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Upper airway and hyoid bone-related morphological parameters associated with the apnea-hypopnea index and lowest nocturnal oxygen saturation: a cephalometric analysis

BMC Oral Health volume 25, Article number: 583 (2025) Cite this article

Abstract

Background

Obstructive sleep apnea (OSA) is a common disorder characterized by repetitive complete or partial closure of the upper airway during sleep, resulting in sleep fragmentation and oxygen desaturation. Cephalogram is recognized as an effective diagnostic tool for predicting OSA risk in clinical practice. This study aims to assess and analyze the morphological characteristics of the upper airway and hyoid bone position associated with OSA using data from polysomnography studies and two-dimensional cephalometric analysis.

Methods

The study included lateral cephalograms and polysomnography reports from the records of 105 adult (64 males & 41 females) patients who underwent comprehensive clinical examination. The severity of OSA was evaluated based on the apnea-hypopnea index (AHI) and lowest nocturnal oxygen saturation (LSaO2). The participants were divided into male and female groups to investigate the correlation between cephalometric parameters and OSA severity. Thirteen cephalometric parameters, including eleven linear measurements and two angular measurements, were analyzed. The significance level was set at P-value < 0.05.

Results

The male group exhibited significantly higher severity of OSA compared to the female group, as indicated by higher AHI and lower LSaO2. There was an inverse association between AHI values with width of upper airway as well as distance between hyoid bone position relative to mandibular plane in both male and female groups. Additionally, only the male group showed a correlation between hyoid bone position relative to gonion/third-fourth vertebrae positions with AHI values. 4 out of 7 parameters associated with AHI in male group remained correlated with LSaO2, while in females only the distance between hyoid bone and line formed by ptergoid and pterygomaxillary fissure point showed correlation with LSaO2.

Conclusion

Correlation analysis revealed that a narrower upper airway was positively associated with increased AHI, while an inferiorly positioned hyoid bone in relation to mandible was negatively correlated with LSaO2. Our findings highlight the importance of several cephalometric parameters in predicting OSA severity based on AHI and LSaO2 levels; moreover, certain parameters exhibited significant gender-specific associations.

Peer Review reports

Background

Obstructive sleep apnea (OSA) is a prevalent disorder characterized by recurrent episodes of airway obstruction during sleep, resulting in symptoms such as snoring, witnessed apnea, and excessive daytime sleepiness [1]. Recent studies have demonstrated a rising prevalence of both pediatric and adult-onset OSA, primarily attributed to the increasing rates of obesity and heightened air pollution. Additionally, hypertension, male sex, age, adenotonsillar hypertrophy, smoking, and diet including supplementations (e.g. vit. D and calcium level) are also correlated with the prevalence and severity of OSA [2,3,4]. Children with specific congenital conditions such as cleft deformities or Down syndrome may also encounter an elevated susceptibility to OSA due to obstructive factors affecting multiple levels of the airway [5, 6].

As a global health issue, pediatric OSA has been associated with neurocognitive deficits, learning difficulties, behavioral issues, stunted growth, and impaired cardiac function [7, 8]. Recent estimates suggest that OSA affects more than 900 million adults aged 30–69 globally, with approximately half experiencing moderate to severe forms of the condition [9]. It is particularly concerning in the elderly population due to its association with various systemic diseases including hypertension, diabetes mellitus, stroke, atherosclerosis, and an elevated risk of cardiovascular mortality [10]. Therefore, early screening and diagnosis of OSA are essential for reducing its negative impact on general health. While polysomnography (PSG) has been widely applied as a screening tool for OSA diagnosis based on various physiologic parameters such as oxygen saturation, brain electroencephalographic activity, eye movements, heart rate, and respiratory function [11, 12], it lacks detailed morphological evaluation of the upper airway structure, making it difficult to identify the obstruction site and predict the treatment outcomes [13]. Anatomical parameters of the craniofacial region including airway width, hyoid bone position, tongue position and volume, an increased mandibular plane angle, as well as maxillary and mandibular retrognathia, have been demonstrated to be determinative factors in the pathogenesis of certain OSA cases, hence complementary diagnostic tools are in need for a comprehensive evaluation of these factors [14,15,16].

