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A retrospective study of the role of hypercapnia in patients with acromegaly

Abstract

Background

Acromegaly is a multisystemic disease characterized by an excessive release of growth hormone (GH) and insulin-like growth factor-1. Obstructive sleep apnea (OSA) is a common consequence of acromegaly, and hypercapnia is frequently observed in patients with acromegaly, OSA, and obesity. However, the effects of hypercapnia on acromegaly remain unknown. This study was designed to investigate whether there are differences in clinical symptoms, sleep variables, and biochemical remission after surgery for acromegaly in patients with OSA with or without hypercapnia.

Methods

A retrospective analysis was conducted involving patients with acromegaly and OSA. The pharmacotherapy history for acromegaly before surgery, anthropometric measures, blood gas, sleep monitoring data, and biochemical assays of hypercapnic and eucapnic individuals were collected 1–2 weeks before surgery. Univariate and multivariate logistic regression analyses were performed to determine the risk factors for failed postoperative biochemical remission.

Results

In this study, 94 patients with OSA and acromegaly were included. Among them, 25 (26.6%) had hypercapnia. The hypercapnic group had higher body mass index (92% vs. 62.3%; p = 0.005) and poorer nocturnal hypoxemia index. No serological differences were found between the two groups. According to the post-surgery GH level, 52 patients (55.3%) reached biochemical remission. Univariate logistic regression analysis revealed that diabetes mellitus (odds ratio [OR], 2.59; 95% confidence interval [CI], 1.02–6.55), instead of hypercapnia (OR, 0.61; 95% CI, 0.24–1.58), was associated with lower remission rates. Patients who received pharmacotherapy for acromegaly before surgery (OR, 0.21; 95% CI, 0.06–0.79) and had higher thyroid-stimulating hormone levels (OR, 0.53; 95% CI, 0.32–0.88) were more likely to have biochemical remission after surgery. Multivariate analysis further showed that only diabetes mellitus (OR, 3.29; 95% CI, 1.15–9.46) and preoperative pharmacotherapy (OR, 0.21; 95% CI, 0.06–0.83) remained significant. Hypercapnia, hormone levels, and sleep indicators had no effect on biochemical remission after surgery.

Conclusions

Single-center evidence shows that hypercapnia alone may not be a risk factor for lower biochemical remission rates. Correcting hypercapnia does not appear to be required before surgery. More evidence is needed to further support this conclusion.

Peer Review reports

Background

Acromegaly is a slow-progressing clinical illness that affects more than 13 individuals of 100 000 [1]. It is characterized by excessive secretion of growth hormone (GH) and insulin-like growth factor-1 (IGF-1), which is caused by a GH-secreting pituitary tumor in most cases and pituitary hyperplasia or ectopic GH or GH-releasing hormone secretion in rare cases. Apart from endocrine problems, active acromegaly could further lead to cardiovascular, pulmonary, and metabolic comorbidities [2].

The primary goals of treatment include symptom relief, tumor control, and reversal of the morbidity and mortality [3]. Transsphenoidal selective adenomectomy (TSA) is the first-line treatment with reported biochemical remission rates ranging from 30 to 85% [4]. Other medical treatments include somatostatin analogs (SSAs) and stereotactic radiosurgery. It is estimated that in the United States, compared with the general population, uncontrolled acromegaly resulted in $285,000 additional comorbidity-related costs, 0.9 fewer years of life, 4.2 fewer quality-adjusted life years, and 1.6 more comorbidities across the remaining lifespan [5]. The huge disease burden for patients with acromegaly makes long-term biochemical remission indispensable, which could drastically reduce the mortality risk of acromegaly to an equivalent level to that in the general population [6].

Obstructive sleep apnea (OSA) and respiratory insufficiency are the most frequent respiratory complications observed in patients with acromegaly because of anatomical changes, including the bone and soft tissues of the craniofacial region, respiratory mucosa/cartilages, lung volumes, and rib cage geometry [7]. Hypercapnia could be presented in acromegaly, particularly in overweight cases. The role of chronic hypercapnia has been well studied in chronic obstructive pulmonary disease (COPD) and acute respiratory failure, with controversial conclusions [8, 9]. Some studies highlighted the negative impact of hypercapnia on respiratory and metabolic diseases [10], whereas others claimed that it had no effect on mortality [11]. Although hypercapnia is a major laboratory finding in obesity hypoventilation syndrome (OHS), because of the exclusionary criteria [12], patients with OSA accompanied by acromegaly cannot be directly diagnosed with OHS. So far, little study has been conducted on the effect of hypercapnia in patients with OSA and acromegaly.

In this study, we conducted a retrospective study to evaluate whether there were differences in clinical symptoms, sleep variables, and biochemical remission after surgery in patients with acromegaly with or without hypercapnia. The influence of potential risk factors, such as hypercapnia, on biochemical remission was further assessed.

