# Enhanced pain sensitivity in obese patients with obstructive sleep apnoea syndrome is partially reverted by treatment: An exploratory study

Clément Lahaye, Magalie Miolanne, Nicolas Farigon, Bruno Pereira, Claude Dubray, Patricia Beudin, Annick Greil, Yves Boirie

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Clément Lahaye, Magalie Miolanne, Nicolas Farigon, Bruno Pereira, Claude Dubray, et al.. Enhanced pain sensitivity in obese patients with obstructive sleep apnoea syndrome is partially reverted by treatment: An exploratory study. European Journal of Pain, 2023, 27 (5), pp.624-635. 10.1002/ejp.2085. hal-04227168

HAL Id: hal-04227168

https://hal.inrae.fr/hal-04227168

Submitted on 3 Oct 2023

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

ORIGINAL ARTICLE

<figure><img src="image_4.png" /></figure>

# Enhanced pain sensitivity in obese patients with obstructive sleep apnoea syndrome is partially reverted by treatment: An exploratory study

Clément Lahaye<fnref n="1" />,<fnref n="2" /> | Claude Dubray<fnref n="5" />

Magalie Miolanne<fnref n="3" /> | Patricia Beudin<fnref n="6" />

Nicolas Farigon<fnref n="3" /> | Annick Greil<fnref n="7" />

Bruno Pereira<fnref n="4" /> | Yves Boirie<fnref n="2" />,<fnref n="3" />

**Correspondence**

Clément Lahaye, Department of
Clinical Nutrition, Hôpital Gabriel
Montpied, CHU Clermont-Ferrand, 58
Rue Montalembert, F-63003 Clermont-
Ferrand, France.

Email: lahaye.clement@orange.fr

**Abstract**

**Background:** Obesity is frequently associated with obstructive sleep apnoea syndrome (OSA) and chronic pain. OSA as well as continuous positive airway pressure (CPAP) treatment may modulate the pain perception threshold (PT) in patients with obesity.

**Methods:** In this prospective, longitudinal study, all patients admitted for obesity assessment were screened for OSA by nocturnal polygraphy (SOMNOcheck®, IAH ≥10) and performed mechanical (Von Frey electronic device) and electrical (PainMatcher®) pain tests. Those with severe OSA were retested for PT 1 month after initiation of CPAP therapy. Newly diagnosed patients with severe OSA (hypopnoea apnoea index >30) have been offered to start CPAP treatment.

**Results:** Among 85 patients, there were 27 OSA patients, aged between 40±13.2 years with a BMI of 42±7.2 kg/m<fnref n="2" />. Severe OSA patients (N = 11) showed a lower PT than non-OSA patients (N = 58) during mechanical (177±120 vs. 328±136 g, *p* < 0.01) and electrical methods (7.4±6.4 vs. 12.9±6.7 stimulation duration steps; *p* = 0.03). In the severe OSA group (N = 7), an increased PT was observed 1 month after CPAP treatment during mechanical pain testing (298±69 vs. 259±68 g, *p* < 0.05), but not during electrical pain testing (11.5±3.0 vs. 12.4±3.8 stimulation duration steps, *p* = 0.50).

**Conclusion:** In patients with obesity, this exploratory study showed that the presence of an OSA is associated with a decreased PT, whereas implantation of a CPAP device tends to normalize pain perception.

**Significance:** Severe obstructive sleep apnoea syndrome in patients with obesity is accompanied by a lower pain perception threshold. In these patients, continuous positive airway pressure therapy may help prevent or reduce chronic pain.

1 | INTRODUCTION

Obesity affects over 650 million people worldwide (World Health Organization) and is associated with a higher incidence of chronic pain compared to the population with a

normal body mass index (BMI; Stone and Broderick, 2012). Mechanical weight constraints (Zheng and Chen, 2015), combined with a fragile psychological context in patients with obesity, make the management of these pains particularly difficult.

<footnote n="1">¹Service de gériatrie, CHU Clermont-Ferrand, Clermont-Ferrand, France</footnote>

<footnote n="2">²INRAE, Unité de Nutrition Humaine, CRNH Auvergne, Université Clermont Auvergne, Clermont-Ferrand, France</footnote>

<footnote n="3">³Service de nutrition clinique, CSO CALORIS, CHU Clermont-Ferrand, Clermont-Ferrand, France</footnote>

<footnote n="4">⁴Délégation Recherche Clinique et Innovation, CHU Clermont-Ferrand, Clermont-Ferrand, France</footnote>

<footnote n="5">⁵Centre de Pharmacologie Clinique, INSERM CIC 501, CHU Clermont-Ferrand, Clermont-Ferrand, France</footnote>

<footnote n="6">⁶Service d'exploration fonctionnelle du système nerveux, CHU Clermont-Ferrand, Clermont-Ferrand, France</footnote>

<footnote n="7">⁷Service de pneumologie, CHU Clermont-Ferrand, Clermont-Ferrand, France</footnote>
Many observational and interventional studies have established a link between sleep disorders or sleep deprivation and pain perception thresholds (PT; Finan et al., 2013, Herrero Babiloni et al., 2020). In healthy volunteers, it has been shown that deep slow sleep rebound following sleep deprivation is responsible for a significant increase in mechanical pain thresholds (Onen et al., 2001). Obstructive sleep apnoea syndrome (OSA), defined as at least 10 apnoea and hypopnoea events per hour of sleep (apnoea-hypopnoea index or AHI ≥10) (International Classification of Sleep Disorders, 1990), induces major disturbances in stages and cycles of sleep. In obesity, fatty infiltration of the tongue and parapharyngeal spaces increases the risk of airway collapsibility (Lin et al., 2020). OSA is also associated with advancing age (Peppard et al., 2013), OSA is accompanied by cardiovascular mortality and impaired quality of life, including asthenia and disabling daytime sleepiness. Young adults with OSA have greater odds of moderate/severe pain (Athar et al., 2020). OSA has also been associated with altered responsiveness to opioids (Cozowicz et al., 2018).

Continuous positive airway pressure (CPAP) is the gold standard for OSA. Although not necessarily accompanied by an improvement in cardiovascular prognosis (Yu et al., 2017), using a CPAP device is accompanied by a clear improvement in quality of life (Kuhn et al., 2017). This effect could in part be mediated by an elevation of the PT, as has been shown in the elderly (Onen et al., 2010).

This work is based on two hypotheses: (1) OSA may lower PT in a population with obesity, and (2) improvements in sleep afforded by CPAP treatment may 'restore' the PT. We, therefore, studied the link between the presence of OSA and PT, and the effects of CPAP therapy on PT in patients with obesity.

## 2 | MATERIALS AND METHODS

### 2.1 | Study design

This prospective, monocentric, longitudinal, controlled study was conducted at the University Hospital of Clermont-Ferrand between February 2010 and February 2017. The University Hospital of Clermont-Ferrand was the promoter of this study and provided funding for an internal tender (AOI 2008 Debouit-Miolanne). Each patient completed an information and consent form. The protocol was approved by the local institutional review board (Comité de Protection des Personnes Sud-Est VI).

