Non-specific Ventilatory Defect Predicts Nocturnal Hypoxemia in Subjects with Obesity

doi:10.21203/rs.3.rs-2980769/v1

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Non-specific Ventilatory Defect Predicts Nocturnal Hypoxemia in Subjects with Obesity

https://doi.org/10.21203/rs.3.rs-2980769/v1

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Although nocturnal hypoxemia has been linked to obesity, the relationship between spirometry parameters and nocturnal oxygen saturation (SpO2) has not been well studied in subjects with obesity.

This a retrospective cross-sectional chart review of adult patients with obesity, who had PFT (pulmonary function tests) and diagnostic polysomnogram within 6 months between 2017-2019.

A total of 227 patients were included in the analysis, of which 69% were females and 43.8% were African Americans. In the absence of obstruction on spirometry, FEV1 (forced expiratory volume in first second) and FVC (forced vital capacity) were associated with lower mean nocturnal SpO2. Non-specific ventilatory defect on PFTs was associated with increased odds of having a mean nocturnal SpO2 <92% compared to normal spirometry, and lung volumes (OR:2.15,95%CI:1.02-4.5,p=0.042) with adjustment for age, sex, BMI (body mass index).

Non-specific PFT pattern should prompt screening for sleep symptoms and considering a polysomnogram in subjects with obesity.

Non-specific pattern

Nocturnal hypoxemia

Obesity

Pulmonary Function Test

Obesity is a significant issue of global public health concern[1]. Obesity is a risk factor for coronary artery disease, hypertension, diabetes, stroke, and certain cancers[1]. Moreover, obesity causes respiratory function impairment due to the altered relationship between the lungs, the chest wall, and the diaphragm[2]. The physical restriction from thoracic and abdominal adiposity causes mechanical disadvantage to the movement of the diaphragm and the compliance of the chest wall[3]. Increased body mass index (BMI) has a significant effect on lung volumes and is associated with a reduction in expiratory reserve volume (ERV) and functional residual capacity (FRC)[4]. Supine positioning exacerbates the mechanical disadvantage of the diaphragm from the cephalad shift of the abdominal adiposity, leading to a further reduction in lung volumes (particularly FRC)[5].

Obesity has been associated with hypoxemia during wakefulness (especially when BMI > 35 kg/m2)[6], and during general anesthesia, endoscopy, and post-operative recovery[7–9]. Moreover, excess body weight is associated with increased severity of oxygen desaturation in obstructive sleep apnea (OSA)[10, 11]. Nocturnal hypoxemia is linked to the upregulation of the renal renin-angiotensin system[12] and increased cardiovascular complications[13]. Bariatric surgery is effective at improving nocturnal hypoxemia in patients with obesity and OSA[14].

Spirometry is usually preserved in patients with obesity except in extreme elevation of BMI[15, 16]. However, an inverse association has been described between abdominal adiposity markers and spirometry parameters: FEV1(forced expiratory volume in first second) and FVC (forced vital capacity)[17]. Although nocturnal hypoxemia has been linked to obesity, the relationship between spirometry parameters and nocturnal oxygen saturation has not been well studied in subjects with obesity.

In this study, we hypothesize that the mean oxygen saturation detected on an attended sleep study is positively associated with spirometry parameters (FEV1 and FVC) in subjects with obesity and suspected OSA. Subsequently, we predict that the presence of a non-specific ventilatory defect (reduced FEV1, FVC, or both with normal FEV1/FVC ratio and normal total lung capacity)[18] on pulmonary function tests (PFT) is associated with nocturnal hypoxemia in this population.

