ORIGINAL ARTICLE

J Urol Surg 2016; 3: 55-64
Received Date: 08.06.2016
Accepted Date: 09.09.2016
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Dr. Suat Seren Chest Diseases and Surgery Training and Research Hospital, Clinic of Chest Diseases, İzmir, Turkey

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Nizip Zerdegümlü Ayşe Çapan Family Health Center, Gaziantep, Turkey

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Antalya Atatürk State Hospital, Clinic of Otorhinolaryngology, Antalya, Turkey

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Dr. Suat Seren Chest Diseases and Surgery Training and Research Hospital, Clinic of Chest Diseases, İzmir, Turkey

The Effect of Non-invasive Mechanic Ventilation Treatment on Lactate Level in Sleep-Related Breathing Disorders

Objective: Lactate, as an indicator of hypoxia, may be useful in sleep-related breathing disorders to identify higher risk groups and monitor the effectiveness of positive airway pressure (PAP) treatment. We aimed to investigate the change in arterial lactate level in blood after PAP treatment in patients with obstructive sleep apnea (OSA) and sleep-related hypoventilation and hypoxemic syndromes and its applicability for monitoring this change regarding the effectiveness of the treatment.
Materials and Methods: PAP titration was applied to 64 OSA patients diagnosed with polysomnography. Measurements included pulmonary function testing, overnight PAP titration, arterial blood gases, and analysis of arterial lactate before and after titration. Overnight lactate level change was calculated.
Results: Of the 64 patients in the study, 49 were in the OSA group and 15 were in the Obesity Hypoventilation syndrome plus OSA group. No statistically significant difference was detected among the patients in terms of lactate levels before and after PAP treatment [1.97 (±0.7) - 1.98 (±0.6)] (p>0.05). In the OSA patient group, we detected an inverse relationship between Lactate and pre-treatment non-rapid eye movement 1-2% (r=-0.328, p=0.021), T 90% (r=-0.356, p=0.012), and total apnea hypopnea index (AHI) (r=-0.424, p=0.002). Lactate is found to be positively correlated with pre-treatment measured oxygen saturation (r=0.396, p=0.005), and with minimum oxygen saturation (r=0.361, p=0.011).
Conclusion: Our study showed that there is a relationship between AHI, average and minimum oxygen saturation and T 90% and lactate difference, which are severity indicators for OSA. These results suggest that PAP treatment may prevent possible lactate increase.

Introduction

Obstructive sleep apnea (OSA) syndrome is characterized by apneas and hypopneas caused by repetitive airway narrowing and associated sleep fragmentation, increased sympathetic drive and intermittent hypoxia (1). Sleep-related hypoventilation and hypoxemic syndromes (SRHHS) include diseases characterized by abnormal gas exchange that occur or get worse during sleep, such as Obesity Hypoventilation syndrome (OHS) (2). Studies have demonstrated that cardiovascular mortality and morbidity increase in sleep-related breathing disorders (SRBD) (3,4). Reduced pyruvate, which is the end product of glycolysis through anaerobic mechanism, generates lactate. In many diseases accompanied by deep hypoxia, lactate-the end product of anaerobic carbohydrate metabolism increases and such increase is found to be in parallel with poor prognosis in some studies. Studies conducted in intensive care units have demonstrated that blood lactate measurements constitute an independent indicator of mortality (5-7). Hypoxia triggers a number of pathophysiological impairments in OSA and OHS cases as well. Again, in OSA, impaired muscle metabolism and excessively increased lactate levels during exercise have been demonstrated in previous studies (8,9).

A study conducted in our clinic found that arterial lactate levels measured with polysomnography (PSG) in the morning were higher in OSA patients compared to the non-OSA patient group. However, there is not enough data on lactate levels in SRBD patients measured after positive airway pressure (PAP) titration. For this reason, in this study we aimed to investigate arterial blood lactate change as an indicator of tissue hypoxia after PAP treatment in OSA and SRHHS patients.