This trial involved patients with obesity (BMI ≥30 kg/m²) of both sexes over the age of 18 under the care of the nutrition and pulmonology departments, and who had undergone sleep recording for OSA. Patients with central sleep apnoea, acute or chronic pain, neuromuscular pathology, chronic analgesic treatment, benzodiazepine, tricyclic or β-blocking therapy, alcohol or illegal drug abuse or dependence (DSM-IV, diagnostic and statistical manual of mental disorders), or those who were not affiliated to the Social Security system were not included. Patients unable to take part due to their involvement in another study, those who received over 4500 euros/year due to their participation in clinical trials, pregnant or breastfeeding women, and individuals subject to a protection measure or deprivation of rights safeguards, were also excluded.

### 2.2 | Biochemical analyses

The International Diabetes Federation 2005 components of metabolic syndrome were used as follows: (1) abdominal obesity, defined as a waist circumference greater than 94 cm in men or greater than 80 cm in women; (2) fasting plasma glucose greater than 100 mg/dL, or high blood glucose treated with medication; (3) serum triglycerides greater than 150 mg/dL, or high triglycerides treated with medication; (4) serum high-density lipoprotein cholesterol (HDL-C) less than 0.40 mg/dL in men and less than 0.50 mg/dL in women or low HDL-C treated with medication; (5) blood pressure higher than 130/85 mmHg, or high blood pressure treated with medication (Alberti et al., 2005).

### 2.3 | Sleep measurements

As part of their care, patients with obesity who were hospitalized in the nutrition and pulmonology departments completed a nocturnal polygraphy (measurement of peripheral oxygen saturation, nasal flow, thoracic and abdominal movements, SOMNOcheck® effort, WEINMANN) to confirm or disprove the presence of OSA. Two groups of patients were created: one group without sleep apnoea (<AHI 10) and one group with apnoea (AHI ≥ 10). The latter group included patients with moderate apnoea (AHI between 10 and 30) and severe apnoea (AHI > 30). These thresholds were set from the 1990 definition of the International Classification of Sleep Disorders, a definition that was still widely used when the protocol was designed in 2009.
All patients were subjected to mechanical and electrical pain tests in the week following the polygraphy. Severe OSA (AHI > 30) was an indication for treatment with CPAP and, once they had given consent, patients with severe OSA were admitted to the pulmonology department to have the CPAP device implanted. Patients were then subjected to mechanical and electrical pain tests on the second day after CPAP treatment had begun. One month after beginning CPAP therapy, patients underwent another ambulatory nocturnal polygraphy as well as further mechanical and electrical pain tests.

## 2.4 | Pain measurements

Two methods for measuring the PT were studied: mechanical and electrical. Mechanical PT was determined through the pressure generated by a Von Frey electronic device (BIOSEB Ltd.). Constantly increasing pressure was applied to the skin using a plastic cone attached to a strain gauge to instantly measure the point pressure exerted and determine the PT. Mechanical PT was determined using the average value of three successive measurements taken on the inside of the forearm (on the non-dominant side). This method has already shown good intraobserver and interobserver reliability (Tena et al., 2012).

Electrical stimulation tests were performed using PainMatcher® (Cefar Medical). This device, with built-in electrodes, was grasped between the thumb and forefinger of the left hand. The device generated single-phase pulses of 15 mA and 10 Hz. The intensity increased with the duration of monophasic pulses in increments of 4 ms (from 4 to 396 ms). The results are expressed in stimulation duration steps (arbitrary unit) between 1 and 99. When they reached their PT, patients let go of the electrodes to interrupt the current, thereby establishing a value between 0 and 99 (Lund et al., 2005). Electrical PT was determined using the average value of three successive measurements with this device.

All these tests were performed on subjects who were comfortably seated in an examination chair in a semi-recumbent position and in a quiet environment. From a baseline level that caused no particular sensation, the mechanical or electrical stimulus was increased at a constant rate of progression. PT, defined as the lowest stimulation intensity that the subject perceived as painful, was used when analysing the primary and secondary endpoints (Tena et al., 2012).

## 2.5 | Evaluation criteria

The primary outcome of the study was an inter-group comparison of PT in patients with obesity, with or without

OSA, in response to electrical or mechanical nociceptive stimuli. The intra-group comparison of the same PT in patients with obesity and severe OSA before and after CPAP therapy was the secondary criterion.

## 2.6 | Statistical analyses

Calculation of the number of patients required was based on the prior experience of the functional nervous system exploration department in measuring pain thresholds by electrical (PainMatcher®) or mechanical (Von Frey electronics) nociceptive stimulation. We took into account the criteria that offer the greatest variability of measurements, that is, those obtained using the Von Frey electronic device (average values in a population of healthy volunteers = 135±40). A pain threshold difference of 20% (i.e. 27) was considered clinically significant. The sample size estimate was 105 (35 and 70 in each group) for a two-sided type I error of 5%, a 90% statistical power and an unbalanced ratio of 1:2 (OSA: Without OSA). Due to recruitment difficulties, inclusions were closed after 8 years with 85 patients (27 OSA and 58 non-OSA), which corresponds to a statistical power of 80%.

The continuous variables were described according to their statistical distribution by mean ± standard deviation or median deviation [interquartile range]. Normality was studied using the Shapiro-Wilk test. Comparisons between groups (primary comparison: non-apnoeic patients vs. patients with OSA, followed by secondary comparison: non-apnoeic patients vs. patients with severe OSA vs. patients with moderate OSA) considered the following statistical tests: (i) for quantitative variables: the ANOVA (analysis of variance) test, or the Kruskal-Wallis test (KW) when assumptions for the ANOVA test were not met ((1) normality and (2) homoscedasticity studied by the Bartlett test), and (ii) for categorical parameters: chi-squared test or Fisher's exact test for comparisons. When appropriate (omnibus *p*-value less than 0.05 for comparisons between non-apnoeic patients, patients with severe OSA and patients with moderate OSA), post hoc tests for multiple comparisons were conducted in order to take into account the correction of the type I error: Tukey-Kramer post the ANOVA test, and Dunn after the KW test for quantitative variables, and Marascuilo post a chi-squared test procedure.

Multivariable analysis was conducted using a multiple linear regression model. The covariates were selected based on the results of univariate analysis and their clinical relevance: age, sex, BMI and tobacco consumption. The normal distribution of residuals was studied using the Shapiro-Wilk test. The results were expressed using effect-sizes and 95% confidence intervals and were interpreted
according to effect-size bounds recommended by Cohen (Cohen, 1988): small (ES: 0.2), medium (ES: 0.5) and large (ES: 0.8, 'grossly perceptible and therefore large').

Finally, paired comparisons were analysed using the Stuart-Maxwell paired test for categorical data, and paired Student or Wilcoxon tests for quantitative variables. All statistical analyses were performed using Stata software (version 13, StataCorp). The type I error was two-sided at 5%.