This is a retrospective cross-sectional study of adult patients with obesity (BMI > = 30 kg/m2) who completed both diagnostic attended polysomnograms (PSG) and complete PFT at a safety-net health care system in 3 years (2017–2019). Only subjects with PSG and PFT done within six months were included. Diagnostic PSGs were indicated due to sleep-disordered breathing symptoms (snoring, witnessed apnea, insomnia, daytime sleepiness, waking up gasping for air). PSG scoring of the apnea hypopnea events was done following AASM (American Academy of Sleep Medicine) guidelines [19]. Pulmonary symptoms were the primary reason for the referrals to pulmonary function testing. Spirometry was performed and parameter percent predicted values were calculated according ERS(European Respiratory Society)/ATS(American Thoracic Society) guidelines [20]. Plethysmography was used to measure lung volumes. Out of a total of 580 patient charts that met inclusion criteria, 12 patients with BMI < 30 were excluded (BMI was > 30 at the time of chart extraction but < 30 at the time of diagnostic studies), 289 patients were excluded due to obstructive ventilatory impairment on PFTs, and 52 patients were excluded because all the parameters of PFTs or PSG were not available. The study was approved by the institutional Internal Review Board (IRB).

Statistics

ANOVA (analysis of variance) was used to compare the means of mean nocturnal oxygen saturation (SpO2). Two sample Wilcoxon rank sum (Mann-Whitney test) was used to compare the mean and medians of the percentage of time spent with SpO2 < 90% (skewed distribution). Logistic regression was used to evaluate whether a non-specific PFT ventilatory defect is predictive of a low mean SpO2 < 92%.

A total of 227 adult patients with obesity were included in the analysis (Table 1 depicts descriptive characteristics). Subjects were stratified by FEV1 percent predicted and FVC percent predicted into three groups (< 80%, >=80% and < 100%, and > = 100%). The nocturnal mean SpO2 was 92.4(+/-3.8)%, 93.5(+/- 3.0)%, and 94.3(+/-2.2)% in the FEV1 < 80% predicted, between > = 80% predicted and < 100% predicted, and > = 100% predicted respectively (statistically significant difference between the means; F = 4.17, p = 0.017). Similarly, The nocturnal mean SpO2 was 92.4(+/-3.8)%, 93.8(+/- 2.8)%, and 94.2(+/-2.2)% in the FVC < 80% predicted, between > = 80% predicted and < 100% predicted, and > = 100% predicted respectively (statistically significant difference between the means; F = 4.66, p = 0.010).

In a subgroup analysis (N = 151), patients with non-specific ventilatory defect on PFT, i.e., normal total lung capacity, normal FEV1/FVC ratio, low FEV1, low FVC, or both (N = 60), were compared to those with normal spirometry and lung volumes (N = 90). The mean nocturnal SpO2 in patients with non-specific ventilatory defect was 92.2(+/- 0.42)% compared to 93.5(+/- 0.29)% in those with normal spirometry and lung volumes (difference = 1.3%, 95%CI: 0.34–2.28,p = 0.009). Similarly, the mean and median percentage of time spent with SpO2 < 90% was higher in those with non-specific PFT pattern [mean 23.1 (+/- 26.8)%, median 7.8%] compared to normal PFT’s [mean 16.5 (+/- 26.7)%, median 2.5%] with statistically significant difference using a Wilcoxon rank-sum test (z = -2.167, p = 0.03). In a multiple logistic regression that included age, gender, and BMI (Table 2), the odds of low mean nocturnal SpO2 (defined as mean SpO2 < 92%) in patients with non-specific ventilatory defect was 2.15 times the odds of low mean nocturnal SpO2 in those with normal spirometry and lung volumes (OR 2.15, 95%CI:1.02–4.5,p = 0.042). However, after including AHI in the regression model (Table 2), there was only a trend for increased odds of low mean nocturnal SpO2 in patients with non-specific ventilatory defect compared to those with normal spirometry and lung volumes (OR:2.0, 95%CI: 0.94–4.24, p = 0.071). Likewise, the odds of having a percentage of nocturnal time with SpO2 < 90% greater > 15% in patients with non-specific ventilatory defect was 2.5 times the odds in those with normal spirometry of lung volumes (OR 2.5, 95% CI 1.18–5.36, p = 0.016, Table 3). After adding AHI to the multiple logistic regression model, the increased odds of a high percentage of nocturnal time with SpO2 < 90% in patients with non-specific ventilatory defect compared to normal spirometry and lung volumes remained statistically significant (OR: 2.32, 95%CI: 1.06–5.07, p = 0.035, Table 3).

