scholarly journals Utilization of Overnight Pulse Oximetry in Fibromyalgia Patients

2019 ◽  
Vol 8 ◽  
pp. 216495611984712
Author(s):  
Stephanie D Clark ◽  
Bradley R Salonen ◽  
Neha V Reddy BS ◽  
Arya B Mohabbat
Keyword(s):  
Sleep Apnea ◽  
High Risk ◽  
Pulse Oximetry ◽  
Retrospective Chart Review ◽  
Screening Tools ◽  
Risk Category ◽  
Exact Test ◽  
Sleep Questionnaire ◽  
Obstructive Sleep ◽  
Berlin Sleep Questionnaire

Objective To assess whether the Berlin Sleep Questionnaire and the Snoring, Tired, Observed, Pressure, Body mass, Age, Neck, and Gender questionnaire (STOP-BANG) might be suitable replacements for an overnight sleep pulse oximetry as screening tools for sleep disordered breathing in patients with fibromyalgia. Participants: From June 8, 2018 through July 25, 2018, adult patients with a confirmed diagnosis of fibromyalgia (via the 1990 and/or 2010 American College of Rheumatology Fibromyalgia Classification Criteria) who attended Mayo Clinic’s Fibromyalgia Treatment Program were invited to participate in the study. Methods: The design was a prospective comparative study with a retrospective chart review component. Participants completed 2 validated surveys: the Berlin Sleep Questionnaire and the STOP-BANG. Medical records were reviewed for demographic information and overnight pulse oximetry test results. Results: Results from both questionnaires indicate that there is an association between sleep apnea risk category (defined by questionnaire) and oximetry results. Fisher’s exact test for STOP-BANG and Berlin Sleep Questionnaire are statistically significant ( P < .001), indicating that participants at high risk for sleep apnea (based on the questionnaires) had a greater prevalence of abnormal oximetry results than those at low risk for sleep apnea. Participants who were classified as high risk (85.7%) or intermediate risk (61.5%) on the STOP-BANG questionnaire for sleep apnea had abnormal oximetry results. Participants who scored as high risk (85.7%) for sleep apnea on the Berlin Sleep Questionnaire had abnormal oximetry results. Conclusions: In patients with fibromyalgia, the Berlin Sleep Questionnaire and the STOP-BANG questionnaires could be beneficial in determining the probability of obstructive sleep apnea and the subsequent need for pulse oximetry testing, in higher risk patients.

scholarly journals Utility of the Pediatric Sleep Questionnaire and Pulse Oximetry as Screening Tools in Pediatric Patients with Suspected Obstructive Sleep Apnea Syndrome

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Jose A. Peña-Zarza ◽  
Borja Osona-Rodriguez de Torres ◽  
Jose Antonio Gil-Sanchez ◽  
Joan Figuerola-Mulet
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Pulse Oximetry ◽  
Clinical Assessment ◽  
Pediatric Patients ◽  
Screening Tools ◽  
Sleep Questionnaire ◽  
Obstructive Sleep ◽  
Pediatric Sleep Questionnaire ◽  
Pulse Oximetry Screening

Objective. To assess the screening tools in snoring patients.Material and Methods. A retrospective review of data was conducted from children between 2 and 15 years old who were referred on suspicion of obstructive sleep apnea-hypopnea (OSAH) between June 2008 and June 2011. We excluded patients with significant comorbidities. Pediatric Sleep Questionnaire (PSQ), physical exam (PE), and pulse-oximetry data were collected and correlated with the results of the nightly polygraph at home.Results. We selected 98 patients. The 22-item version of the PSQ had sensitivity of 96% and specificity of 36.8%. The overall value of the clinic predictor of OSAH (PSQ and PE together) exhibited an increased specificity 57.6% with 94.6% of sensitivity. The nocturnal home oximetry method used alone was very specific, 92.1%, but had a lower sensitivity, 77.1%. The set of clinical assessment tools used together with pulse-oximetry screening provided excellent specificity 98.1% and a positive predictive value 94.1% globally. The performance of this screening tool is related with the severity of OSAH and accuracy is better in moderate and severe cases.Conclusion. The combination of clinical assessment and pulse-oximetry screening can provide a sufficient diagnostic approach for pediatric patients with suspected OSAH at least in moderate and severe cases.

