Can Sleep Apnea Cause Low Oxygen Levels During the Day
Sleep. 2008 Feb i; 31(two): 249–255.
The Human relationship of Daytime Hypoxemia and Nocturnal Hypoxia in Obstructive Sleep Apnea Syndrome
Francesco Fanfulla
anePulmonary Sectionalisation, Istituto Scientifico di Pavia and
Mario Grassi
2Montescano, Fondazione S. Maugeri, IRCCS, Pavia, Italy
Anna Eugenia Taurino
3Department of Wellness Sciences, Section of Medical Statistics and Epidemiology, Academy of Pavia, Italia
Nadia D'Artavilla Lupo
3Department of Health Sciences, Section of Medical Statistics and Epidemiology, University of Pavia, Italy
Rossella Trentin
3Department of Health Sciences, Section of Medical Statistics and Epidemiology, Academy of Pavia, Italy
Abstruse
Question of the study:
Prevalence and determinants of daytime hypoxemia in patients with obstructive sleep apnea (OSA) syndrome are non well established. The aims of this written report, conducted in a large series of OSA patients, were to judge the prevalence of daytime hypoxemia, to assess the reciprocal effects betwixt daytime PaOii and nocturnal SpO2, and to investigate the directly and indirect role of slumber apnea severity in determining feedback gas exchange abnormalities.
Materials and methods:
In 456 patients a daytime hypoxemia-nocturnal hypoxia feedback structural equations model was designed. PaOii adjusted for age (% of predicted), percentage sleep time spent with SpOii <xc% (TST90), oxygen desaturation index and the apnea-hypopnea index, were adamant as the measures of daytime hypoxemia, nocturnal hypoxia, and sleep apnea severity, respectively, after adjusting for the severity of obesity and lung volumes.
Results:
The TST90-PaO2 feed-back structural equations modeling showed that daytime PaO2 was inversely related (P<0.001) to nocturnal hypoxia (−4.0% of PaOtwo per i SD of TSTxc). The severity of OSA (−1.0%) was an indirect determinant of daytime PaO2 via the TST90 pathway. In contrast, daytime PaOtwo did non influence (P>0.05) the extent of nocturnal hypoxia.
Conclusions:
In OSA patients, the extent of nocturnal hypoxia seems to be both a direct determinant and a mediator of the indirect effect of sleep apnea on the development of daytime hypoxemia.
Commendation:
Fanfulla F; Grassi M; Taurino AE; Lupo ND; Trentin R. The relationship of daytime hypoxemia and nocturnal hypoxia in obstructive slumber apnea syndrome. SLEEP 2008;31(2):249–255.
Keywords: Sleep apnea, hypoxemia, structural equation model, respiratory part, polysomnography
SLEEP APNEA IS A CHRONIC CONDITION CHARACTERIZED By UPPER AIRWAY Plummet DURING Sleep. THE RESULTING Subtract OR Cessation OF airflow is generally associated with recurrent drops in oxyhemoglobin saturation. Gas exchange during sleep may be severely affected in certain patients, especially in those who are grossly obese or have chronic respiratory disorders, such as chronic obstructive pulmonary affliction (COPD).1–2 Daytime hypoxemia has been reported to develop in patients with obstructive slumber apnea (OSA).iii–8 In the past, looking for the physiological determinants of nocturnal arterial oxygenation in OSA patients, it was constitute that derangements of pulmonary mechanics and awake PaO2 were of major importance in establishing the severity of nocturnal hypoxemia.ix Other studies showed that the main determinant of daytime hypoxemia is not the OSA per se but rather concomitant comorbidity such as COPD.7–8,10 Notwithstanding, all these studies were performed on heterogeneous populations with a very high prevalence of COPD patients, so that airway obstruction and lung hyperinflation had major roles in determining the lower values of PaO2. Moreover, the PaO2 level at balance is highly dependent on historic period, and none of the studies previously cited corrected the level of PaO2 for age, thus invalidating any comparisons of the level of oxygenation in patients with widely unlike ages.