Obesity is associated with respiratory function impairment [4–7]. As the BMI increases, there is a modest reduction of FEV1 and FVC, but they remain above the lower limit of normal in obese individuals who are otherwise healthy[17]. In our study, we found that FEV1% and FVC% predicted are positively associated with mean nocturnal SpO2 in obese patients referred for PFT and without obstruction by spirometry as defined by the ERS/ATS guidelines [19]. This association appeared to persist even within the normal FEV1% predicted range (between 80 and 100% predicted compared to > 100% predicted).

Obesity is commonly associated with a non-specific pattern on PFTs (reduced FEV1, FVC, or both with normal FEV1/FVC ratio and normal total lung capacity)[21]. In our study, we evaluated the relationship between non-specific ventilatory defect on PFTs (compared to normal spirometry and lung volumes) and nocturnal hypoxemia. Compared to those with normal spirometry and lung volumes, subjects with a non-specific ventilatory defect were about two times more likely to have low mean SpO2 (< 92%) and two times more likely to have 15% or more nocturnal time spent with SpO2 < 90%, with adjustment for age, sex, and BMI. The association between non-specific pattern and mean Spo2 became not statistically significant after including AHI in the analysis; however, there was a trend for statistical significance (p = 0.071). After introducing AHI in the analysis for 15% or more of nocturnal time spent with SpO2 < 90%, the association remained statistically significant (p = 0.035). Overall, a nonspecific ventilatory defect on PFTs may indicate obesity-related chest wall limitation leading to negative physiological effects and hypoxemia. However, it is essential to note that we cannot exclude other underlying pulmonary etiologies, including early obstruction, as a cause of the non-specific pattern for these patients with obesity. It is safe to say, however, regardless of the underlying etiology, non-specific ventilatory defect (compared to normal spirometry and lung volumes) is associated with an increased likelihood of low nocturnal oxygenation in subjects with obesity.

There are significant limitations to this study. First, a major limitation is referral bias. The patients included in our analysis underwent PFT and sleep studies primarily due to the presence of pulmonary and sleep-disordered breathing symptoms. Although we excluded patients with obstruction on spirometry, COPD (chronic obstructive pulmonary disease), emphysema and asthma diagnoses were present in 10.6%, 20.3% and 58.1% of subjects, respectively. It is frequently challenging to determine the relative contribution of chest wall limitation from obesity and the physiological effects of other conditions that can cause ventilatory impairment. Therefore, this study links PFT parameters with nocturnal hypoxemia in subjects with obesity, irrespective of the underlying pathology. Second, this study is from a single healthcare system and is limited by a relatively small sample size. Third, transcutaneous carbon dioxide monitoring was not routinely measured in sleep studies; therefore, hypoventilation was not assessed in this study.

In adults with obesity referred to testing for pulmonary and sleep-disordered breathing symptoms and with no obstruction on spirometry, lower nocturnal oxygen saturation was associated with lower FEV1 and FVC percent predicted. Moreover, a non-specific PFT ventilatory defect (reduced FEV1, FVC, or both with normal FEV1/FVC ratio and normal total lung capacity) was associated with nocturnal hypoxemia (SpO2 < 92%; >15% of nocturnal time with SpO2 < 90%) in subjects with obesity and suspected OSA. Further research is recommended to elucidate the physiological effects of obesity on lung function and subsequent oxygenation.

