Difference between apnea-hypopnea index (AHI) and oxygen desaturation index (ODI): proportional increase associated with degree of obesity

Ernst, Glenda; Bosio, Martín; Salvado, Alejandro; Dibur, Eduardo; Nigro, Carlos; Borsini, Eduardo

doi:10.1007/s11325-016-1330-3

Cited by 43 publications

(37 citation statements)

References 24 publications

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“…Although participants with high NH-BDI were more likely to be older and male (regardless of H-BDI), it was those individuals with high H-BDI (vs low H-BDI) that had slightly higher BMIs, concordant with the findings that increased weight is associated with a desaturating sleep-disordered breathing. 8,43 This relationship was also supported by our longitudinal model (Table 5), as increases in desaturations after 4-year follow-up (ΔH-BDI) were not only associated with baseline H-BDI, age, and BMI, but also by baseline frequency of nondesaturating events (NH-BDI) and changes in BMI that have occurred over 4 years (ΔBMI). The fact that participants with higher H-BDI are generally more obese and have greater neck girth 8,43 is also in agreement with our observation that increased body weight contributes to the emergence of desaturating breathing disturbances.…”

Section: Discussionsupporting

confidence: 70%

“…8,43 This relationship was also supported by our longitudinal model (Table 5), as increases in desaturations after 4-year follow-up (ΔH-BDI) were not only associated with baseline H-BDI, age, and BMI, but also by baseline frequency of nondesaturating events (NH-BDI) and changes in BMI that have occurred over 4 years (ΔBMI). The fact that participants with higher H-BDI are generally more obese and have greater neck girth 8,43 is also in agreement with our observation that increased body weight contributes to the emergence of desaturating breathing disturbances. Breathing disturbances associated with oxygen drops (H-BDI) were also significantly longer in duration (Figure 1) suggesting that with time and increased BMI, participants may be less arousable, leading to longer, more severe pauses that have time to produce significant desaturations.…”

Section: Discussionsupporting

confidence: 70%

“…In order to determine whether NH-BDI represented a less severe form of sleep-disordered breathing, a general linear model was used to assess the associated change in H-BDI over a 4-year time interval (ΔH-BDI) in the 654 individuals with follow-up sleep studies. The model incorporated commonly associated clinical variables, including baseline BMI, age, sex, alcohol consumption (number of drinks), smoking status (current, never, previous), neck girth, log 2 -transformed NH-BDI, log 2 -transformed H-BDI baseline, and the change in BMI over the same time period (added in order to account for the known effect of BMI on desaturating event rate 8,43 ). Age, alcohol consumption, and NH-BDI were the only significant baseline factors, with NH-BDI β-coefficient = 1.96, indicating an estimated, co-variate adjusted 4-year increase in the H-BDI of nearly two events per hour for every doubling of baseline NH-BDI, p = .0002.…”

Section: Resultsmentioning

confidence: 99%

“…6 The Medicare and AASM 2007 standard criteria for scoring OSA events result in substantially different prevalence rates at equivalent frequency cutoffs. 7,8 Even individuals with the same AHI have vast differences in SDB characteristics. 9,10 Recent studies have highlighted that the oxygen-desaturation index (ODI) 11 or event duration 9,12 may be more predictive of cardiovascular outcomes.…”

Section: Introductionmentioning

confidence: 99%

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Breathing Disturbances Without Hypoxia Are Associated With Objective Sleepiness in Sleep Apnea

Koch

Schneider

Finn

et al. 2017

Sleep

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Study Objectives: To determine whether defining two subtypes of sleep-disordered breathing (SDB) events-with or without hypoxia-results in measures that are more strongly associated with hypertension and sleepiness. Methods: A total of 1 022 participants with 2 112 nocturnal polysomnograms from the Wisconsin Sleep Cohort were analyzed with our automated algorithm, developed to detect breathing disturbances and desaturations. Breathing events were time-locked to desaturations, resulting in two indices-desaturating (hypoxia-breathing disturbance index [H-BDI]) and nondesaturating (nonhypoxia-breathing disturbance index [NH-BDI]) events-regardless of arousals. Measures of subjective (Epworth Sleepiness Scale) and objective (2 981 multiple sleep latency tests from a subset of 865 participants) sleepiness were analyzed, in addition to clinically relevant clinicodemographic variables. Hypertension was defined as BP ≥ 140/90 or antihypertensive use. Results: H-BDI, but not NH-BDI, correlated strongly with SDB severity indices that included hypoxia (r ≥ 0.89, p ≤ .001 with 3% oxygen-desaturation index [ODI] and apnea hypopnea index with 4% desaturations). A doubling of desaturation-associated events was associated with hypertension prevalence, which was significant for ODI but not H-BDI (3% ODI OR = 1.06, 95% CI = 1.00-1.12, p < .05; H-BDI OR 1.04, 95% CI = 0.98-1.10) and daytime sleepiness (β = 0.20 Epworth Sleepiness Scale [ESS] score, p < .0001; β = −0.20 minutes in MSL on multiple sleep latency test [MSLT], p < .01). Independently, nondesaturating event doubling was associated with more objective sleepiness (β = −0.52 minutes in MSL on MSLT, p < .001), but had less association with subjective sleepiness (β = 0.12 ESS score, p = .10). In longitudinal analyses, baseline nondesaturating events were associated with worsening of H-BDI over a 4-year follow-up, suggesting evolution in severity. Conclusions: In SDB, nondesaturating events are independently associated with objective daytime sleepiness, beyond the effect of desaturating events.