Materials and Methods

Selection of Patients

This prospective study was conducted on a total of 64 patients with OSA; 49 with OSA (grouped as 1) and 15 with both OSA and OHS (grouped as 2) who were referred to the sleep outpatient clinic in our hospital over the period from 27.04.2011 to 01.10.2011. A total of 312 patients had an overnight PSG during this period in our clinic that 234 of them diagnosed as OSA. One hundred eighty two of these OSA patients had the indication for PAP treatment. The subjects who met the criteria for inclusion in the study (n=64) were also diagnosed with overnight PSG. All the participants’ had indication for PAP [continuous PAP (CPAP), bi-level PAP (BPAP) and auto PAP (APAP)] treatment. The study protocol was approved by the Institutional Review Board of the research hospital (Dr. Suat Seren Chest Diseases and Surgery Training and Research Hospital Ethics Committee No: 279 01.09.2010). Patients included in the study completed an informed written consent form.

OSA and SRHHS diagnoses were based on the International Classification (ICSD-2) of the American Academy of Sleep Medicine (AASM) (10). PAP treatment was offered to those scoring equal to or higher than 30 in the apnea hypopnea index (AHI), independent of the subjects’ complaints (11). Further, subjects with documented cardiovascular diseases such as hypertension, ischemic coronary disease and stroke and/or symptoms like increased daytime sleepiness, cognitive dysfunction, mood disorders, sleeplessness with AHI score between 5 and 30 per hour were also given PAP treatment (12-17).

BPAP was applied to the OSA cases with intolerance to CPAP treatment because of high nasal airflow, air leak or poor exhalation under positive pressure as well as those with a co morbidity accompanying OSA (cases with nocturnal respiratory problems such as morbid obesity or nocturnal hypoventilation) (18-22). Physicians specialized in sleep disorders have preferred APAP treatment for cases who failed treatment with fixed pressure (23,24).

All patients were evaluated according to their co morbidities such as hypertension, hyperlipidemia, diabetes mellitus, cardiac disease, thyroid diseases, etc. Hypertensive patients were those whose blood pressure is determined to be higher than 135/85 mmHg after two independent measurements (25). Patients diagnosed with hyperlipidemia display increased levels of cholesterol and/or triglyceride in their plasma (26). Cardiac patients constitute the patient group who received treatment with arrhythmia or ischemic cardiac disorder in their medical history, and with ejection fraction higher than 50%. Finally, the group diagnosed with diabetes mellitus covers those who received antidiabetic medication (except metformin) and whose fasting glucose levels after PSG recording equals to 7.0 mmol/L (126 mg/dL) (27).

Exclusion Criteria

Patients with comorbidities that may alter lactate metabolism, such as severe renal failure, chronic hemodialysis treatment, hepatic failure, acidosis, diabetes requiring insulin, deep anemia, hemoglobinopathy, congestive cardiac failure, as well as those with chronic alcohol consumption, those receiving metformin, methyldopa, oral contraceptives, statin/3-hydroxy-3-methylglutaryl-coenzyme reductase inhibitors, acetaminophen, diclofenac, amoxicillin, amiodarone, chlorpromazine, ciprofloxacin, erythromycin, fluconazole, isoniazid, ripamfin, and valproic acid, were excluded from the study. We also excluded chronic obstructive pulmonary disease (COPD) patients from the study.

Polysomnography

PSG was performed with a PSG running Somnologica, version 4.0 (Embla Systems®, Broomfield, CO) and included four electroencephalography channels (C3-A1, C4-A2, O1-A2, O2-A1), right and left electrooculography channels, one chin electromyography (EMG) channel and four tibialis anterior EMG channels, finger pulse oximeter, strain gauges for thoraco-abdominal movements, one electrocardiography lead, a nasal airflow (pressure cannula), and a digital microphone for snoring detection. PSG recordings were scored in 30-second periods for sleep, breathing, and oxygenation according to the standard criteria of AASM (24). “Obstructive apneas” were defined as a complete cessation of oronasal airflow for at least 10 seconds in the presence of chest-wall motion. “Hypopneas” were defined as a reduction in respiratory airflow of 50% or more or a clear reduction in airflow related with more than 3% arterial oxygen desaturation or an arousal lasting for at least 10 seconds. The AHI was calculated as the total number of apneas and hypopneas per hour of sleep. Sleep was staged manually using the standard criteria of AASM (24,25). According to ICSD-2 classification, the diagnosis of SRBD is based on PSG and includes:

-    OSAS: AHI -5 per hour of sleep.