Methods

Study population

Patients admitted to the Neurosurgery Department of Peking Union Medical College Hospital (PUMCH) from 2013 to 2021 were enrolled in this study. The inclusion criteria were as follows: (1) patients diagnosed with active acromegaly according to the Endocrine Society Guidelines [13] (elevated IGF-1 levels and unsuppressed GH in the oral glucose tolerance test (OGTT)); (2) those who went through TSA during hospitalization; and (3) those who completed overnight sleep recording and arterial blood gas analysis before surgery. The exclusion criteria were as follows: (1) patients aged < 18 or > 70 years; (2) those who were pregnant or had severe diseases, such as kidney failure, liver failure, or cancer; (3) those with a history of surgery for acromegaly before sleep recording; (4) those receiving long-term domiciliary oxygen therapy or bi-level positive airway pressure use before admission; and (5) those with insufficient medical data. This study was conducted according to the Declaration of Helsinki and was approved by the Ethics Committee of PUMCH. Moreover, obtaining informed consent from the patients was unnecessary because no information regarding privacy was collected. A flowchart for the study population selection and enrollment is presented in Fig. 1.

Fig. 1
figure 1

Flow chart of the study population. PM, Portable monitoring; ABG, Atrial blood gas

Demographic characteristics and sleep recording

Data on the baseline demographic characteristics, including sex, age, weight, height, comorbidities including hypertension and diabetes, use of pharmacotherapy before surgery for acromegaly, disease duration, and current smoking status, were obtained and recorded. A full night portable sleep recording was performed using Embla X100 (Embla, UK) for at least 7 h. Signals, including nasal airflow, pulse oxygen saturation (SpO2), sleep positions, and thoracic and abdominal movements, were collected. An experienced sleep laboratory technician reviewed the recording data for analysis according to the criteria listed in the 2017 American Academy of Sleep Medicine [14]. The apnea hypopnea index (AHI) was defined as the average number of apnea and hypopnea events each hour. The diagnosis of OSA was made according to the third edition of the International Classification of Sleep Disorders [15]. OSA severity was classified as follows: mild OSA (15 events/h > AHI ≥ 5 events/h); moderate OSA (30 events/h > AHI ≥ 15 events/h); and severe OSA (AHI ≥ 30 events/h). Nocturnal hypoxemia metrics, such as the oxygen desaturation index (ODI), mean and lowest values of SpO2 (LSpO2), and the percentage of time spent at SpO2 < 90% in total sleep time (T90) during sleep, were also collected.

Biological measurements

Laboratory tests for acromegaly were performed 1–2 weeks before surgery and were recorded in the electronic medical recording system. Blood routine examination, arterial blood gas, serum lipid, uric acid (UA), fasting blood glucose (FBG), random GH, IGF-1, total cortisol, prolactin, and thyroid function parameters were retrospectively collected. The nadir and random GH within 1 week after surgery were also collected. Arterial blood was drawn when the patients were in the sitting position and breathed room air. An arterial blood gas analyzer (ABL800, Radiometer, Copenhagen, Denmark) was used to analyze the potential of hydrogen, partial pressure of oxygen (PaO2), carbon dioxide (PaCO2), and bicarbonate. The criterion for postoperative biochemical remission was defined as a random or nadir GH after OGTT < 1 ug/L [16]. Patients with hypercapnia were defined as PaCO2 ≥ 45 mmHg, while the rest were considered eucapnic controls. Body mass index (BMI) was calculated as weight (kg) divided by height squared (m2); BMI > 25 kg/m2 was defined as obesity [17]. The disease duration was calculated as the occurrence of symptoms related to acromegaly to the date of surgery.

Statistical analysis

All data were analyzed using Statistical Package for the Social Sciences (version 24.0, IBM Corp., Armonk, NY, USA). The normality of the variables was tested using the Kolmogorov–Smirnov test. Categorical variables are described as numbers with percentages. Continuous variables are expressed as means ± standard deviations or medians with interquartile ranges (25%–75%) depending on whether the data were normally distributed. Comparisons between groups were analyzed using the chi-square test, Fisher’s exact test, and unpaired, two-tailed t-test. The non-parametric Mann–Whitney U-test was used when the data were not normally distributed. Logistic regression analysis was used to determine the risk factors for failed postoperative biochemical remission. Covariates with p-values < 0.1 after the univariate analysis or supposed to be clinically significant will be reexamined by multivariate analysis. Two-sided p-values of less than 0.05 were used to indicate statistical significance.