Cephalometry is recognized as an efficient screening procedure to evaluate skeletal and soft tissue characteristics due to its cost-effectiveness, low radiation exposure, and ease of implementation [17, 18]. The current diagnostic and severity grading criteria for OSA are based on the apnea hypopnea index (AHI), which represents the number of apnea and/or hypopnea events per hour during sleep, regardless of related nocturnal oxygen desaturation [19]. Consequently, most cephalometric studies have investigated the correlation between craniofacial morphological characteristics and severity of OSA solely based on AHI values [15]. However, substantial evidence has shown that AHI alone does not fully reflect the clinical symptoms and prognosis of OSA patients. Mediano et al. reported that individuals with similar AHIs may exhibit varying levels of daytime sleepiness, sleep latency, and nocturnal oxygenation [20]. Asano et al. found that although some patients share a similar mean AHI, the severity of hypoxia and incidence of cardiovascular events were significantly different [21]. Wang et al. suggested that oxygen saturation below 90% during total sleep time was independently associated with the risk of hypertension in severe OSA patients after adjusting for traditional risk factors such as AHI and body mass index [22]. Considering these aforementioned studies, it is crucial to assess the correlation between cephalometric parameters and oxygen saturation in OSA patients to identify potential risk factors for nocturnal hypoxia and assist the treatment planning for this condition. Therefore, the aim of this study is to identify upper airway dimensions and hyoid bone position related variables associated with OSA severity using lateral cephalograms, considering both AHI values and lowest oxygen saturation as indicators.

Methods

Study design and samples

The study was designed as a retrospective cohort study. The study population included patients referred to the Department of Orthodontics in Hospital of Stomatology, Sun Yat-sen University, between January 2019 and June 2024. This study was approved by the Medical Ethics Committee of Hospital of Stomatology, Sun Yat-sen University (Approval No.KQEC-2024-99-01). Inclusion criteria were as follows: age over 18 years, diagnosis of OSA confirmed by PSG, availability of a digital lateral cephalogram taken with the same cephalostat positioning in an upright position, natural head posture, and centric occlusion at the end-tidal breathing phase [23]. Patients with craniofacial or growth abnormalities, history of orthodontic treatment, tonsillectomy or adenoidectomy were excluded. Based on these inclusion/exclusion criteria, a total of 105 patients were included in this observational retrospective study. All data used in this study were obtained from medical record review.

PSG

All participants involved in this study underwent standard overnight polysomnographic monitoring. Respiratory events were diagnosed as apnea or hypopnea, and the apnea-hypopnea index (AHI) was calculated as the total number of events per hour of sleep and classified according to the American Academy of Sleep Medicine Criteria 2012 (version 2.0) [24]. AHI and lowest oxygen saturation (LSaO2) level during sleep were recorded for further analysis in this study.

Cephalometric analysis

The standardized lateral cephalogram were obtained using the same cephalostat at the Hospital of Stomatology, Sun Yat-sen University. The patients were positioned upright with their head in a natural posture and centric occlusion, at the end of tidal breathing. Cephalometric tracings were performed by an examiner who was blinded to the PSG reports and clinical examination results. All angular and linear measurements were calculated using the Digident software (Boltzmann Zhibei Technology Co., Ltd, Chengdu, China) [25]. Thirteen variables of linear and angular measurements were derived from fourteen landmarks digitized on each radiograph, as described in Fig. 1; Table 1.

Fig. 1
figure 1

Graphical representation of landmarks: B, supramentale; N, Nasion; Me, Menton, most inferior point on bony chin; S, sella, centre of sella turcica; Ba, basion; Go, gonion; PNS, posterior nasal spine; Pt, Ptergoid; Ptm, pterygomaxillary fissure point; U, the tip of the uvula; MPW, foot point of perpendicular line from point U to posterior pharyngeal wall; TPPW, point of intersection of posterior pharyngeal wall and extension of line B-Go; TB, point of intersection of base of tongue and extension of line B-Go; V, the most posteroinferior point on base of tongue; LPW, foot point of perpendicular line from point V to posterior pharyngeal wall; C3, the middle point of the third vertebra; C4, the middle point of the forth vertebra; AD2, the intersection point between the perpendicular line connecting PNS and Ba-S and the posterior pharyngeal wall; H1, the most superior point of hyoid bone; H2, the most anterior point of hyoid bone; H3, the most inferior point of hyoid bone