-    Obesity hypoventilation syndrome:

Obese patients [body mass index (BMI) -30 kg/m2] with one of the following (10):

-    SpO2 during sleep of less than 90% for more than five minutes with a minimum of at least 85%;

-    More than 30% of total sleep time with an SpO2 of less than 90%;

-    Sleeping arterial blood gas with PaCO2 that is abnormally high or disproportionately increased relative to levels during wakefulness.

Bi-Level Positive Airway Pressure, Continuous Positive Airway Pressure and Auto Positive Airway Pressure Titration

PAP titration was performed by a sleep technician at night under expiration pressure with 1 cmH2O pressure increases until the sufficient pressure was reached for all apneas, flow limitations and snoring to disappear, and under inspiration pressure with 1 cmH2O pressure increases until the sufficient pressure was reached for hypopnea, hypoxia, and hypoventilation to disappear. Manual CPAP titration was performed by a sleep technician at night with 1 cmH2O pressure increases until all apneas, hypopneas, flow limitations and snoring disappeared. We performed APAP titration with rapid eye movement sleep (REM) star Auto (Respironics, Germany). We analyzed the average pressure required through the night after BPAP, Manual CPAP and APAP titration, maximum pressure required for 90% of the night, and average mask leak data.

Arterial Blood Gas Lactate Measurement

The first 2 mL arterial blood gas sample was taken before manual PAP titration in the night in supine position while the subject is asleep and awake, and the second was taken after titration in the morning in the same position, from the radial artery via heparinized tubes. We evaluated samples immediately via Rapidlab Analyzer 860 (Bayer Health Care Systems-Siemens, USA). Laboratory reference value for lactate was 0.5-2 mmol/lt.

Overnight lactate change was calculated based on the following formula: ∆lactate=(blood gas lactate)Morning - (blood gas lactate)Night

Other Measurements

Fasting blood samples were taken in the following morning for an evaluation of biochemical parameters such as hemogram and fasting glucose, lipid profile, and thyroid function tests. Pulmonary function test (PFT) measurements were conducted with a ZAN 100, (Flow Handy, Germany) device in standing position and by using nasal clips in order to exclude COPD (28). At least three and up to five forced expiratory maneuvers were performed to obtain three technically acceptable blows. The highest forced vital capacity (FVC) and forced expiratory volume in the first second (FEV1) were recorded. We used Epworth sleepiness scale (ESS) to measure daytime sleepiness and ESS >10 was defined to indicate excessive daytime sleepiness (29).

Statistical Analysis

Analyses were conducted by using SPSS 17 package software. Variables for classification were described in frequency and percentage, continuous variables in average and standard deviation or median and min-max values. Mode and frequency values were used for describing the first and second titration pressures. We tested lactate differences between groups and changes in lactate levels with median testing. In comparing average values, we used the Mann-Whitney U test for independent samples, and Wilcoxon test for dependent samples. We investigated the relationship between other parameters and lactate difference as well as change of lactate with respect to initial condition through partial correlation analysis (adjusted according to BMI). All analyses were conducted with 95% level of confidence and p<0.05 was considered to indicate statistical significance.

Results

Forty-nine patients diagnosed with OSA syndrome out of 64 included in the study constituted group 1, and 15 patients with OHS constituted group 2. Age and gender characteristics were found to be similar between two groups (Table 1). Average BMI value was 34.2 in group 1 and 42.2 in group 2 (p=0.001). Hypertension was the co-morbidity with the highest frequency observed in both groups (n=31, 48.4%) in which it was found to be 51% in group 1, and 40% in group 2 (Table 1).