The aims of the current study were: (i) to estimate the prevalence of alterations in daytime oxygenation in a very large grouping of OSA patients with a very broad spectrum of affliction severity and obesity; (ii) to appraise the reciprocal (feedback) effects between daytime PaO2 and nocturnal SaO2, adjusted for comorbidities such as obesity and lung volumes; and (iii) to investigate the direct and indirect role of slumber apnea severity in determining feedback gas exchange abnormalities. Some of the results of this study have been previously reported in the course of an abstruse.eleven
METHODS
Patients and Written report Design
We studied 456 consecutive patients (49.4 ± 10.7 years, 160 females) who complained of snoring and excessive daytime sleepiness and had been consecutively referred to our laboratory for investigations of possible OSA. These investigations consisted of standard polysomnography and, the day subsequently, conclusion of static and dynamic lung volumes and blood gas measurements. Patients with previously diagnosed or radiologically evident respiratory diseases, radiologically axiomatic lung lesions (e.grand., previous tuberculosis treated physically, pulmonary abscesses, pneumothorax), neuromuscular disorders (e.thou., mail-polio lesions), breast-wall defects, previous use of ambition suppressants or a clinical history of venous thromboembolic disease, a bronchopulmonary infection, or cardiac or respiratory failure in the preceding 6 months were excluded from the study, equally were patients with a previous diagnosis of pulmonary arterial hypertension.
The protocol was submitted to the Technical and Ethical Committees. The former approved the protocol and the latter stated that approval was waived since, on access to infirmary, patients are asked to sign whether they consent or non to the utilize of their medical records and "routine" examination results for enquiry purposes. Nosotros analyzed only records of patients who agreed to the use of their information.
Measurements
Sleep Written report
Full standard in-laboratory polysomnography (Embla, Medcare, Reykyiavik, Republic of iceland) was performed using current procedures and scored manually according to the criteria of Rechtschaffen and Kales.12 The polysomnography included: EEGs (Ciii-A2, C4-Aane), EOGdue south, submental EMG, inductive tibialis electromyograms, nasal cannula airflow signal using a nasal cannula/pressure transducer system, oral thermistor, ECG and body position. SpO2 was recorded by means of an in-built pulse oximeter (Nonin Medical Inc., Minneapolis, MN, Us) with an Oximax sensor (Nellcore, Pleasanton, CA, USA). The equipment provides both an averaged (four seconds) and a beat-to-beat SpOii value. Respiratory efforts were monitored by the plethysmographic method (10-trace, Medcare, Iceland), so that the sum of thoracic and abdominal activities was obtained.
Arousals were scored according to standard criteria.13 Apnea was divers as a abeyance of airflow for ≥10 seconds, while hypopnea as a clear amplitude reduction of a validated measure out of animate during sleep (but less than a fifty% reduction from baseline) associated with an oxygen desaturation of >three% or an arousal.fourteen
We determined the apnea-hypopnea alphabetize (AHI), and the oxygen desaturation index (ODI), and the percent sleep fourth dimension spent with SpO2 <xc% (TSTninety).
Evaluation of Daytime Respiratory Role and Claret Gas Assays
Pulmonary function tests (Masterlab, Jaeger, Hochberg, Germany) were performed every bit described in the European Respiratory Gild argument.xv Respiratory function data were compared with predicted normal values obtained using the European Community for Steel and Coal (ECSC) 1983 regression equations. Diffuse airway obstruction was divers equally a FEVane < lxx% of predicted and FEV1/VC <60%, according to a previous study.six
Arterial blood-gases were analyzed by an automatic, computerized gas analyzer (ABL 550, Radiometer, Copenhagen, Denmark). PaO2 was adapted for historic period and expressed as per centum of predicted according to a reference equation for the Italian population.sixteen All the measurements were performed between x:00 and 12:00 a.thousand. Daytime hypoxemia was defined every bit PaO2% <ninety%, while nocturnal hypoxia was divers as TST90 > 1%.