## 3 | RESULTS

### 3.1 | Participants and clinic-biological characteristics

Most of the 1455 patients hospitalized between 2010 and 2017 had exclusion criteria such as chronic pain or interfering treatments (Figure 1). Although only 6% of patients were included, the demographic characteristics of the 91 patients included were comparable in terms of age, BMI and sex to all patients with obesity admitted to the nutrition department over that period. Six patients were excluded secondarily, and 85 were included in the analysis,

including 27 patients who had been diagnosed as apnoeic (AHI≥10). Only 11 patients with severe OSA (AHI>30) who agreed to undergo CPAP could be analysed.

The clinic-biological characteristics of the 91 patients included are shown in Table 1. Most of our patients had grade 3 obesity (90%) and metabolic syndrome (66%). Apnoeic patients were older (45.7±12.3 vs 37.5±12.9, *p*<0.01) and had a lower female predominance (78 vs. 52%, *p* = 0.02) compared to the non-apnoeic patients. The Epworth score (threshold at 10/24) was in no way discriminatory towards our population in terms of screening of apnoeic subjects Cumulative time spent with Peripheral blood oxygen saturation below 90% (CT90) was higher among apnoeic patients (19.44±23.7 vs 3.9±6.3, *p*<0.001).

### 3.2 | Pain PTs

To take into account possible confounders, a multivariable analysis was performed to adjust PT for age, gender, BMI and smoking status. With respect to inter-group analyses, apnoeic patients had a lower PT according to the mechanical method (ES = -0.46 [-0.85;-0.08]*t* = 2.40, *p* = 0.019)

<figure><img src="image_5.png" /><figcaption>**FIGURE 1** Flow diagram of patients participating in the study and major analyses performed. CPAP, continuous positive airway pressure; OSA, obstructive sleep aponea syndrome.</figcaption></figure>
<table><caption>TABLE 1 Clinico-biological characteristics of patients at baseline.</caption><thead><tr><th></th><th>Total<br>(n = 85)</th><th>Without OSA<br>(n = 58)</th><th>OSA</th><th>p value<sup>b</sup></th><th>Moderate OSA<br>(n = 16)</th><th>Severe OSA<br>(n = 11)</th></tr></thead><tbody><tr><td>Age (years)</td><td>40.1 ± 13.2</td><td>37.5 ± 12.9</td><td>45.7 ± 12.3</td><td>&lt;0.0011<sup>c</sup></td><td>44.7 ± 13.3</td><td>47.3 ± 11.0</td></tr><tr><td>Women (%)</td><td>69</td><td>78</td><td>52</td><td>0.023<sup>e</sup></td><td>69</td><td>27</td></tr><tr><td>BMI (kg/m<sup>2</sup>)</td><td>42.0 ± 7.2</td><td>41.1 ± 7.5</td><td>43.9 ± 6.3</td><td>0.081<sup>c</sup></td><td>43.1 ± 5.6</td><td>45.1 ± 7.4</td></tr><tr><td>Smoking (%)</td><td>24</td><td>22</td><td>26</td><td>0.723<sup>e</sup></td><td>25</td><td>27</td></tr><tr><td>Metabolic syndrome<sup>a</sup> (%)</td><td>66</td><td>66</td><td>67</td><td>0.803<sup>e</sup></td><td>63</td><td>73</td></tr><tr><td>Increased waist size</td><td>100</td><td>100</td><td>100</td><td></td><td>100</td><td>100</td></tr><tr><td>High blood pressure</td><td>72</td><td>69</td><td>78</td><td>0.403<sup>e</sup></td><td>75</td><td>82</td></tr><tr><td>Hypertriglyceridemia</td><td>35</td><td>36</td><td>33</td><td>0.803<sup>e</sup></td><td>19</td><td>55</td></tr><tr><td>Decreased HDL</td><td>64</td><td>67</td><td>56</td><td>0.303<sup>e</sup></td><td>56</td><td>55</td></tr><tr><td>Fasting hyperglycaemia</td><td>26</td><td>21</td><td>37</td><td>0.113<sup>e</sup></td><td>44</td><td>27</td></tr><tr><td>Score de Framingham</td><td>7.4 ± 7.5</td><td>7.1 ± 7.3</td><td>8.0 ± 7.9</td><td>0.603<sup>e</sup></td><td>9.2 ± 7.5</td><td>6.3 ± 8.7</td></tr><tr><td>CRP (mg/L)</td><td>6.3 ± 5.5</td><td>6.7 ± 5.9</td><td>5.4 ± 3.5</td><td>0.432<sup>d</sup></td><td>6.2 ± 4.7</td><td>4.8 ± 3.1</td></tr><tr><td>Epworth score, /24</td><td>7.9 ± 4.0</td><td>8.3 ± 4.2</td><td>6.9 ± 3.0</td><td>0.161<sup>c</sup></td><td>9.1 ± 4.3</td><td>8.9 ± 6.7</td></tr><tr><td>AHI</td><td>11.5 ± 20.1</td><td>1.8 ± 2.0</td><td>32.5 ± 24.9</td><td>&lt;0.0012<sup>d</sup></td><td>15.4 ± 4.1</td><td>57.5 ± 20.9</td></tr><tr><td>CT90</td><td>8.5 ± 15.6</td><td>1 [0–4]</td><td>6 [3–29]</td><td>&lt;0.0012<sup>d</sup></td><td>5 [2–23]</td><td>11 [5–41]</td></tr></tbody></table>

Note: Values expressed as means ± standard deviation.

Abbreviations: AHI, apnoea-hypopnoea index, CT90, Cumulative time spent with Peripheral blood oxygen saturation below 90%, OSA, obstructive sleep apnoea syndrome.

<sup>a</sup>International Diabetes Federation 2005 criteria.

<sup>b</sup>p value OSA vs. without OSA.

<sup>c</sup>Student or Welch test.

<sup>d</sup>Mann-Whitney.

<sup>e</sup>Chi-squared test.

<figure><img src="image_6.png" /><figcaption>FIGURE 2 Comparison of pain perception thresholds for patients without apnoea (N = 58) and patients with OSA (N = 27), tested using mechanical and electrical methods. OSA: obstructive sleep apnoea syndrome. Values adjusted for age, sex, BMI and smoking status.

\*p < 0.05. Mechanical PT was determined through a constantly increasing pressure generated by a Von Frey electronic on a plastic cone applied on the inside of the non-dominant forearm (average value of three successive measurements). Electrical PT was determined using a PainMatcher<sup>*</sup>, a built-in electrodes device (grasped between the thumb and forefinger of the left hand) generating single-phase pulses of 15 mA and 10 Hz with gradual increased in duration of monophasic pulses. The intensity of electric current corresponds to the stimulation duration steps (arbitrary unit) between 1 and 99. Electrical and mechanical PT were determined using the average value of three successive measurements. PT was defined as the lowest stimulation intensity that the subject perceived as painful.</figcaption></figure>

but not the electrical method (ES = -0.30 [-0.68;0.09], t = 1.54, p = 0.12) in multivariable analysis adjusted for age, gender, BMI and smoking status (Figure 2).