Both groups had similar hemogram, biochemical parameters, thyroid functioning test scores and lipid profiles. When we compared the PFT parameters of both groups, average values for FEV1 in group 1 (2.6 L vs. 2.07 L, respectively, p=0.02) and FVC (3.1 L vs. 2.3 L, respectively, p=0.006) were found to be higher than group 2 on a statistically significant level. ESS average values for group 1 and group 2 were determined to be above ESS >10, which is accepted as a threshold value for daytime sleepiness (11.4 and 12.4, respectively, p>0.005).

When PSG findings were compared between the groups, in group 2, the percentage of time spent at O2 saturation under 90% (T90%) (33.7 min. vs. 120 min., respectively, p<0.001) was longer, minimum O2 saturation value (74.9% vs. 61.6%, respectively, p=0.012) was lower, and average O2 saturation value (90.3% vs. 87.1%, respectively, p=0.003) was lower (Table 2). No difference was detected between the groups in terms of REM latency and percentage, non-REM (NREM) percentage, AHI, total sleep time and sleep effectiveness (p>0.05) (Table 2).

After PAP titration, all patients displayed, on statistically significant levels, increased REM% (p<0.001), decreased NREM 1-2% (p<0.001), decreased T90% (p<0.001), increased minimum O2 saturation (from 71.8% to 85.5%, p<0.001) and average O2 saturation (from 89.6% to 94.1%, p<0.001), and decreased total AHI (p<0.001) (Table 3). Further, we detected a statistically significant increase in arterial blood gas partial oxygen pressure (PaO2) after PAP titration (from 70.6% to 78.4%, p<0.001) (Table 3).

No statistically significant difference was detected among the patients in terms of lactate levels before and after treatment [1.97 (±0.7) - 1.98 (±0.6)] (p>0.05) (Table 4). There was a negative correlation between BMI and lactate difference (Δlactate) across the entire group (r=-0.277 p=0.027). We found BMI-adjusted pre- and post-treatment lactate levels (lactate difference) of patients to be positively correlated with REM latency (r=0.37 p=0.03), positively correlated with sleep effectiveness (r=0.38, p=0.026), and negatively correlated with ESS score (r=-0.389, p=0.025). Changes in lactate levels and post-treatment AHI were inversely related on a statistically significant level (r=-0.5, p=0.003) (Table 5).

No statistically significant difference was detected between pre- (1.88±0.6) and post-treatment (1.98±0.6) lactate levels in the OSA patient group (group 1) (p>0.05). In the OSA patient group, we detected an inverse relationship between Δlactate and pre-treatment NREM 1-2% (r=-0.328, p=0.021), T90% (r=-0.356, p=0.012), and total AHI (r=-0.424, p=0.002). We found Δlactate to be positively correlated with pre-treatment average O2 saturation (r=0.396, p=0.005), and with minimum O2 saturation (r=0.361, p=0.011) in group 1. This patient group also displayed an inverse relation between post-treatment total AHI and Δlactate, which was statistically significant on a reasonable level (r=-0.320, p=0.0025). Again, we determined that the difference between pre- and post-treatment AHI (Δtotal AHI) and the lactate difference was positively correlated (r=0.394, p=0.005) (Table 6).

There was not any statistically significant difference between pre- (2.24±1.1) and post-treatment (1.98±0.6) lactate levels in patients diagnosed with OSA plus OHS (group 2) (p>0.05). This group displayed a statistically significant positive correlation between pre-treatment lactate levels and minimum pre-treatment O2 saturation, an inverse relationship between post-treatment lactate levels and post-treatment T90% (r=-0.539, p=0.038), and a statistically significant positive correlation between post-treatment lactate levels and average post-treatment O2 saturation (r=0.558, p=0.031). No statistically significant correlation was found between Δlactate and PSG parameters in this patient group (Table 7).

Discussion

This study revealed no significant difference between nocturnal lactate levels and lactate levels after PAP treatment in patients diagnosed with OSA and OHS. Besides, in the OSA patient group, we found a relationship between the lactate level difference and AHI, minimum and average O2 saturation and T90%, which are indicators of disease severity. We found a statistically significant correlation between AHI difference and lactate difference measured before and after PAP treatment.