Results

Baseline characters

In this study, 94 patients who fulfilled the inclusion criteria were recruited. The prevalence of hypercapnia was 26.6% (25/94) in the study population. Table 1 shows the basic demographic characteristics and sleep parameters between eucapnic and hypercapnic patients with acromegaly. The hypercapnic group had more patients with obesity (BMI > 25 kg/m2) than the eucapnic group (92% vs. 62.3%; p = 0.005). No significant differences in age, sex, BMI, and smoking status were observed between the two groups. 17 patients received pharmacotherapy before surgery. The disease duration and use of pharmacotherapy for acromegaly before surgery were not significantly different. As for the sleep recordings, although no significant difference in the AHI was found, the hypercapnic group had a higher proportion of patients with severe OSA (52% vs. 27.5%; p = 0.027). Moreover, patients with hypercapnia showed worse nocturnal hypoxemia variables, including the ODI (29.4% vs. 14.4%; p = 0.035), LSpO2 (79% vs. 85%; p = 0.013), and T90 (1.9% vs. 0.4%; p = 0.012).

Table 1 Basic demographic and sleep parameters of the patients with acromegaly

Laboratory tests

Table 2 shows the laboratory findings during the perioperative period between the two groups. Among the patients included in this study, 52 (55.3%) reached postoperative biochemical remission. We found no differences in the metabolic profiles, such as FBG, UA, total cholesterol, triglyceride, and lipoproteins. Hormone levels, such as thyroid function parameters, total cortisol, and prolactin, were maintained. No statistically significant differences in disease condition, such as preoperative random fasting GH and IGF-1 levels, and the proportion of postoperative nadir GH in the OGTT > 1 were observed.

Table 2 Laboratory findings of the patients with acromegaly

Potential risk factors for low biochemical remission

We further performed univariate and multivariate logistic regression analyses to explore the potential factors for unsuccessful postoperative biochemical remission. Demographic characteristics, pharmacotherapy for acromegaly, sleep indicators, and biological measurements along with hypercapnia were examined. The results are demonstrated in Table 3. In the univariate analysis, medical history of diabetes mellitus (odds ratio [OR], 2.59; 95% confidence interval [CI], 1.02–6.55), instead of hypercapnia (OR, 0.61; 95% CI, 0.24–1.58), statistically increased the likelihood of procedure failure. In contrast, the preoperative use of pharmacotherapy for acromegaly (OR, 0.21; 95% CI, 0.06–0.79) and higher thyroid-stimulating hormone levels (OR, 0.53; 95% CI, 0.32–0.88) were associated with a higher probability of achieving postoperative biochemical remission. In the multivariate analysis, the prognostic value of diabetes and medical therapy remained significant (OR, 3.29 and 0.21; 95% CI, 1.15–9.46 and 0.06–0.83, respectively). However, hypercapnia, as well as hormone levels and sleep indicators, could not significantly influence postoperative biochemical remission.

Table 3 Logistic regression analysis of factors associated with postoperative biochemical remission in patients with acromegaly

Discussion

In this study, we compared the effects of hypercapnia with those of eucapnia on patients with OSA and acromegaly. The hypercapnic group had higher BMI and poorer nocturnal hypoxemia parameters than the eucapnic group. A further logistic regression analysis found that diabetes, instead of hypercapnia, was a risk factor for a lower probability of achieving postoperative biochemical remission, whereas preoperative medical treatment was associated with long-term biochemical remission. The result remained significant in the multivariate analysis.

Chronic daytime hypercapnia is caused by decreased minute ventilation/global hypoventilation, increased dead space, or increased carbon dioxide (CO2) production. Diseases related to the nervous system, respiratory muscles, and upper airway or lungs can contribute to hypercapnia. Respiratory acidosis has controversial clinical effects attributed to the overproduction of hydrogen ions (H+). While it could lead to the favorable effects, such as improvement in gas exchange and protection of ventricular function, excessive H+ could reduce diaphragmatic contractility, which is the main damage to the respiratory system [18, 19]. Cardiovascular instability, hypotension, and decline in neurocognitive function are other end-organ side effects [20, 21].

Hypercapnia could result from acromegalic complications, such as OSA and obesity. However, studies examining the mechanism and influence of hypercapnia on acromegaly are scarce. Several studies focused on the effects of chronic metabolic acidosis on the GH/IGF-1 endocrine axis. This situation could be reflected by growth retardation in children suffering from chronic acidosis and reduced bone mass in adults. Animal experiments have found that the expression of GH and IGF-1 receptors is suppressed under acidic conditions at both the mRNA and protein levels, whereas the expression of IGF-binding proteins 2 and 4 is enhanced, which could inhibit IGF-1 activity [22, 23]. Human trials revealed that chronic metabolic acidosis reduces the serum concentration of IGF-1 and is associated with a resistance to the hepatocellular action of GH [24]. These studies showed the interference of acidosis with the GH/IGF-1 endocrine axis. The same acidic condition induced by hypercapnia may have similar results, and thus, it may affect some aspects of acromegaly, including biochemical remission.

