Choroidal Vascular and Oropharyngeal Morphological Indicators in Predicting CPAP Treatment Efficacy in Severe OSAS Patients: A Prospective Cohort Study

Choroidal Vascular and Oropharyngeal Morphological Indicators in Predicting CPAP Treatment Efficacy in Severe OSAS Patients: A Prospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Choroidal Vascular and Oropharyngeal Morphological Indicators in Predicting CPAP Treatment Efficacy in Severe OSAS Patients: A Prospective Cohort Study Chenxu Wang, Jingjing Yu, Yue Gu, Zhen Wu, Yimin Xia This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6389207/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Oct, 2025 Read the published version in Head & Face Medicine → Version 1 posted 11 You are reading this latest preprint version Abstract Objective The goal of this paper is to explore the value of choroidal vascular and oropharyngeal morphological indicators in predicting the efficacy of Continuous Positive Airway Pressure (CPAP) treatment in patients with severe Obstructive Sleep Apnea Syndrome (OSAS). Methods A total of 245 patients with severe OSAS between January 2022 and June 2024 from a hospital, treated with CPAP, were enrolled. Patients were divided into two groups based on treatment efficacy: the Good response group and the Poor response group. Choroidal vascular indicators [subfoveal choroidal thickness (SF-CT), choriocapillaris vessel density (CC-VD), choroidal vascularity index (CVI)] and oropharyngeal morphological indicators [posterior nasal spine to menton distance (PNS-Me), hyoid-mental distance (HMD), soft palate length (posterior nasal spine to uvular tip point, PNS-P1)] were compared between the two groups. Receiver Operating Characteristic (ROC) curves were drawn to analyze the predictive efficacy of these indicators for CPAP treatment in severe OSAS patients. A nomogram and calibration curve were created to develop a prediction model for CPAP treatment efficacy in severe OSAS patients. Results In the Poor response group, the longest apnea duration (LAD), percentage of time with oxygen saturation < 90% (TS90%), and apnea-hypopnea index (AHI) were all significantly higher than those in the Good response group. The lowest arterial oxygen saturation (LSaO2) was notably lower in the Poor response group compared to the other one ( P < 0.05). The area under the curve (AUC) values ​​of SF-CT, CC-VD, and CVI for predicting the outcome of IBD patients were 0.835, 0.805, and 0.910, respectively. The AUC values ​​of PNS-Me, HMD, and PNS-P1 were 0.897, 0.937, and 0.898, respectively. In addition, the nomogram prediction model constructed with choroidal vascular and oropharyngeal morphology indicators had high accuracy. Conclusion Choroidal vascular and oropharyngeal morphological indicators have a good predictive effect on CPAP treatment efficacy in patients with severe OSAS. Choroidal vascular indicators Oropharyngeal morphological indicators Severe OSAS patients CPAP Treatment efficacy Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Obstructive Sleep Apnea Syndrome (OSAS) is a common clinical sleep disorder characterized by repeated upper airway obstruction during sleep, accompanied by arousals and daytime sleepiness. As the condition progresses, it may lead to symptoms such as chronic intermittent hypoxia and carbon dioxide retention [1-3] . Epidemiological studies have found that the prevalence rate of OSAS in adults is around 20%, with approximately 90% of patients remaining undiagnosed and not receiving active treatment. The early diagnosis rate of OSAS is low [4] . Due to the relaxation of the soft tissues around the oropharynx or the respiratory muscles during sleep, the upper airway is prone to obstruction, which may hinder gas exchange in the respiratory tract and lead to intermittent hypoxia. Prolonged intermittent hypoxia can cause neurological damage [5] . Cognitive dysfunction is prevalent in patients with severe OSAS and significantly impairs their life quality. Studies show that the incidence of this complication ranges from 35.2% to 80.0% [6] . Furthermore, OSAS increases the risk of Alzheimer's disease in patients, possibly due to the imbalance of neurotransmitter systems in the brain caused by sleep deprivation, leading to impaired memory pathways and reduced efficiency in synaptic signaling [7] . Therefore, it is particularly important to implement scientific and effective treatment plans for patients with severe OSAS. Continuous positive airway pressure (CPAP) is currently the most effective treatment for patients with moderate to severe OSAS. The primary mechanism of action is to provide positive airway pressure through a ventilator, which helps maintain airway tension, effectively prevents upper airway airflow obstruction during sleep and improves respiratory function and sleep quality of OSAS patients [8] . CPAP treatment not only improves hypoxemia in OSAS patients but also reduces the frequency of apneas during sleep, restores sleep structure, and helps alleviate daytime sleepiness to some extent, thus reducing cognitive dysfunction [9] . However, the use of CPAP may cause various complications (such as nasal congestion, dry mouth, barotrauma, upper respiratory tract infections, pneumothorax, etc.), which may hinder patient recovery. Therefore, regular assessment of the effectiveness and side effects of CPAP treatment during the course of therapy is essential. In recent years, clinical observations have revealed that intermittent tissue hypoxia and arousal symptoms in patients with severe OSAS can stimulate the sympathetic nervous system, triggering a series of cascading responses. The OSAS also affects the ocular vascular autoregulatory function, because of the fact that intermittent hypoxia can disrupt the balance between vasoconstrictor and vasodilator factors in the circulation, leading to abnormal autonomic regulation of the optic nerve vasculature, which in turn results in impaired retinal tissue function. Choroidal lesions are relatively common in this context [10, 11] . Therefore, monitoring the improvement of choroidal vascular indicators in patients with severe OSAS is of significant value in evaluating the effectiveness of CPAP treatment. Studies suggest that the onset of OSAS is closely related to upper airway narrowing, which is caused by the relaxation of oropharyngeal muscle tone and changes in the morphological structure of the airway [12] . Clinically, previous interventions for severe OSAS patients have focused on leading forwards the mandible or tongue to prevent oropharyngeal soft tissues from obstructing the posterior pharyngeal wall, thereby widening upper airway and ensuring unobstructed breathing during sleep. Therefore, changes in oropharyngeal morphological parameters before and after CPAP treatment in severe OSAS patients are also important observational indicators for assessing treatment efficacy. This study primarily analyzes the predictive role of choroidal vascular indicators and oropharyngeal morphological indicators in determining the effectiveness of CPAP treatment for severe OSAS patients, aiming to provide accurate reference for further modifying treatment plans. Information and methods General Information Study Subjects This study is a single-center, prospective observational analysis, involving 245 patients with severe OSAS from a hospital between January 2022 and June 2024. The study has been approved by the hospital's ethics committee, and all procedures were conducted in accordance with the ethical standards outlined in the 1964 Declaration of Helsinki and its subsequent amendments. Inclusion and exclusion criteria Inclusion criteria: (1) patients who meet the diagnostic criteria for OSAS outlined in the Society of Anesthesia and Sleep Medicine Guidelines on Preoperative Screening and Assessment of Adult Patients with Obstructive Sleep Apnea [13] , confirmed by clinical symptoms and imaging examination; (2) apnea-hypopnea index (AHI) ≥ 30; (3) age ≥ 18 years old; (4) no other eye diseases; (5) patients and their families have signed the Informed Consent Form ; (6) no psychiatric disorders. Exclusion criteria: (1) patients with malignant tumors; (2) patients with contraindications for the relevant examinations in this study; (3) patients with severe organ dysfunction, such as severe heart, liver, or kidney failure; (4) patients with active systemic infections; (5) patients with chronic obstructive pulmonary disease, interstitial lung disease, or other chronic hypoxic diseases; (6) patients with severe neurological diseases or cognitive dysfunction; (7) pregnant or breastfeeding women. General information This is a retrospective study, and all patient data were collected through the medical record system. The collected information includes: gender, age, medical history (all diabetic patients met the diagnostic criteria for diabetes outlined in the 2019 ESC Guidelines on