Statistical Analysis
Results are expressed as hateful ± SD, and t-tests because equal or unequal variances were used to compare data amidst the two groups of patients classified by the dichotomized definitions of TST90 and PaOii. Pearson'south r correlation coefficients and forwards stepwise regression analyses were performed to evaluate bivariate associations betwixt pairwise variables, and the predictors that explain the variance of continuous measurements of TST90 and PaOtwo, respectively.
The relationship between daytime hypoxemia and nocturnal hypoxia was investigated past structural equations modeling (SEM).17,xviii This is a statistical multivariate approach based on the use of a system of simultaneous equations to draw a priori relationships of observed (manifest) and unobserved (latent) variables of the physical process that generates the data.
A special type of structural equations modeling is the Path Analysis model in which but observed variables are considered in simultaneous equations. Path Assay distinguishes iii types of effects: direct, indirect, and full effects. The direct consequence of an explanatory variable on a response variable is the net issue of a predictor setting all the other predictors in the built-in equations existence equal. The indirect event of an explanatory variable is the effect mediated by the pathway relationships of the other variables built-in the equations. The total effect is the sum of both the directly and indirect effects: full issue = straight event + indirect effect. The decomposition of furnishings is e'er with respect to a specific model.
Based on a preliminary statistical analysis (a stepwise regression assay), and clinical prove, a Path Analysis of a TSTninety−PaO2% feedback model was designed (Figure 1) to appraise the reciprocal furnishings between TSTxc and PaO2%, and the direct and indirect effects of sleep apnea severity (expressed by AHI and ODI) in determining TSTninety−PaOtwo% feedback, adjusted for obesity (expressed past BMI), and lung volumes (expressed by VC%). A gender stratification assay was besides planned.
Path diagram of the dependencies of the TST90−PaOii feed back structural equations designed (*). The observed variables are enclosed in boxes, and the unobserved variables (error terms) are circled. An arrow from one variable to another indicates that the beginning variable has a direct influence on the second, 2 straight unmarried-headed arrows connecting 2 variables signal a reciprocal straight influence, and a curved two-headed arrow signifies a correlation betwixt two variables. The path coefficients displayed on the arrows are the regression coefficients for the observed variables, and the residue variances/covariances for the unobserved errors.
(*) VC%: vital capacity in % of predicted; BMI: body mass index (Kg/m2); TST90: percent sleep time spent with SaO2 <90%; PaOii%: partial oxygen arterial pressure in % of predicted; ODI: oxygen desaturation index; AHI: apnea-hypopnea index. The SEM is written equally:
TSTxc = α1 BMI + αii VC% + α3 PaO2% + α4 ODI + α5 AHI + due east one
PaOii% = β1 BMI + β2 VC% + β3 TST90 + e 2
var (east one)= σi; var (due east 2)= σ2; cov (due east i; e 2) = σ12
The structural equations were fitted using maximum likelihood estimates (MLE). The χ2 divergence exam of "fitted" vs. "saturated" models was used for hypothesis testing to evaluate the ceremoniousness of the feed-back model; big P-value (P > 0.05) was the criteria for data support. The regression parameter estimates (straight, indirect, and total effects) of simultaneous equations were re-expressed in a standardized course multiplying the unstandardized one past ane standard divergence (SD) of the explanatory variables. The P-values of the straight, indirect, and total estimates were evaluated past t-tests (=estimate/standard error) using robust standard errors; the level of statistical significance was set at P < 0.05, two-sided.
Descriptive and exploratory statistics were analyzed with SPSS 13.0 software (www.spss.com), while the feedback structural equations modeling was performed with Mplus 3.11 software (world wide web.statmodel.com).