In addition, severe apnoeic subjects had a significantly lower PT than non-apnoeic patients when using the mechanical method (ES = -0.85 [-0.93; -0.16], t = 2.82, p < 0.01) and
electrical (ES = -0.42 [-0.80; -0.04], t = 2.19, p = 0.03) stimulations (Figure 3). On the other hand, there was no significant difference in PT between the two severity levels of OSA regardless of the method tested.

Regarding the intragroup analysis of the 11 patients who were treated with CPAP, only seven patients had performed the pain tests at 1 month. An increase in PT was observed following CPAP therapy according to the mechanical method (298 ± 69 vs. 259 ± 68 g, t = 2.50, p < 0.05) but not with electric stimulation (11.5 ± 3.0 vs. 12.4 ± 3.8, t = 0.72, p = 0.50) (Figure 4).

## 3.3 | Correlation

There was a significant negative correlation between AHI and mechanical PT (r = -0.239, p = 0.03, Spearman) but not with electrical PT (r = -0.01, p = 0.96, Spearman) (Figure 5). The two modalities of PT were correlated (r = 0.5618, p < 0.001, Spearman). As CT90 was not correlated with either electrical (r = -0.047, p = 0.69, Spearman) or mechanical PT (r = -0.007, p = 0.95, Spearman), it was not included in the model.

## 4 | DISCUSSION

The present study suggests that obesity and severe OSA are associated with a decrease in the pain PT and that CPAP therapy could enhance PT in severe OSA. These effects are observed specifically on PT related to mechanical stimulation but not in case of electrical stimulation. This

work supports the epidemiological link between sleep pathology and the development of chronic pain as well as the link between sleep deprivation and lowering of the threshold of pain sensitivity (Finan et al., 2013). However, most of these interventional studies involved healthy populations (Onen et al., 2001). On the contrary, our study focused on a poorly studied population with grade 3 obesity. Finally, compared to other studies using painful stimulation via a single modality, we chose to explore mechanical and electrical modalities (Onen et al., 2010).

## 4.1 | Factors taken into account in the adjustment of PT

Many factors that may influence the frequency of chronic pain have been identified in the literature. High BMI has been associated with an increased frequency of pain whether overall pain (Stone and Broderick, 2012), lower back pain (Heuch et al., 2013), or headaches (Bigal et al., 2007), even once adjustments have been made for age, sex and smoking (Stone and Broderick, 2012). Beyond BMI, percentage of fat mass and central distribution (increased waist circumference) have been associated with back, knee and foot pain intensity and disability (Hussain et al., 2017; Peiris et al., 2021). This high incidence of musculoskeletal pain in obese people has been linked to mechanical joint overload, a source of early osteoarthritis (Kulkarni et al., 2016). In addition, nociceptor hypersensitivity may result from the chronic low-grade inflammatory state associated with obesity (Eichwald & Talbot, 2020). An increasing percentage of body fat has

<figure><img src="image_7.png" /></figure>

**FIGURE 3** Comparison of pain perception thresholds for patients without apnoea (N = 58), moderately apnoeic patients (N = 16) and severely apnoeic patients (N = 11), using mechanical and electrical methods. Values adjusted for age, sex, BMI and smoking status. \*p < 0.05 between the groups no apnea and severe OSA. Mechanical PT was determined through a constantly increasing pressure generated by a Von Frey electronic on a plastic cone applied on the inside of the non-dominant forearm (average value of three successive measurements). Electrical PT was determined using a PainMatcher\*, a built-in electrodes device (grasped between the thumb and forefinger of the left hand) generating single-phase pulses of 15 mA and 10 Hz with gradual increased in duration of monophasic pulses. The intensity of electric current corresponds to the stimulation duration steps (arbitrary unit) between 1 and 99. Electrical and mechanical PT were determined using the average value of three successive measurements. PT was defined as the lowest stimulation intensity that the subject perceived as painful.
<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

**FIGURE 4** Comparison of pain perception thresholds before and after CPAP treatment, using mechanical (a and c) and electrical methods (b and d) in severely apnoeic patients (N = 7). (a) and (b) The mean values and standard deviations (values adjusted for age, sex, BMI and smoking status; \*p < 0.05). (c) and (d) represent individual variations. CPAP, continuous positive airway pressure. Mechanical PT was determined through a constantly increasing pressure generated by a Von Frey electronic on a plastic cone applied on the inside of the non-dominant forearm (average value of 3 successive measurements). Electrical PT was determined using a PainMatcher\*, a built-in electrodes device (grasped between the thumb and forefinger of the left hand) generating single-phase pulses of 15 mA and 10 Hz with gradual increased in duration of monophasic pulses. The intensity of electric current corresponds to the stimulation duration steps (arbitrary unit) between 1 and 99. Electrical and mechanical PT were determined using the average value of 3 successive measurements. PT was defined as the lowest stimulation intensity that the subject perceived as painful. CPAP, continuous positive airway pressure.

previously been associated with a decrease in pressure pain threshold (Tashani et al., 2017). However, these differences may be affected by the test site and by the thickness of the subcutaneous fat (waist vs. thenar eminence). Here, we chose a rather classical site on the internal face of the forearm, which is only moderately affected by the increase in subcutaneous fat.

Chronic pain is particularly common with age, affecting almost 50% of the population over 65, and particularly correlates with functional impairment (Patel et al., 2013). This frequency seems to relate to inflammation and dysregulated cytokine production (Cruz-Almeida et al., 2015). Conversely, some experimental studies show an increase in pain thresholds with age, particularly in the lower limbs (Riley et al., 2014). Differences in pain sensitivity and response to analgesics have been found between men and women in relation to genetic, hormonal and psycho-social factors (Bartley & Fillingim, 2013) Although experimentally nicotine may have antalgic

properties, epidemiological studies show on the contrary a connection between smoking and painful, chronic pathologies (Shi et al., 2010).

The pathophysiology of these statistical associations is often too uncertain to establish causal links. To compensate for the uneven distribution of some of these factors in our different groups, an age adjustment for sex, BMI and smoking was performed. However, the study's design did not allow for the collection of the data needed to take into account genetic or dietary factors, physical activity or thymic state.

## 4.2 | Other potential factors influencing pain perception

The link between inflammation, the local production of cytokines, which sensitize nociceptors, and inflammatory pain is well established and explains the analgesic efficacy of
<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /><figcaption>**FIGURE 5** Correlations between apnoea-hypopnoea index and electrical pain (a) or mechanical pain threshold (b). AHI, apnoea-hypopnoea index.</figcaption></figure>

anti-inflammatory treatments (Guillot et al., 2012). Adipose tissue releases numerous mediators, named adipokines, with both paracrine and systemic actions. In patients with obesity and visceral fat accumulation, the inflammatory ones (resistin, leptin, chemerin and visfatin-1) tend to be overexpressed, while others with anti-inflammatory effects are reduced (adiponectin and omentin), leading to low-grade systemic inflammation (Azamar-Llamas 2017). Epidemiologically, an inverse relationship between the pain score (pain component of SF36) and the nutritional quality score (Healthy Eating Index 2010) has been reported. This effect seems particularly mediated by foods with anti-inflammatory effects (rich in omega 3) (Emery et al., 2017). However, the effect on pain of low-level systemic inflammation in chronic diseases such as obesity or cancer remains controversial (Paulsen et al., 2017). Thus, the only marker of inflammation measured in our population, the C Reactive Protein level, was not higher in cases of OSA or even severe OSA, while the percentage of body fat was higher than in non-apnoeics.