Our results showed that the hypercapnic group had a higher proportion of obesity and worse nocturnal hypoxemia indicators than the eucapnic group. The possible explanations to these are listed as follows: (1) hypercapnia could be an indicator of OSA severity. Kaw et al. compared hypercapnic and eucapnic patients with OSA and concluded that daytime hypercapnia was associated with the severity of OSA, higher BMI levels, and degree of restrictive chest wall mechanics [25]. Furthermore, it has been proven that daytime hypercapnia and nocturnal hypoxia are independent predictors of CPAP failure in patients with OSA and COPD [26]. (2) As previously stated, continuous hypercapnia reduces diaphragmatic contractility. In OSA, this effect could be exacerbated by nocturnal hypercapnia. Severe acidosis may reduce the central respiratory drive, resulting in a depressed level of consciousness (known as CO2 narcosis) and hypoxemia. (3) Apart from OSA, hypercapnia could be observed in OHS and COPD. OHS is characterized by high BMI, hypercapnia, and hypoxemia [27]. COPD and OSA could be presented together, which is known as the overlap syndrome [28]. Because of the lack of pulmonary function data, the validation of these complications is limited.

There seemed to be little difference in the metabolic and hormonal profiles between the two groups. The negative results may be due to the following reasons: (1) the overall severity of PaCO2 was mild to moderate in our clinical samples. The average pH level in the aforementioned human trials reached 7.31, while the pH of our samples was 7.39 ± 0.03. Mild acidosis may have little impact on the GH/IGF-1 endocrine axis. (2) The blood gas analysis was performed a week within the procedure. Only the hypercapnia status rather than its duration could be confirmed. Most pieces of previous evidence were based on the long-term effects of metabolic acidosis. The exact degree and duration of hypercapnia that significantly change the secretion of GH/IGF-1 are unknown. A prospective study involving more severe cases with definite hypercapnia duration is needed for the comprehensive assessment.

To achieve biochemical remission, identifying patients who might benefit from primary medical therapy or require multimodality treatment besides surgery is necessary. Numerous studies have been conducted to determine proper prognostic factors for biochemical remission. Most studies focused on the demographic characteristics and preoperative biochemical and imaging parameters. Though the criterion for postoperative biochemical remission has changed over these years [3, 16], a general consensus of predictors has been reached, which includes cavernous sinus invasion (CSI) by imaging [29,30,31,32], larger tumor size [33,34,35], and higher GH levels [36,37,38]. Other promising predictive markers include younger age [37, 39], female [30], higher IGF-1 [32, 36], and Knosp grades [34, 39, 40]. A multivariate logistic regression model [31] has been developed based on these parameters. The area under the receiver operating characteristic curve (AUC) is 0.933, whereas the AUC of the model that consists of tumor diameter and CSI only is 0.800 (p = 0.02).

Other than reviewing the conclusions of previous studies, our primary goal was to determine whether hypercapnia could be a risk factor for a lower probability of achieving biochemical remission. The results showed that hypercapnia could not significantly influence the postoperative biochemical remission rate. A few details may explain this: (1) acromegaly is a multisystem disorder and hypercapnia alone might exert bilateral influence on endocrine secretion as mentioned in the mechanism above. (2) The severity and duration of hypercapnia may play a more important role in the course of the disease. The negative result may be because of the selection bias of mild hypercapnia in our participants. (3) The small number of participants in this study may not be fully representative of the real situation.

Despite the negative finding, the results suggested that patients with a medical history of diabetes and the use of pharmacotherapy before surgery should have prognostic values. Diabetes and insulin resistance (IR) are responsible for several side effects in patients with acromegaly. Improving insulin sensitivity is a major goal of treatment. Several studies have confirmed that TSA can normalize GH-induced glycol-metabolism disorder and insulin sensitivity [41]. Diabetes could be viewed as a result of GH overproduction, which is a proven marker of biochemical remission. The coexistence of diabetes could alter GH and IGF-1 levels and influence the OGTT result and the clinical judgment of biochemical remission [42]. Furthermore, our previous study has proven that IR is a significant risk factor for cardiovascular disease in patients with acromegaly and OSA [43]. Controlling hyperglycemia throughout the entire course of acromegaly seems plausible.

