Accuracy of clinical scoring tools for the diagnosis of pediatric obstructive sleep apnea

Patel, Anant; Meghji, Sheneen; Phillips, John S.

doi:10.1002/lary.28146

Cited by 39 publications

(44 citation statements)

References 53 publications

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“…These results are consistent with a recent systematic review which investigated the diagnostic accuracy of clinical scoring tools for pediatric OSA. 22 We also found that children with larger tonsils were more likely to have OSA by PSG ( P = .0007). There is conflicting data on these associations in the literature with some studies finding history 13,14 and tonsil size 15,19 to be poor predictors of OSA severity whereas others report the contrary.…”

Section: Discussionsupporting

confidence: 53%

Predictors of a Normal Sleep Study in Healthy Children with Sleep Disordered Breathing Symptoms

Abraham

Bains

Rubin

et al. 2021

Ann Otol Rhinol Laryngol

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Objective: To determine the prevalence and characteristics of children with normal elective polysomnography for obstructive sleep disordered breathing (oSDB) based on the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) guidelines. Study Design: In this retrospective cohort study, we identified patients ages 2 to 18 who underwent diagnostic polysomnography (PSG) ordered by our otolaryngology department for SDB between 2012 and 2018. Setting: All patients were seen by otolaryngologists at an urban tertiary safety net hospital. Subjects and Methods: There were a total of 456 patients studied (average age 5.66 ± 3.19; 263 (57.7%) males, 193 (42.3%) females. Demographic factors (age, gender, race, ethnicity, language, insurance status) and clinical findings (symptom severity, tonsil size) were recorded. The data were analyzed by univariate and multivariate analysis. Results: Two hundred four patients (44.7%) had no obstructive sleep apnea (OSA) based on AHI<2 on PSG. Children with a larger tonsil size had 3.18 times the odds of OSA compared to those with a medium tonsil size (95% CI 1.64, 6.19) when adjusting for symptoms, age category, and race ( P = .0007). Children ages 4 to 6 years had 0.25 times the odds of OSA compared to those ages 2-3 years (95% CI 0.12, 1.54) when adjusting for symptoms, tonsil size, and race ( P = .0011). White children had 0.28 times the odds of OSA compared to Black children (95% CI 0.14, 0.57) when adjusting for symptoms, tonsil size, and age category ( P = .0004). Conclusion: Among our patient population, 44.7% had normal sleep studies. Younger children (ages 2-3) were less likely to have normal polysomnography. This research demonstrates that obtaining sleep studies in otherwise healthy children with SDB can affect management decisions, and they should be discussed with families with a focus on patient centered decision making.

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Section: Discussionsupporting

confidence: 53%

Predictors of a Normal Sleep Study in Healthy Children with Sleep Disordered Breathing Symptoms

Abraham

Bains

Rubin

et al. 2021

Ann Otol Rhinol Laryngol

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“…It was identified that the OSA-18 was initially designed as a diseasespecific quality of life tool that does not predict obstructive sleep apnea (OSA) symptoms consistent with the gold-standard PSG. Recently Patel et al (151) scrutinized the accuracy of such clinical scoring tools. Additionally, the study by Soh et al (80) acknowledged that there exists a lack of parental understanding of some items and their wording in the original instrument.…”

Section: Discussionmentioning

confidence: 99%

Pediatric Sleep Tools: An Updated Literature Review

Sen

Spruyt

2020

Front. Psychiatry

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Since a thorough review in 2011 by Spruyt, into the integral pitfalls of pediatric questionnaires in sleep, sleep researchers worldwide have further evaluated many existing tools. This systematic review aims to comprehensively evaluate and summarize the tools currently in circulation and provide recommendations for potential evolving avenues of pediatric sleep interest. 144 "tool"-studies (70 tools) have been published aiming at investigating sleep in primarily 6-18 years old per parental report. Although 27 new tools were discovered, most of the studies translated or evaluated the psychometric properties of existing tools. Some form of normative values has been established in 18 studies. More than half of the tools queried general sleep problems. Extra efforts in tool development are still needed for tools that assess children outside the 6-to-12-year-old age range, as well as for tools examining sleep-related aspects beyond sleep problems/disorders. Especially assessing the validity of tools has been pursued vis-à-vis fulfillment of psychometric criteria. While the Spruyt et al. review provided a rigorous step-by-step guide into the development and validation of such tools, a pattern of steps continue to be overlooked. As these instruments are potentially valuable in assisting in the development of a clinical diagnosis into pediatric sleep pathologies, it is required that while they are primary subjective measures, they behave as objective measures. More tools for specific populations (e.g., in terms of ages, developmental disabilities, and sleep pathologies) are still needed.