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Table 1 Description of the cephalometric measurements
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Statistical analysis

The statistical analysis was performed using SPSS 25.0 software (SPSS Inc., Chicago, IL, USA). Descriptive data were presented as mean ± standard deviation (SD), median with interquartile range (IQR), or number (percentage), as appropriate. Correlation coefficients were measured through Pearson correlation analysis if the variables followed a normal distribution, while those that were not normally distributed were examined through Spearman rank correlation analysis. Based on the univariate analyses, the correlation between the cephalometric variables and severity of OSA was determined by multiple regression analysis. P<0.05 was considered statistically significant.

The sample size calculation was performed based on a previous study [26]. In order to detect a correlation of ± 0.45 using a two-sided hypothesis test with a significance level of 0.05 and a power of 0.80, 36 subjects would be required for each group.

Results

Demographic data

A total of 105 adult participants were included in this study, with a male to female ratio of 64:41. The mean age was 28.5 ± 7.28 years, ranging from 18 to 52 years. The mean age for males was 28.8 ± 7.49 years, while for females it was 28.0 ± 7.01 years (Table 2 provides detailed demographic data). Correlation analysis showed that AHI was negatively correlated with LSaO2 in both gender groups (Male: r=-0.644, P<0.001, Female: r=-0.561, P<0.001). To investigate gender differences in the PSG results and craniofacial parameters used in this study, the participants were divided into male and female groups accordingly. As both AHI and LSaO2 showed significant variation between different genders, further analysis was conducted separately for each gender group to explore potential gender-specific predictors for OSA risk.

Table 2 Demographic, polysomnographic and cephalometric parameters
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Correlation analysis between upper airway and hyoid bone-related parameters and OSA-severity indicators

In this study, we investigated the associations between upper airway and hyoid bone-related parameters and OSA-severity indicators (AHI and LSaO2). In male individuals, U-MPW, TB-TPPW, H2-S-N, H1-VC3C4, H3-MP, H3-Go, H3-Me-Go exhibited statistically significant correlations with AHI. While U-MPW, TB-TPPW, H3-MP and H3-Me-Go demonstrated statistically significant correlations with AHI in female groups (Table 3). Regarding LSaO2 levels, U-MPW, H1-VC3C4, H3-MP and H3-Go were identified as parameters with statistically significant correlations in male group. In female group, the only statistically significant parameter was H3-PtPtm (Table 4).

Table 3 Correlation analysis between cephalometric parameters and AHI in male and female individuals
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Table 4 Correlation analysis between cephalometric parameters and LSaO2 in male and female individuals
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Multiple regression analysis between upper airway and hyoid bone-related parameters and OSA-severity indicators

Based on the results of the correlation analysis presented above, we selected the parameters that showed strong correlation with AHI and LSaO2 in both gender groups to perform a multiple regression analysis.

The Multiple regression coefficients were employed to determine the correlation between the selected variables with AHI (Tables 5 and 6). The model was designed to predict AHI based on the upper airway and hyoid bone-related parameters. AHI and LSaO2 were used as dependent variables to study the correlation between other independent variables. The variance inflation factor (VIF) values between 1 and 5 of the variables indicated moderate multicollinearity between the variables and AHI/LSaO2. Additionally, we found a significant correlation between H1-VC3C4 with AHI in the male group. In terms of LSaO2, H1-VC3C4 demonstrated a significant correlation in males, while H3-Me-Go showed a significant correlation with LSaO2 in females. Both regression models proved effective in predicting the AHI and LSaO2 based on the R2 value and F value, but the level of correlation is relatively low.