RESULTS
All patients enrolled completed the study. The hateful PaOtwo value was lower than expected on the basis of age (80.2% ± x.7% of predicted). Fourteen patients (3% of 456 patients) had diffuse airway obstruction only they did not differ (P >0.05) from the remaining for PaOtwo% of predicted (76.3% ± 12.3% vs. 80.3% ± 10.seven%), AHI (46.8 ± 22.3 vs. 48.4 ± 33.iv) or TST90 (31.ii ± 39.6 vs. 24.2 ± xxx.ane). Every bit expected, the patients with diffuse airway obstacle were older (age 60.7 ± half dozen.6 vs. 49.1 ± 12.2 yrs, P<0.001) and less obese (BMI 34.8 ± 6.9 vs. 42.vii ± 10.9 kg/thoutwo, P = 0.01) than the entire sample.
The great majority of patients (81.half-dozen% of the 456 patients, 95% CI: 78.0% to 85.1%) had a PaOii <90% of predicted. As shown in Tabular array 1, the subjects with preserved PaO2 were older, and less obese than the patients with PaOii <90% of predicted. The accented FEV1/VC ratio was similar in these 2 groups of patients; while patients with daytime PaO2 >90% of predicted showed lower hateful values of AHI, ODI, and TST90 in comparison with patients with daytime hypoxemia.
Table one
Anthropometric, Lung Volumes, Blood Gas, and Sleep Information of Patients Classified past the Presence of Daytime Hypoxemia (PaO2 %<90 of Predicted)
| PaO2%<90 (n = 372) | PaO2%>ninety (due north = 84) | P-value (#) | |
|---|---|---|---|
| Mean ± SD | Hateful ± SD | ||
| Sexual practice (% (n) male) | 63.7 (237) | lxx.2 (52) | 0.311 |
| Age (yr) | 48.one ± 11.9 | 55.2 ± 12.i | <0.001 |
| BMI (Kg/m2) | 44.3 ± 10.five | 35.8 ± 12.1 | <0.001 |
| BSA (mii) | two.36 ± 0.32 | 2.09 ± 0.26 | <0.001 |
| VC (% pred.) | 92.9 ± xiv.5 | 99.2 ± xvi.one | 0.0013 |
| FEV1 (% of pred.) | 91.iii ± 17.ane | 110.3 ± xviii.1 | <0.001 |
| FEV1/VC (abs value) | 78.iii ± eight.four | 79.4 ± 7.7 | 0.2531 |
| FRC (% of pred.) | 75.5 ± 20.v | 83.iii ± 20.six | 0.0017 |
| RV (% of pred.) | ninety.4 ± 23.9 | xc.ane ± 17.seven | 0.9162 |
| TLC (% of pred.) | 90.7 ± 12.iii | 94.0 ± 13.4 | 0.0302 |
| MEF50 (% of pred.) | ninety.9 ± 34.5 | 96.2 ± 36.3 | 0.2083 |
| PaO2 (mmHg) | 68.ix ± 7.7 | 83.9 ± 6.4 | <0.001 |
| PaCO2 (mmHg) | twoscore.four ± 4.7 | 37.0 ± 3.1 | <0.001 |
| AHI (event-hour-i) | 50.7 ± 34.2 | 38.2 ± 25.7 | 0.0021 |
| ODI (event-hour-ane) | 52.i ± 34.ii | 37.6 ± 25.three | <0.001 |
| TST90 (%) | 13.1 ± 42.7 § | ane.45 ± 15.6 § | <0.001 |
The great majority of patients (79.4% of the 456 patients, 95% CI: 75.7% to 83.one%) had contradistinct gas exchange during sleep, defined every bit TST90 >ane% of total sleep time. As shown in Table 2, patients with nocturnal hypoxia had smaller lung volumes, simply similar FEV1/VC ratio, functional residual capacity and residual volumes. In contrast, they had more than severe sleep apnea and more impaired daytime PaOtwo.