Serum bicarbonate level improves specificity of Berlin Sleep Questionnaire for obstructive sleep apnea

2020 ◽  
pp. 1-7
Author(s):  
Mazlum Dursun ◽  
Hadice Selimoğlu Şen ◽  
Süreyya Yılmaz ◽  
Melike Demir ◽  
Gökhan Kırbaş ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Bicarbonate Level ◽  
Serum Bicarbonate ◽  
Sleep Questionnaire ◽  
Obstructive Sleep ◽  
Serum Bicarbonate Level ◽  
Berlin Sleep Questionnaire

Acromegaly and Obstructive Sleep Apnea: Identifying the High-Risk Group

2019 ◽  
Author(s):  
Xiaojun Zhan ◽  
Chandala Chitguppi ◽  
Ethan Berman ◽  
Gurston Nyquist ◽  
Tomas Garzon-Muvdi ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
High Risk ◽  
Risk Group ◽  
High Risk Group ◽  
Obstructive Sleep

420 Evaluating the Rate of Referral for Obstructive Sleep Apnea in a Pre-Doctoral Dental Clinic Using the STOP-Bang Questionnaire

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A166-A166
Author(s):  
Nathan Guess ◽  
Henry Fischbach ◽  
Andy Ni ◽  
Allen Firestone
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
High Risk ◽  
Electronic Health Record ◽  
Health Record ◽  
Dental Clinic ◽  
Neck Size ◽  
Previous Diagnosis ◽  
Obstructive Sleep ◽  
Electronic Health

Abstract Introduction The STOP-Bang Questionnaire is a validated instrument to assess an individual’s risk for obstructive sleep apnea (OSA). The prevalence of OSA is estimated at 20% in the US with only 20% of those individuals properly diagnosed. Dentists are being asked to screen and refer patients at high risk for OSA for definitive diagnosis and treatment. The aim of this study was to determine whether patients in a dental school student clinic who were identified as high-risk for OSA, were referred for evaluation of OSA. Methods All new patients over the age of 18 admitted to The Ohio State University - College of Dentistry complete an “Adult Medical History Form”. Included in this study were 21,312 patients admitted between July 2017 and March 2020. Data were extracted from the history form to determine the STOP-Bang Score for all patients: age, sex, BMI, self-reported snoring-, stopped breathing/choking/gasping while sleeping-, high blood pressure-, neck size over 17” (males) or 16” (females)-, and tiredness. Each positive response is a point, for a maximum of 8 points possible. Additionally, any previous diagnosis of sleep apnea, and the patient’s history of referrals were extracted from the health record. According to clinic policy, if the patient did not have a previous diagnosis for OSA noted in the health history, and scored 5 or more on the STOP-Bang Questionnaire, they should receive a referral for an evaluation for OSA. Notes and referral forms were reviewed to determine if the appropriate referrals occurred for patients at high risk without a previous diagnosis. Results Of the 21,312 patients screened; 1098 (5.2%) screened high-risk for OSA, of which 398 had no previous diagnosis of OSA. Of these 398 patients, none (0%) had referrals for further evaluation for OSA. Conclusion The rate of appropriate referrals from a student dental clinic with an electronic health record was unacceptably low. Continued education and changes to the electronic health record are needed to ensure those at high-risk for OSA are appropriately referred and managed. Support (if any):

scholarly journals Paediatric Sleep Questionnaire for Obstructive Sleep Apnoea Syndrome Screening: Is Sleep Quality Worthy of Note?

2021 ◽  
Vol 11 (4) ◽  
pp. 1440 ◽  
Author(s):  
Vera Panzarella ◽  
Giovanna Giuliana ◽  
Paola Spinuzza ◽  
Gaetano La Mantia ◽  
Laura Maniscalco ◽  
...  
Keyword(s):  
Sleep Quality ◽  
Obstructive Sleep Apnoea ◽  
Sleep Apnoea ◽  
Screening Tools ◽  
Obstructive Sleep Apnoea Syndrome ◽  
P Value ◽  
Predictive Values ◽  
Sleep Questionnaire ◽  
Sleep Apnoea Syndrome ◽  
Obstructive Sleep

Obstructive sleep apnoea syndrome (OSAS) is the most severe condition on the spectrum of sleep-related breathing disorders (SRBDs). The Paediatric Sleep Questionnaire (PSQ) is one of the most used and validated screening tools, but it lacks the comprehensive assessment of some determinants of OSAS, specifically anamnestic assessment and sleep quality. This study aims to assess the accuracy of some specific items added to the original PSQ, particularly related to the patient’s anamnestic history and to the quality of sleep, for the screening of OSAS in a paediatric population living in Sicily (Italy). Fifteen specific items, divided into “anamnestic” and “related to sleep quality” were added to the original PSQ. The whole questionnaire was administered via a digital form to the parents of children at 4 schools (age range: 3–13 years). For each item, sensitivity and specificity, positive and negative predictive values, and positive and negative likelihood ratios were calculated. The highest sensitivity (80.0, 95% CI: 28.4; 99.5), in combination with the highest specificity (61.1, 95% CI: 35.7; 82.7), was found for the Item 32 (“assumption of bizarre or abnormal positions during sleep”). This item was found statistically significant for predicting the occurrence of OSAS in children (p-value ≤0.003). The study demonstrates the accuracy of specific items related to sleep quality disturbance for the preliminary assessment of the disease. Although these results should be validated on a larger sample of subjects, they suggest that including the factors discriminating sleep quality could further increase the efficiency and accuracy of PSQ.

