELEHEALTH CARE. Telemedicine: pediatric applications. Pediatrics 2015; 136; e293 doi: 10.1542/peds.2015-1517 originally published online June 29, 2015.CrossRefGoogle ScholarPubMed
McConnochie, K, Wood, N, Herendeen, N, ten Hoopen, C, Denk, L, Neuderfer, J. Integrating telemedicine in urban pediatric primary care: provider perspectives and performance. Telemed J E Health 2010; 16: 280288. doi: 10.1089/tmj.2009.0112 CrossRefGoogle ScholarPubMed
Tenforde, AS, Iaccarino, MA, Borgstrom, H, et al. Telemedicine during COVID-19 for outpatient sports and musculoskeletal medicine physicians [published online ahead of print, 2020 May 18]. PM R 2020. doi: 10.1002/pmrj.12422. doi:10.1002/pmrj.12422 CrossRefGoogle ScholarPubMed
Basu, S, Phillips, RS, Phillips, R, Peterson, LE, Landon, BE. Primary care practice finances in the United States amid the COVID-19 pandemic [published online ahead of print, 2020 Jun 25]. Health Aff (Millwood) 2020; 101377hlthaff202000794. doi: 10.1377/hlthaff.2020.00794 Google ScholarPubMed
Bashshur, R, Doarn, CR, Frenk, JM, Kvedar, JC, Woolliscroft, JO. Telemedicine and the COVID-19 pandemic, lessons for the future. Telemed J E Health 2020; 26: 571573. doi: 10.1089/tmj.2020.29040.rb CrossRefGoogle ScholarPubMed
Marino, BS, Tomlinson, RS, Wernovsky, G, et al. Validation of the pediatric cardiac quality of life inventory. Pediatrics 2010; 126: 498508. doi: 10.1542/peds.2009-2973 CrossRefGoogle ScholarPubMed
Marino, BS, Drotar, D, Cassedy, A, et al. External validity of the pediatric cardiac quality of life inventory. Qual Life Res 2011; 20: 205214. doi: 10.1007/s11136-010-9731-4 CrossRefGoogle ScholarPubMed
Olivieri, LJ, Zurakowski, D, Ramakrishnan, K, et al. Novel, 3D display of heart models in the postoperative care setting improves CICU caregiver confidence. World J Pediatr Congenit Heart Surg 2018; 9: 206213. doi: 10.1177/2150135117745005 CrossRefGoogle ScholarPubMed
McHugh, ML. Interrater reliability: the kappa statistic. Biochem Med (Zagreb) 2012; 22: 276282.CrossRefGoogle ScholarPubMed
Cohen, J. Weighted kappa: nominal scale agreement provision for scaled disagreement or partial credit. Psychol Bull 1968; 70: 213220.CrossRefGoogle ScholarPubMed
Whitley, E, Ball, J. Statistics review 6: nonparametric methods. Crit Care 2002; 6: 509513. doi: 10.1186/cc1820 CrossRefGoogle ScholarPubMed
Veldtman, GR, Matley, SL, Kendall, L, et al. Illness understanding in children and adolescents with heart disease. Heart 2000; 84: 395397. doi: 10.1136/heart.84.4.395 CrossRefGoogle ScholarPubMed
Uzark, K, Afton, K, Yu, S, Lowery, R, Smith, C, Norris, MD. Transition readiness in adolescents and young adults with heart disease: can we improve quality of life? J Pediatr 2019; 212: 7378. doi: 10.1016/j.jpeds.2019.04.060 CrossRefGoogle Scholar
Ping, W, Zheng, J, Niu, X, et al. Evaluation of health-related quality of life using EQ-5D in China during the COVID-19 pandemic. PLoS One 2020; 15: e0234850. Published 2020 Jun 18. doi: 10.1371/journal.pone.0234850 CrossRefGoogle ScholarPubMed
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