Predicting obstructive sleep apnea severity in children referred for polysomnography: use of the Pediatric Sleep Questionnaire and Subscales

Bseikri, Mustafa; Zhang, Jie; Kirley, Jocelyn; Lee, Catherine; Castillo, Adrienne; Feliciano, Elizabeth M. Cespedes

doi:10.1007/s11325-022-02647-6

Cited by 6 publications

(4 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The ANB parameter, which reflects the relationship between the anteroposterior and anteroposterior relative positions of the maxilla and mandible, can also predict the degree of severity to a certain extent, indicating that we can roughly determine the impact and severity of OSA on the maxillofacial region through facial appearance. Most studies indicated that the ability of the questionnaire to screen OSA was low, 65 , 66 but higher than that of videotape with OSA characteristics 67 . It was discovered in this study that neither the CSHQ nor the OSA-18 68 could predict the severity of OSA.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Nomogram for Predicting Obstructive Sleep Apnea Severity in Children

Liu,

Xie,

Yang

et al. 2024

NSS

View full text Add to dashboard Cite

Purpose The clinical presentation of Obstructive Sleep Apnea (OSA) in children is insidious and harmful. Early identification of children with OSA, particularly those at a higher risk for severe symptoms, is essential for making informed clinical decisions and improving long-term outcomes. Therefore, we developed and validated a risk prediction model for severity in Chinese children with OSA to effectively identify children with moderate-to-severe OSA in a clinical setting. Patients and Methods From June 2023 to September 2023, we retrospectively analyzed the medical records of 367 Children diagnosed with OSA through portable bedside polysomnography (PSG). Predictor variables were screened using the least absolute shrinkage and selection operator (LASSO) and logistic regression techniques to construct nomogram to predict the severity of OSA. Receiver operating characteristic curve (ROC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC) were used to determine the discrimination, calibration, and clinical usefulness of the nomogram. Results A total of 367 children with a median age of 84 months were included in this study. Neck circumference, ANB, gender, learning problem, and level of obstruction were identified as independent risk factors for moderate-severe OSA. The consistency indices of the nomogram in the training and validation cohorts were 0.841 and 0.75, respectively. The nomogram demonstrated a strong concordance between the predicted probabilities and the observed probabilities for children diagnosed with moderate-severe OSA. With threshold probabilities ranging from 0.1 to 1.0, the predictive model demonstrated strong predictive efficacy and yielded improved net benefit for clinical decision-making. ROC analysis was employed to classify the children into high and low-risk groups, utilizing the Optimal Cutoff value of 0.39. Conclusion A predictive model using LASSO regression was developed and validated for children with varying levels of OSA. This model identifies children at risk of developing OSA at an early stage.

show abstract

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Nomogram for Predicting Obstructive Sleep Apnea Severity in Children

Liu,

Xie,

Yang

et al. 2024

NSS

View full text Add to dashboard Cite

show abstract

“…The authors noted that their results might have been affected by population differences compared with the initial validation study (children referred for PSG due to pre‐test concerns). The authors also suggested augmenting the PSQ with additional clinical variables to improve its predictive utility 20 …”

Section: Diagnosis Of Sdb: Beyond the Ahimentioning

confidence: 99%

“…The authors also suggested augmenting the PSQ with additional clinical variables to improve its predictive utility. 20…”

Section: Questionnairesmentioning

confidence: 99%

“…The PSQ on the other hand, is a widely used tool for screening SDB in children. Research by Bseikri et al 20 looked at the feasibility of predicting the severity of the OSA in children referred for PSG based on the PSQ to improve triaging. They found in a cohort of 477 children referred for PSG that the sleep‐related breathing disorder (SRDB) subscale from the PSQ was not predictive of the severity of OSA at any OAHI threshold, while the snoring subscale was only modestly predictive.…”

Section: Diagnosis Of Sdb: Beyond the Ahimentioning

confidence: 99%

See 1 more Smart Citation

Pediatric pulmonology year in review 2022: Sleep medicine

Cabrera,

Tapia

2023

Pediatric Pulmonology

View full text Add to dashboard Cite

Pediatric pulmonology publishes original research, review articles, and case reports on a wide variety of pediatric respiratory disorders. In this article, we summarized the past year's publications in sleep medicine and reviewed selected literature from other journals in this field. We focused on original research articles exploring aspects of sleep‐disordered breathing in patients with underlying conditions such as asthma, neuromuscular disorders, and Down syndrome. We also explored sleep‐disordered breathing risk factors, monitoring, diagnosis, and treatment; and included recent recommendations for drug‐induced sleep endoscopy and ways to monitor and improve PAP adherence remotely.

show abstract

Assessment of the Pediatric Patient with Obesity

Sweeney,

Fernandez

2023

Managing Pediatric Obesity Using Advanced Therapies

View full text Add to dashboard Cite

Predicting obstructive sleep apnea severity in children referred for polysomnography: use of the Pediatric Sleep Questionnaire and Subscales

Cited by 6 publications

References 23 publications

Development and Validation of a Nomogram for Predicting Obstructive Sleep Apnea Severity in Children

Development and Validation of a Nomogram for Predicting Obstructive Sleep Apnea Severity in Children

Pediatric pulmonology year in review 2022: Sleep medicine

Assessment of the Pediatric Patient with Obesity

Contact Info

Product

Resources

About