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Section: Discussionsupporting

confidence: 70%

Section: Discussionsupporting

confidence: 70%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Breathing Disturbances Without Hypoxia Are Associated With Objective Sleepiness in Sleep Apnea

Koch

Schneider

Finn

et al. 2017

Sleep

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“…In patients with this condition, there is a greater prevalence of obesity than in the general population, according to available studies, in 40-70% of patients with OSAS (ref. 5,6 ), and thus considered to be one of the respiratory complications of obesity. This fact is serious because of its increasing incidence 7 with 10-25% of the European and American population having a BMI more than 30 (ref.…”

Section: Introductionmentioning

confidence: 99%

Risk factors for failure of continuous positive airway pressure treatment in patients with ostructive sleep apnoea

Slouka¹,

Honnerova²,

Hošek³

et al. 2018

Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub

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Background and Aims. Obstructive sleep apnoea is a potentially serious sleep disorder associated with the risk of cardiovascular disease. It is treated with continuous airway pressure (CPAP) but this is not always successful. Unsuccessful cases should be treated by bilevel positive airway pressure (BiPAP). The aim of this study was to determine whether common respiratory parameters and/or body mass index (BMI) can be used to predict the probability CPAP failure and hence start such patients on BiPAP from the outset. Methods. A sample of patients treated by CPAP for OSAS was evaluated a retrospective cohort study. The data measured in sleep monitoring of the successfully treated group and of the group where CPAP had failed were compared. Subsequently, the predictive abilities of BMI, Apnoea Index (AI), Apnoea-Hypopnea Index (AHI), percentage of sleep time in less than 90% oxygen saturation (T90), average oxygen saturation over the duration of sleep (SaO2) and average desaturation per hour of sleep (ODI) were assessed with respect to CPAP failure, both individually and in combination. Results. A sample of 479 patients was included in the study. All of the recorded variables except AI were significantly associated with failure of CPAP and their ability to predict the failure ranged from poor to moderate. Since there was significant correlation among all the variables measured a two-variable prediction model combining T90 and BMI produced no significant improvement in the quality of CPAP failure prediction. Conclusions. BMI was a significant predictor of CPAP failure although it was slightly less predictive than T90. The set of monitored variables included in our study does not allow for CPAP failure to be predicted with clinically relevant reliability.

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Prediction of Oxygen Desaturation by Using Sound Data From a Noncontact Device: A Proof‐of‐Concept Study

et al. 2021

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Objectives/Hypothesis: Prediction of the apnea-hypopnea index (AHI) from breathing sounds during sleep could be used to prescreen for obstructive sleep apnea (OSA). In addition, the oxygen desaturation index (ODI) is a known risk factor for developing cardiovascular disease in OSA patients. This study focused on estimation of ODI from a noncontact manner from sleep breathing sounds.Study Design: Retrospective study. Methods: Patients who visited the sleep center due to snoring or sleep apnea underwent polysomnography in lab overnight. Sound recordings were made during polysomnography using a microphone. After noise reduction, the sound data were segmented into 5 seconds windows and features were extracted. Binary classification and regression analyses were performed to estimate the ODI during sleep (model 1). This was re-tested after inclusion of body mass index (BMI) and age as additional features (model 2: BMI only, model 3: BMI and age).Results: We included 116 patients. The mean age and AHI of all patients were 50.4 AE 16.7 years and 23.0 AE 24.0 events/hr. In binary classification, for ODI cutoff values of 5, 15, and 30 events/hr, the areas under the curve were 0.88, 0.93, 0.91, respectively, and accuracies were 85.34, 86.21, and 87.07, respectively. In regression analysis, the correlation coefficient and mean absolute error were 0.80 and 9.60 events/hr, respectively. In models 2 and 3, the correlation coefficient and mean absolute error were 0.82, 9.44 events/hr and 0.81, 9.6 events/hr, respectively.Conclusion: Prediction of ODI from sleep sound seems to be feasible. Additional clinical feature such as BMI may increase overall predictability.

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Difference between apnea-hypopnea index (AHI) and oxygen desaturation index (ODI): proportional increase associated with degree of obesity

Cited by 43 publications

References 24 publications

Breathing Disturbances Without Hypoxia Are Associated With Objective Sleepiness in Sleep Apnea

Breathing Disturbances Without Hypoxia Are Associated With Objective Sleepiness in Sleep Apnea

Risk factors for failure of continuous positive airway pressure treatment in patients with ostructive sleep apnoea

Prediction of Oxygen Desaturation by Using Sound Data From a Noncontact Device: A Proof‐of‐Concept Study

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