Chronic pain is a classic symptom in diabetes that takes several years to develop as a result of peripheral neurological involvement. In addition, there appears to be hypersensitivity to nociceptive stimuli as early as the insulin resistance stage (Zhai et al., 2016, Iftikhar et al., 2015).

Depression and other psychological disorders such as anxiety are frequently associated with obesity (Luppino et al. 2010). These psycho-thymic disorders are also linked to pain hypersensitivity due to possible altered central pain mechanics (e.g. altered descending pain modulation or emotional aspect of pain) (Nahman-Averbuch et al., 2016). Depression is associated with an increased incidence of chronic pain, particularly lower back pain (Lopez-Lopez et al., 2017) and headaches (Lampl et al., 2016). Similarly, sedentariness compared to low to moderate physical activity is associated with increased pain

frequency, possibly due to the positive effects of physical activity on psychological well-being (Krøll et al., 2017, Naugle et al., 2017). Research involving pairs of twins has highlighted the importance of genetics in many painful pathologies beyond mood state and environmental factors (Dario et al., 2016). Some genetic or environmental factors seem able to influence the frequency of both chronic pain and depression (Pinheiro et al., 2015).

## 4.3 | Pathophysiological hypotheses linking pain and OSA

Sleep disturbance has been previously linked to pain hypersensitivity. Thus, a night of poor sleep quality or difficulty falling asleep has been associated with worsening pain symptoms (Alsaadi et al., 2014). Reciprocally, some authors suggest that pain disturbs sleep continuity/quality and poor sleep further exacerbates pain, generating a vicious circle (Alsaadi et al., 2014; Smith & Haythornthwaite, 2004). Although the underlying mechanisms connecting sleep disturbance and pain hypersensitivity are unclear, some brain areas have been suggested to modulate both sleep stages and pain. Thus, the raphe nuclei are involved in the descending pain control system and the ascending reticular activating system, which is also responsible for the transition between sleep and wakefulness (Lu et al., 2006). This bidirectional relationship between sleep and pain could involve many neurobiological mechanisms, including the opioid, monoaminergic, orexinergic, immune, melatonin and endocannabinoid systems; the hypothalamus-pituitary-adrenal axis and adenosine and nitric oxide signalling (Haack et al. 2020).

Some of the previously mentioned factors explain both the reduced pain thresholds in the population with particularly severe apnoea and the effectiveness of CPAP
treatment on pain PTs. Severe OSA has been implicated in a reduction in functional abilities (Ben Saad et al., 2015), which may itself promote a sedentary lifestyle, combined with fatigue relating to poor quality of sleep. OSA treatment improves sleep quality (Cruz et al., 2012), daytime sleepiness (Giles et al., 2006) and overall levels of physical activity (Jean et al., 2017). Depression contributes to the quality of life in OSA patients (Lee et al., 2016; Stelmach-Mardas et al., 2016). CPAP therapy appears to reduce symptoms of anxiety and depression (Gupta et al., 2016) as well as the quality of life (Kuhn et al., 2017), particularly in severely apnoeic patients (Batool-Anwar et al., 2016). However, it remains difficult to establish whether pain perception benefits from mood improvement, or whether it is a contributing factor. In addition, improvement in depression scores could also, at least in part, be mediated by the attention offered by healthcare teams to an often isolated and frail population (Newton et al., 2017). Finally, treatment with CPAP has been associated with a lasting improvement in insulin resistance (Iftikhar et al., 2015; Martínez-Cerón et al., 2016). However, this improvement is still contested (Zhu et al., 2017).

## 4.4 | Other considerations

In our study, the effect of OSA on PT, which is observed with the mechanical method, has only been significantly demonstrated with electrical stimulation in severely apnoeic populations. Tashani et al. (2017) have also reported that obese individuals were more sensitive than non-obese individuals to pressure pain but not to thermal pain. The different nervous pathways used by the two stimulations can explain this discrepancy. On the one hand, mechanical or thermal stimulations directly implicate peripheral nociceptive endings. On the other hand, electrical stimulations are not a physiological pain stimulus and activate various types of nerve fibre in a more undifferentiated way (Balogun, 1986; Reddy et al., 2012). Moreover, this difference may be explained by the low statistical power that resulted from the small number of patients who showed greater PT variability with the electrical method.

The link between OSA and hypertension, diabetes and metabolic syndrome potentiates cardiovascular risk (Heinzer et al., 2015). The presence of a metabolic syndrome in 2/3 of our patients is thus consistent with the main data found in the literature. However, our small numbers of patients do not allow us to establish an over-representation of metabolic syndrome in apnoeic patients as compared to controls.

The Epworth score assesses the degree of daytime sleepiness and has been used as an OSA test for many years. However, in a population with grade III obesity,

this score seems to be a very poor predictor of AHI during sleep recording (Dixon et al., 2007). The presence of obesity hypoventilation syndrome or depression is a common factor influencing the level of daytime sleepiness, regardless of the presence of OSA. In our study, the Epworth score proved to be a very poor screening tool, highlighting the importance of routine sleep recording in a population with obesity.

## 4.5 | Strengths, limitations and perspectives

Our study was based on a properly phenotyped population with obesity. The evaluation of pain PTs was carried out using two different methods with validated tools and performed by a single trained operator.

This study has several limitations. First, the estimated sample size was not reached. However, our results are based on a small size population, particularly in intervention groups, and should be considered as an exploratory investigation. Thus, our findings need to be further confirmed by larger studies in the future. Second, the level of physical activity, as a possible confounding factor, should have been assessed and reassessed 1 month after CPAP treatment. Third, the selected exclusion criteria have ruled out certain populations with obesity, particularly populations with painful, chronic conditions. This subpopulation may have specific PT and it would be interesting to study the impact of CPAP therapy on the consumption of algalics. Finally, the reduction in the pain PT related to SAOS might modify eating behaviours (eating balance, compulsive eating, etc.). Thus, sleep disorders associated with OSA may be an underestimated factor in eating disturbance that could be the subject of more targeted studies in the future.

## 5 | CONCLUSION

In patients with obesity, the presence of OSA is associated with a decreased PT, particularly using mechanical stimuli and in severe OSA. This might therefore contribute to the frequency of chronic pain phenomena in this population. CPAP therapy tends to limit this discrepancy. More than ever, screening and management of OSA is therefore a major challenge in terms of quality of life for patients with obesity.

