Development of a pediatric obstructive sleep apnea triage algorithm
Abstract Introduction Diagnosis and treatment of obstructive sleep apnea (OSA) in children is often delayed due to the high prevalence and limited physician and sleep testing resources. As a result, children may be referred to multiple specialties, such as pediatric sleep medicine and pediatric otol...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2021-07-01
|
| Series: | Journal of Otolaryngology - Head and Neck Surgery |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40463-021-00528-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832568825067864064 |
|---|---|
| author | D. S. Heath H. El-Hakim Y. Al-Rahji E. Eksteen T. C. Uwiera A. Isaac M. Castro-Codesal C. Gerdung J. Maclean P. J. Mandhane |
| author_facet | D. S. Heath H. El-Hakim Y. Al-Rahji E. Eksteen T. C. Uwiera A. Isaac M. Castro-Codesal C. Gerdung J. Maclean P. J. Mandhane |
| author_sort | D. S. Heath |
| collection | DOAJ |
| description | Abstract Introduction Diagnosis and treatment of obstructive sleep apnea (OSA) in children is often delayed due to the high prevalence and limited physician and sleep testing resources. As a result, children may be referred to multiple specialties, such as pediatric sleep medicine and pediatric otolaryngology, resulting in long waitlists. Method We used data from our pediatric OSA clinic to identify predictors of tonsillectomy and/or adenoidectomy (AT). Before being seen in the clinic, parents completed the Pediatric Sleep Questionnaire (PSQ) and screening questionnaires for restless leg syndrome (RLS), nasal rhinitis, and gastroesophageal reflux disease (GERD). Tonsil size data were obtained from patient charts and graded using the Brodsky-five grade scale. Children completed an overnight oximetry study before being seen in the clinic, and a McGill oximetry score (MOS) was assigned based on the number and depth of oxygen desaturations. Logistic regression, controlling for otolaryngology physician, was used to identify significant predictors of AT. Three triage algorithms were subsequently generated based on the univariate and multivariate results to predict AT. Results From the OSA cohort, there were 469 eligible children (47% female, mean age = 8.19 years, SD = 3.59), with 89% of children reported snoring. Significant predictors of AT in univariate analysis included tonsil size and four PSQ questions, (1) struggles to breathe at night, (2) apneas, (3) daytime mouth breathing, and (4) AM dry mouth. The first triage algorithm, only using the four PSQ questions, had an odds ratio (OR) of 4.02 for predicting AT (sensitivity = 0.28, specificity = 0.91). Using only tonsil size, the second algorithm had an OR to predict AT of 9.11 (sensitivity = 0.72, specificity = 0.78). The third algorithm, where MOS was used to stratify risk for AT among those children with 2+ tonsils, had the same OR, sensitivity, and specificity as the tonsil-only algorithm. Conclusion Tonsil size was the strongest predictor of AT, while oximetry helped stratify individual risk for AT. We recommend that referral letters for snoring children include graded tonsil size to aid in the triage based on our findings. Children with 2+ tonsil sizes should be triaged to otolaryngology, while the remainder should be referred to a pediatric sleep specialist. Graphical abstract |
| format | Article |
| id | doaj-art-1b7798466da8484b8631b7577ea472c2 |
| institution | Kabale University |
| issn | 1916-0216 |
| language | English |
| publishDate | 2021-07-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Journal of Otolaryngology - Head and Neck Surgery |
| spelling | doaj-art-1b7798466da8484b8631b7577ea472c22025-02-03T00:22:59ZengSAGE PublishingJournal of Otolaryngology - Head and Neck Surgery1916-02162021-07-015011710.1186/s40463-021-00528-8Development of a pediatric obstructive sleep apnea triage algorithmD. S. Heath0H. El-Hakim1Y. Al-Rahji2E. Eksteen3T. C. Uwiera4A. Isaac5M. Castro-Codesal6C. Gerdung7J. Maclean8P. J. Mandhane9Department of Educational Psychology, University of AlbertaDivision of Otolaryngology Head and Neck Surgery, Department of Surgery and Pediatrics, University of AlbertaDivision of Otolaryngology Head and Neck Surgery, Department of Surgery and Pediatrics, University of AlbertaDivision of Otolaryngology Head and Neck Surgery, Department of Surgery and Pediatrics, University of AlbertaDivision of Otolaryngology Head and Neck Surgery, Department of Surgery and Pediatrics, University of AlbertaDivision of Otolaryngology Head and Neck