SAS score: Targeting high-specificity for efficient population-wide monitoring of obstructive sleep apnea

Topîrceanu, Alexandru; Udrescu, Mihai; Udrescu, Lucreţia; Ardelean, Carmen; Dan, Rodica; Reisz, Daniela; Mihăicuţă, Ştefan

doi:10.1371/journal.pone.0202042

Cited by 12 publications

(11 citation statements)

References 40 publications

(46 reference statements)

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“…Somnolence evaluated with the Epworth scale has a better prediction value when it is included in a validated prediction score (9). In comparison with the existing algorithm, SAS score is a more appropriate screening tool for monitoring large populations, due to its improved specificity, but probably because of a small number of patients, it fails to show a significant difference between the two groups of our population (10). Obesity is an important comorbidity associated with SAS and HF, but in our cohort, both groups show a similar level 2 BMI of obesity (11).…”

Section: Discussionmentioning

confidence: 95%

Risk for stroke and chronic kidney disease in patients with sleep apnea syndrome and heart failure with different ejection fractions

Ardelean

Lighezan

Morar³

et al. 2019

Pneumologia

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Background Patients with sleep apnea syndrome (SAS) and heart failure (HF) have concomitant different comorbidities and increased risk of morbidity. Aim The aim of this study was to analyze differences between patients with SAS and heart failure with preserved ejection fraction (HFpEF; ejection fraction [EF]≥50%) – group 1 and those with SAS and heart failure with reduced ejection fraction (HFrEF; EF<50%) – group 2. Methods We evaluated 51 patients with SAS and HF in the sleep laboratory of Timisoara Victor Babes Hospital. We collected general data, sleep questionnaires, anthropometric measurements (neck circumference [NC], abdominal circumference [AC]), somnography for apnea–hypopnea index (AHI), oxygen desaturation index (ODI), echocardiographic data, comorbidities, and laboratory test. Results The study included 51 patients who were divided into two groups depending on EF, with the following characteristics: Group 1 (HFpEF): 26 patients, 19 males, seven females, age 61.54±9.1 years, body mass index (BMI) 37±6.4 kg/m2, NC 45.4±3.6 cm, AC 126.6±12.9 cm, AHI 48.3±22.6 events/hour, central apnea 5.6±11.4 events/hour, obstructive apnea 25.7±18.7 events/hour, ODI 41.2±21.2/hour and lowest SpO2 –72.1±14%. Group 2 (HFrEF): 25 patients, 18 males, seven females, age 63.6±8.8 years, BMI 37.9±7.5 kg/m2, NC 46±4.4 cm, AC 127.2±13.9 cm, AHI 46.4±21.7 events/hour, central apnea 4.6±8.3 events/hour, obstructive apnea 25.9±18.5 events/hour, ODI 44.8±27.1/hour and lowest SpO2 –70.6±12.1%. Differences between groups regarding anthropometric and somnographic measurements and lipidic profile were not statistically significant. Significant differences were observed regarding stroke (23% vs. 4%, p=0.04) in the group with HFpEF and regarding creatinine measurements (1.1±0.2 vs. 1.4±0.7, p=0.049), aortic insufficiency (11.5% vs. 36%, p=0.04) and tricuspid insufficiency (6.1% vs. 80%, p=0.01) in the group with HFrEF. Conclusions Patients with SAS and HFpEF have a higher risk of stroke. Patients with SAS and HFrEF have a significantly increased risk of developing a life-long chronic kidney disease and aortic and tricuspid insufficiency. These results may suggest pathogenic links between SAS and the mentioned comorbidities, and this may explain the higher mortality when this association is present.

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Section: Discussionmentioning

confidence: 95%

Risk for stroke and chronic kidney disease in patients with sleep apnea syndrome and heart failure with different ejection fractions

Ardelean

Lighezan

Morar³

et al. 2019

Pneumologia

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“…In our study, the optimal cutoff point is 41 cm with a sensitivity of 0.8099 and specificity of 0.5185, which indicates that patients with an NC

cm are less likely to be diagnosed with OSA using polysomnography. Our result suggests that it is not necessary to have a very thick neck in order to develop OSA, even for male subjects [ 22 , 46 ].…”

Section: Discussionmentioning

confidence: 96%

“…Our research group reports previous studies using network science to identify subgroups (phenotypes) of patients with OSA [ 21 , 22 , 29 ]. However, in this retrospective study, we focus on using network analysis explicitly to analyze patients’ response to CPAP treatment.…”

Section: Discussionmentioning

confidence: 99%

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Analyzing Neck Circumference as an Indicator of CPAP Treatment Response in Obstructive Sleep Apnea with Network Medicine