Diabetes, Pre-diabetes, and Cardiovascular Diseases developed in collaboration with the EASD [14] ; all hypertensive patients met the diagnostic criteria for hypertension as outlined in the Blood Pressure and the New ACC/AHA Hypertension Guidelines [15] ), course of the desease (determined through communication with patients by professional physicians using scientific interviewing techniques), smoking history (smoking ≥ 100 cigarettes within the past year), alcohol consumption history (drinking ≥ 1 time per week for at least 5 continuous months), body mass index (BMI, BMI = weight (kg)/height squared (m 2 )), etc. CPAP and polysomnography (PSG) All patients received CPAP treatment using a non-invasive ventilator (Model: REMstar Auto 557P, Philips Respironics, USA). The initial pressure was set at 4 cmH 2 O (1 cmH 2 O = 0.098 kPa). Based on the signals obtained from PSG monitoring (including electroencephalogram, electromyogram, electrooculogram, apnea, heart rate, nasal and oral airflow and blood oxygen levels, etc.), the CPAP pressure is adjusted to suit patients condition, then the pressure is gradually increased until their blood oxygen saturation reaches ≥ 90% and apnea is resolved. During CPAP treatment, all patients underwent PSG monitoring using a polysomnography device (Model: TREX HD, NICO Instruments, USA). The monitoring period was from 9:00 PM to 6:00 AM the following morning. Patients were instructed to refrain from alcohol, smoking, coffee, strong tea and taking sedative or psychotropic medications for 24 hours prior to the PSG test. The monitoring parameters included: electroencephalogram, electrooculogram, nasal and oral airflow, mandibular electromyogram, blood oxygen saturation and thoracoabdominal respiratory movement. The key sleep respiratory parameters recorded included: longest apnea duration (LAD), lowest arterial oxygen saturation (LSaO2), percentage of time with SpO2 < 90% (TS90%) and apnea-hypopnea index (AHI). A trained technician reviewed and assisted in generating the required sleep respiratory parameters for this study. Ophthalmic examination Optical coherence tomography (OCT) examination by one ophthalmologist was conducted for all patients. The device used was the RTVueXR Avanti OCT instrument (Optovue, USA). Procedure: before the examination, patients were administered mydriatic drops (compound tropicamide) to dilate the pupils followed by sitting comfortably with their chin on a support, and different regions of the retina were scanned. The device’s software was used for automatic measurement. Three measurements were taken from the same eye, and the average value was recorded. The data were then uploaded to a computer-based image analysis system for further analysis. Measured parameters: a. Subfoveal choroidal thickness (SF-CT): The inner boundary of the choroid at the Bruch membrane of the macular fovea, from 9 μm to the choroidal-scleral interface. b. Choriocapillaris vessel density (CC-VD): Blood flow density in the capillary layer, located 30 μm to 60 μm below the retinal pigment epithelium. c. Choroidal vascularity index (CVI): The ratio of the vascular luminal area to the total choroidal area [16] . Oropharyngeal CT examination The instrument used was a cone-beam CT scanner (Model: 3DXam, KaVo, Germany). Patients were instructed to sit upright, with both eyes looking straight ahead. The frankfurt horizontal (FH) plane was aligned parallel to the floor, and the teeth were positioned in the natural occlusion with the jaw in the centric position. After the scan, the oral landmarks were identified, including: posterior nasal spine (PNS), uvular tip (U) and mental point (Me). Based on these landmarks, the following (a, b and c) oropharyngeal morphological indicators were measured three times, and the average value was taken. a. Posterior Nasal Spine to Menton Distance (PNS-Me): The distance from the PNS point to the Me point; b. Hyoid-Mental Distance (HMD): The distance between the hyoid bone and the lower margin of the mandible; c. Posterior Nasal Spine to Uvular Tip point (PNS-P1): The distance from the junction of the hard and soft palate to the U point. Laboratory tests Blood samples (4 mL) were collected from all patients via fasting peripheral venous blood and placed in vacuum blood collection tubes. The blood samples were promptly sent for testing and centrifuged at room temperature for 15 min (1900 r·min − 1 ) to obtain serum and plasma samples, which were stored at low temperatures (-80°C) for further analysis. Complete blood count (CBC) test. Instrument: 5-part hematology analyzer (Model: BC5300, Shenzhen Mindray, China). Laboratory personnel strictly followed the operating procedures to conduct CBC tests on all patient blood samples, recording the red blood cell count, neutrophil count, and hemoglobin concentration. It is important to complete the blood sample testing within 4 hours of sample collection. Blood glucose test. Instruments: Open automatic biochemical analyzer (Model: RocheModular P800, Roche, Switzerland) and fully automatic HbA1c analyzer (Model: HLC-723 G7, Tosoh Corporation, Japan). Laboratory personnel tested the fasting blood glucose (FBG) and glycosylated hemoglobin (HbAlc) content in serum samples; FBG detection used glucose oxidase method and HbAlc detection used high performance liquid chromatography. Note that the blood sample testing should be completed within 4 hours of sample collection. Efficacy evaluation criteria The efficacy was evaluated based on the relevant standards from the Sleep Apnea Syndrome (SAS) Clinical Practice Guidelines 2020 [17] as follows: ① significantly effective: clinical symptoms and signs are significantly improved, with a decrease in AHI ≥ 10 times·h⁻¹ after treatment; ②effective: clinical symptoms and signs are improved, with a decrease in AHI ≥ 5 times·h⁻¹ after treatment; ③ ineffective: no significant changes in clinical symptoms, signs, or AHI after treatment. Patients with significantly effective and effective outcomes were included in the Good response group, while those with ineffective outcomes were included in the Poor response group. Statistical analysis Data were analyzed using IBM SPSS 27.0 (IBM Corp., Armonk, N.Y., USA) statistical software. Counting data were expressed as [n] and analyzed by the x ² test. For measuring data, the Shapiro-Wilk test was used to assess the normality of the distribution. Non-normally distributed data were expressed as median and interquartile range [M (P25, P75)], while the data that met the normal distribution were expressed as ( ± s), and the t test was used, with P < 0.05 as statistically significant. The relationship between choroidal vascular indicators, oropharyngeal morphology indicators, and CPAP treatment efficacy in severe OSAS patients was analyzed using multivariate Logistic regression. A nomogram model was constructed, and calibration curves were drawn for internal validation to assess the model's discrimination and calibration. The significance level was set at α = 0.05. Results General information and laboratory tests General information In this study, 86 of the 245 patients were evaluated as receiving significantly effective CPAP treatment, and 78 were effective, who were included in the Good response group (n = 164); 81 ineffective patients were included in the Poor response group (n = 81). There was no significant difference in gender, age, average course of disease, BMI, smoking history, drinking history and medical history between the Good response group and the Poor response group ( P values ​​were all > 0.05, Table 1 ). Table 1 Comparison of general information between the two groups Items Good response group (n = 164) Poor response group (n = 81) χ 2 /Z P Gender (number) Male 93(56.71) 47(58.02) 0.038 0.845 Female 71(43.29) 34(41.98) Age [M(P25, P75)] 45.00(43.00,48.00) 46.00(43.00,49.50) -0.981 0.327 Average course of disease [month, M(P25, P75)] 7.57(6.50,8.40) 7.36(6.50,8.70) -1.058 0.290 BMI[kg·m − 2 , M(P25, P75)] 25.63(24.10,27.30) 26.09(24.70,27.80) -1.790 0.074 Smoking history 28(17.07) 15(18.52) 0.078 0.780 Drinking history 35(21.34) 18(22.22) 0.025 0.875 Medical history Hypertension 39(23.78) 21(25.93) 0.135 0.713 Diabetes 25(15.24) 13(16.05) 0.027 0.870 Laboratory tests No significant differences were observed in red blood cell count (5.34 ± 1.03×10 12 /L vs 5.57 ± 1.01×10 12 /L), neutrophil count (7.18 ± 1.49×10 9 /L vs 7.45 ± 1.56×10 9 /L), hemoglobin concentration (157.36 ± 17.84 g·L − 1 vs 161.29 ± 17.36 g·L − 1 ), FBG (4.12 ± 0.93 mmol·L − 1 vs 4.29 ± 0.96 mmol·L − 1 ) and HbAlc (6.20 ± 1.14% vs 6.37 ± 1.28%) between the two groups (all P >0.05, Table 2 ). Table 2 Comparison of laboratory test results between the two groups after treatment Items Good response group (n = 164) Poor response group (n = 81) t P Red blood cell count (×10 12 /L) 5.34 ± 1.03 5.57 ± 1.01 1.655 0.099 Neutrophil count (×10 9 /L) 7.18 ± 1.49 7.45 ± 1.56 1.314 