The use of oximetry and a questionnaire in primary care enables exclusion of a subsequent obstructive sleep apnea diagnosis.

Sleep Breath

Department of Pulmonology, Medisch Spectrum Twente, Onderzoeksbureau Longgeneeskunde, P.O. Box 50000, 7500KA, Enschede, The Netherlands.

Published: March 2020

Purpose: The study aims to prospectively validate the prognostic value of oximetry alone or combined in a two-step strategy with a questionnaire for the exclusion of obstructive sleep apnea (OSA) in primary care.

Methods: A total of 140 subjects with suspected OSA were included from 54 participating primary care practices. All subjects completed the Philips questionnaire and underwent one night of oximetry prior to referral to a sleep center. The prognostic value of two strategies was evaluated against the diagnosis of the sleep center as the gold standard: (1) assume OSA and subsequently refer to a sleep center if the oxygen desaturation index (ODI) is ≥ 5 and (2) assume OSA and refer to a sleep center if the Philips questionnaire score is ≥ 55% (regardless of the ODI) or if the Philips questionnaire score is < 55% and the ODI is ≥ 5.

Results: OSA was diagnosed in the sleep centers in 100 (71%) of the included subjects. Using ODI ≥ 5 alone resulted in a sensitivity of 99.0%, a specificity of 50.0%, a negative predictive value of 95.2%, and a positive predictive value 83.2%. Using the two-step strategy, oximetry would be performed on 39% of the subjects. This strategy resulted in a sensitivity of 100%, a specificity of 35.0%, a negative predictive value of 100%, and a positive predictive value of 79.4%.

Conclusions: In a Dutch primary care population with a clinical suspicion of OSA and low frequency of cardiovascular comorbidities, the use of oximetry alone or combined in a two-step strategy with a questionnaire enables exclusion of a sleep center diagnosis of OSA.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7127990PMC
http://dx.doi.org/10.1007/s11325-019-01834-2DOI Listing

Publication Analysis

Top Keywords

sleep center
16
philips questionnaire
12
primary care
8
obstructive sleep
8
sleep apnea
8
assume osa
8
refer sleep
8
questionnaire score
8
sleep
6
oximetry questionnaire
4

Similar Publications

Persistent COVID-19 symptoms and associated factors in a tertiary hospital in Thailand.

J Infect Dev Ctries

December 2024

Division of Pulmonary and Critical Care Medicine, Department of Medicine, Faculty of Medicine, Thammasat University, Pathumthani 12120, Thailand.

Introduction: Coronavirus disease 2019 (COVID-19) is associated with long-term symptoms, but the spectrum of these symptoms remains unclear. We aimed to identify the prevalence and factors associated with persistent symptoms in patients at the post-COVID-19 outpatient clinic.

Methodology: This cross-sectional, observational study included hospitalized severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infected patients followed-up at a post-COVID-19 clinic between September 2021 and January 2022.

View Article and Find Full Text PDF

Background: Developing interventions along with the population of interest using systems thinking is a promising method to address the underlying system dynamics of overweight. The purpose of this study is twofold: to gain insight into the perspectives of adolescents regarding: (1) the system dynamics of energy balance-related behaviours (EBRBs) (physical activity, screen use, sleep behaviour and dietary behaviour); and (2) underlying mechanisms and overarching drivers of unhealthy EBRBs.

Methods: We conducted Participatory Action Research (PAR) to map the system dynamics of EBRBs together with adolescents aged 10-14 years old living in a lower socioeconomic, ethnically diverse neighbourhood in Amsterdam East, the Netherlands.

View Article and Find Full Text PDF

A multicenter study of neurofibromatosis type 1 utilizing deep learning for whole body tumor identification.

NPJ Digit Med

January 2025

Neurofibromatosis Type 1 Center and Laboratory for Neurofibromatosis Type 1 Research, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.

Deep-learning models have shown promise in differentiating between benign and malignant lesions. Previous studies have primarily focused on specific anatomical regions, overlooking tumors occurring throughout the body with highly heterogeneous whole-body backgrounds. Using neurofibromatosis type 1 (NF1) as an example, this study developed highly accurate MRI-based deep-learning models for the early automated screening of malignant peripheral nerve sheath tumors (MPNSTs) against complex whole-body background.

View Article and Find Full Text PDF

Background: Gestational exposure to non-persistent endocrine-disrupting chemicals (EDCs) may be associated with adverse pregnancy outcomes. While many EDCs affect the endocrine system, their effects on endocrine-related metabolic pathways remain unclear. This study aims to explore the global metabolome changes associated with EDC biomarkers at delivery.

View Article and Find Full Text PDF

Polysomnography (PSG) is crucial for diagnosing sleep disorders, but manual scoring of PSG is time-consuming and subjective, leading to high variability. While machine-learning models have improved PSG scoring, their clinical use is hindered by the 'black-box' nature. In this study, we present SleepXViT, an automatic sleep staging system using Vision Transformer (ViT) that provides intuitive, consistent explanations by mimicking human 'visual scoring'.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!