M M J Singendonk1, R Rosen2, J Oors1, N Rommel3,4, M P van Wijk1,5, M A Benninga1, S Nurko2, T I Omari4,6,7. 1. Pediatric Gastroenterology and Nutrition, Emma Children's Hospital/AMC, Amsterdam, The Netherlands. 2. Division of Gastroenterology, Center for Motility and Functional Gastrointestinal Disorders, Boston, MA, USA. 3. Translational Research Center for Gastrointestinal Diseases, University of Leuven, Leuven, Belgium. 4. Department of Neurosciences, ExpORL, University of Leuven, Leuven, Belgium. 5. Department of Pediatric Gastroenterology, VU University Medical Center, Amsterdam, The Netherlands. 6. Gastroenterology Unit, Women's and Children's Health Network, Adelaide, SA, Australia. 7. School of Medicine, Flinders University, Bedford Park, SA, Australia.
Abstract
BACKGROUND: Subtyping achalasia by high-resolution manometry (HRM) is clinically relevant as response to therapy and prognosis have shown to vary accordingly. The aim of this study was to assess inter- and intrarater reliability of diagnosing achalasia and achalasia subtyping in children using the Chicago Classification (CC) V3.0. METHODS: Six observers analyzed 40 pediatric HRM recordings (22 achalasia and 18 non-achalasia) twice by using dedicated analysis software (ManoView 3.0, Given Imaging, Los Angeles, CA, USA). Integrated relaxation pressure (IRP4s), distal contractile integral (DCI), intrabolus pressurization pattern (IBP), and distal latency (DL) were extracted and analyzed hierarchically. Cohen's κ (2 raters) and Fleiss' κ (>2 raters) and the intraclass correlation coefficient (ICC) were used for categorical and ordinal data, respectively. RESULTS: Based on the results of dedicated analysis software only, intra- and interrater reliability was excellent and moderate (κ=0.89 and κ=0.52, respectively) for differentiating achalasia from non-achalasia. For subtyping achalasia, reliability decreased to substantial and fair (κ=0.72 and κ=0.28, respectively). When observers were allowed to change the software-driven diagnosis according to their own interpretation of the manometric patterns, intra- and interrater reliability increased for diagnosing achalasia (κ=0.98 and κ=0.92, respectively) and for subtyping achalasia (κ=0.79 and κ=0.58, respectively). CONCLUSIONS: Intra- and interrater agreement for diagnosing achalasia when using HRM and the CC was very good to excellent when results of automated analysis software were interpreted by experienced observers. More variability was seen when relying solely on the software-driven diagnosis and for subtyping achalasia. Therefore, diagnosing and subtyping achalasia should be performed in pediatric motility centers with significant expertise.
BACKGROUND: Subtyping achalasia by high-resolution manometry (HRM) is clinically relevant as response to therapy and prognosis have shown to vary accordingly. The aim of this study was to assess inter- and intrarater reliability of diagnosing achalasia and achalasia subtyping in children using the Chicago Classification (CC) V3.0. METHODS: Six observers analyzed 40 pediatric HRM recordings (22 achalasia and 18 non-achalasia) twice by using dedicated analysis software (ManoView 3.0, Given Imaging, Los Angeles, CA, USA). Integrated relaxation pressure (IRP4s), distal contractile integral (DCI), intrabolus pressurization pattern (IBP), and distal latency (DL) were extracted and analyzed hierarchically. Cohen's κ (2 raters) and Fleiss' κ (>2 raters) and the intraclass correlation coefficient (ICC) were used for categorical and ordinal data, respectively. RESULTS: Based on the results of dedicated analysis software only, intra- and interrater reliability was excellent and moderate (κ=0.89 and κ=0.52, respectively) for differentiating achalasia from non-achalasia. For subtyping achalasia, reliability decreased to substantial and fair (κ=0.72 and κ=0.28, respectively). When observers were allowed to change the software-driven diagnosis according to their own interpretation of the manometric patterns, intra- and interrater reliability increased for diagnosing achalasia (κ=0.98 and κ=0.92, respectively) and for subtyping achalasia (κ=0.79 and κ=0.58, respectively). CONCLUSIONS: Intra- and interrater agreement for diagnosing achalasia when using HRM and the CC was very good to excellent when results of automated analysis software were interpreted by experienced observers. More variability was seen when relying solely on the software-driven diagnosis and for subtyping achalasia. Therefore, diagnosing and subtyping achalasia should be performed in pediatric motility centers with significant expertise.
Authors: Ishita Dhawan; Brendon O'Connell; Amit Patel; Ron Schey; Henry P Parkman; Frank Friedenberg Journal: Dig Dis Sci Date: 2018-12 Impact factor: 3.199
Authors: Corinne A Jones; Nicole M Rogus-Pulia; Angela L Forgues; Jason Orne; Cameron L Macdonald; Nadine P Connor; Timothy M McCulloch Journal: Dysphagia Date: 2018-10-31 Impact factor: 3.438
Authors: Maartje M J Singendonk; Lara F Ferris; Lisa McCall; Grace Seiboth; Katie Lowe; David Moore; Paul Hammond; Richard Couper; Rammy Abu-Assi; Charles Cock; Marc A Benninga; Michiel P van Wijk; Taher I Omari Journal: Neurogastroenterol Motil Date: 2019-09-30 Impact factor: 3.598
Authors: Lusine Ambartsumyan; Julie Khlevner; Samuel Nurko; Rachel Rosen; Ajay Kaul; John E Pandolfino; Elyanne Ratcliffe; Desale Yacob; B U K Li; Jaya Punati; Manu Sood; Satish S C Rao; Marc A Levitt; Jose T Cocjin; Leonel Rodriguez; Alejandro Flores; John M Rosen; Jaime Belkind-Gerson; Miguel Saps; Jose M Garza; John E Fortunato; Rose L Schroedl; Laurie A Keefer; Joel Friedlander; Robert O Heuckeroth; Meenakshi Rao; Khalil El-Chammas; Karla Vaz; Bruno P Chumpitazi; Rina Sanghavi; Sravan K R Matta; Tanaz Danialifar; Carlo Di Lorenzo; Anil Darbari Journal: J Pediatr Gastroenterol Nutr Date: 2020-08 Impact factor: 2.839