Tabular array 2
Anthropometric, Lung Volumes, Blood Gas, and Sleep Data of Patients Classified by Presence of Nocturnal Hypoxia (TST90≥1.)
| TST90<1 % (north=94) | TST90 ≥ane % (n=362) | P-value (#) | |
|---|---|---|---|
| Mean ± SD | Hateful ± SD | ||
| Sex (% (n) male) | 56.iv (53) | 67.one (243) | 0.068 |
| Age (twelvemonth) | l.5 ± 13.4 | 49.2 ± 11.ix | 0.3466 |
| BMI (Kg/m2) | twoscore.0 ± 12.6 | 43.4 ± x.9 | 0.0086 |
| BSA (chiliadii) | two.xix ± 0.31 | ii.34 ± 0.32 | <0.001 |
| VC (% pred.) | 98.half dozen ± 15.1 | 92.ix ± xiv.8 | <0.001 |
| FEVone (% of pred.) | 96.seven ± 18.one | 92.0 ± 17.4 | 0.0195 |
| FEVone/VC (abs value) | 78.5 ± 8.one | 78.v ± 8.4 | 0.9547 |
| FRC (% of pred.) | 80.five ± nineteen.half-dozen | 76.0 ± 21.0 | 0.0605 |
| VR (% of pred.) | 94.0 ± 20.seven | 89.4 ± 23.iv | 0.0878 |
| TLC (% of pred.) | 94.ii ± 12.4 | 90.5 ± 12.5 | 0.0117 |
| MEFl (% of pred.) | 92.4 ± 36.4 | 91.7 ± 34.4 | 0.8713 |
| PaO2 (mm Hg) | 77.3 ± 8.0 | seventy.2 ± 9.3 | <0.001 |
| PaCO2 (mm Hg) | 37.7 ± iii.7 | 40.3 ± 4.vii | <0.001 |
| AHI (outcome-hr−1) | 26.8 ± 23.ii | 54.0 ± 33.0 | <0.001 |
| ODI (upshot-hour−1) | 28.4 ± 26.0 | 54.ix ± 32.8 | <0.001 |
| PaO2 (% of pred) | 87.0 ± 9.ii | 78.5 ± 10.4 | <0.001 |
A stepwise regression process included the predictors VC, BMI, AHI, ODI, and PaOii% in the regression equation of TSTxc from all the potential predictor variables listed in Table two; while VC, BMI, and TSTninety were the selected predictors in the regression equation of PaOii% from all the potential predictor variables listed in Table one (data non shown). The results of separate linear regression models for PaO2% and TSTninety were used to define the Path Analysis model with the improver of the feedback loop.
The maximum likelihood estimates and robust 95% CI of the standardized regression coefficient parameters (=average modify of the response variable by 1 standard deviation (SD) increment of the explanatory variable) for the TSTninety-PaOtwo feedback structural equations of Figure 1 are reported in Table 3. The chi-foursquare testing (χ2 = iii.242, df = 1, P = 0.072 NS) provided prove of the ceremoniousness of the feedback model given the observed data. The 2 feedback structural equations explained 34.two% and 31.3% of the full variance of continuous measurements of TST90 and PaO2%, respectively, while the residual correlation betwixt TST90 and PaOtwo% was fixed to 0 to ensure that the regression parameters of the estimated structural model were identified.