Surgery, Department of Surgery and Pediatrics, University of AlbertaStollery Children’s Hospital, University of AlbertaStollery Children’s Hospital, University of AlbertaStollery Children’s Hospital, University of AlbertaStollery Children’s Hospital, University of AlbertaAbstract Introduction Diagnosis and treatment of obstructive sleep apnea (OSA) in children is often delayed due to the high prevalence and limited physician and sleep testing resources. As a result, children may be referred to multiple specialties, such as pediatric sleep medicine and pediatric otolaryngology, resulting in long waitlists. Method We used data from our pediatric OSA clinic to identify predictors of tonsillectomy and/or adenoidectomy (AT). Before being seen in the clinic, parents completed the Pediatric Sleep Questionnaire (PSQ) and screening questionnaires for restless leg syndrome (RLS), nasal rhinitis, and gastroesophageal reflux disease (GERD). Tonsil size data were obtained from patient charts and graded using the Brodsky-five grade scale. Children completed an overnight oximetry study before being seen in the clinic, and a McGill oximetry score (MOS) was assigned based on the number and depth of oxygen desaturations. Logistic regression, controlling for otolaryngology physician, was used to identify significant predictors of AT. Three triage algorithms were subsequently generated based on the univariate and multivariate results to predict AT. Results From the OSA cohort, there were 469 eligible children (47% female, mean age = 8.19 years, SD = 3.59), with 89% of children reported snoring. Significant predictors of AT in univariate analysis included tonsil size and four PSQ questions, (1) struggles to breathe at night, (2) apneas, (3) daytime mouth breathing, and (4) AM dry mouth. The first triage algorithm, only using the four PSQ questions, had an odds ratio (OR) of 4.02 for predicting AT (sensitivity = 0.28, specificity = 0.91). Using only tonsil size, the second algorithm had an OR to predict AT of 9.11 (sensitivity = 0.72, specificity = 0.78). The third algorithm, where MOS was used to stratify risk for AT among those children with 2+ tonsils, had the same OR, sensitivity, and specificity as the tonsil-only algorithm. Conclusion Tonsil size was the strongest predictor of AT, while oximetry helped stratify individual risk for AT. We recommend that referral letters for snoring children include graded tonsil size to aid in the triage based on our findings. Children with 2+ tonsil sizes should be triaged to otolaryngology, while the remainder should be referred to a pediatric sleep specialist. Graphical abstracthttps://doi.org/10.1186/s40463-021-00528-8Sleep-related breathing disorderObstructive sleep apneaSnoringTonsillectomyAdenoidectomyOximetry |
| spellingShingle | D. S. Heath H. El-Hakim Y. Al-Rahji E. Eksteen T. C. Uwiera A. Isaac M. Castro-Codesal C. Gerdung J. Maclean P. J. Mandhane Development of a pediatric obstructive sleep apnea triage algorithm Journal of Otolaryngology - Head and Neck Surgery Sleep-related breathing disorder Obstructive sleep apnea Snoring Tonsillectomy Adenoidectomy Oximetry |
| title | Development of a pediatric obstructive sleep apnea triage algorithm |
| title_full | Development of a pediatric obstructive sleep apnea triage algorithm |
| title_fullStr | Development of a pediatric obstructive sleep apnea triage algorithm |
| title_full_unstemmed | Development of a pediatric obstructive sleep apnea triage algorithm |
| title_short | Development of a pediatric obstructive sleep apnea triage algorithm |
| title_sort | development of a pediatric obstructive sleep apnea triage algorithm |
| topic | Sleep-related breathing disorder Obstructive sleep apnea Snoring Tonsillectomy Adenoidectomy Oximetry |
| url | https://doi.org/10.1186/s40463-021-00528-8 |
| work_keys_str_mv | AT dsheath developmentofapediatricobstructivesleepapneatriagealgorithm AT helhakim developmentofapediatricobstructivesleepapneatriagealgorithm AT yalrahji developmentofapediatricobstructivesleepapneatriagealgorithm AT eeksteen developmentofapediatricobstructivesleepapneatriagealgorithm AT tcuwiera developmentofapediatricobstructivesleepapneatriagealgorithm AT aisaac developmentofapediatricobstructivesleepapneatriagealgorithm AT mcastrocodesal developmentofapediatricobstructivesleepapneatriagealgorithm AT cgerdung developmentofapediatricobstructivesleepapneatriagealgorithm AT jmaclean developmentofapediatricobstructivesleepapneatriagealgorithm AT pjmandhane developmentofapediatricobstructivesleepapneatriagealgorithm |