In a previous study conducted in our clinic, morning lactate levels were significantly higher in the SRBD group than the No-SRBD group (1.65 +/- 0.48 and 1.35 +/- 0.57 mmol/L, respectively) (p=0.003) (30). After an adjustment for age, gender, and BMI, lactate levels before PSG were related to the apnea-hypopnea index (β: 0.004, 95% CI: 0.000-0.008) and percentage of time spent at O2 saturation under 90% (T90%). The following morning lactate level was correlated with the T 90% (β: 0.005, 95% CI: 0.000-0.010). After an adjustment for lactate levels before PSG, lactate in the morning was correlated with T90% (β: 0.004, 95% CI: 0.000-0.008). This study revealed no statistically significant difference between night lactate before PSG and morning lactate after PSG in the SRBD patient group (30). Another recent study considered uric acid and lactate levels as indicators of hypoxia, and as a result, suggested that lactate might prove to be a better parameter than uric acid since lactate values are higher in the morning (31). Our study supported these findings. We determined a relationship between lactate difference and indicators of disease severity. Further, the fact that morning lactate levels of patients receiving treatment displayed no increase in comparison to the night levels might be related with the effectiveness of PAP treatment.

Increased lactate production and reduced excretion might be associated with intermittent hypoxia and sleep disruptions, which are the two significant outcomes of OSA. Sleep disruptions result in reduced sleep quality and NREM 3 phase (32). Sleep disruptions reduce sleep quality, together with significant decreases in NREM 3 phase and distort the oxidative metabolism by causing abnormal secretion of hormones such as catecholamine and growth hormone (33,34). Sleep disruption indicator NREM 3 is shorter in patients with sleep-related respiratory disorders (SRDs) than in healthy individuals. As defined in the literature, the time spent in the REM sleep is significantly reduced in OSA and SRHHS (32). Since all striated muscles except the diaphragm are at rest during the REM sleep, lactate production is expected to fall. High lactate levels in patients with SRD might be associated with increased sympathetic activity, sleep disruptions and/or intermittent hypoxemia. PAP treatment increases oxygenation and thus ameliorates peripheral and myocardial oxygen supply. This reduces anaerobic stress in peripheral tissues, results in lactate clearance and decreases systemic stress response. Further, CPAP treatment reduces increased sympathetic activity in the morning and at night in patients with OSA (35). Cooper et al. (36) evaluated the effect of nasal continuous PAP treatment on venous lactate in six obese patients. Although lactate levels were not different after continuous PAP treatment as compared to baseline levels, higher baseline lactate/pyruvate ratios suggested glycolytic flux during a hypoxic night. There was no significant relationship between the severity of hypoxemia and the lactate/pyruvate ratio, which may be due to the small sample size of the study. Our study also revealed no change in lactate level after PAP treatment.

Vanuxem et al. (9) reported an association between night desaturation, AHI and lactate elimination during exercise in patients with OSA. However, in contrast to Vanuxem et al. (9) data, Bonanni et al. (37) did not find any relationship between AHI and blood lactate level, and refused the role of sympathetic activity in the increased lactate production in muscles of OSA patients. Bonanni et al. (37) suggested the primary defect in the muscle oxygen metabolism through adaptation to chronic nocturnal hypoxemia as an explanation for excessive lactate production. Another study found morning plasma lactate levels to be related with AHI and T90% in the patients with OSA (31). It is known that apnea, hypopnea and hypoventilation cause chronic intermittent hypoxemia, which was compensated by increasing the rate of breathing in SRD (38). The study conducted by Ucar et al. (30) determined both night and morning lactate levels to be correlated with AHI and T90% in the SRD group with respect to the control group. In the OSA patient group, we found a relationship between the arterial lactate level differences measured before and after PAP treatment and AHI, average O2 saturation, and T90%, which are indicators of disease severity. Again, we found a statistically significant correlation between AHI difference and lactate difference measured before and after PAP treatment. In patients with OSA accompanied by OHS, we determined similar lactate levels and post-treatment lactate difference.

