Symptomless Multi-Variable Apnea Prediction Index Assesses Obstructive Sleep Apnea Risk and Adverse Outcomes in Elective Surgery

Lyons, M. Melanie; Keenan, Brendan T.; Li, Junxin; Khan, Tanya; Elkassabany, Nabil; Walsh, Colleen M.; Williams, Noel N.; Pack, Allan I.; Gurubhagavatula, Indira

doi:10.1093/sleep/zsw081

Cited by 14 publications

(10 citation statements)

References 35 publications

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“…Although the above indicators are also risk factors for OSAHS, it is relatively one-sided to use one or two alone to evaluate the risk of OSAHS. The sMVAP index proves to be a practical OSAHS screening tool [ 3 ], including parameters such as age, gender, and BMI that only need to be extracted from the patient's electronic medical record. In this current study, the increased D-dimer and history of coronary heart disease were associated with poor prognosis, reflecting the direct effect of patients' coagulation function and cardiac dysfunction on mortality, consistent with previous reports [ 19 , 20 ].…”

Section: Discussionmentioning

confidence: 99%

“…The sMVAP index is calculated as: sMVAP = e X /(1 + e X ), where “e” is natural constant (Its value is about 2.718281828459) and X = −10.784 + 0.203 × (BMI) + 0.043 × (Age) + 1.004 × (Gender: 0 = female, 1 = male) [ 3 ]. The sMVAP ranges from 0 to 1, with higher values indicating higher OSAHS risk.…”

Section: Methodsmentioning

confidence: 99%

“…At the same time, due to the lack of sufficient attention to OSAHS, many patients were not collected for OSAHS-related clinical manifestations such as neck circumference, snoring, and daytime sleepiness, Therefore, it is difficult to use the STOP-Bang questionnaire [ 1 ] and NoSAS questionnaire [ 2 ] to perform OSAHS screening for COVID-19 patients. The sMVAP index has proved to be an effective tool for screening OSAHS [ 3 ], including only parameters such as gender, age and body mass index (BMI). This study explored the relationship between sMVAP index and adverse outcomes of patients with COVID-19, trying to reveal the effect of OSAHS on COVID-19.…”

Section: Introductionmentioning

confidence: 99%

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Symptomless multi-variable apnea prediction index assesses adverse outcomes in patients with Corona Virus Disease 2019

Zhang

et al. 2020

Sleep Medicine

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Purpose To explore the relationship between symptomless multi-Variable apnea prediction (sMVAP) index and adverse outcomes of patients with Corona Virus Disease 2019 (COVID-19). Methods According to the sMVAP quartiles, we divided all patients into four groups. The clinical electronic medical records, nursing records, laboratory findings, and radiological examinations for all patients with laboratory confirmed Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection were reviewed. Cox proportional hazard ratio (HR) models were used to determine the risk factors associated with in hospital death. Results A total of 97 patients were included in this study. The “Quartile 4” group 's ICU transfer rate was significantly higher than the “Quartile 1” group. Coronary heart disease, high d-dimer and sMVAP at admission were associated with increased odds of death. Conclusions Using the sMVAP index for obstructive sleep apnea hypopnea syndrome (OSAHS) risk assessment, and then predicting the adverse outcomes of COVID-19 patients, is an effective method. Therefore, the use of sMVAP index for OSAHS screening for inpatients with COVID-19 should be vigorously promoted, and high-risk patients should be effectively managed.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Symptomless multi-variable apnea prediction index assesses adverse outcomes in patients with Corona Virus Disease 2019

Zhang

et al. 2020

Sleep Medicine

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“…No observational evidence directly addressing the question was found. Meta-analysis of observational studies suggested that patients with obstructive sleep apnea or related disorders were more likely to sustain atrial fibrillation (OR 1.51, 95% CI 1.36 to 1.69) or hypoxemia (WMD − 3.8%, 95% CI − 5.4% to − 2.2%) [45][46][47][48][49][50][51][52][53][54][55][56][57][58][59]. The latter outcome might not be clinically important, whereas the summary certainty in the evidence was very low due to risk of bias (non-controlled confounders in cohort studies), imprecision, statistical and conceptual heterogeneity (differences in definition of sleep apnea and method of diagnosis) (Supplementary Table 6).…”

Section: Justificationmentioning

confidence: 99%

Clinical practice guidelines of the European Association for Endoscopic Surgery (EAES) on bariatric surgery: update 2020 endorsed by IFSO-EC, EASO and ESPCOP