The use of SSA before surgery could improve the biochemical remission rate, which was proven by our study result. Although the Endocrine Society clinical practice guidelines in 2014 recommended against the routine use of preoperative SSA therapy to improve biochemical control after surgery [13], some studies reported higher surgical control rates with the pretreatment of SSA [44, 45]. Previous data from our center also revealed that prolonged preoperative treatment of acromegaly with SSA (> 6 months) may improve surgical outcomes in patients with invasive pituitary macroadenoma [46]. The use of SSA could alleviate acromegaly symptoms, induce clinically relevant tumor shrinkage, and lower surgical risk by decreasing arterial stiffness; reducing soft tissue swelling, particularly in the upper airways; and inducing better blood pressure control [47]. Despite all these potential advantages, there is still limited data concerning perioperative morbidity and postoperative biochemical outcomes. Currently, the preoperative use of SSA is recommended only in patients with severe cardiac and respiratory complications. More investigation and investment in large randomized long-term clinical trials are needed to define the precise role and duration of preoperative SSA in patients with acromegaly.

It is worth noting that although metrics related to OSA were not significantly associated with the risk of biochemical remission failure, there were protective trends toward significance in some variables, including LSpO2 (OR, 1.04; 95% CI, 0.99–1.09; p = 0.088), T90 (OR, 0.97; 95% CI, 0.93–1.00; p = 0.059), and AHI > 30/h (OR, 0.43; 95% CI, 0.17–1.05; p = 0.063) in the univariate analysis. So far, few studies have focused on the influence of the coexistence and severity of OSA on postoperative biochemical remission in patients with acromegaly. It is plausible that OSA, characterized by intermittent hypoxemia and sleep fragmentation, may bring worse outcomes to acromegaly similar to other metabolic complications [48]. However, our results showed the potential protective role of OSA. Because of the relatively small study sample, more participants are needed to further corroborate the significance of the results of this study.

This study has several limitations. First, considering the small sample size and the retrospective nature of this single-center study, the strength of this study is limited. Second, the diagnosis of OSA was based on the result of a portable overnight sleep recording, which contains less information compared to polysomnography and due to this, the severity of OSA might be underestimated. Third, pulmonary function was not evaluated in this study, making it difficult to distinguish the reason for hypercapnia. As mentioned above, patients with chronic respiratory diseases like COPD and OHS often present with hypercapnia. Heterogeneities in the hypercapnic group might be overlooked. Fourth, because of the short-term follow-up of this study, the likelihood of biochemical remission might be misestimated. A large sample size with a randomized study design and long-term follow-up is needed. Different conditions including OHS, COPD or other comorbidities should also be examined. A complete and standard evaluation procedure including polysomnography, pituitary magnetic resonance imaging and blood gas analysis across perioperative period and follow-up should be performed in the future. However, despite these shortcomings, to the best of our knowledge, this is the first study that examined the role of hypercapnia in the clinical symptoms, disease severity, and prognostic value of acromegaly in patients with OSA.

Conclusions

Patients with acromegaly and hypercapnia are characterized by higher BMI and worse sleep indicators. Diabetes mellitus, instead of hypercapnia, might be a predictor of low probability of achieving postoperative biochemical remission, whereas the preoperative use of SSA therapy may improve the biochemical remission rate. Correcting hypercapnia before surgery seems unnecessary. More attention should be paid to the management of the cause of hypercapnia. Studies are needed to further support the conclusion and determine the potential role of OSA in biochemical remission.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

AHI:

Apnea hypopnea index

AUC:

Receiver operating characteristic curve

BMI:

Body mass index

CI:

Confidence interval

CO2 :

Carbon dioxide

COPD:

Chronic obstructive pulmonary disease

CSI:

Cavernous sinus invasion

FBG:

Fasting blood glucose

GH:

Growth hormone

IGF-1:

Insulin-like growth factor-1

IR:

Insulin resistance

LSpO2 :

Mean and lowest values of SpO2

ODI:

Oxygen desaturation index

OGTT:

Oral glucose tolerance test

OHS:

Obesity hypoventilation syndrome

OR:

Odds ratio

OSA:

Obstructive sleep apnea

SpO2 :

Pulse oxygen saturation

SSAs:

Somatostatin analogs

T90:

Percentage of time spent at SpO2 < 90% in total sleep time

TSA:

Transsphenoidal selective adenomectomy

TSH:

Thyroid stimulating hormone

UA:

Uric acid

References

  1. Colao A, Grasso L, Giustina A, et al. Acromegaly. Nat Rev Dis Primers. 2019;5(1):20. https://doi.org/10.1038/s41572-019-0071-6.

    Article  PubMed  Google Scholar 

  2. Wolters T, Netea MG, Riksen NP, et al. Acromegaly, inflammation and cardiovascular disease: a review. Rev Endocr Metab Disord. 2020;21(4):547–68. https://doi.org/10.1007/s11154-020-09560-x.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Melmed S, Bronstein MD, Chanson P, et al. A consensus statement on acromegaly therapeutic outcomes. Nat Rev Endocrinol. 2018;14(9):552–61. https://doi.org/10.1038/s41574-018-0058-5.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Sarkar S, Chacko AG. Surgery for acromegaly. Neurol India. 2020;68(Supplement):S44-51. https://doi.org/10.4103/0028-3886.287664.