0.190 Hemoglobin concentration (g·L − 1 ) 157.36 ± 17.84 161.29 ± 17.36 1.636 0.103 FBG (mmol·L − 1 ) 4.12 ± 0.93 4.29 ± 0.96 1.332 0.184 HbAlc (%) 6.20 ± 1.14 6.37 ± 1.28 1.054 0.293 Sleep breathing parameters Compared with the parameters of the Good response group, the LAD (23.16 ± 1.95 s vs 35.22 ± 2.78 s), TS90% (8.34 ± 0.76% vs 19.65 ± 1.53%) and AHI (17.68 ± 1.03 times·h − 1 vs 32.05 ± 2.94 times·h − 1 ) of the patients in the Poor response group after treatment were higher, and the differences were statistically significant ( P < 0.05), while the TS90% (89.12 ± 2.04% vs 78.45 ± 3.69%) showed contradictory results with statistically significant difference ( P < 0.05, Fig. 1 ). Prediction of CPAP treatment efficacy of choroidal vascular indicators in patients with severe OSAS Comparison of choroidal vascular indicators between the two groups Compared with the Good response group, the SF-CT (273.07 ± 29.43 µm vs 319.52 ± 37.14 µm) and CVI (33.06 ± 1.25% vs 35.45 ± 1.33%) values ​​of patients in the Poor response group after treatment were higher, and the difference was statistically significant ( t1 = 10.631, t2 = 8.483, P values ​​were both < 0.001); compared with the Good response group, the CC-VD (47.95 ± 4.22% vs 43.49 ± 3.04%) values ​​of the patients in the Poor response group after treatment were lower with statistically significant difference ( t3 = 13.782, P < 0.001, Table 3 ). Table 3 Comparison of choroidal vascular indicators between the two groups Indicators Good response group (n = 164) Poor response group (n = 81) t P SF-CT (µm) 273.07 ± 29.43 319.52 ± 37.14 10.631 <0.001 CC-VD (%) 47.95 ± 4.22 43.49 ± 3.04 8.483 <0.001 CVI (%) 33.06 ± 1.25 35.45 ± 1.33 13.782 <0.001 ROC of choroidal vascular indicators predicting the efficacy of CPAP treatment in patients with severe OSAS ROC curves were drawn and it was found that the AUC value of SF-CT, CC-VD and CVI in predicting the efficacy of CPAP treatment in patients with severe OSAS was 0.835 (95% CI: 0.767–0.893), 0.805 (95% CI: 0.758–0.858) and 0.910 (95% CI: 0.878–0.944) respectively, indicating that the choroidal vascular indicators have a high predictive value for the efficacy of CPAP treatment in patients with severe OSAS, as shown in Fig. 2 A. Nomogram and calibration curve for choroidal vascular indicators predicting the efficacy of CPAP treatment in patients with severe OSAS A nomogram model for choroidal vascular indicators predicting the efficacy of CPAP treatment in patients with severe OSAS was constructed and a calibration curve was drawn. It was found that SF-CT, CC-VD, and CVI had high values ​​for predicting the efficacy of CPAP treatment in patients with severe OSAS, and the calibration curve was similar to the standard curve, indicating that the consistency and predictive ability of the nomogram were good, and the accuracy of the model was high. As shown in Fig. 3 . Prediction of the efficacy of CPAP treatment in patients with severe OSAS by oropharyngeal morphological indicators Comparison of oropharyngeal morphological indices between the two groups Compared with the Good response group, the patients in the Poor response group had lower mean values ​​of PNS-Me (6.51 ± 1.14 mm vs 4.68 ± 0.90 mm) and HMD (23.40 ± 1.87 mm vs 19.83 ± 1.46 mm) after treatment, and the difference was statistically significant ( t4 = 12.629, t5 = 15.059, P values ​​were both < 0.001), while the patients in the Poor response group had higher mean values ​​of PNS-P1 (40.09 ± 1.09 mm vs 41.92 ± 1.01mm) after treatment, and the difference was statistically significant ( t6 = 12.661, P < 0.001, Table 4 ), as shown in for details. Table 4 Comparison of oropharyngeal morphological indicators between the two groups Indicators Good efficacy group (n = 164) Less effective group (n = 81) t P PNS-Me (mm) 6.51 ± 1.14 4.68 ± 0.90 12.629 <0.001 HMD (mm) 23.40 ± 1.87 19.83 ± 1.46 15.059 <0.001 PNS-P1 (mm) 40.09 ± 1.09 41.92 ± 1.01 12.661 <0.001 ROC of oropharyngeal morphology indicators for predicting the efficacy of CPAP treatment in patients with severe OSAS ROC curves were drawn and it was found that the AUC value of PNS-Me, HMD and PNS-P1 for predicting the efficacy of CPAP treatment in patients with severe OSAS was 0.897 (95% CI: 0.859–0.925), 0.937 (95% CI: 0.907–0.964) and 0.898 (95% CI: 0.862–0.935),respectively, indicating that the oropharyngeal morphology indicators have a high predictive value for the efficacy of CPAP treatment in patients with severe OSAS, as shown in Fig. 2 B. Nomogram and calibration curve for oropharyngeal morphology indicators predicting the efficacy of CPAP treatment in patients with severe OSAS A nomogram model for oropharyngeal morphology indicators predicting the efficacy of CPAP treatment in patients with severe OSAS was constructed and a calibration curve was drawn. It was found that PNS-Me, HMD and PNS-P1 had high values ​​for predicting the outcome of IBD patients, and the calibration curve was similar to the standard curve, indicating that the consistency and predictive ability of the nomogram were good, and the model is highly accurate. As shown in Fig. 4 . Discussion OSAS mainly refers to hypoventilation and repeated apnea caused by upper airway stenosis or obstruction during sleep, which results in the body being in an intermittent hypoxic state and fragmented sleep [18] . CPAP is the first-line solution for the treatment of OSAS, and the efficacy evaluation of this technology has always been a key issue of concern to clinical physicians. With the deepening of research, some scholars have found in recent years that OSAS patients have a higher risk of developing central serous retinochoroidopathy; continuous hypoventilation may activate the body's hypoxia-inducible factor, promote the high expression of angiogenic factors, damage vascular endothelial tissue, and change vascular permeability, ultimately leading to thinning of the choroid and abnormal vascular structure [19] . Related reports point out that the mechanism of recurrent central serous retinochoroidopathy in OSAS patients may be related to a series of pathophysiological changes (including choroidal vasoconstriction, local blood flow reduction, etc.) caused by direct stimulation of the choroid by long-term secondary hypoxemia and hypercapnia [20] . Studies have confirmed that hypoxemia and hypercapnia can lead to choroidal vasodilation and increased blood flow in the early stages. The hypoxic state of patients with severe OSAS lasts for a long period of time, which can easily lead to choroidal vascular autoregulation dysfunction, increase vascular resistance, aggravate local blood hyperviscosity and trigger metabolic disturbance, ultimately causing endothelial cell damage and increasing the risk of local thrombosis. At the same time, local blood flow stagnation can also increase red blood cell aggregation, leading to shortening of microvilli and aggravation of choroidal vascular deformation [21] . The retina has a high oxygen demand and the choroid has a relatively rich vascular tissue structure. The photoreceptors are most densely populated in the fovea, and their blood supply mainly comes from the choroid, which is the thickest in this area, and the thickness of the choroid gradually becomes thinner from the fovea to the periphery. SF-CT is an important indicator for evaluating eye diseases and systemic diseases (caused by ischemia, hypoxia, etc.). Changes in SF-CT values ​​can provide a reliable basis for the early diagnosis of central serous retinal choroidopathy. Related studies have also pointed out that the SF-CT of patients with moderate to severe OSAS is significantly thinner, and the degree of thinning is related to the oxygen depletion index. The frequency of intermittent nocturnal hypoxia in OSAS patients has a greater impact on SF-CT [22] . Other scholars have pointed out that changes in SF-CT values ​​are correlated with circadian rhythms, which may directly reflect the improvement of the condition of patients with severe OSAS [23] . The unique physiological characteristics of the choroid (fast blood flow and small oxygen partial pressure difference between arteries and veins) make it insensitive to changes in blood oxygen saturation, but the choroid is highly sensitive to changes in blood carbon dioxide partial pressure (i.e., an increase in blood carbon dioxide partial pressure in the human body by 1 mmHg, choroidal blood flow increases by 1.5%) [24] . Therefore, strengthening CC-VD monitoring is of great significance to evaluate the improvement of choroidal lesions. Alternating hypoxia may stimulate patients' sympathetic nervous system, resulting in damage to the nerve tissue distributed in the choroidal vascular layer, persistent hypoxia of local tissue, and ultimately causing changes in the choroidal vascular structure. As a new biological indicator of the choroid, CVI can accurately reflect the dynamic changes of the choroidal matrix and