Table 5 Multiple regression for cephalometric variables associated with AHI in male and female individuals
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Table 6 Multiple regression for cephalometric variables associated with LSaO2 in male and female individuals
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Discussion

The pathogenesis of obstructive sleep apnea involves recurrent upper airway obstruction, resulting in sleep fragmentation and intermittent hypoxia during sleep. This condition affects 3-20% of the general population, with its prevalence on the rise [27]. Untreated OSA is associated with long-term detrimental health outcomes, including cognitive impairment, cardiovascular disease, and metabolic disorders, thereby imposing a significant socioeconomic burden [28].

Clinically, PSG is commonly used to assess the severity of OSA. The primary diagnostic strategies typically involve the AHI measurements derived from PSG recordings. However, AHI alone merely quantifies the frequency of apneas and hypopneas per hour of sleep, without reflecting the extent of hypoxia experienced during these events [29]. Recent studies showed that patients with the similar AHI values may exhibit variations in clinical symptoms and complications due to different level of hypoxia [30]. Fernandes et al. reported that AHI was weakly correlated with an inflammatory profile in OSA patients; while individuals experienced lower nocturnal oxygen saturation were more likely to exhibit elevated levels of total leukocytes, neutrophils, neutrophil-lymphocyte ratio, and C-reactive protein concentration, suggesting a potential correlation between nocturnal oxygen saturation and inflammation levels [31]. In addition, certain patients fail to demonstrate sufficient improvement in hypoxemia in spite of reductions observed in their AHI following treatment interventions. Therefore, pre-treatment LSaO2 should be considered when planning therapeutic strategies for OSA management as it closely relates to improvements achieved in oxygenation levels subsequent to OSA treatment [32].

As an effective tool to identify the risk of OSA, cephalometric analysis has been widely utilized to investigate the occurrence of OSA based on AHI [33, 34]. Nevertheless, it remains unclear whether the anatomic features of the upper airway and hyoid bone position depicted by lateral cephalograms can accurately reflect the severity of nocturnal hypoxia. Recent research implied that OSA and sleep-related hypoxia have been associated with higher rates of hospitalization and mortality among patients with Coronavirus disease 2019 (COVID-19) [35]. An analysis involving 204 orthodontic patients who tested positive for COVID-19 revealed that lower face height, vertical airway length, and a superiorly positioned hyoid bone were correlated with more severe COVID-19 symptoms, indicating that craniofacial morphological features may be a link between OSA severity and OSA-related respiratory diseases [36].

In this study, we explored the relationship between morphological characteristics observed on cephalogram and the severity of OSA based on both AHI and LSaO2. As anticipated, several cephalometric parameters exhibited statistically significant correlations with AHI and LSaO2, with variations observed between male and female groups. U-MPW and TB-TPPW reflected the width of upper airway, which are significantly correlated with AHI in both gender groups. H3-MP and H3-Me-Go represented the position of hyoid bone. Our findings showed that a lower positioned hyoid bone with a greater distance from the hyoid bone to the inferior line of the mandible were associated with higher AHI values in male and female groups. Similarly, Mathilde Jadoul et al. found that the distance between the hyoid bone and the mandibular plane was increased in OSA patients compared to the non-OSA group, which may be partially attributed to a reduced size of mandible [37]. Additionally, H2-S-N, H1-VC3C4, and H3-Go showed statistical significance only in males. A greater H2-S-N value indicated a more anteriorly positioned hyoid bone linked to higher AHI levels, while larger values of H1-VC3C4 and H3-Go reflected an elongated distance from the hyoid bone to mandible. The results on H3-Go align well with previous studies [14, 38]. In brief, our findings suggest that U-MPW, TB-TPPW, H3-MP, and H3-Me-Go can serve as common indicators for higher AHI levels across both genders; however, H2-S-N, H1-VC3C4, and H3-Go may be more suitable for evaluating elevated risk of higher AHIs specifically in males.

Regarding the correlation analysis of cephalometric parameters and LSaO2, we found that U-MPW, H1-VC3C4, H3-MP and H3-Go are statistically significant in male group, which is similar to the results on AHI. However, only H3-PtPtm, an indicator of posterior positioned hyoid bone, is significant in the female group.