    Article  PubMed  Google Scholar 

  5. Whittington MD, Munoz KA, Whalen JD, Ribeiro-Oliveira A, Campbell JD. Economic and clinical burden of comorbidities among patients with acromegaly. Growth Horm IGF Res. 2021;59:101389. https://doi.org/10.1016/j.ghir.2021.101389.

    Article  PubMed  Google Scholar 

  6. Maione L, Brue T, Beckers A, et al. Changes in the management and comorbidities of acromegaly over three decades: the French acromegaly registry. Eur J Endocrinol. 2017;176(5):645–55. https://doi.org/10.1530/EJE-16-1064.

    Article  CAS  PubMed  Google Scholar 

  7. Giustina A, Barkan A, Beckers A, et al. A consensus on the diagnosis and treatment of acromegaly comorbidities: an update. J Clin Endocrinol Metab. 2020;105(4):dgz096. https://doi.org/10.1210/clinem/dgz096.

    Article  PubMed  Google Scholar 

  8. Raveling T, Bladder G, Vonk J, et al. Improvement in hypercapnia does not predict survival in COPD patients on chronic noninvasive ventilation. Int J Chron Obstruct Pulmon Dis. 2018;13:3625–34. https://doi.org/10.2147/COPD.S169951.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Zhou D, Ye Y, Kong Y, et al. The effect of mild hypercapnia on hospital mortality after cardiac arrest may be modified by chronic obstructive pulmonary disease. Am J Emerg Med. 2021;44:78–84. https://doi.org/10.1016/j.ajem.2021.01.093.

    Article  PubMed  Google Scholar 

  10. Lecuona E, Sun H, Chen J, et al. Protein kinase A-Iα regulates Na, K-ATPase endocytosis in alveolar epithelial cells exposed to high CO(2) concentrations. Am J Respir Cell Mol Biol. 2013;48(5):626–34. https://doi.org/10.1165/rcmb.2012-0373OC.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Peltekova V, Engelberts D, Otulakowski G, et al. Hypercapnic acidosis in ventilator-induced lung injury. Intensive Care Med. 2010;36(5):869–78. https://doi.org/10.1007/s00134-010-1787-7.

    Article  PubMed  Google Scholar 

  12. Mokhlesi B, Masa JF, Brozek JL, et al. Evaluation and management of obesity hypoventilation syndrome. An official American Thoracic Society clinical practice guideline. Am J Respir Crit Care Med. 2019;200(3):e6–24. https://doi.org/10.1164/rccm.201905-1071ST.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Katznelson L, Laws EJ, Melmed S, et al. Acromegaly: an endocrine society clinical practice guideline. J Clin Endocrinol Metab. 2014;99(11):3933–51. https://doi.org/10.1210/jc.2014-2700.

    Article  CAS  PubMed  Google Scholar 

  14. Kapur VK, Auckley DH, Chowdhuri S, et al. Clinical practice guideline for diagnostic testing for adult obstructive sleep apnea: an American Academy of Sleep Medicine clinical practice guideline. J Clin Sleep Med. 2017;13(3):479–504. https://doi.org/10.5664/jcsm.6506.

    Article  PubMed  PubMed Central  Google Scholar 

  15. American Academy of Sleep Medicine. International classification of sleep disorders, 3rd ed. Darien: American Academy of Sleep Medicine; 2014.

  16. Giustina A, Chanson P, Bronstein MD, et al. A consensus on criteria for cure of acromegaly. J Clin Endocrinol Metab. 2010;95(7):3141–8. https://doi.org/10.1210/jc.2009-2670.

    Article  CAS  PubMed  Google Scholar 

  17. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157–63. https://doi.org/10.1016/S0140-6736(03)15268-3.

    Article  Google Scholar 

  18. Morales-Quinteros L, Camprubí-Rimblas M, Bringué J, et al. The role of hypercapnia in acute respiratory failure. Intensive Care Med Exp. 2019;7(S1):39. https://doi.org/10.1186/s40635-019-0239-0.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Jonville S, Delpech N, Denjean A. Contribution of respiratory acidosis to diaphragmatic fatigue at exercise. Eur Respir J. 2002;19(6):1079–86. https://doi.org/10.1183/09031936.02.00268202.