Table 3
Maximum Likelihood Estimates, and Robust 95% CI of Directly and Indirect Consequence Parameters of the Fitted (*) TST90-PaOtwo Feedback Structural Equations of Figure 1
| TSTxc (%) | PaOii (%) | |||
|---|---|---|---|---|
| β (95%CI) § | P-value | β (95%CI) § | P-value | |
| Feed-back loop: | ||||
| TST90 (%) | − | − | −3.96 (−2.11 to −5.82) | <0.001 |
| PaO2 (%) | +0.xv (−half-dozen.35 to +6.65) | 0.965 | − | − |
| Cor (TSTninety; PaOtwo) | 0 # | 0 # | ||
| Straight effects: | ||||
| BMI (kg/10002) | +3.91 (+0.61 to +vii.21) | 0.020 | −3.33 (−2.xiv to −4.53) | <0.001 |
| Vital capacity (%) | −four.91 (−2.24 to −7.58) | <0.001 | +one.50 (+0.59 to +2.41) | 0.002 |
| AHI (upshot-hr−1) | +7.99 (+3.63 to +12.iii) | <0.001 | − | − |
| ODI (event-hr−one) | +7.01 (+2.45 to +11.half dozen) | 0.003 | − | − |
| Indirect effects: | ||||
| AHI (event-hr−1) via TSTninety | − | − | −1.03 (−0.25 to −1.81) | 0.008 |
| ODI (result-60 minutes−1) via TST90 | − | − | −0.93 (−0.28 to −1.58) | 0.009 |
| R-square | 0.342 | 0.313 | ||
The daytime PaO2 % of predicted was statistically significantly associated (P<0.001) with the feedback effect of nocturnal hypoxia (TSTninety) and with the effects of obesity (BMI) and lung volumes (VC%). Specifically, an increment of 1 SD (30.five%) of TSTxc produced a reduction of 3.96% (95% CI: −2.11% to −5.82%) in the PaOtwo % of predicted; an increase of one SD (xi.iii kg/mtwo) of BMI produced a turn down of 3.33% (95% CI: −2.xiv% to −iv.53%); and an increment of ane SD (xv%) of VC% produced a rise of 1.five% (95% CI: +0.59% to +two.41%).
In dissimilarity, the daytime PaO2 feedback effect did not influence (P = 0.965) the extent of nocturnal hypoxia, which was statistically significantly related with the severity of OSA (P <0.001), and background measurements (BMI, P = 0.020 and VC%, P<0.001). Specifically, an increment of 1 SD (33 events/1 hour) in the AHI or ODI increased TSTxc by 7.99% (95% CI: +3.63% to +12.iii%) or seven.01% (95% CI: +2.45% to +xi.6%), respectively; TST90 also increased by three.91% (95% CI: +0.61% to +seven.21%) for ane SD of BMI and declined 4.91% (95% CI: −2.24% to −7.58%) for 1 SD of VC%.
The above described changes were net furnishings (direct effects); however, the severity of OSA, expressed by AHI and ODI, also had statistically significant indirect furnishings (P = 0.009) on daytime hypoxemia via the nocturnal hypoxia pathway, i.due east., TST90 is a variable that mediates the effect of OSA on PaO 2 consequence. Specifically, via the TST90 path, an increment of 1 SD in the AHI or ODI decreased PaO 2 % of predicted by about 1% (95% CI: −0.25% to −1.81% for AHI, and −0.28% to −1.58% for ODI).
None of the results changed if PaO2 was considered in absolute values rather than in % of predicted.
Stratification according to gender did not show any major differences in feedback, direct or indirect effects between subgroups (data not shown).
DISCUSSION
The main findings of this study are: (i) patients with OSA, in the absenteeism of lung comorbidity such as diffuse airway obstruction, had lower values of PaO2 than those expected on the ground of age; and (ii) a feedback model of daytime hypoxemia-nocturnal hypoxia (Figure 1) was non supported, even after adjustment for obesity and lung book, and gender stratification. An increment of per centum sleep fourth dimension with reduced SpOii is associated with a decrease in daytime PaOii, while the level of nocturnal SpOii is non related to the level of daytime PaO2. Moreover, considering nocturnal hypoxia is related to the severity of OSA (expressed by AHI and ODI), the level of nocturnal SaO2 is as well a mediator of the severity of the OSA effect on daytime hypoxemia.
We performed the nowadays study in an attempt to determine the direction of the relationship between daytime hypoxemia and nocturnal hypoxia. This issue is related to an appropriate definition of daytime hypoxemia and an appropriate identification of the population of patients. Firstly, virtually of the previous papers reported that a normal value of PaO2 at rest is ≥fourscore mm Hg, hypoxemia is nowadays when the PaO2 is below lxxx mm Hg, and astringent hypoxemia when the PaO2 is ≤65 mm Hg.1,3,seven,viii,10 None of these studies adapted the PaO2 values for age, obesity or lung volumes. We corrected the PaO2 data according to the reference equation for the Italian population, thus defining the PaOii as a pct of predicted. In this way, nosotros establish that the slap-up bulk of subjects had reduced PaO2 values. Indeed, simply 84 (18%) patients had a PaO2 higher than ninety% of predicted. This upshot did not change when unlike reference values of PaOtwo published in the literature were applied (information not shown),nineteen,20 or when the PaO2 was considered as an absolute value.