vascular structure, and the measurement of this indicator is not easily affected by external factors (such as patient age, axial length, disease status, etc.). The data of this study showed that the SF-CT and CVI values ​​of patients in the Poor response group were higher than those in the Good response group after treatment, and their CC-VD values ​​were significantly lower than those in the Good response group; suggesting that various choroidal vascular indicators may play a certain role in the evaluation of the efficacy of CPAP treatment in patients with severe OSAS, which maybe based on the fact that the vascular network distributed in the choroid is relatively loose, therefore it can intuitively reflect the vascular spasm state of patients with severe OSAS. After CPAP treatment intervention, patients' systemic hypoxia condition was improved, and the symptoms of choroidal vasospasm were significantly alleviated. Upper airway stenosis caused by physiological factors (such as tongue root retardation caused by excessive supine lying) and pathological factors (such as nasal polyps, allergic rhinitis, loose soft palate, excessively long and thick uvula, temporomandibular joint dysfunction, and abnormal muscle control caused by brain nerve tissue damage) is the main pathological basis of OSAS [25] . Respiratory apnea and/or hypopnea caused by collapse of upper airway soft tissue during sleep can lead to long-term chronic hypoxia in patients, which can progress to hypoxemia and hypercapnia in severe cases [26] . Oropharyngeal morphological indicators directly reflect the abnormal anatomical structure of the upper airway, providing a reliable basis for clinical timely detection of upper airway muscle relaxation and collapse. HMD is one of the anatomical features of the upper airway, and changes in this indicator indicate abnormal oropharyngeal function. PNS-P1 is an objective indicator for evaluating the downward movement of the soft palate. The larger the PNS-P1, the more severe the soft palate ptosis and the higher the risk of respiratory disorders in patients [27] . In this study, the PNS-Me and HMD values ​​of the patients in the Poor response group after treatment were lower than those in the Good response group, and their PNS-P1 values ​​were significantly higher than those in the other group. The results showed that CPAP treatment had a good regulatory effect on oropharyngeal muscle tension, which can improve the upper airway stenosis in patients with severe OSAS to a certain extent. Through ROC analysis, it was found that the oropharyngeal morphology indicators had a high predictive value for the efficacy of CPAP treatment in patients with severe OSAS, which fully demonstrated that oropharyngeal morphology indicators can be used as reliable indicators to evaluate the outcome of CPAP treatment. This study still has some limitations: for example, the sample size is small and relatively single (i.e., the representativeness of the sample may vary due to different regions and races); the objective analysis is not comprehensive (such as the correlation between sleep breathing parameters and choroidal vascular indicators and oropharyngeal morphological indicators is not analyzed, etc.); other factors (such as the examination results may be limited by individual differences in patients, the technical level of physicians, image clarity, etc.) that may affect the accuracy of the prediction model results are not considered. Therefore, in future clinical trials, it may be beneficial to analyze objective indicators from multiple perspectives, appropriately increase the sample size, select more representative samples, and reasonably avoid factors that may influence the research outcomes so as to help improve the stability and reliability of the model and provide a deeper analysis of the predictive efficacy of choroidal vascular and oropharyngeal morphological indicators for the CPAP treatment efficacy in severe OSAS patients. Conclusion In summary, the patients in the Good response group underwent OCT and oral CT examinations, and their choroidal vascular indicators (SF-CT, CC-VD and CVI) and oropharyngeal morphological indicators were significantly different from those in the Poor response group. The ophthalmic parameters and oral indicators have good predictive value for the efficacy of CPAP treatment in patients with severe OSAS, and have good application prospects in the evaluation of OSAS disease severity an outcome, being worthy of clinical reference. Declarations Data Availability Statement The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. Conflicts of Interest No potential conflict of interest was reported by the authors. Funding Not appliance. Authors' contributions Chenxu Wang * and Jingjing Yu * : Co-first authors, contributed equally to study design, data collection, analysis, etc. Yue Gu: Specific role, performed experiments, methodology development. Zhen Wu # and Yimin Xia # : Co-corresponding authors, supervised the research, provided critical revisions, and approved the final manuscript. * These authors contributed equally to this work. Ethics approval This study was reviewed and approved by the Ethics Committee of Affiliated Changshu Hospital of Nantong University. Written informed consent was obtained from all participants, and all procedures followed the principles of the Declaration of Helsinki. Clinical trial number: not applicable. Consent to participate Consent for participant is not applicable as this study did not involve human participants or personal data. Human Ethics and Consent to Participate declarations: not applicable. Consent for publication Consent for publication is not applicable as this study did not involve human participants or personal data. References LV R, LIU X, ZHANG Y, et al. Pathophysiological mechanisms and therapeutic approaches in obstructive sleep apnea syndrome [J]. 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Zh Nevrol Psikhiatr Im S S Korsakova, 2020, 120(1): 90-5. NOKES B, COOPER J, CAO M. Obstructive sleep apnea: personalizing CPAP alternative therapies to individual physiology [J]. Expert Rev Respir Med, 2022, 16(8): 917-29. TONDO P, SCIOSCIA G, SABATO R, et al. Mortality in obstructive sleep apnea syndrome (OSAS) and overlap syndrome (OS): The role of nocturnal hypoxemia and CPAP compliance [J]. Sleep Med, 2023, 112(Dec)96-103. KIM J, LEE H J, LEE D A, et al. Choroid plexus enlargement in patients with obstructive sleep apnea [J]. Sleep Med, 2024, 121(Sep)179-83. OZCAN G, TEMEL E, ORNEK K, et al. Choroidal vascularity index in obstructive sleep apnea syndrome [J]. Sleep Breath, 2022, 26(4): 1655-9. KUO C J, LIN C S, CHUANG C H, et al. Quantitative Morphometric Measurements of the Oropharynx in Obstructive Sleep Apnea Syndrome Using a Laser Depth Measurement Module [J]. Nat Sci Sleep, 2020, 12(14)1181-90. CHUNG F, MEMTSOUDIS S G, RAMACHANDRAN S K, et al. Society of Anesthesia and Sleep Medicine Guidelines on Preoperative Screening and Assessment of Adult Patients With Obstructive Sleep Apnea [J]. Anesth Analg, 2016, 123(2): 452-73. COSENTINO F, GRANT P J, ABOYANS V, et al. 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD [J]. Eur Heart J, 2020, 41(2): 255-323. FLACK J M, ADEKOLA B. Blood pressure and the new ACC/AHA hypertension guidelines [J]. Trends Cardiovasc Med, 2020, 30(3): 160-4. MARINO A V, COSTIGLIOLA R, FIORETTO I. Choroidal vascularity index in obstructive sleep apnea syndrome [J]. Sleep Breath, 2023, 27(2): 771. AKASHIBA T, INOUE Y, UCHIMURA N, et al. Sleep Apnea Syndrome (SAS) Clinical Practice Guidelines 2020 [J]. Respir Investig, 2022, 60(1): 3-32. HUANG H H, TSAO C H, WEI J C. Voice Assessment in Patients With Obstructive Sleep Apnea Syndrome After Transoral Robotic Surgery [J]. Front Surg, 2021, 8(17)647792. BAI X Q, SUN X G. [Sleep apnea and ocular diseases] [J]. Zhonghua Yan Ke Za Zhi, 2024, 60(3): 296-302. NARANJO-BONILLA P, MUNOZ-VILLANUEVA M C, GIMENEZ-GOMEZ R, et al. Retinal and choroidal thickness measurements in obstructive sleep apnea: impacts of continuous positive airway pressure treatment [J]. Graefes Arch Clin Exp Ophthalmol, 2021, 259(11): 3381-93. MAVIGOK E, OZCAN A A, ULAS B. Obsructive sleep apnea syndrome: is it a risk factor for ocular surface disease and ocular comorbidities? [J]. Int Ophthalmol, 2023, 43(7): 2329-34. COLAK M, OZEK D, OZCAN K M, et al. Evaluation of retinal vessel density and foveal avascular zone measurements in patients with obstructive sleep apnea syndrome [J]. Int Ophthalmol, 2021, 41(4): 1317-25. ALTINEL M G, USLU H, KANRA A Y, et al. Effect of obstructive sleep apnoea syndrome and continuous positive airway pressure treatment on choroidal structure [J]. Eye (Lond), 2022, 36(10): 1977-81. AZAD A D, DAVILA J R, RAYESS N, et al. The Effect of Obstructive Sleep Apnea Treatment and Severity on Choroidal Thickness in Patients With Central Serous Chorioretinopathy [J]. J Vitreoretin Dis, 2022, 6(1): 22-30. XU Q, WANG X, LIU P, et al. Correlation of cephalometric variables with obstructive sleep apnea severity among children: a hierarchical regression analysis [J]. Cranio, 2022, 26(Aug):1-8. GOVINDAGOUDAR M B, LALWANI L K, SINGH P K, et al. Dynamic assessment of oropharynx with ultrasonography as a screening tool for obstructive sleep apnea [J]. J Sleep Res, 2023, 32(1): e13712. LUN H M, LIU R C, HU Q, et al. Potential ultrasonic anatomical markers of obstructive sleep apnoea-hypopnoea syndrome [J]. Clin Radiol, 2023, 78(2): e137-e42. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 02 Oct, 2025 Read the published version in Head & Face Medicine → Version 1 posted Editorial decision: Revision requested 12 May, 2025 Reviews received at journal 11 May, 2025 Reviews received at journal 06 May, 2025 Reviewers agreed at journal 05 May, 2025 Reviews received at journal 01 May, 2025 Reviewers agreed at journal 01 May, 2025 Reviewers agreed at journal 29 Apr, 2025 Reviewers invited by journal 29 Apr, 2025 Editor assigned by journal 09 Apr, 2025 Submission checks completed at journal 09 Apr, 2025 First submitted to journal 06 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6389207","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":449661568,"identity":"ea018b14-8658-4592-97e1-96a1f07343c1","order_by":0,"name":"Chenxu Wang","email":"","orcid":"","institution":"Affiliated Changshu Hospital of Nantong University","correspondingAuthor":false,"prefix":"","firstName":"Chenxu","middleName":"","lastName":"Wang","suffix":""},{"id":449661569,"identity":"ad9b5baf-d6f3-47de-94be-7e7ad2016ee1","order_by":1,"name":"Jingjing Yu","email":"","orcid":"","institution":"Affiliated Changshu Hospital of Nantong University","correspondingAuthor":false,"prefix":"","firstName":"Jingjing","middleName":"","lastName":"Yu","suffix":""},{"id":449661570,"identity":"5e49d36e-dc54-4731-ba16-e84da67647b1","order_by":2,"name":"Yue Gu","email":"","orcid":"","institution":"Shandong University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Gu","suffix":""},{"id":449661571,"identity":"4cc5866b-9b94-4674-9203-685b77fa04d1","order_by":3,"name":"Zhen Wu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYHACNijNfODAhx8kaWFjSzw4s4c0LTzGhznY8CsFA4Mb6c8efNzBIGcu3/PhMAMPgzy/2AFCWhLSDWeeYTC2bOPdcLjAgsFw5uwE/FrMbiQck+ZtY0jccAyoZQYPQ4LBbYJaEtuk/7Yx1G84xvPgMA8bUVqS2aQZ24Aqj/EwEKfF/swzNsneNgbDDcfSDICBLEHYL5Lt6c8kfrYxyBscPvz4w4cfNvL80gS0QMF/GEOCKOWjYBSMglEwCggAALcSQ9ZYdLkRAAAAAElFTkSuQmCC","orcid":"","institution":"Affiliated Changshu Hospital of Nantong University","correspondingAuthor":true,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Wu","suffix":""},{"id":449661572,"identity":"a533d8e7-e46e-4ffa-9f20-eb848bc4db61","order_by":4,"name":"Yimin Xia","email":"","orcid":"","institution":"Shanghai University of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yimin","middleName":"","lastName":"Xia","suffix":""}],"badges":[],"createdAt":"2025-04-07 01:53:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6389207/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6389207/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13005-025-00523-8","type":"published","date":"2025-10-02T15:58:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82149886,"identity":"b8263951-cb90-4c3f-a36d-9a67a4a89838","added_by":"auto","created_at":"2025-05-07 07:12:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":293351,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of sleep breathing parameters between the two groups\u003c/p\u003e\n\u003cp\u003eA: Comparison of LAD and LSaO2;\u003c/p\u003e\n\u003cp\u003eB: Comparison of TS90% and AHI; (indicates P \u0026lt; 0.001)\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6389207/v1/5096ef00baa7bb32e2693117.png"},{"id":82149883,"identity":"eebd4f18-54f8-45a1-91e2-0a2e4592e7c6","added_by":"auto","created_at":"2025-05-07 07:12:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":404356,"visible":true,"origin":"","legend":"\u003cp\u003eROC diagram of choroidal vascular indicators and oropharyngeal morphology indicators predicting the efficacy of CPAP treatment in patients with severe OSAS\u003c/p\u003e\n\u003cp\u003eA: ROC diagram of choroidal vascular indicators predicting the efficacy of CPAP treatment;\u003c/p\u003e\n\u003cp\u003eB: ROC diagram of oropharyngeal morphology indicators predicting the efficacy of CPAP treatment.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6389207/v1/04b3efe2a1a496f7ff141896.png"},{"id":82149884,"identity":"4ac79105-f091-463b-9831-885dbddf0a10","added_by":"auto","created_at":"2025-05-07 07:12:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1479453,"visible":true,"origin":"","legend":"\u003cp\u003eNomogram and calibration curve of choroidal vascular indicators for predicting the efficacy of CPAP treatment in patients with severe OSAS\u003c/p\u003e\n\u003cp\u003eA: nomogram of choroidal vascular indicators for predicting the efficacy of CPAP treatment in patients with severe OSAS;\u003c/p\u003e\n\u003cp\u003eB: calibration curve of choroidal vascular indicators for predicting the efficacy of CPAP treatment.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6389207/v1/ba05594814963b3f6ab74398.png"},{"id":82149887,"identity":"cb1cc66f-6c6e-4875-b26d-f447b6a3d8bf","added_by":"auto","created_at":"2025-05-07 07:12:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1598041,"visible":true,"origin":"","legend":"\u003cp\u003eNomogram and calibration curve of oropharyngeal morphological indicators for predicting the efficacy of CPAP treatment in patients with severe OSAS\u003c/p\u003e\n\u003cp\u003eA: nomogram of oropharyngeal morphological indicators;\u003c/p\u003e\n\u003cp\u003eB: calibration curve of oropharyngeal morphological indicators.\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6389207/v1/866c4b660bae4857039a5cee.png"},{"id":92883874,"identity":"abe4a744-4b1e-4059-aa85-a26a7952cb0f","added_by":"auto","created_at":"2025-10-06 16:10:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4823824,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6389207/v1/69717dfd-f8e0-4ef7-a2b6-d6431750d243.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Choroidal Vascular and Oropharyngeal Morphological Indicators in Predicting CPAP Treatment Efficacy in Severe OSAS Patients: A Prospective Cohort Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObstructive Sleep Apnea Syndrome (OSAS) is a common clinical sleep disorder characterized by repeated upper airway obstruction during sleep, accompanied by arousals and daytime sleepiness. As the condition progresses, it may lead to symptoms such as chronic intermittent hypoxia and carbon dioxide retention\u003csup\u003e[1-3]\u003c/sup\u003e. Epidemiological studies have found that the prevalence rate of OSAS in adults is around 20%, with approximately 90% of patients remaining undiagnosed and not receiving active treatment. The early diagnosis rate of OSAS is low\u003csup\u003e[4]\u003c/sup\u003e. Due to the relaxation of the soft tissues around the oropharynx or the respiratory muscles during sleep, the upper airway is prone to obstruction, which may hinder gas exchange in the respiratory tract and lead to intermittent hypoxia. Prolonged intermittent hypoxia can cause neurological damage\u003csup\u003e[5]\u003c/sup\u003e. Cognitive dysfunction is prevalent in patients with severe OSAS and significantly impairs their life quality. Studies show that the incidence of this complication ranges from 35.2% to 80.0%\u003csup\u003e[6]\u003c/sup\u003e . Furthermore, OSAS increases the risk of Alzheimer\u0026apos;s disease in patients, possibly due to the imbalance of neurotransmitter systems in the brain caused by sleep deprivation, leading to impaired memory pathways and reduced efficiency in synaptic signaling\u003csup\u003e[7]\u003c/sup\u003e. Therefore, it is particularly important to implement scientific and effective treatment plans for patients with severe OSAS.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Continuous positive airway pressure (CPAP) is currently the most effective treatment for patients with moderate to severe OSAS. The primary mechanism of action is to provide positive airway pressure through a ventilator, which helps maintain airway tension, effectively prevents upper airway airflow obstruction during sleep and improves respiratory function and sleep quality of OSAS patients\u003csup\u003e[8]\u003c/sup\u003e. CPAP treatment not only improves hypoxemia in OSAS patients but also reduces the frequency of apneas during sleep, restores sleep structure, and helps alleviate daytime sleepiness to some extent, thus reducing cognitive dysfunction\u003csup\u003e[9]\u003c/sup\u003e. However, the use of CPAP may cause various complications (such as nasal congestion, dry mouth, barotrauma, upper respiratory tract infections, pneumothorax, etc.), which may hinder patient recovery. Therefore, regular assessment of the effectiveness and side effects of CPAP treatment during the course of therapy is essential.