## AUTHOR CONTRIBUTIONS

CL: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Project administration; Resources; Supervision; Validation; Visualization;
original draft; review & editing. MM: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Supervision; Validation; review & editing. NF: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Supervision; Validation; review & editing. BP: Conceptualization; Data curation; Methodology; Software; Validation; Visualization; review & editing. CD: Methodology; Validation; Visualization; review & editing. PB: Conceptualization; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Software; Supervision; Validation; review & editing. AG: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Software; Supervision; Validation; Visualization; review & editing. YB: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Resources; Supervision; Validation; Visualization; review & editing.

## ACKNOWLEDGEMENTS

The authors thank Sylvie Eschalier from the Clinical Investigation Center (CIC) of Clermont-Ferrand for carrying out the pain assessments, and the volunteers for their participation.

We also thank the University Hospital of Clermont-Ferrand as the promoter and funder of this study (AOI 2008 Debouit-Miolanne).

## FUNDING INFORMATION

This study was funded by the University Hospital of Clermont-Ferrand (AOI 2008 Debouit-Miolanne; 20,000 euros).

## CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

## ORCID

Clément Lahaye https://orcid.org/0000-0002-0839-9971

## REFERENCES

Alberti, K. G. M., Zimmet, P., & Shaw, J. (2005). The metabolic syndrome—A new worldwide definition. *The Lancet*, **366**, 1059–1062. https://doi.org/10.1016/S0140-6736(05)67402-8

Alsaadi, S. M., McAuley, J. H., Hush, J. M., Lo, S., Bartlett, D. J., Grunstein, R. R., & Maher, C. G. (2014). The bidirectional relationship between pain intensity and sleep disturbance/quality in patients with low back pain. *The Clinical Journal of Pain*, **30**(9), 755–765. https://doi.org/10.1097/AJP.0000000000000055

Athar, W., Card, M. E., Charokopos, A., Akgün, K. M., DeRycke, E. C., Haskell, S. G., Yaggi, H. K., & Bastian, L. A. (2020). Obstructive sleep apnea and pain intensity in Young adults.

Proceedings of the American Thoracic Society, **17**, 1273–1278. https://doi.org/10.1513/AnnalsATS.201910-750OC

Balogun, J. A. (1986). Pain complaint and muscle soreness associated with high-voltage electrical stimulation: Effect of ramp time. *Perceptual and Motor Skills*, **62**, 799–810. https://doi.org/10.2466/pms.1986.62.3.799

Batool-Anwar, S., Goodwin, J. L., Kushida, C. A., Walsh, J. A., Simon, R. D., Nichols, D. A., & Quan, S. F. (2016). Impact of continuous positive airway pressure (CPAP) on quality of life in patients with obstructive sleep apnea (OSA). *Journal of Sleep Research*, **25**, 731–738. https://doi.org/10.1111/jsr.12430

Bartley, E. J., & Fillingim, R. B. (2013). Sex differences in pain: A brief review of clinical and experimental findings. *British Journal of Anaesthesia*, **111**, 52–58. https://doi.org/10.1093/bja/aet127

Ben Saad, H., Ben Hassen, I., Ghannouchi, I., Latiri, I., Rouatbi, S., Escourrou, P., Ben Salem, H., Benzarti, M., & Abdelghani, A. (2015). 6-min walk-test data in severe obstructive-sleep-apnea-hypopnea-syndrome (OSAHS) under continuous-positive-airway-pressure (CPAP) treatment. *Respiratory Medicine*, **109**, 642–655. https://doi.org/10.1016/j.rmed.2015.03.001

Bigal, M. E., Tsang, A., Loder, E., Serrano, D., Reed, M. L., & Lipton, R. B. (2007). Body mass index and episodic headaches: A population-based study. *Archives of Internal Medicine*, **167**, 1964–1970. https://doi.org/10.1001/archinte.167.18.1964

Cohen, J. (1988). *Statistical power analysis for the behavioral sciences* (2nd ed.). Routledge. https://doi.org/10.4324/9780203771587

Cozowicz, C., Chung, F., Doufas, A. G., Nagappa, M., & Memtsoudis, S. G. (2018). Opioids for acute pain management in patients with obstructive sleep apnea: a systematic review. *Anesthesia and Analgesia*, **127**(4), 988–1001. https://doi.org/10.1213/ANE.00000000000003549

Cruz, I. A. C., Drummond, M., & Winck, J. C. (2012). Obstructive sleep apnea symptoms beyond sleepiness and snoring: Effects of nasal APAP therapy. *Sleep Breath Schlaf Atm*, **16**, 361–366. https://doi.org/10.1007/s11325-011-0502-4

Cruz-Almeida, Y., Aguirre, M., Sorenson, H. L., Tighe, P., Wallet, S. M., & Riley, J. L. (2015). Age differences in cytokine expression under conditions of health using experimental pain models. *Experimental Gerontology*, **72**, 150–156. https://doi.org/10.1016/j.exger.2015.09.017

Dario, A. B., Ferreira, M. L., Refshauge, K., Sánchez-Romera, J. F., Luque-Suarez, A., Hopper, J. L., Ordoñana, J. R., & Ferreira, P. H. (2016). Are obesity and body fat distribution associated with low back pain in women? A population-based study of 1128 Spanish twins. *European Spine Journal*, **25**, 1188–1195. https://doi.org/10.1007/s00586-015-4055-2

Dixon, J. B., Dixon, M. E., Anderson, M. L., Schachter, L., & O'Brien, P. E. (2007). Daytime sleepiness in the obese: Not as simple as obstructive sleep apnea. *Obesity*, **15**, 2504–2511. https://doi.org/10.1038/oby.2007.297

Eichwald, T., & Talbot, S. (2020). Neuro-immunity controls obesity-induced pain. *Frontiers in Human Neuroscience*, **14**, 181. https://doi.org/10.3389/fnhum.2020.00181

Emery, C. F., Olson, K. L., Bodine, A., Lee, V., & Habash, D. L. (2017). Dietary intake mediates the relationship of body fat to pain. *Pain*, **158**, 273–277. https://doi.org/10.1097/j.pain.0000000000000754

Finan, P. H., Goodin, B. R., & Smith, M. T. (2013). The association of sleep and pain: An update and a path forward. *Journal of Pain*, **14**(12), 1539–1552.
Giles, T. L., Lasserson, T. J., Smith, B. J., White, J., Wright, J., & Cates, C. J. (2006). Continuous positive airways pressure for obstructive sleep apnoea in adults. *Cochrane Database of Systematic Reviews*. (1), CD001106. https://doi.org/10.1002/14651858.CD001106.pub2

Guillot, X., Semerano, L., Decker, P., Falgarone, G., & Boissier, M.-C. (2012). Pain and immunity. *Joint Bone Spine Revue du rhumatisme*, *79*, 228–236. https://doi.org/10.1016/j.jbspin.2011.10.008