The 2d bespeak regards the choice of the population of the patients. In the present study we included consecutive patients with slumber apnea, so that all biases related to disordered respiratory mechanics could be excluded. This was non the example in the previous studies in which a significant proportion of patients, ranging from 11% to 25%, were afflicted by concomitant COPD, with the prevalence of COPD, sometimes with FEV1 < ane litre.1,3,7–8,ten In COPD, peripheral airway obstruction, parenchymal destruction, and pulmonary vascular abnormalities reduce the lung'due south capacity for gas exchange, producing hypoxemia and, after on, hypercapnia.21 Since daytime PaOii data were not corrected for historic period or lung office and, since subjects with concomitant COPD were older than those with unproblematic OSA, the effect of age and lung office impairment in determining lower values of PaO2 were mutually enhanced.22
We found that TST90, an index of nocturnal hypoxia, was a valuable determinant of the evolution of daytime hypoxemia, even after adjustment for the caste of obesity, lung volumes and sex stratification. AHI and ODI, expressions of the severity of sleep apnea, were besides significant determinants although their effect was mediated through TST90. Of interest, the level of TSTninety appears contained of daytime PaO2, considering the feedback (reciprocal) upshot was not supported. This latter is an intriguing ascertainment since in the past it was hypothesized that a low level of daytime PaOii may account for the severity of the nocturnal hypoxia.x Indeed, Bradley et al. observed, in a group of OSA patients, that the master predictors of nocturnal desaturation, expressed by the mean value of SaO2 beyond the night, were daytime PaO2, alterations in respiratory mechanics (once again mainly related to airway obstruction and the caste of obesity), and the slumber time spent in apnea. On the opposite, our results are in agreement with data, reported by Sanders et al, obtained from the Sleep Heart Wellness Written report.23 They plant that patients with slumber apnea without obstructive airway disease had a 20-fold higher odds ratio for nocturnal desaturation than that of healthy subjects, even afterwards adjustment for historic period, sex, height, weight, race, smoking status and awake SaOtwo.
The development of daytime hypoxemia in OSA patients has generally been related to the presence of subclinical arterial pulmonary hypertension (PH).three–6 However, this association with pulmonary hypertension is at present a matter of give-and-take since most of the studies produced conflicting results. It should be considered that all the studies that gave negative results were the oldest ones and the ones with a relevant percentage of COPD patients, equally stated higher up.1–iii,vii–8,10 There is, notwithstanding, a growing body of evidence that highlights the role of sleep apnea in the development of daytime gas exchange abnormalities through the pathophysiological effect of chronic intermittent hypoxia. The occurrence of PH in OSA patients without concomitant lung affliction ranged from twenty% to 43%.4–6,24 In all these studies PH patients had a more altered nocturnal gas exchange and in ii of them a lower level of daytime PaO2.6,24
The increasing of pulmonary arterial pressure has been associated with hypoxia-induced pulmonary vasoconstriction.5,25,26 Beast models showed increases in right ventricular mass, hematocrit level and pulmonary arterial pressure during exposure to chronic intermittent hypoxia or asphyxia.27,28 Chronic intermittent hypoxia activates homeostatic mechanisms in the respiratory organisation that induce changes in factor expression by mediation of several transcription factors, such as hypoxia-inducible cistron (HIF).29 Experimental data showed that hypoxia inducible factors (both HIF-1α and HIF-2α) are involved in physiological responses of pulmonary arterioles to chronic intermittent hypoxia, collectively producing hypertrophy and depolarization of pulmonary arteriolar polish muscle.29
Recent studies suggested that the hypoxia inducible factor-1 pathway response to chronic intermittent hypoxia seems to be activated only in patients with moderate to severe nocturnal gas exchange alterations.30 These patients showed a significantly increased level of erythropoietin during slumber, differently from patients with less severe OSA.31 On the contrary, in these latter chronic intermittent hypoxia activated a different pathway mediated through the transcription factor nuclear factor-κB that, in turn, increased the expression of tumor necrosis factor-α, which may contribute to endothelial dysfunction.32 Finally, treatment with CPAP has been demonstrated to reduce pulmonary arterial force per unit area levels also in patients with a pressure <xx mm Hg.26,33