Previous studies have consistently reported a higher prevalence and severity of OSA in males compared to females, which can be affected by sex hormones, body fat distribution patterns, neck circumference, and central ventilatory control [39, 40]. It’s quite intriguing to find out that a gender-dependent pattern also extends to the association between cephalometric parameters related to upper airway morphology and hyoid bone position with OSA severity in adult individuals. Previous studies have revealed that OSA patients presented a lower hyoid position compared to control groups, and hyoid bone is positioned more superiorly and posteriorly in females than males among different skeletal patterns [14, 41, 42]. Similarly, we noticed that H3-PtPtm, a parameter associated with the horizontal position of the hyoid bone, was correlated with LSaO2 in female patients. However, a significant correlation between vertical position of hyoid bone and LSaO2 was only observed in male patients (Table 4). This suggests that the horizontal position of the hyoid bone may also reflects OSA severity in a gender-specific pattern. Further studies should investigate whether the divergence in cephalometric parameters between males and females contributes to the differential clinical manifestations of OSA.

Interestingly, none of the statistically significant AHI-related parameters are present in the correlation analysis of LSaO2 in females, which suggests that different measurements should be considered to evaluate the apnea-hypopnea frequency and hypoxia risk in female individuals. In the multiple regression analysis, only H1-VC3C4 is recognized as statistically significant in predicting both AHI and LSaO2 in males. Additionally, a negative correlation is observed between H3-Me-Go and LSaO2, indicating that an increased distance from hyoid bone to mandible is associated with decreased oxygen saturation levels. Although all models pass F examination effectively, the relatively low R2 value across all groups indicates that the upper airway and hyoid bone-related cephalometric parameters can only explain a moderate portion of changes in AHI and LSaO2. Recent studies have shown that reduced nocturnal oxygen saturation not only reflects the severity of OSA, but also increases the severity of systemic diseases related to OSA as an independent risk factor. Mahmoud et al. found that nocturnal hypoxemia but not AHI, was correlated with glycosylated hemoglobin levels in OSA patients combined with type II diabetes mellitus [43]. Similar results were also observed in patients suffering from pulmonary and cardiovascular diseases, emphasizing the advantage of hypoxia-related indicators in capturing the depth of OSA-related symptoms compared to conventional “frequency-based” metrics like AHI [44, 45]. Therefore, investigating whether there is any hypoxemia-related cephalometric parameter is of great clinical significance. Our results indicate that while some cephalometric parameters are correlated with both AHI and LSaO2, there are also LSaO2-specific parameters that can be utilized to predict the severity of OSA-related complications when no abnormalities are present in AHI-related parameters.

According to the American Academy of Sleep Medicine Clinical Practice Guideline, the primary healthcare provider to diagnose and treat OSA patients should be a sleep medicine specialist. Therefore, it appears that orthodontists are not necessarily involved in the diagnosis and management of OSA [46]. However, since many OSA patients seek orthodontic treatment for malocclusion, it’s quite easy for orthodontists to identify the risk of OSA by evaluating the clinical symptoms and through radiological examinations such as lateral cephalogram [47]. When performing cephalometric analysis, orthodontists can readily evaluate the patient’s craniofacial morphological features while simultaneously predicting the risk of OSA. In addition, orthodontists have the responsibility to consider the effect of orthodontic or orthognathic intervention on the prognosis of OSA. Although maxillomandibular advancement surgery has proven successful in treating OSA surgically, its association with orthognathic surgery, higher cost as well as the consequent change in profile often discourages patients from selecting this approach [48, 49]. In contrast, mandibular advancement devices demonstrate efficacy for certain patients, but their side effects such as pain and temporomandibular discomfort, protrusion of lower incisors and appearance of lateral gaps relegate them to a last-resort status [50, 51]. Other orthodontic treatments for OSA such as maxillary expansion either lack sufficient reliability or require long-term clinical follow up [52, 53]. Therefore, based on previous research and the results of this study, we suggest that orthodontists should pay closer attention to the cephalometric parameters related to upper airway morphology and hyoid-bone position-especially those related to AHI and LSaO2 levels. If the cephalometric analysis implies a higher risk of OSA, it is advisable for the orthodontist to consider recommending the patient to consult a sleep specialist for further advice.

