Predictive value of clinical features for the obstructive sleep apnoea syndrome

Deegan, Paul; McNicholas, WT

doi:10.1183/09031936.96.09010117

Cited by 232 publications

(160 citation statements)

References 25 publications

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“…1,[30][31][32][33] In adults, OSA is linked to obesity. [34][35][36][37][38] In a prospective evaluation of adults, NC corrected for height was actually a better predictor of OSA than symptoms or general obesity, as assessed by body mass index (BMI). This implies that the relationship between OSA and obesity is dependent on the variation in NC and suggests that central fat deposition in the neck and viscera is more contributory than generalized adiposity 38,39 to OSA development.…”

Section: Discussionmentioning

confidence: 99%

Inter‐ and intra‐rater reliability of neck circumference measurements in children

LaBerge

Vaccani

Gow

et al. 2008

Pediatric Pulmonology

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Summary. Rationale: Increased neck circumference is a risk factor for obstructive sleep apnea in adults. With rising obesity prevalence in children, it may be an important identifier of obstructive sleep apnea in children. The reliability of measuring neck circumference in children has not been systematically evaluated. Objective: To determine the inter-and intra-rater reliability of neck circumference measurements in children aged 2-16 years. Methods: Children aged 2-16 years with limb fractures were recruited. Neck circumference was measured by three investigators each using two separate unmarked paper tapes in the 2-5 year age group (N ¼ 43), and three separate tapes in the 6-10 and 11-16 year age groups (N ¼ 18 and 40). Results: Neck circumference measurements showed excellent inter-rater reliability for children 6-10 and 11-16 years (ICC ¼ 0.952 and 0.989). Substantial variation was observed for the 2-5 year age group (ICC ¼ 0.701). Good intra-rater reliability was demonstrated for the three groups (ICC range: 0.776, 0.950). Repeatability coefficients were 2.5-3.4 cm in the youngest age group and were 1.2-1.4 cm in the 6-16 year age group. Conclusion: In children 6-16 years old, neck circumference shows very good inter and good intra-rater reliability. Multiple measurements are not required for precision and reliability.

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Section: Discussionmentioning

confidence: 99%

Inter‐ and intra‐rater reliability of neck circumference measurements in children

LaBerge

Vaccani

Gow

et al. 2008

Pediatric Pulmonology

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“…Those models differ in terms of the variables included and the case definitions, making it difficult to compare the results across studies. (12,13,27,28) The use of multiple regression analyses with the inclusion of clinical variables has produced good prediction models. In a prospective study evaluating four AHI prediction models, their sensitivity was found to be high (85-98%), although their specificity was low (33-39%).…”

Section: Discussionmentioning

confidence: 99%

“…(11) The clinical impression alone has low accuracy for the diagnosis of sleep-disordered breathing, and polysomnography therefore remains indispensable. (12,13) A meta-analysis of clinical studies for the diagnosis of obstructive sleep apnea revealed that clinical models have higher OR values for diagnosis and severity than do questionnaire-based models (10.49 and 17.24 vs. 5.02 and 10.12, respectively). (14) In that study, the clinical elements associated with an OR > 2 were BMI, arterial hypertension, and a history of nocturnal choking.…”

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confidence: 99%

Avaliação de um modelo de predição para apneia do sono em pacientes submetidos a polissonografia

et al. 2011

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Objective: To test a prediction model for sleep apnea based on clinical and sociodemographic variables in a population suspected of having sleep disorders and submitted to polysomnography. Methods: We included 323 consecutive patients submitted to polysomnography because of the clinical suspicion of having sleep disorders. We used a questionnaire with sociodemographic questions and the Epworth sleepiness scale. Blood pressure, weight, height, and SpO 2 were measured. Multiple linear regression was used in order to create a prediction model for sleep apnea, the apnea-hypopnea index (AHI) being the dependent variable. Multinomial logistic regression was used in order to identify factors independently associated with the severity of apnea (mild, moderate, or severe) in comparison with the absence of apnea. Results: The prevalence of sleep apnea in the study population was 71.2%. Sleep apnea was more prevalent in men than in women (81.2% vs. 56.8%; p < 0.001). The multiple linear regression model, using log AHI as the dependent variable, was composed of the following independent variables: neck circumference, witnessed apnea, age, BMI, and allergic rhinitis. The best-fit linear regression model explained 39% of the AHI variation. In the multinomial logistic regression, mild apnea was associated with BMI and neck circumference, whereas severe apnea was associated with age, BMI, neck circumference, and witnessed apnea. Conclusions: Although the use of clinical prediction models for sleep apnea does not replace polysomnography as a tool for its diagnosis, they can optimize the process of deciding when polysomnography is indicated and increase the chance of obtaining positive polysomnography findings.Keywords: Sleep apnea syndromes; Polysomnography; Sleep apnea, obstructive; Body mass index. ResumoObjetivo: Testar um modelo de predição para apneia do sono a partir de variáveis sociodemográficas e clínicas em uma população com suspeita de distúrbio do sono e submetida à polissonografia. Métodos: Foram incluídos no estudo 323 pacientes consecutivos submetidos à polissonografia por suspeita clínica de distúrbio do sono. Utilizou-se um questionário com questões sociodemográficas e a escala de sonolência de Epworth. Foram medidos pressão arterial, peso, altura e SpO 2 . A regressão linear múltipla, tendo o índice de apneia-hipopneia (IAH) como variável dependente, foi utilizada para construir um modelo de predição de apneia do sono. A regressão logística multinomial foi realizada para verificar fatores associados de forma independente à gravidade da apneia (leve, moderada ou grave) em comparação à ausência de apneia. Resultados: A prevalência de apneia do sono na população de estudo foi de 71,2%, e foi mais prevalente nos homens que nas mulheres (81,2% vs. 56,8%; p < 0,001). O modelo de regressão linear múltipla, com o log IAH como variável dependente, foi composto pelas seguintes variáveis independentes: circunferência do pescoço, apneia testemunhada, idade, IMC e presença de rinite alérgica. O melhor modelo de reg...