However, daytime hypoxemia in OSA patients may develop through mismatching of ventilation and perfusion, every bit a result of dissimilar mechanisms, such as changes in mechanical properties of the lung or evolution of subclinical interstitial pulmonary edema. An increase in elastance of the whole lung during slumber was found in patients with OSA.34 Slumber may induce a loss in the mechanical coupling between airways and lung parenchyma which, in turn, allows the airways to narrow more easily.35 Alternatively, the reduction of lung volumes during slumber could not but decrease parenchymal attachments but also increase the forces arising from surface tension, which would lead to an increase in elastance. Indeed, information technology was shown that the severity of apnea-induced desaturation was correlated with lung volume, specially with the divergence between supine expiratory reserve volume and seated closing volume.36 These mechanical modifications may induce closure of some respiratory units during upper airway obstruction, which is reversed at the end of the obstruction. These transient abnormalities in the recruitment of lung units resulting in air space closure reduce the gas exchange capacity of the lungs independently from the level of daytime gas exchange.34
Chronic intermittent hypoxia induces proliferation of the vasculature due to angiogenesis but tin also change the integrity of vessels, leading to changes in vascular permeability.37 Fletcher et al., in a canine model of OSA, demonstrated that pulmonary edema tin develop after recurrent obstructive apneas.38 They establish a significant deterioration of gas exchange in those animals with histologic and/or electron microscopy testify of lung edema compared to those without edema and controls and a substantial fall in the aamplitude of apnea desaturation related to deterioration of gas commutation. It has been demonstrated that hypoxia induces angiogenesis upregulating the vascular endothelial growth factor (VEGF).39 Schulz et al. found that the serum levels of VEGF are elevated in severely hypoxic patients with OSA and are related to the caste of nocturnal oxygen desaturation.40 Of interest, patients with the highest degree of nocturnal desaturation were those with the lowest level of daytime PaOtwo.
Recently, Guardiola et al. suggested that the mechanical changes and increased interstitial lung water described above were not immediately reversed since they found that OSA patients had lower PaO2 values in the forenoon than in the evening.41
A possible limitation of our study, like that of the other studies, is the lack of information near the intensity and elapsing of exposure to nocturnal hypoxia. Dissimilar durations of disease, or, more than probably, an early onset of OSA may contribute to explain the variability between the results nosotros obtained and those of the previous studies. One particularly complex methodological result in characterizing the progression of OSA is the worsening epidemic of obesity in western countries such that it tin can be very difficult to separate the furnishings on gas exchange of prolonged OSA from those related to increasing body weight.42 Indeed, a longitudinal study on sleep disordered breathing performed in a nonclinic population found that changes in the respiratory disturbance index over fourth dimension practise not vary uniformly with age, sex, and weight.43
Finally, most of the patients enrolled in our report were obese and therefore caution needs to be exercised regarding the generalizability of our findings. Even so, all the results were statistically adjusted for the level of obesity and so that the effect of this anthropometric parameter in our specific cohort could exist minimized.
In conclusion, our data support the evidence that nocturnal hypoxia seems to exist both a direct determinant and a mediator of the indirect effect of sleep apnea on the development of daytime hypoxemia. Follow-upwards studies are needed to evaluate the time course of daytime gas exchange abnormalities and to assess the role of therapy in stopping or slowing down this evolution.
Footnotes
Disclosure Statement
This was not an industry supported study. The authors have indicated no financial conflicts of involvement.
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Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2225567/
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