Mihăicuţă

Udrescu

et al. 2021

Diagnostics

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We explored the relationship between obstructive sleep apnea (OSA) patients’ anthropometric measures and the CPAP treatment response. To that end, we processed three non-overlapping cohorts (D1, D2, D3) with 1046 patients from four sleep laboratories in Western Romania, including 145 subjects (D1) with one-night CPAP therapy. Using D1 data, we created a CPAP-response network of patients, and found neck circumference (NC) as the most significant qualitative indicator for apnea–hypopnea index (AHI) improvement. We also investigated a quantitative NC cutoff value for OSA screening on cohorts D2 (OSA-diagnosed) and D3 (control), using the area under the curve. As such, we confirmed the correlation between NC and AHI (ρ=0.35, p<0.001) and showed that 71% of diagnosed male subjects had bigger NC values than subjects with no OSA (area under the curve is 0.71, with 95% CI 0.63–0.79, p<0.001); the optimal NC cutoff is 41 cm, with a sensitivity of 0.8099, a specificity of 0.5185, positive predicted value (PPV) = 0.9588, negative predicted value (NPV) = 0.1647, and positive likelihood ratio (LR+) = 1.68. Our NC =41 cm threshold classified the D1 patients’ CPAP responses—measured as the difference in AHI prior to and after the one-night use of CPAP—with a sensitivity of 0.913 and a specificity of 0.859.

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“…In our group, all the patients have severe OSAS, regardless of EF. Patients with severe, untreated OSAS have a higher risk of fatal cardiovascular events, some studies show [33].…”

Section: Discussionmentioning

confidence: 99%

Particularities of Older Patients with Obstructive Sleep Apnea and Heart Failure with Mid-Range Ejection Fraction

Ardelean

Pescariu

et al. 2019

Medicina

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Background and objectives: Obstructive sleep apnea syndrome (OSAS) and heart failure (HF) are increasing in prevalence with a greater impact on the health system. The aim of this study was to assess the particularities of patients with OSAS and HF, focusing on the new class of HF with mid-range ejection fraction (HFmrEF, EF = 40%–49%), and comparing it with reduced EF (HFrEF, EF < 40%) and preserved EF (HFpEF, EF ≥ 50%). Materials and Methods: A total of 143 patients with OSAS and HF were evaluated in three sleep labs of “Victor Babes” Hospital and Cardiovascular Institute, Timisoara, Western Romania. We collected socio-demographic data, anthropometric sleep-related measurements, symptoms through sleep questionnaires and comorbidity-related data. We performed blood tests, cardio-respiratory polygraphy and echocardiographic measurements. Patients were divided into three groups depending on ejection fraction. Results: Patients with HFmrEF were older (p = 0.0358), with higher values of the highest systolic blood pressure (mmHg) (p = 0.0016), higher serum creatinine (p = 0.0013), a lower glomerular filtration rate (p = 0.0003), higher glycemic levels (p = 0.008) and a larger left atrial diameter (p = 0.0002). Regarding comorbidities, data were presented as percentage, HFrEF vs. HFmrEF vs. HFpEF. Higher prevalence of diabetes mellitus (52.9 vs. 72.7 vs. 40.2, p = 0.006), chronic kidney disease (17.6 vs. 57.6 vs. 21.5, p < 0.001), tricuspid insufficiency (76.5 vs. 84.8 vs.59.1, p = 0.018) and aortic insufficiency (35.3 vs.42.4 vs. 20.4, p = 0.038) were observed in patients with HFmrEF, whereas chronic obstructive pulmonary disease(COPD) (52.9 vs. 24.2 vs.18.3, p = 0.009), coronary artery disease(CAD) (82.4 vs. 6.7 vs. 49.5, p = 0.026), myocardial infarction (35.3 vs. 24.2 vs. 5.4, p < 0.001) and impaired parietal heart kinetics (70.6 vs. 68.8 vs. 15.2, p < 0.001) were more prevalent in patients with HFrEF. Conclusions: Patients with OSAS and HF with mid-range EF may represent a new group with increased risk of developing life-long chronic kidney disease, diabetes mellitus, tricuspid and aortic insufficiency. COPD, myocardial infarction, impaired parietal kinetics and CAD are most prevalent comorbidities in HFrEF patients but they are closer in prevalence to HFmrEF than HFpEF.

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SAS score: Targeting high-specificity for efficient population-wide monitoring of obstructive sleep apnea

Cited by 12 publications

References 40 publications

Risk for stroke and chronic kidney disease in patients with sleep apnea syndrome and heart failure with different ejection fractions

Risk for stroke and chronic kidney disease in patients with sleep apnea syndrome and heart failure with different ejection fractions

Analyzing Neck Circumference as an Indicator of CPAP Treatment Response in Obstructive Sleep Apnea with Network Medicine

Particularities of Older Patients with Obstructive Sleep Apnea and Heart Failure with Mid-Range Ejection Fraction

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