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“…[5][6][7][8] However, there has been related work on the prediction of sleep disordered breathing and RDI. For example, a recent review of prediction formulas for severe sleep disordered breathing (RDI ≥ 20/h) reported sensitivities varying between 76% and 96% and specificities varying between 13% and 54%.…”

Section: In the Routine Clinical Evaluation Of Patients For Possible mentioning

confidence: 99%

A Novel Approach to Prediction of Mild Obstructive Sleep Disordered Breathing in a Population-Based Sample: The Sleep Heart Health Study

2010

Sleep

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1641Prediction of Mild Obstructive SDB-Caffo et al IN THE ROUTINE CLINICAL EVALUATION OF PATIENTS FOR POSSIBLE SLEEP DISORDERED BREATHING, PHY-SICIANS MAKE JUDGMENTS AS TO THE LIKELIHOODthat a particular person is affected and decide whether polysomnography is warranted based on this likelihood. Their judgments draw on elements of the patient's history, such as reports of snoring or excessive daytime somnolence, demographic factors, and weight or body mass index (BMI). If the estimated likelihood is sufficiently high, then the physician may consider ordering a polysomnogram (PSG). Similarly, media outlets and medical societies put forward recommendations to the public for self-referral to a primary care or sleep physician for the evaluation of possible sleep disordered breathing. For example, in response to the recent publication of the authors' manuscript on sleep and mortality, 1 CBS news recommended that patients discuss with their physicians the need for polysomnography in the presence of severe snoring, restless sleep, frequent waking up at night, and excessive daytime exhaustion.2 Faced with continued patient concern about having sleep disordered breathing, clinicians need tools to identify those individuals most likely to have sleep disordered breathing so as to avoid unneeded referral for a PSG.At the core of this discussion are two questions related to the prediction of the eventual result of a PSG in the general population: first, how predictable is the result of a PSG, and second, what easily collected variables are most influential for predicting the result of a PSG?A number of previous studies have considered whether the respiratory disturbance index (RDI) or the apnea-hypopnea index (AHI) can be predicted with sufficient certainty using such clinical information; these findings reviewed below generally indicate limited predictive power.In this manuscript, we consider the prediction of RDI in participants in the Sleep Heart Health Study (SHHS) 3 using modern ensemble learning algorithms to make predictions based on classifications of predictor variables. 4 Ensemble learning algorithms base their predictions on a collection (ensemble) of simpler prediction equations. We focus on the prediction of mildly elevated RDI values, because patients with severe disease are presumably easier to diagnose without the aid of screening prediction algorithms. The goals of this manuscript are 3-fold: The first is to investigate the cross-sectional prediction of RDI in a population-based sample using these modern ensemble learning algorithms, which sort the data based on patterns of clustering of classifiers.4 A related second goal is to investigate the overall predictability of RDI in this population. A third goal is to demonstrate the utility of ensemble learning algorithms to sleep researchers, as these methods are potentially useful for reducing large amounts of data, such as polysomnographic data, to their most informative elements.This study differs from other previous analyses that focused on individual predic...

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Predictive value of clinical features for the obstructive sleep apnoea syndrome

Cited by 232 publications

References 25 publications

Inter‐ and intra‐rater reliability of neck circumference measurements in children

Inter‐ and intra‐rater reliability of neck circumference measurements in children

Avaliação de um modelo de predição para apneia do sono em pacientes submetidos a polissonografia

A Novel Approach to Prediction of Mild Obstructive Sleep Disordered Breathing in a Population-Based Sample: The Sleep Heart Health Study

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