    Article  CAS  PubMed  Google Scholar 

  20. Xue J, Allaband C, Zhou D, et al. Influence of intermittent hypoxia/hypercapnia on atherosclerosis, gut microbiome, and metabolome. Front Physiol. 2021;12:663950. https://doi.org/10.3389/fphys.2021.663950.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Kung S, Shen Y, Chang E, Hong Y, Wang L. Hypercapnia impaired cognitive and memory functions in obese patients with obstructive sleep apnoea. Sci Rep. 2018;8(1):17551. https://doi.org/10.1038/s41598-018-35797-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Green J, Maor G. Effect of metabolic acidosis on the growth hormone/IGF-I endocrine axis in skeletal growth centers. Kidney Int. 2000;57(6):2258–67. https://doi.org/10.1046/j.1523-1755.2000.00086.x.

    Article  CAS  PubMed  Google Scholar 

  23. Challa A, Krieg RJ, Thabet MA, Veldhuis JD, Chan JC. Metabolic acidosis inhibits growth hormone secretion in rats: mechanism of growth retardation. Am J Physiol. 1993;265(4 Pt 1):E547–53. https://doi.org/10.1152/ajpendo.1993.265.4.E547.

    Article  CAS  PubMed  Google Scholar 

  24. Brungger M, Hulter HN, Krapf R. Effect of chronic metabolic acidosis on the growth hormone/IGF-1 endocrine axis: new cause of growth hormone insensitivity in humans. Kidney Int. 1997;51(1):216–21. https://doi.org/10.1038/ki.1997.26.

    Article  CAS  PubMed  Google Scholar 

  25. Kaw R, Hernandez AV, Walker E, Aboussouan L, Mokhlesi B. Determinants of hypercapnia in obese patients with obstructive sleep apnea: a systematic review and metaanalysis of cohort studies. Chest. 2009;136(3):787–96. https://doi.org/10.1378/chest.09-0615.

    Article  PubMed  Google Scholar 

  26. Kuklisova Z, Tkacova R, Joppa P, Wouters E, Sastry M. Severity of nocturnal hypoxia and daytime hypercapnia predicts CPAP failure in patients with COPD and obstructive sleep apnea overlap syndrome. Sleep Med. 2017;30:139–45. https://doi.org/10.1016/j.sleep.2016.02.012.

    Article  PubMed  Google Scholar 

  27. Masa JF, Pépin JL, Borel JC, et al. Obesity hypoventilation syndrome. Eur Respir Rev. 2019;28(151). https://doi.org/10.1183/16000617.0097-2018.

  28. McNicholas WT. COPD-OSA overlap syndrome: evolving evidence regarding epidemiology, clinical consequences, and management. Chest. 2017;152(6):1318–26. https://doi.org/10.1016/j.chest.2017.04.160.

    Article  PubMed  Google Scholar 

  29. Kim JH, Hur KY, Lee JH, et al. Outcome of endoscopic transsphenoidal surgery for acromegaly. World Neurosurg. 2017;104:272–8. https://doi.org/10.1016/j.wneu.2017.04.141.

    Article  PubMed  Google Scholar 

  30. Park SH, Ku CR, Moon JH, et al. Age- and sex-specific differences as predictors of surgical remission among patients with acromegaly. J Clin Endocrinol Metab. 2018;103(3):909–16. https://doi.org/10.1210/jc.2017-01844.

    Article  PubMed  Google Scholar 

  31. Anthony JR, Alwahab UA, Kanakiya NK, et al. Significant elevation of growth hormone level impacts surgical outcomes in acromegaly. Endocr Pract. 2015;21(9):1001–9. https://doi.org/10.4158/EP14587.OR.

    Article  PubMed  Google Scholar 

  32. Sun H, Brzana J, Yedinak CG, et al. Factors associated with biochemical remission after microscopic transsphenoidal surgery for acromegaly. J Neurol Surg B Skull Base. 2014;75(1):47–52. https://doi.org/10.1055/s-0033-1354578.

    Article  PubMed  Google Scholar 

  33. Albarel F, Castinetti F, Morange I, et al. Outcome of multimodal therapy in operated acromegalic patients, a study in 115 patients. Clin Endocrinol (Oxf). 2013;78(2):263–70. https://doi.org/10.1111/j.1365-2265.2012.04492.x.

    Article  CAS  PubMed  Google Scholar 

  34. Shirvani M, Motiei-Langroudi R. Transsphenoidal surgery for growth hormone-secreting pituitary adenomas in 130 patients. World Neurosurg. 2014;81(1):125–30. https://doi.org/10.1016/j.wneu.2013.01.021.

    Article  PubMed  Google Scholar 

  35. Almeida JP, Ruiz-Treviño AS, Liang B, et al. Reoperation for growth hormone-secreting pituitary adenomas: report on an endonasal endoscopic series with a systematic review and meta-analysis of the literature. J Neurosurg. 2018;129(2):404–16. https://doi.org/10.3171/2017.2.JNS162673.