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; In recent years, clinical observations have revealed that intermittent tissue hypoxia and arousal symptoms in patients with severe OSAS can stimulate the sympathetic nervous system, triggering a series of cascading responses. The OSAS also affects the ocular vascular autoregulatory function, because of the fact that intermittent hypoxia can disrupt the balance between vasoconstrictor and vasodilator factors in the circulation, leading to abnormal autonomic regulation of the optic nerve vasculature, which in turn results in impaired retinal tissue function. Choroidal lesions are relatively common in this context\u003csup\u003e[10, 11]\u003c/sup\u003e. Therefore, monitoring the improvement of choroidal vascular indicators in patients with severe OSAS is of significant value in evaluating the effectiveness of CPAP treatment. Studies suggest that the onset of OSAS is closely related to upper airway narrowing, which is caused by the relaxation of oropharyngeal muscle tone and changes in the morphological structure of the airway\u003csup\u003e[12]\u003c/sup\u003e. Clinically, previous interventions for severe OSAS patients have focused on leading forwards the mandible or tongue to prevent oropharyngeal soft tissues from obstructing the posterior pharyngeal wall, thereby widening upper airway and ensuring unobstructed breathing during sleep. Therefore, changes in oropharyngeal morphological parameters before and after CPAP treatment in severe OSAS patients are also important observational indicators for assessing treatment efficacy. This study primarily analyzes the predictive role of choroidal vascular indicators and oropharyngeal morphological indicators in determining the effectiveness of CPAP treatment for severe OSAS patients, aiming to provide accurate reference for further modifying treatment plans.\u003c/p\u003e"},{"header":"Information and methods","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eGeneral Information\u003c/h2\u003e \u003cdiv id=\"Sec3\" class=\"Section3\"\u003e \u003ch2\u003eStudy Subjects\u003c/h2\u003e \u003cp\u003eThis study is a single-center, prospective observational analysis, involving 245 patients with severe OSAS from a hospital between January 2022 and June 2024. The study has been approved by the hospital's ethics committee, and all procedures were conducted in accordance with the ethical standards outlined in the 1964 \u003cem\u003eDeclaration of Helsinki\u003c/em\u003e and its subsequent amendments.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eInclusion and exclusion criteria\u003c/h3\u003e\n\u003cp\u003eInclusion criteria: (1) patients who meet the diagnostic criteria for OSAS outlined in the \u003cem\u003eSociety of Anesthesia and Sleep Medicine Guidelines on Preoperative Screening and Assessment of Adult Patients with Obstructive Sleep Apnea\u003c/em\u003e\u003csup\u003e[13]\u003c/sup\u003e, confirmed by clinical symptoms and imaging examination; (2) apnea-hypopnea index (AHI)\u0026thinsp;\u0026ge;\u0026thinsp;30; (3) age\u0026thinsp;\u0026ge;\u0026thinsp;18 years old; (4) no other eye diseases; (5) patients and their families have signed the \u003cem\u003eInformed Consent Form\u003c/em\u003e; (6) no psychiatric disorders.\u003c/p\u003e \u003cp\u003eExclusion criteria: (1) patients with malignant tumors; (2) patients with contraindications for the relevant examinations in this study; (3) patients with severe organ dysfunction, such as severe heart, liver, or kidney failure; (4) patients with active systemic infections; (5) patients with chronic obstructive pulmonary disease, interstitial lung disease, or other chronic hypoxic diseases; (6) patients with severe neurological diseases or cognitive dysfunction; (7) pregnant or breastfeeding women.\u003c/p\u003e\n\u003ch3\u003eGeneral information\u003c/h3\u003e\n\u003cp\u003eThis is a retrospective study, and all patient data were collected through the medical record system. The collected information includes: gender, age, medical history (all diabetic patients met the diagnostic criteria for diabetes outlined in the \u003cem\u003e2019 ESC Guidelines on Diabetes, Pre-diabetes, and Cardiovascular Diseases developed in collaboration with the EASD\u003c/em\u003e\u003csup\u003e[14]\u003c/sup\u003e; all hypertensive patients met the diagnostic criteria for hypertension as outlined in the \u003cem\u003eBlood Pressure and the New ACC/AHA Hypertension Guidelines\u003c/em\u003e\u003csup\u003e[15]\u003c/sup\u003e), course of the desease (determined through communication with patients by professional physicians using scientific interviewing techniques), smoking history (smoking\u0026thinsp;\u0026ge;\u0026thinsp;100 cigarettes within the past year), alcohol consumption history (drinking\u0026thinsp;\u0026ge;\u0026thinsp;1 time per week for at least 5 continuous months), body mass index (BMI, BMI\u0026thinsp;=\u0026thinsp;weight (kg)/height squared (m\u003csup\u003e2\u003c/sup\u003e)), etc.\u003c/p\u003e\n\u003ch3\u003eCPAP and polysomnography (PSG)\u003c/h3\u003e\n\u003cp\u003eAll patients received CPAP treatment using a non-invasive ventilator (Model: REMstar Auto 557P, Philips Respironics, USA). The initial pressure was set at 4 cmH\u003csub\u003e2\u003c/sub\u003eO (1 cmH\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;=\u0026thinsp;0.098 kPa). Based on the signals obtained from PSG monitoring (including electroencephalogram, electromyogram, electrooculogram, apnea, heart rate, nasal and oral airflow and blood oxygen levels, etc.), the CPAP pressure is adjusted to suit patients condition, then the pressure is gradually increased until their blood oxygen saturation reaches\u0026thinsp;\u0026ge;\u0026thinsp;90% and apnea is resolved.\u003c/p\u003e \u003cp\u003eDuring CPAP treatment, all patients underwent PSG monitoring using a polysomnography device (Model: TREX HD, NICO Instruments, USA). The monitoring period was from 9:00 PM to 6:00 AM the following morning. Patients were instructed to refrain from alcohol, smoking, coffee, strong tea and taking sedative or psychotropic medications for 24 hours prior to the PSG test. The monitoring parameters included: electroencephalogram, electrooculogram, nasal and oral airflow, mandibular electromyogram, blood oxygen saturation and thoracoabdominal respiratory movement. The key sleep respiratory parameters recorded included: longest apnea duration (LAD), lowest arterial oxygen saturation (LSaO2), percentage of time with SpO2\u0026thinsp;\u0026lt;\u0026thinsp;90% (TS90%) and apnea-hypopnea index (AHI). A trained technician reviewed and assisted in generating the required sleep respiratory parameters for this study.\u003c/p\u003e\n\u003ch3\u003eOphthalmic examination\u003c/h3\u003e\n\u003cp\u003eOptical coherence tomography (OCT) examination by one ophthalmologist was conducted for all patients. The device used was the RTVueXR Avanti OCT instrument (Optovue, USA). Procedure: before the examination, patients were administered mydriatic drops (compound tropicamide) to dilate the pupils followed by sitting comfortably with their chin on a support, and different regions of the retina were scanned. The device\u0026rsquo;s software was used for automatic measurement. Three measurements were taken from the same eye, and the average value was recorded. The data were then uploaded to a computer-based image analysis system for further analysis. Measured parameters:\u003c/p\u003e \u003cp\u003ea. Subfoveal choroidal thickness (SF-CT): The inner boundary of the choroid at the Bruch membrane of the macular fovea, from 9 \u0026mu;m to the choroidal-scleral interface.\u003c/p\u003e\n\u003cp\u003eb. Choriocapillaris vessel density (CC-VD): Blood flow density in the capillary layer, located 30 \u0026mu;m to 60 \u0026mu;m below the retinal pigment epithelium.\u003c/p\u003e\n\u003cp\u003ec. Choroidal\u0026nbsp;vascularity\u0026nbsp;index (CVI): The ratio of the vascular luminal area to the total choroidal area\u003csup\u003e[16]\u003c/sup\u003e.\u003c/p\u003e\n\u003ch2\u003eOropharyngeal CT examination\u003c/h2\u003e\n\u003cp\u003eThe instrument used was a cone-beam CT scanner (Model: 3DXam, KaVo, Germany). Patients were instructed to sit upright, with both eyes looking straight ahead. The frankfurt horizontal (FH) plane was aligned parallel to the floor, and the teeth were positioned in the natural occlusion with the jaw in the centric position. After the scan, the oral landmarks were identified, including: posterior nasal spine (PNS), uvular tip (U) and mental point (Me). Based on these landmarks, the following (a, b and c) oropharyngeal morphological indicators were measured three times, and the average value was taken.