Gupta, M. A., Simpson, F. C., & Lyons, D. C. A. (2016). The effect of treating obstructive sleep apnea with positive airway pressure on depression and other subjective symptoms: A systematic review and meta-analysis. *Sleep Medicine Reviews*, *28*, 55–68. https://doi.org/10.1016/j.smrv.2015.07.002

Haack, M., Simpson, N., Sethna, N., Kaur, S., & Mullington, J. (2020). Sleep deficiency and chronic pain: Potential underlying mechanisms and clinical implications. *Neuropsychopharmacology*, *45*(1), 205–216. https://doi.org/10.1038/s41386-019-0439-z

Heinzer, R., Vat, S., Marques-Vidal, P., Marti-Soler, H., Andries, D., Tobback, N., Mooser, V., Preisig, M., Malhotra, A., Waeber, G., Vollenweider, P., Tafti, M., & Haba-Rubio, J. (2015). Prevalence of sleep-disordered breathing in the general population: The HypnoLaus study. *The Lancet Respiratory Medicine*, *3*, 310–318. https://doi.org/10.1016/S2213-2600(15)00043-0

Herrero Babiloni, A., De Koninck, B. P., Beetz, G., De Beaumont, L., Martel, M. O., & Lavigne, G. J. (2020). Sleep and pain: Recent insights, mechanisms, and future directions in the investigation of this relationship. *Journal of Neural Transmission*, *127*(4), 647–660. https://doi.org/10.1007/s00702-019-02067-z

Heuch, I., Heuch, I., Hagen, K., & Zwart, J.-A. (2013). Body mass index as a risk factor for developing chronic low back pain: A follow-up in the Nord-Trøndelag health study. *Spine*, *38*, 133–139. https://doi.org/10.1097/BRS.0b013e3182647af2

Hussain, S. M., Urquhart, D. M., Wang, Y., Shaw, J. E., Magliano, D. J., Wluka, A. E., & Cicuttini, F. M. (2017). Fat mass and fat distribution are associated with low back pain intensity and disability: Results from a cohort study. *Arthritis Research & Therapy*, *19*(1), 26. https://doi.org/10.1186/s13075-017-1242-z

Iftikhar, I. H., Hoyos, C. M., Phillips, C. L., & Magalang, U. J. (2015). Meta-analyses of the Association of Sleep Apnea with insulin resistance, and the effects of CPAP on HOMA-IR, adiponectin, and visceral adipose fat. *Journal of Clinical Sleep Medicine*, *11*, 475–485. https://doi.org/10.5664/jcsm.4610

Jean, R. E., Duttuluri, M., Gibson, C. D., Mir, S., Fuhrmann, K., Eden, E., & Supariwala, A. (2017). Improvement in physical activity in persons with obstructive sleep apnea treated with continuous positive airway pressure. *Journal of Physical Activity & Health*, *14*, 176–182. https://doi.org/10.1123/jpah.2016-0289

Krøll, L. S., Hammarlund, C. S., Westergaard, M. L., Nielsen, T., Sloth, L. B., Jensen, R. H., & Gard, G. (2017). Level of physical activity, well-being, stress and self-rated health in persons with migraine and co-existing tension-type headache and neck pain. *The Journal of Headache and Pain*, *18*, 46. https://doi.org/10.1186/s10194-017-0753-y

Kuhn, E., Schwarz, E. I., Bratton, D. J., Rossi, V. A., & Kohler, M. (2017). Effects of CPAP and mandibular advancement devices on health-related quality of life in OSA: A systematic review and meta-analysis. *Chest*, *151*, 786–794. https://doi.org/10.1016/j.chest.2017.01.020

Kulkarni, K., Karssiens, T., Kumar, V., & Pandit, H. (2016). Obesity and osteoarthritis. *Maturitas*, *1(89)*, 22–28. https://doi.org/10.1016/j.maturitas.2016.04.006

Lampl, C., Thomas, H., Tassorelli, C., Katsarava, Z., Laínez, J. M., Lantéri-Minet, M., Rastenyte, D., Ruiz de la Torre, E., Stovner, L. J., Andrée, C., & Steiner, T. J. (2016). Headache, depression and anxiety: Associations in the Eurolight project. *The Journal of Headache and Pain*, *17*, 59. https://doi.org/10.1186/s10194-016-0649-2

Lin, H., Xiong, H., Ji, C., Wang, C., Li, Y., An, Y., Li, G., Guo, J., Huang, X., Zhang, H., Liu, H., Li, T., Li, Z., Xian, J., & Huang, Y. (2020). Upper airway lengthening caused by weight increase in obstructive sleep apnea patients. *Respiratory Research*, *21*(1), 272. https://doi.org/10.1186/s12931-020-01532-8

Lee, W., Lee, S.-A., Ryu, H. U., Chung, Y.-S., & Kim, W. S. (2016). Quality of life in patients with obstructive sleep apnea: Relationship with daytime sleepiness, sleep quality, depression, and apnea severity. *Chronic Respiratory Disease*, *13*, 33–39. https://doi.org/10.1177/1479972315606312

Lopez-Lopez, D., Vilar-Fernandez, J. M., Calvo-Lobo, C., Losa-Iglesias, M. E., Rodriguez-Sanz, D., & Becerro-de-Bengoa-Vallejo, R. (2017). Evaluation of depression in subacute low Back pain: A case control study. *Pain Physician*, *20*, E499–E505.

Lu, J., Jhou, T. C., & Saper, C. B. (2006). Identification of wake-active dopaminergic neurons in the ventral periaqueductal gray matter. *The Journal of Neuroscience*, *26*(1), 193–202. https://doi.org/10.1523/JNEUROSCI.2244-05.2006

Lund, I., Lundeberg, T., Kowalski, J., Sandberg, L., Budh, C. N., & Svensson, E. (2005). Evaluation of variations in sensory and pain threshold assessments by electrocutaneous stimulation. *Physiotherapy Theory and Practice*, *21*, 81–92.

Luppino, F. S., de Wit, L. M., Bouvy, P. F., Stijnen, T., Cuijpers, P., Penninx, B. W. J. H., & Zitman, F. G. (2010). Overweight, obesity, and depression: A systematic review and meta-analysis of longitudinal studies. *Archives of General Psychiatry*, *67*(3), 220–229. https://doi.org/10.1001/archgenpsychiatry.2010.2

Martínez-Cerón, E., Barquiel, B., Bezos, A.-M., Casitas, R., Galera, R., García-Benito, C., Hernanz, A., Alonso-Fernández, A., & Garcia-Rio, F. (2016). Effect of continuous positive airway pressure on glycemic control in patients with obstructive sleep apnea and type 2 diabetes. A randomized clinical trial. *American Journal of Respiratory and Critical Care Medicine*, *194*, 476–485. https://doi.org/10.1164/rccm.201510-1942OC

Nahman-Averbuch, H., Nir, R. R., Sprecher, E., & Yarnitsky, D. (2016). Psychological factors and conditioned pain modulation: A meta-analysis. *The Clinical Journal of Pain*, *32*(6), 541–554. https://doi.org/10.1097/AJP.0000000000000296