AASM

American Academy of Sleep Medicine

AHI

Apnea Hypopnea Index

ANOVA

Analysis of Variance

BMI

Body Mass Index

CDC

Centers for Disease Control and Prevention

EMR

Electronic Medical Record

DLCO

Diffusing capacity of Lung for Carbon Monoxide

ERV

Expiratory Reserve Volume

FEV1

Forced Expiratory Volume in 1 sec

FRC

Functional Residual Capacity

FVC

Forced Vital Capacity

IRB

Internal Review Board

PFT

Pulmonary Function Test

PSG

Polysomnogram

Residual Volume

SpO2

Oxygen saturation in percentage

TLC

Total Lung Capacity

Summary conflict of interest - The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Funding information – Not applicable

Acknowledgements –

IL is the guarantor of the content of the manuscript, including the data and analysis. All the authors had access to all the data related to study and takes responsibility for the integrity of the data and the accuracy of data analysis. IL and MA were responsible for the study design, data analysis and interpretation. IL, FQ and SS were responsible for data collection by chart review from abstracted patient charts. IL and FQ were responsible for writing the first draft of manuscript. All the authors had an opportunity to review and revise the manuscript and approved its final submitted version.

Financial/nonfinancial disclosures –

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Adult Obesity Facts: Centers for Disease Control and Prevention 2022 [Available from: https://www.cdc.gov/obesity/data/adult.html]
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Table 1

Baseline characteristics
Characteristic	N = 227
	% or Mean (+/- SD)
Age (in years)	53 (+/-13.4)
BMI (kg/m2)	40.8 (+/-8.2)
Gender
Males	30.3%
Females	69.7%
Race/Ethnicity
White	41.7%
African American	43.8%
Asian	1.3%
Hispanic	7.5%
Others	5.7%
Smoking
Current	20.3%
Former	28.6%
Never	51.1%
Insurance
Medicare	32.4%
Medicaid	32.9%
Private	30.7%
Uninsured	4%
Comorbidities (based on EMR documentation)
Asthma	58.1%
COPD	10.6%
Emphysema	20.3%
ILD	6.1%
Sarcoidosis	7%
Congestive Heart Failure	19.8%
PFT/PSG parameters
FEV1% Predicted	78.1 (+/- 17)
FVC% Predicted	76.4 (+/- 15)
DLCO % Predicted	91 (+/- 25)
Nonspecific pattern (n)	61
Mean SpO2 in total sleep time (in %)	93 (+/-3.5)
Mean AHI (events/hour)	35.9 (+/- 32.7)

Table 2

Multivariate logistic regression for low mean nocturnal SpO2 (< 92%) and non-specific PFT pattern compared to normal PFT (normal spirometry and lung volumes) after adjustment for covariates (without and with AHI)
Not Including AHI Including AHI
Variable	Odds ratio	p-value	95% CI	Odds ratio	p-value	95% CI
Non-specific pattern on PFT	2.15	0.042	1.027-4.50	2.000	0.071	0.942–4.248
Age (years)	1.046	0.005	1.014–1.079	1.040	0.016	1.007–1.074
BMI (kg/m2)	1.028	0.266	0.980–1.078	1.017	0.511	0.967–1.069
Sex*	1.456	0.376	0.634–3.343	1.150	0.754	0.479–2.764
AHI (events/hour)				1.014	0.033	1.001–1.027
*Odds ratio: male to female

Table 3

Multivariate logistic regression for low saturation (> 15% time of sleep spent in SpO2 < 90%) and non-specific PFT pattern compared to normal PFT (normal spirometry and lung volumes and other covariates (without and with AHI)
Not Including AHI Including AHI
Variable	Odds ratio	p-value	95% CI	Odds ratio	p-value	95% CI
Non-specific pattern on PFT	2.523	0.016	1.189–5.357	2.000	0.071	0.942–4.248
Age (years)	1.050	0.003	1.016–1.084	1.040	0.016	1.007–1.074
BMI (kg/m2)	1.041	0.106	0.991–1.094	1.017	0.511	0.967–1.069
Sex*	1.838	0.156	0.793–4.261	1.150	0.754	0.479–2.764
AHI (events/hour)				1.014	0.033	1.001–1.027
*Odds ratio: male to female

No competing interests reported.

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Non-specific Ventilatory Defect Predicts Nocturnal Hypoxemia in Subjects with Obesity

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