    Article  PubMed  Google Scholar 

  36. Sala E, Ferrante E, Locatelli M, et al. Diagnostic features and outcome of surgical therapy of acromegalic patients: experience of the last three decades. Hormones (Athens). 2014;13(1):95–103. https://doi.org/10.1007/BF03401325.

    Article  PubMed  Google Scholar 

  37. Haliloglu O, Kuruoglu E, Ozkaya HM, et al. Multidisciplinary approach for acromegaly: a single tertiary center’s experience. World Neurosurg. 2016;88:270–6. https://doi.org/10.1016/j.wneu.2015.12.092.

    Article  PubMed  Google Scholar 

  38. Wang Q, Guo X, Gao L, et al. Surgical outcome of growth hormone-secreting pituitary adenoma with empty sella using a new classification. World Neurosurg. 2017;105:651–8. https://doi.org/10.1016/j.wneu.2017.06.071.

    Article  PubMed  Google Scholar 

  39. Taghvaei M, Sadrehosseini SM, Ardakani JB, Nakhjavani M, Zeinalizadeh M. Endoscopic endonasal approach to the growth hormone-secreting pituitary adenomas: endocrinologic outcome in 68 patients. World Neurosurg. 2018;117:e259–68. https://doi.org/10.1016/j.wneu.2018.06.009.

    Article  PubMed  Google Scholar 

  40. Asha MJ, Takami H, Velasquez C, et al. Long-term outcomes of transsphenoidal surgery for management of growth hormone-secreting adenomas: single-center results. J Neurosurg. 2019;11:1–11. https://doi.org/10.3171/2019.6.JNS191187.

    Article  Google Scholar 

  41. Reyes-Vidal C, Fernandez JC, Bruce JN, et al. Prospective study of surgical treatment of acromegaly: effects on ghrelin, weight, adiposity, and markers of CV risk. J Clin Endocrinol Metab. 2014;99(11):4124–32. https://doi.org/10.1210/jc.2014-2259.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Freda PU. Monitoring of acromegaly: what should be performed when GH and IGF-1 levels are discrepant? Clin Endocrinol (Oxf). 2009;71(2):166–70. https://doi.org/10.1111/j.1365-2265.2009.03556.x.

    Article  CAS  PubMed  Google Scholar 

  43. Cao W, Wang X, Luo J, Huang R, Xiao Y. Impact of obstructive sleep apnea on cardiovascular risk in patients with acromegaly. Sleep Med. 2021;80:193–8. https://doi.org/10.1016/j.sleep.2021.01.033.

    Article  PubMed  Google Scholar 

  44. Pita-Gutierrez F, Pertega-Diaz S, Pita-Fernandez S, et al. Place of preoperative treatment of acromegaly with somatostatin analog on surgical outcome: a systematic review and meta-analysis. Plos One. 2013;8(4):e61523. https://doi.org/10.1371/journal.pone.0061523.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Nunes VS, Correa JMS, Puga MES, Silva EMK, Boguszewski CL. Preoperative somatostatin analogues versus direct transsphenoidal surgery for newly-diagnosed acromegaly patients: a systematic review and meta-analysis using the GRADE system. Pituitary. 2015;18(4):500–8. https://doi.org/10.1007/s11102-014-0602-9.

    Article  CAS  PubMed  Google Scholar 

  46. Duan L, Zhu H, Xing B, Gu F. Prolonged preoperative treatment of acromegaly with somatostatin analogs may improve surgical outcome in patients with invasive pituitary macroadenoma (Knosp grades 1–3): a retrospective cohort study conducted at a single center. Bmc Endocr Disord. 2017;17(1):55. https://doi.org/10.1186/s12902-017-0205-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Giustina A, Mazziotti G, Torri V, et al. Meta-analysis on the effects of octreotide on tumor mass in acromegaly. Plos One. 2012;7(5):e36411. https://doi.org/10.1371/journal.pone.0036411.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Framnes SN, Arble DM. The bidirectional relationship between obstructive sleep apnea and metabolic disease. Front Endocrinol (Lausanne). 2018;9:440. https://doi.org/10.3389/fendo.2018.00440.

    Article  PubMed  Google Scholar 

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Acknowledgements

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Funding

This study has been funded by the National Key Research and Development Projects of China (No. 2013BAI09B10).

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JG collected data and was the major contributor in writing the manuscript. WC and JL analyzed and interpreted the patient data. RH and YX designed the study and revised the manuscript. All authors read and approved the final manuscript.

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Correspondence to Yi Xiao.

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Guo, J., Cao, W., Luo, J. et al. A retrospective study of the role of hypercapnia in patients with acromegaly. BMC Pulm Med 23, 186 (2023). https://doi.org/10.1186/s12890-023-02488-3

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