et al. 2020

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Background Surgery for obesity and metabolic diseases has been evolved in the light of new scientific evidence, long-term outcomes and accumulated experience. EAES has sponsored an update of previous guidelines on bariatric surgery. Methods A multidisciplinary group of bariatric surgeons, obesity physicians, nutritional experts, psychologists, anesthetists and a patient representative comprised the guideline development panel. Development and reporting conformed to GRADE guidelines and AGREE II standards. Results Systematic review of databases, record selection, data extraction and synthesis, evidence appraisal and evidence-todecision frameworks were developed for 42 key questions in the domains Indication; Preoperative work-up; Perioperative management; Non-bypass, bypass and one-anastomosis procedures; Revisional surgery; Postoperative care; and Investigational procedures. A total of 36 recommendations and position statements were formed through a modified Delphi procedure. and Other Interventional Techniques Disclaimer This clinical practice guideline has been developed under the auspice of the European Association for Endoscopic Surgery (EAES). It is intended to be used primarily by health professionals (e.g. surgeons, anesthetists, physicians) and to assist in making informed clinical decisions on diagnostic measures and therapeutic management. It is also intended to inform individual practice of allied health professionals (e.g. surgical nurses, dietitians, physical rehabilitation therapists, psychologists); to inform strategic planning and resource management by healthcare authorities (e.g. regional and national authorities, healthcare institutions, hospital administration authorities); and to inform patients wishing to obtain an overview of the condition of interest and its management. The use of recommendations contained herein must be informed by supporting evidence accompanying each recommendation and by research evidence that might not have been published by the time of writing the present document. Users must thus base their actions informed by newly published evidence at any given point Electronic supplementary material The online version of this article (

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“…While prior studies among individuals referred for sleep studies suggest that a high percentage may have undiagnosed OSA 88–91 , these studies are typically biased given the increased risk among those already referred for diagnostic testing. In our previous validation study 55 , when calculating the likelihood of OSA based on the symptomless multi-variable prediction score 92 , almost 70% of non-cases had a predicted OSA probability <0.2, while fewer than 3% had a probability of 0.7 or above. Thus, there is strong evidence that a majority of individuals defined in our study as non-cases are true controls.…”

Section: Discussionmentioning

confidence: 97%

Characterization of Genetic and Phenotypic Heterogeneity of Obstructive Sleep Apnea Using Electronic Health Records

Veatch

Bauer

Josyula

et al. 2019

Preprint

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38Obstructive sleep apnea (OSA) is defined by frequent episodes of reduced or complete 39 cessation of airflow during sleep and is linked to negative health outcomes. Understanding the 40 genetic factors influencing expression of OSA may lead to new treatment strategies. Electronic 41 health records can be leveraged to both validate previously reported OSA-associated genomic 42 variation and detect novel relationships between these variants and comorbidities. We identified 43 candidate single nucleotide polymorphisms (SNPs) via systematic literature review of existing 44 research. Using datasets available at Geisinger (n=39,407) and Vanderbilt University Medical 45Center (n=24,084), we evaluated associations between 48 SNPs and OSA diagnosis, defined 46 using clinical codes. We also evaluated associations between these SNPs and OSA severity 47 measures obtained from sleep reports at Geisinger (n=6,571). Finally, we used a phenome-wide 48 approach to perform discovery and replication analyses testing associations between OSA 49 candidate SNPs and other clinical codes and laboratory values. Ten SNPs were associated with 50 OSA diagnosis in at least one dataset, and one additional SNP was associated following meta-51 analysis across all datasets. Three other SNPs were solely associated in subgroups defined by 52 established risk factors (i.e., age, sex, and BMI). Five OSA diagnosis-associated SNPs, and 16 53 additional SNPs, were associated with OSA severity measures. SNPs associated with OSA 54 diagnosis were also associated with codes reflecting cardiovascular disease, diabetes, celiac 55 disease, peripheral nerve disorders and genitourinary symptoms. Results highlight robust OSA-56 associated SNPs, and provide evidence of convergent mechanisms influencing risk for co-57 occurring conditions. This knowledge can lead to more personalized treatments for OSA and 58 related comorbidities. 59 60In the United States (US), 50-70 million individuals suffer from a disorder of sleep and 62 wakefulness 1 . Among the most common sleep disorders is obstructive sleep apnea (OSA). OSA 63 is defined by frequent episodes of reduced (hypopnea) or complete cessation (apnea) of airflow 64 that occur as a consequence of upper airway obstruction during sleep. Approximately 34% of 65 men and 17% of women aged 30-70 exhibit mild OSA, and 13% and 6%, respectively, suffer 66 from moderate to severe OSA 2 . Notably, prevalence rates substantially increase by the age of 67 50 years old 2 . When left untreated, OSA represents a significant public health burden carrying a 68 higher risk of serious comorbidities such as cardiovascular disease 3-11 , cancer incidence 12 and 69 mortality, all causes 13; 14 , cognitive impairment 15 , and rate of progression of 70 neurodegeneration 16 . As such, identifying more effective diagnosis and management of OSA 71 are important areas of research. 72OSA is a complex, phenotypically heterogeneous disorder driven by both obesity-related 73 factors and other mechanisms [17][18][19] . A number of studies have ...

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Symptomless Multi-Variable Apnea Prediction Index Assesses Obstructive Sleep Apnea Risk and Adverse Outcomes in Elective Surgery

Cited by 14 publications

References 35 publications

Symptomless multi-variable apnea prediction index assesses adverse outcomes in patients with Corona Virus Disease 2019

Symptomless multi-variable apnea prediction index assesses adverse outcomes in patients with Corona Virus Disease 2019

Clinical practice guidelines of the European Association for Endoscopic Surgery (EAES) on bariatric surgery: update 2020 endorsed by IFSO-EC, EASO and ESPCOP

Characterization of Genetic and Phenotypic Heterogeneity of Obstructive Sleep Apnea Using Electronic Health Records

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