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ea. Posterior Nasal Spine to Menton Distance (PNS-Me): The distance from the PNS point to the Me point;\u003c/p\u003e\n\u003cp\u003eb. Hyoid-Mental Distance (HMD): The distance between the hyoid bone and the lower margin of the mandible;\u003c/p\u003e\n\u003cp\u003ec. Posterior Nasal Spine to Uvular Tip point (PNS-P1): The distance from the junction of the hard and soft palate to the U point.\u003c/p\u003e\n\u003ch3\u003eLaboratory tests\u003c/h3\u003e\n\u003cp\u003eBlood samples (4 mL) were collected from all patients via fasting peripheral venous blood and placed in vacuum blood collection tubes. The blood samples were promptly sent for testing and centrifuged at room temperature for 15 min (1900 r\u0026middot;min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) to obtain serum and plasma samples, which were stored at low temperatures (-80\u0026deg;C) for further analysis.\u003c/p\u003e \u003cp\u003eComplete blood count (CBC) test. Instrument: 5-part hematology analyzer (Model: BC5300, Shenzhen Mindray, China). Laboratory personnel strictly followed the operating procedures to conduct CBC tests on all patient blood samples, recording the red blood cell count, neutrophil count, and hemoglobin concentration. It is important to complete the blood sample testing within 4 hours of sample collection.\u003c/p\u003e \u003cp\u003eBlood glucose test. Instruments: Open automatic biochemical analyzer (Model: RocheModular P800, Roche, Switzerland) and fully automatic HbA1c analyzer (Model: HLC-723 G7, Tosoh Corporation, Japan). Laboratory personnel tested the fasting blood glucose (FBG) and glycosylated hemoglobin (HbAlc) content in serum samples; FBG detection used glucose oxidase method and HbAlc detection used high performance liquid chromatography. Note that the blood sample testing should be completed within 4 hours of sample collection.\u003c/p\u003e\n\u003ch3\u003eEfficacy evaluation criteria\u003c/h3\u003e\n\u003cp\u003eThe efficacy was evaluated based on the relevant standards from the \u003cem\u003eSleep Apnea Syndrome (SAS) Clinical Practice Guidelines 2020\u003c/em\u003e\u003csup\u003e[17]\u003c/sup\u003e as follows: ① significantly effective: clinical symptoms and signs are significantly improved, with a decrease in AHI\u0026thinsp;\u0026ge;\u0026thinsp;10 times\u0026middot;h⁻\u0026sup1; after treatment; ②effective: clinical symptoms and signs are improved, with a decrease in AHI\u0026thinsp;\u0026ge;\u0026thinsp;5 times\u0026middot;h⁻\u0026sup1; after treatment; ③ ineffective: no significant changes in clinical symptoms, signs, or AHI after treatment. Patients with significantly effective and effective outcomes were included in the Good response group, while those with ineffective outcomes were included in the Poor response group.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using IBM SPSS 27.0 (IBM Corp., Armonk, N.Y., USA) statistical software. Counting data were expressed as [n] and analyzed by the \u003cem\u003ex\u003c/em\u003e\u0026sup2; test. For measuring data, the \u003cem\u003eShapiro-Wilk\u003c/em\u003e test was used to assess the normality of the distribution. Non-normally distributed data were expressed as median and interquartile range [M (P25, P75)], while the data that met the normal distribution were expressed as (\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e\u0026plusmn;\u0026thinsp;s), and the \u003cem\u003et\u003c/em\u003e test was used, with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as statistically significant. The relationship between choroidal vascular indicators, oropharyngeal morphology indicators, and CPAP treatment efficacy in severe OSAS patients was analyzed using multivariate \u003cem\u003eLogistic\u003c/em\u003e regression. A nomogram model was constructed, and calibration curves were drawn for internal validation to assess the model's discrimination and calibration. The significance level was set at α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eGeneral information and laboratory tests\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003eGeneral information\u003c/h2\u003e \u003cp\u003eIn this study, 86 of the 245 patients were evaluated as receiving significantly effective CPAP treatment, and 78 were effective, who were included in the Good response group (n\u0026thinsp;=\u0026thinsp;164); 81 ineffective patients were included in the Poor response group (n\u0026thinsp;=\u0026thinsp;81). There was no significant difference in gender, age, average course of disease, BMI, smoking history, drinking history and medical history between the Good response group and the Poor response group (\u003cem\u003eP\u003c/em\u003e values ​​were all \u0026gt;\u0026thinsp;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of general information between the two groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGood response group (n\u0026thinsp;=\u0026thinsp;164)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePoor response group (n\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e/Z\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender (number)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93(56.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47(58.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.845\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e71(43.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34(41.98)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge [M(P25, P75)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.00(43.00,48.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.00(43.00,49.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.981\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAverage course of disease [month, M(P25, P75)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.57(6.50,8.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.36(6.50,8.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI[kg\u0026middot;m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e, M(P25, P75)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.63(24.10,27.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.09(24.70,27.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28(17.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15(18.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.780\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDrinking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(21.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18(22.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMedical history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39(23.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21(25.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25(15.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13(16.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.870\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory tests\u003c/h2\u003e \u003cp\u003eNo significant differences were observed in red blood cell count (5.34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L vs 5.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L), neutrophil count (7.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.49\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L vs 7.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L), hemoglobin concentration (157.36\u0026thinsp;\u0026plusmn;\u0026thinsp;17.84 g\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e vs 161.29\u0026thinsp;\u0026plusmn;\u0026thinsp;17.36 g\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), FBG (4.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93 mmol\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e vs 4.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96 mmol\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and HbAlc (6.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14% vs 6.37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28%) between the two groups (all \u003cem\u003eP\u003c/em\u003e\u0026gt;0.05, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of laboratory test results between the two groups after treatment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood response group (n\u0026thinsp;=\u0026thinsp;164)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoor response group (n\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed blood cell count (\u0026times;10\u003csup\u003e12\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.57\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil count (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e7.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e7.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.190\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin concentration\u003c/p\u003e \u003cp\u003e(g\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e157.36\u0026thinsp;\u0026plusmn;\u0026thinsp;17.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e161.29\u0026thinsp;\u0026plusmn;\u0026thinsp;17.