Ron B Mitchell1, Suzan Garetz2, Reneé H Moore3, Carol L Rosen4, Carole L Marcus5, Eliot S Katz6, Raanan Arens7, Ronald D Chervin8, Shalini Paruthi9, Raouf Amin10, Lisa Elden11, Susan S Ellenberg12, Susan Redline13. 1. Department of Otolaryngology-Head and Neck Surgery, University of Texas Southwestern and Children's Medical Center, Dallas2Department of Pediatrics, University of Texas Southwestern and Children's Medical Center, Dallas. 2. Department of Otolaryngology-Head and Neck Surgery, Sleep Disorders Center, University of Michigan, Ann Arbor. 3. Department of Statistics, North Carolina State University, Raleigh. 4. Department of Pediatrics, Rainbow Babies and Children's Hospital, Case Western Reserve University School of Medicine, Cleveland, Ohio. 5. Department of Pediatrics, Sleep Center, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia. 6. Division of Respiratory Diseases, Boston Children's Hospital, Boston, Massachusetts. 7. Department of Pediatrics, Montefiore Medical Center, Children's Hospital at Montefiore, Albert Einstein College of Medicine, Bronx, New York. 8. Department of Neurology and Sleep Disorders Center, University of Michigan, Ann Arbor. 9. Department of Pediatrics, Cardinal Glennon Children's Medical Center, Saint Louis University, St Louis, Missouri. 10. Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio. 11. Department of Otolaryngology-Head and Neck Surgery, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio. 12. Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia. 13. Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts15Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts.
Abstract
IMPORTANCE: It is important to distinguish children with different levels of severity of obstructive sleep apnea syndrome (OSAS) preoperatively using clinical parameters. This can identify children who most need polysomnography (PSG) prior to adenotonsillectomy (AT). OBJECTIVE: To assess whether a combination of factors, including demographics, physical examination findings, and caregiver reports from questionnaires, can predict different levels of OSAS severity in children. DESIGN, SETTING, AND PARTICIPANTS: Baseline data from 453 children from the Childhood Adenotonsillectomy (CHAT) study were analyzed. Children 5.0 to 9.9 years of age with PSG-diagnosed OSAS, who were considered candidates for AT, were included. INTERVENTIONS: Polysomnography for diagnosis of OSAS. MAIN OUTCOMES AND MEASURES: Linear or logistic regression models were fitted to identify which demographic, clinical, and caregiver reports were significantly associated with the apnea hypopnea index (AHI) and oxygen desaturation index (ODI). RESULTS: Race (African American), obesity (body mass index z score > 2), and the Pediatric Sleep Questionnaire (PSQ) total score were associated with higher levels of AHI and ODI (P = .05). A multivariable model that included the most significant variables explained less than 3% of the variance in OSAS severity as measured by PSG outcomes. Tonsillar size and Friedman palate position were not associated with increased AHI or ODI. Models that tested for potential effect modification by race or obesity showed no evidence of interactions with any clinical measure, AHI, or ODI (P > .20 for all comparisons). CONCLUSIONS AND RELEVANCE: This study of more than 450 children with OSAS identifies a number of clinical parameters that are associated with OSAS severity. However, information on demographics, physical findings, and questionnaire responses does not robustly discriminate different levels of OSAS severity. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00560859.
RCT Entities:
IMPORTANCE: It is important to distinguish children with different levels of severity of obstructive sleep apnea syndrome (OSAS) preoperatively using clinical parameters. This can identify children who most need polysomnography (PSG) prior to adenotonsillectomy (AT). OBJECTIVE: To assess whether a combination of factors, including demographics, physical examination findings, and caregiver reports from questionnaires, can predict different levels of OSAS severity in children. DESIGN, SETTING, AND PARTICIPANTS: Baseline data from 453 children from the Childhood Adenotonsillectomy (CHAT) study were analyzed. Children 5.0 to 9.9 years of age with PSG-diagnosed OSAS, who were considered candidates for AT, were included. INTERVENTIONS: Polysomnography for diagnosis of OSAS. MAIN OUTCOMES AND MEASURES: Linear or logistic regression models were fitted to identify which demographic, clinical, and caregiver reports were significantly associated with the apnea hypopnea index (AHI) and oxygen desaturation index (ODI). RESULTS: Race (African American), obesity (body mass index z score > 2), and the Pediatric Sleep Questionnaire (PSQ) total score were associated with higher levels of AHI and ODI (P = .05). A multivariable model that included the most significant variables explained less than 3% of the variance in OSAS severity as measured by PSG outcomes. Tonsillar size and Friedman palate position were not associated with increased AHI or ODI. Models that tested for potential effect modification by race or obesity showed no evidence of interactions with any clinical measure, AHI, or ODI (P > .20 for all comparisons). CONCLUSIONS AND RELEVANCE: This study of more than 450 children with OSAS identifies a number of clinical parameters that are associated with OSAS severity. However, information on demographics, physical findings, and questionnaire responses does not robustly discriminate different levels of OSAS severity. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00560859.
Authors: Tanya G Weinstock; Carol L Rosen; Carole L Marcus; Susan Garetz; Ron B Mitchell; Raouf Amin; Shalini Paruthi; Eliot Katz; Raanan Arens; Jia Weng; Kristie Ross; Ronald D Chervin; Susan Ellenberg; Rui Wang; Susan Redline Journal: Sleep Date: 2014-02-01 Impact factor: 5.849
Authors: Carole L Marcus; Reneé H Moore; Carol L Rosen; Bruno Giordani; Susan L Garetz; H Gerry Taylor; Ron B Mitchell; Raouf Amin; Eliot S Katz; Raanan Arens; Shalini Paruthi; Hiren Muzumdar; David Gozal; Nina Hattiangadi Thomas; Janice Ware; Dean Beebe; Karen Snyder; Lisa Elden; Robert C Sprecher; Paul Willging; Dwight Jones; John P Bent; Timothy Hoban; Ronald D Chervin; Susan S Ellenberg; Susan Redline Journal: N Engl J Med Date: 2013-05-21 Impact factor: 91.245
Authors: Teresa M Ward; Maida Lynn Chen; Carol A Landis; Sarah Ringold; Dean W Beebe; Kenneth C Pike; Carol A Wallace Journal: Qual Life Res Date: 2016-12-16 Impact factor: 4.147
Authors: Sukhpreet K Tamana; Lisa Smithson; Amanda Lau; Jennifer Mariasine; Rochelle Young; Joyce Chikuma; Diana L Lefebvre; Padmaja Subbarao; Allan B Becker; Stuart E Turvey; Malcolm R Sears; Jacqueline Pei; Piush J Mandhane Journal: Sleep Date: 2018-01-01 Impact factor: 5.849
Authors: Anna Tomkies; Romaine F Johnson; Gopi Shah; Michelle Caraballo; Patricia Evans; Ron B Mitchell Journal: J Clin Sleep Med Date: 2019-10-15 Impact factor: 4.062
Authors: Rajeev Bhatia; Daniel J Lesser; Flavia G S A Oliveira; Winston H Tran; Thomas G Keens; Michael C K Khoo; Sally L Davidson Ward Journal: J Clin Sleep Med Date: 2015-09-15 Impact factor: 4.062
Authors: Scott R Plotkin; Stephanie D Davis; Kent A Robertson; Srivandana Akshintala; Julian Allen; Michael J Fisher; Jaishri O Blakeley; Brigitte C Widemann; Rosalie E Ferner; Carole L Marcus Journal: Neurology Date: 2016-08-16 Impact factor: 9.910