scholarly journals Validation of the Berlin Questionnaire and American Society of Anesthesiologists Checklist as Screening Tools for Obstructive Sleep Apnea in Surgical Patients

2008 ◽  
Vol 108 (5) ◽  
pp. 822-830 ◽  
Author(s):  
Frances Chung ◽  
Balaji Yegneswaran ◽  
Pu Liao ◽  
Sharon A. Chung ◽  
Santhira Vairavanathan ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
High Risk ◽  
Screening Tools ◽  
Surgical Patients ◽  
Apnea Hypopnea Index ◽  
Berlin Questionnaire ◽  
Obstructive Sleep ◽  
American Society ◽  
American Society Of Anesthesiologists ◽  
Stop Questionnaire

Background Because of the high prevalence of obstructive sleep apnea (OSA) and its adverse impact on perioperative outcome, a practical screening tool for surgical patients is required. This study was conducted to validate the Berlin questionnaire and the American Society of Anesthesiologists (ASA) checklist in surgical patients and to compare them with the STOP questionnaire. Methods After hospital ethics approval, preoperative patients aged 18 yr or older and without previously diagnosed OSA were recruited. The scores from the Berlin questionnaire, ASA checklist, and STOP questionnaire were evaluated versus the apnea-hypopnea index from in-laboratory polysomnography. The perioperative data were collected through chart review. Results Of 2,467 screened patients, 33, 27, and 28% were respectively classified as being at high risk of OSA by the Berlin questionnaire, ASA checklist, and STOP questionnaire. The performance of the screening tools was evaluated in 177 patients who underwent polysomnography. The sensitivities of the Berlin questionnaire, ASA checklist, and STOP questionnaire were 68.9-87.2, 72.1-87.2, and 65.6-79.5% at different apnea-hypopnea index cutoffs. There was no significant difference between the three screening tools in the predictive parameters. The patients with an apnea-hypopnea index greater than 5 and the patients identified as being at high risk of OSA by the STOP questionnaire or ASA checklist had a significantly increased incidence of postoperative complications. Conclusions Similar to the STOP questionnaire, the Berlin questionnaire and ASA checklist demonstrated a moderately high level of sensitivity for OSA screening. The STOP questionnaire and the ASA checklist were able to identify the patients who were likely to develop postoperative complications.

419 STOP-Bang Score and History of Radiation Predicts Risk of Obstructive Sleep Apnea in Cancer Patients: A Machine Learning Study

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A166-A166
Author(s):  
Ankita Paul ◽  
Karen Wong ◽  
Anup Das ◽  
Diane Lim ◽  
Miranda Tan
Keyword(s):  
Machine Learning ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Cancer Patients ◽  
Prediction Accuracy ◽  
Screening Tools ◽  
Cancer Type ◽  
Sleep Study ◽  
Obstructive Sleep ◽  
History Of

Abstract Introduction Cancer patients are at an increased risk of moderate-to-severe obstructive sleep apnea (OSA). The STOP-Bang score is a commonly used screening questionnaire to assess risk of OSA in the general population. We hypothesize that cancer-relevant features, like radiation therapy (RT), may be used to determine the risk of OSA in cancer patients. Machine learning (ML) with non-parametric regression is applied to increase the prediction accuracy of OSA risk. Methods Ten features namely STOP-Bang score, history of RT to the head/neck/thorax, cancer type, cancer stage, metastasis, hypertension, diabetes, asthma, COPD, and chronic kidney disease were extracted from a database of cancer patients with a sleep study. The ML technique, K-Nearest-Neighbor (KNN), with a range of k values (5 to 20), was chosen because, unlike Logistic Regression (LR), KNN is not presumptive of data distribution and mapping function, and supports non-linear relationships among features. A correlation heatmap was computed to identify features having high correlation with OSA. Principal Component Analysis (PCA) was performed on the correlated features and then KNN was applied on the components to predict the risk of OSA. Receiver Operating Characteristic (ROC) - Area Under Curve (AUC) and Precision-Recall curves were computed to compare and validate performance for different test sets and majority class scenarios. Results In our cohort of 174 cancer patients, the accuracy in determining OSA among cancer patients using STOP-Bang score was 82.3% (LR) and 90.69% (KNN) but reduced to 89.9% in KNN using all 10 features mentioned above. PCA + KNN application using STOP-Bang score and RT as features, increased prediction accuracy to 94.1%. We validated our ML approach using a separate cohort of 20 cancer patients; the accuracies in OSA prediction were 85.57% (LR), 91.1% (KNN), and 92.8% (PCA + KNN). Conclusion STOP-Bang score and history of RT can be useful to predict risk of OSA in cancer patients with the PCA + KNN approach. This ML technique can refine screening tools to improve prediction accuracy of OSA in cancer patients. Larger studies investigating additional features using ML may improve OSA screening accuracy in various populations Support (if any):

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