Limitations

There are several limitations of our study. Firstly, all the subjects were Chinese patients, and the sample size was small. Besides, given that this study was designed as a retrospective study, our examination was confined to the accessible data, specifically lateral cephalograms and PSG reports, which precluded the inclusion of a control group. Furthermore, there were uncontrolled variables such as weight, height, lifestyle habits and other socioeconomic factors. Although lateral cephalogram remains valuable for evaluating craniofacial anatomical features due to its ease of use, cost-effectiveness, and widespread availability in many hospitals, its accuracy of diagnosing the widths of respiratory system was insufficient compared with CBCT [54, 55]. In addition, while cephalometric analysis can reflect anatomical characteristics of the craniofacial region, many studies reported inconsistencies in upper airway width changes observed via cephalograms following orthodontic or orthognathic treatment when compared to changes in OSA-severity indicators presented by PSG reports; these discrepancies probably arise from a lack of three-dimensional information [56, 57].

Conclusion

Several cephalometric parameters related to upper airway width and hyoid bone position were correlated with the severity of OSA as indicated by AHI and LSaO2. Some of the parameters were gender-specific. A narrower upper airway width was associated with increased AHI, while a more inferiorly positioned hyoid bone in relation to the mandible was negatively correlated with LSaO2. Our findings highlight the role of key cephalometric parameters in predicting OSA severity based on AHI and LSaO2 levels.

Data availability

No datasets were generated or analysed during the current study.

Abbreviations

OSA:

Obstructive sleep apnea

AHI:

Apnea-hypopnea index

LSaO2 :

Lowest nocturnal oxygen saturation

PSG:

Polysomnography

VIF:

Variance inflation factor

IQR:

Interquartile range

SD:

Standard deviation

AI:

Artificial intelligence

H2-S-N:

Angle between point H2 and N at S

H3-Me-Go:

Angle between point H3 and Go at Me

PNS-UPW:

Distance between PNS and UPW

PNS-AD2:

Distance between PNS and AD2

U-MPW:

Distance between U and MPW

TB-TPPW:

Distance between TB and TPPW

V-LPW:

Distance between V and LPW

H3-PtPtm:

Distance between H3 and line Pt-Ptm

H3-C4:

Distance between H3 and C4

H1-VC3C4:

Distance between H1 and perpendicular bisector of line C3-C4

H3-MP:

Distance between H3 and mandibular plane

H3-Me:

Distance between H3 and Me

H3-Go:

Distance between H3 and Go

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Acknowledgements

We thank the department of radiology in Hospital of Stomatology, Sun Yat-sen University with cephalogram data management.

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Author notes

  1. Zhili Dong and Yue Zeng contributed equally to this work.

Authors and Affiliations

  1. Hospital of Stomatology, Guangdong Provincial Clinical Research Center of Oral Diseases, Sun Yat-sen University, Guangzhou, Guangdong, China

    Zhili Dong, Jieyi Chen, Liping Wu & Hong Hong

  2. Department of Stomatology, The People’s Hospital of Guangxi Zhuang Autonomous Region & Guangxi Academy of Medical Sciences, Nanning, Guangxi, China

    Yue Zeng

Authors
  1. Zhili Dong
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Contributions

Z.D: Conceptualization, methodology, writing original draft. Y.Z: Review and editing, investigation, data curation. J.C: Investigation, review and editing. L.W: Review and editing, data curation. H.H: Review and editing; supervision. All authors reviewed the manuscript.

Corresponding authors

Correspondence to Liping Wu or Hong Hong.

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Ethics approval and consent to participate

This study was approved by the Medical Ethics Committee of Hospital of Stomatology, Sun Yat-sen University (Approval No.KQEC-2024-99-01). Informed written consent was obtained from all the patients.

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Not applicable.

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The authors declare no competing interests.

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Dong, Z., Zeng, Y., Chen, J. et al. Upper airway and hyoid bone-related morphological parameters associated with the apnea-hypopnea index and lowest nocturnal oxygen saturation: a cephalometric analysis. BMC Oral Health 25, 583 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12903-025-05969-5

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Keywords

BMC Oral Health

ISSN: 1472-6831

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