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“…14 In an effort to identify pediatric patients who are at risk of OSA, multiple studies have emerged, and have focused on the development of a questionnaire tool. [15][16][17][18] However, the majority of these questionnaires is generally too lengthy and time-consuming to be used as a screening tool by primary care physicians in their customary busy practices, since each of such questionnaires includes between 22 and 40 questions. 2,19 In addition, most of these questionnaires do not accurately predict a diagnosis of pediatric OSA as collaborated by a PSG.…”

Section: Introductionmentioning

confidence: 99%

“…2,19 In addition, most of these questionnaires do not accurately predict a diagnosis of pediatric OSA as collaborated by a PSG. 17 As a potential solution, Spruyt and Gozal conducted a comprehensive machine learning analysis of a large number of a priori relevant questions related to pediatric OSA symptoms, and a set of six short, hierarchically arranged questions was proposed as a new screening instrument, the Pediatric Obstructive Sleep Apnea Screening Tool (POSAST). The POSAST was brief and easy to use in clinical practice, 20 and was subsequently validated in the English language, 18 whereby using an equation-derived score ≥ 1 yielded a sensitivity of 83%, a specificity of 64%, positive predictive value (PPV) of 28%, and negative predictive value (NPV) of 96% for diagnosing moderate and severe OSA (apnea-hypopnea index, AHI ≥ 5 events/h).…”

Section: Introductionmentioning

confidence: 99%

Validity and reliability of the Thai version of the pediatric obstructive sleep apnea screening tool

Tanphaichitr

Chuenchod

Ungkanont

et al. 2021

Pediatric Pulmonology

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Objective: Obstructive sleep apnea (OSA) is highly prevalent in children and requires an expensive and relatively unavailable sleep study for diagnosis. This study was undertaken to translate the previously validated pediatric OSA screening tool (POSAST) to the Thai language and assess its accuracy and test-retest reliability in at-risk symptomatic children.Study Design: Prospective cross-sectional cohort study.Methods: Pediatric patients clinically referred for suspected OSA who underwent overnight polysomnography (PSG) were recruited, and caregivers completed the Thai version of the POSAST. The same questionnaire was completed again after 2-4 weeks. The reliability of the questionnaire was determined by internal consistency and test-retest reliability. The validity of the questionnaire was assessed by constructing receiver operating characteristic (ROC) curves to identify the equation-derived score and total additive score cutoff points that identify high risk for moderate and severe OSA (AHI of ≥ 5 events/h).Results: One hundred and ten subjects completed the study. The mean age was 8.4 ± 2.9 years. The mean apnea-hypopnea index (AHI) was 10.9 ± 11.9 events/h. Test-retest reliability (Pearson correlation coefficient = 0.96, p < .001) and internal consistency between each question (Cronbach's alpha coefficient = 0.82, p < .001) were excellent. An equation-derived score cut-off of 1.9 yielded 78.4% sensitivity, 50.0% specificity, 76.3% positive predictive value (PPV), and 52.9% negative predictive value (NPV), while a total additive score cut-off of 8 corresponded to 81.1% sensitivity, 52.8% specificity, 77.9% PPV, and 57.6% NPV for diagnosing moderate and severe OSA (AHI ≥ 5 events/h). Conclusion:The internal consistency and reproducibility of the Thai version of the POSAST are satisfactory, display acceptable validity, and the instrument can be used for screening symptomatic Thai children for OSA.

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Accuracy of clinical scoring tools for the diagnosis of pediatric obstructive sleep apnea

Cited by 39 publications

References 53 publications

Predictors of a Normal Sleep Study in Healthy Children with Sleep Disordered Breathing Symptoms

Predictors of a Normal Sleep Study in Healthy Children with Sleep Disordered Breathing Symptoms

Pediatric Sleep Tools: An Updated Literature Review

Validity and reliability of the Thai version of the pediatric obstructive sleep apnea screening tool

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