Naugle, K. M., Ohlman, T., Naugle, K. E., Riley, Z. A., & Keith, N. R. (2017). Physical activity behavior predicts endogenous pain modulation in older adults. *Pain*, *158*, 383–390. https://doi.org/10.1097/j.pain.0000000000000769

Newton, S., Braithwaite, D., & Akinyemiju, T. F. (2017). Socio-economic status over the life course and obesity: Systematic review and meta-analysis. *PLoS One*, *12*, e0177151. https://doi.org/10.1371/journal.pone.0177151

Onen, S. H., Alloui, A., Gross, A., Eschallier, A., & Dubray, C. (2001). The effects of total sleep deprivation, selective sleep interruption and sleep recovery on pain tolerance thresholds in healthy subjects. *Journal of Sleep Research*, *10*, 35–42. https://doi.org/10.1046/j.1365-2869.2001.00240.x
Onen, S.-H., Onen, F., Albrand, G., Decullier, E., Chapuis, F., & Dubray, C. (2010). Pain tolerance and obstructive sleep apnea in the elderly. *Journal of the American Medical Directors Association, 11*, 612–616. https://doi.org/10.1016/j.jamda.2010.04.003

Patel, K. V., Guralnik, J. M., Dansie, E. J., & Turk, D. C. (2013). Prevalence and impact of pain among older adults in the United States: Findings from the 2011 National Health and aging trends study. *Pain, 154*, 2649–2657. https://doi.org/10.1016/j.pain.2013.07.029

Paulsen, Ø., Laird, B., Aass, N., Lea, T., Fayers, P., Kaasa, S., & Klepstad, P. (2017). The relationship between pro-inflammatory cytokines and pain, appetite and fatigue in patients with advanced cancer. *PLoS One, 12*, e0177620. https://doi.org/10.1371/journal.pone.0177620

Peiris, W. L., Cicuttini, F. M., Hussain, S. M., Estee, M. M., Romero, L., Ranger, T. A., Fairley, J. L., McLean, E. C., & Urquhart, D. M. (2021). Is adiposity associated with back and lower limb pain? A systematic review. *PLoS One, 16*(9), e0256720. https://doi.org/10.1371/journal.pone.0256720

Peppard, P. E., Young, T., Barnet, J. H., Palta, M., Hagen, E. W., & Hla, K. M. (2013). Increased prevalence of sleep-disordered breathing in adults. *American Journal of Epidemiology, 177*, 1006–1014. https://doi.org/10.1093/aje/kws342

Pinheiro, M. B., Ferreira, M. L., Refshauge, K., Colodro-Conde, L., Carrillo, E., Hopper, J. L., Ordoñana, J. R., & Ferreira, P. H. (2015). Genetics and the environment affect the relationship between depression and low back pain: A co-twin control study of Spanish twins. *Pain, 156*, 496–503. https://doi.org/10.1097/01.j.pain.0000460330.56256.25

Reddy, K. S., MUR, N., Rani, P. U., & TRK, R. (2012). Human experimental pain models: A review of standardized methods in drug development. *Journal of Research in Medicinal Science, 17*, 587–595.

Riley, J. L., III, Cruz-Almeida, Y., Glover, T. L., King, C. D., Goodin, B. R., Sibille, K. T., Bartley, E. J., Herbert, M. S., Sotolongo, A., Fessler, B. J., Redden, D. T., Staud, R., Bradley, L. A., & Fillingim, R. B. (2014). Age and race effects on pain sensitivity and modulation among middle-aged and older adults. *Pain forum, 15*, 272–282. https://doi.org/10.1016/j.jpain.2013.10.015

Shi, Y., Weingarten, T. N., Mantilla, C. B., Hooten, W. M., & Warner, D. O. (2010). Smoking and pain: Pathophysiology and clinical implications. *Anesthesiology, 113*, 977–992. https://doi.org/10.1097/ALN.0b013e3181ebdaf9

Smith, M. T., & Haythornthwaite, J. A. (2004). How do sleep disturbance and chronic pain inter-relate? Insights from the longitudinal and cognitive-behavioral clinical trials literature. *Sleep Medicine Reviews, 8*(2), 119–132. https://doi.org/10.1016/S1087-0792(03)00044-3

Stelmach-Mardas, M., Mardas, M., Iqbal, K., Tower, R. J., Boeing, H., & Piorunek, T. (2016). Quality of life, depression and dietary intake in obstructive sleep apnea patients. *Health and Quality of Life Outcomes, 14*, 111. https://doi.org/10.1186/s12955-016-0516-5

Stone, A. A., & Broderick, J. E. (2012). Obesity and pain are associated in the United States. *Obes Silver Spring Md, 20*, 1491–1495. https://doi.org/10.1038/oby.2011.397

Tashani, O. A., Astita, R., Sharp, D., & Johnson, M. I. (2017). Body mass index and distribution of body fat can influence sensory detection and pain sensitivity. *European Journal of Pain, 21*(7), 1186–1196. https://doi.org/10.1002/ejp.1019

Tena, B., Escobar, B., Arguis, M. J., Cantero, C., Rios, J., & Gomar, C. (2012). Reproducibility of electronic Von Frey and Von Frey monofilaments testing. *The Clinical Journal of Pain, 28*, 318–323. https://doi.org/10.1097/AJP.0b013e31822f0092

World Health Organization. Obesity and overweight [Internet]. http://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight

Yu, J., Zhou, Z., McEvoy, R. D., Anderson, C. S., Rodgers, A., Perkovic, V., & Neal, B. (2017). Association of positive airway pressure with cardiovascular events and death in adults with sleep apnea: a systematic review and meta-analysis. *JAMA, 318*, 156–166. https://doi.org/10.1001/jama.2017.7967

Zhai, X., Sun, C., Rong, P., Li, S., McCabe, M. F., Wang, X., Mao, J., & Wang, S. (2016). A correlative relationship between chronic pain and insulin resistance in Zucker fatty rats: Role of downregulation of insulin receptors. *Pain forum, 17*, 404–413. https://doi.org/10.1016/j.jpain.2015.12.003

Zheng, H., & Chen, C. (2015). Body mass index and risk of knee osteoarthritis: Systematic review and meta-analysis of prospective studies. *BMJ Open, 5*, e007568. https://doi.org/10.1136/bmjopen-2014-007568

Zhu, B., Ma, C., Chaiard, J., & Shi, C. (2017). Effect of continuous positive airway pressure on glucose metabolism in adults with type 2 diabetes: A systematic review and meta-analysis of randomized controlled trials. *Sleep Breath Schlaf Atm, 22*, 287–295. https://doi.org/10.1007/s11325-017-1554-x

**How to cite this article:** Lahaye, C., Miolanne, M., Farigon, N., Pereira, B., Dubray, C., Beudin, P., Greil, A., & Boirie, Y. (2023). Enhanced pain sensitivity in obese patients with obstructive sleep apnoea syndrome is partially reverted by treatment: An exploratory study. *European Journal of Pain, 27*, 624–635. https://doi.org/10.1002/ejp.2085