Studies have demonstrated that OSA poses a risk for obesity, hypertension, CHD, and DM. The prevalence of OSA is 25% in the non-obese population, and 45% in the obese population, whereas prevalence of obesity is 70% among patients with OSA (39). Güven et al. (40) assumed obesity threshold to be BMI >29 kg/m2 in a series of 67 cases, and determined 69% obesity among the cases with mild OSA, and 77% obesity in those with medium and severe OSA. Ursavaş et al. (41) assumed BMI >26 kg/m2 and found obesity ratio to be 77%. In our study, BMI average was 34.2 kg/m2 for OSA, and 42.3 kg/m2 in OSA and inattention-hyperactivity score; and BMI average were higher than 30 kg/m2 in all patient groups. Further, BMI was higher on a statistically significant level in group 2 than the group 1.

It has been shown that obese individuals display high lactate levels, which are reduced by weight loss (42). Chen et al. (43) found lactate levels to be low in low-weight individuals, high in non-diabetic individuals, and high in both diabetic and obese individuals. Most lactate production is caused by fat tissue in obese individuals (44). Reduced blood flow in fat tissue causes local hypoxia and results in increased lactate production in obese individuals. Consequently, lactate production in the fat tissue increases as the fat tissue grows due to limited oxygen diffusion (45). Our study found a negative correlation between BMI and lactate difference in patients with OSA. This finding has been detected in the other group that might be due to the limited number of sample size. In addition, we found BMI to be higher on a statistically significant level in the OSA and OHS group in comparison to the OSA group, although no statistically significant difference was detected among all groups in terms of night and morning lactate levels. In this study, a relationship was demonstrated between Δlactate level and BMI, but multiple regression analysis was conducted to control the potential confounding effect of BMI.

This study is one of the first studies to investigate lactate changes after PAP treatment in the OSA and OHS patient groups. The small sample size and cross-sectional design were the main limitations of this study, making it difficult to interpret the findings. Along with this, arterial lactate level measurement in the post-titration morning was the result of a one-night monitoring and may not be sufficient for monitoring the effectiveness of the PAP treatment. Arterial lactate levels measured during follow-ups through long-term and regular PAP treatment may prove to be more valuable.

This study has demonstrated a relationship between lactate difference, which is an indicator of tissue hypoxia and therefore an indicator of prognosis, and severity indicators (AHI, average and minimum oxygen saturation and T90%) for OSA. These results suggest that PAP treatment may prevent possible lactate increase. Further and more comprehensive studies are required on this matter.

Conclusion

Lactate the end product of anaerobic carbohydrate metabolism has not been investigated in OSA for monitoring the effectiveness of treatment. This paper investigates the use of arterial blood lactate change after PAP treatment in patients with OSA and SRHHS. In this study there was no significant difference among the patients in terms of lactate levels before and after PAP treatment. There was a relation between lactate difference and AHI, average and minimum oxygen saturation and percentage of time spent at O2 saturation under 90% (T90%). These results suggest that PAP treatment may prevent possible lactate increase.

Ethics

Ethics Committee Approval: Dr. Suat Seren Chest Diseases and surgery Education and Training Hospital Ethics Committee No: 279 01.09.2010, Informed Consent: It was taken.

Peer-review: Internally peer-reviewed.

Authorship Contributions

Concept: Zeynep Zeren Uçar, Design: Reyhan Gümüşburun, Zeynep Zeren Uçar, Data Collection or Processing: Özlem Egemen Tüzel, Analysis or Interpretation: Fadıl Murat Gümüşburun, Yelda Varol, Hüseyin Halilçolar, Literature Search: Özlem Egemen Tüzel, Erdem Atalay Çetinkaya, Writing: Yelda Varol.

Conflict of Interest: No conflict of interest was declared by the authors.

Financial Disclosure: The authors declared that this study received no financial support.

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