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFBG (mmol\u0026middot;L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbAlc (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.37\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSleep breathing parameters\u003c/h2\u003e \u003cp\u003eCompared with the parameters of the Good response group, the LAD (23.16\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95 s vs 35.22\u0026thinsp;\u0026plusmn;\u0026thinsp;2.78 s), TS90% (8.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76% vs 19.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53%) and AHI (17.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03 times\u0026middot;h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e vs 32.05\u0026thinsp;\u0026plusmn;\u0026thinsp;2.94 times\u0026middot;h\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) of the patients in the Poor response group after treatment were higher, and the differences were statistically significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while the TS90% (89.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04% vs 78.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3.69%) showed contradictory results with statistically significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePrediction of CPAP treatment efficacy of choroidal vascular indicators in patients with severe OSAS\u003c/h2\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003eComparison of choroidal vascular indicators between the two groups\u003c/h2\u003e \u003cp\u003eCompared with the Good response group, the SF-CT (273.07\u0026thinsp;\u0026plusmn;\u0026thinsp;29.43 \u0026micro;m vs 319.52\u0026thinsp;\u0026plusmn;\u0026thinsp;37.14 \u0026micro;m) and CVI (33.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25% vs 35.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33%) values ​​of patients in the Poor response group after treatment were higher, and the difference was statistically significant (\u003cem\u003et1\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10.631, \u003cem\u003et2\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.483, \u003cem\u003eP\u003c/em\u003e values ​​were both \u0026lt;\u0026thinsp;0.001); compared with the Good response group, the CC-VD (47.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.22% vs 43.49\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04%) values ​​of the patients in the Poor response group after treatment were lower with statistically significant difference (\u003cem\u003et3\u003c/em\u003e\u0026thinsp;=\u0026thinsp;13.782, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of choroidal vascular indicators between the two groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood response group (n\u0026thinsp;=\u0026thinsp;164)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePoor response group (n\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSF-CT (\u0026micro;m)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e273.07\u0026thinsp;\u0026plusmn;\u0026thinsp;29.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e319.52\u0026thinsp;\u0026plusmn;\u0026thinsp;37.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCC-VD (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e47.95\u0026thinsp;\u0026plusmn;\u0026thinsp;4.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e43.49\u0026thinsp;\u0026plusmn;\u0026thinsp;3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCVI (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e33.06\u0026thinsp;\u0026plusmn;\u0026thinsp;1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e35.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.782\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eROC of choroidal vascular indicators predicting the efficacy of CPAP treatment in patients with severe OSAS\u003c/b\u003e \u003c/p\u003e \u003cp\u003eROC curves were drawn and it was found that the AUC value of SF-CT, CC-VD and CVI in predicting the efficacy of CPAP treatment in patients with severe OSAS was 0.835 (95% CI: 0.767\u0026ndash;0.893), 0.805 (95% CI: 0.758\u0026ndash;0.858) and 0.910 (95% CI: 0.878\u0026ndash;0.944) respectively, indicating that the choroidal vascular indicators have a high predictive value for the efficacy of CPAP treatment in patients with severe OSAS, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eNomogram and calibration curve for choroidal vascular indicators predicting the efficacy of CPAP treatment in patients with severe OSAS\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA nomogram model for choroidal vascular indicators predicting the efficacy of CPAP treatment in patients with severe OSAS was constructed and a calibration curve was drawn. It was found that SF-CT, CC-VD, and CVI had high values ​​for predicting the efficacy of CPAP treatment in patients with severe OSAS, and the calibration curve was similar to the standard curve, indicating that the consistency and predictive ability of the nomogram were good, and the accuracy of the model was high. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePrediction of the efficacy of CPAP treatment in patients with severe OSAS by oropharyngeal morphological indicators\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eComparison of oropharyngeal morphological indices between the two groups\u003c/h2\u003e \u003cp\u003eCompared with the Good response group, the patients in the Poor response group had lower mean values ​​of PNS-Me (6.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14 mm vs 4.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90 mm) and HMD (23.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87 mm vs 19.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46 mm) after treatment, and the difference was statistically significant (\u003cem\u003et4\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12.629, \u003cem\u003et5\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15.059, \u003cem\u003eP\u003c/em\u003e values ​​were both \u0026lt;\u0026thinsp;0.001), while the patients in the Poor response group had higher mean values ​​of PNS-P1 (40.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09 mm vs 41.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01mm) after treatment, and the difference was statistically significant (\u003cem\u003et6\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12.661, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), as shown in for details.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of oropharyngeal morphological indicators between the two groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndicators\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood efficacy group (n\u0026thinsp;=\u0026thinsp;164)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLess effective group (n\u0026thinsp;=\u0026thinsp;81)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNS-Me (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e6.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHMD (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e23.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e19.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePNS-P1 (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e40.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e41.92\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eROC of oropharyngeal morphology indicators for predicting the efficacy of CPAP treatment in patients with severe OSAS\u003c/b\u003e \u003c/p\u003e \u003cp\u003eROC curves were drawn and it was found that the AUC value of PNS-Me, HMD and PNS-P1 for predicting the efficacy of CPAP treatment in patients with severe OSAS was 0.897 (95% CI: 0.859\u0026ndash;0.925), 0.937 (95% CI: 0.907\u0026ndash;0.964) and 0.898 (95% CI: 0.862\u0026ndash;0.935),respectively, indicating that the oropharyngeal morphology indicators have a high predictive value for the efficacy of CPAP treatment in patients with severe OSAS, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNomogram and calibration curve for oropharyngeal morphology indicators predicting the efficacy of CPAP treatment in patients with severe OSAS\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA nomogram model for oropharyngeal morphology indicators predicting the efficacy of CPAP treatment in patients with severe OSAS was constructed and a calibration curve was drawn. It was found that PNS-Me, HMD and PNS-P1 had high values ​​for predicting the outcome of IBD patients, and the calibration curve was similar to the standard curve, indicating that the consistency and predictive ability of the nomogram were good, and the model is highly accurate. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOSAS mainly refers to hypoventilation and repeated apnea caused by upper airway stenosis or obstruction during sleep, which results in the body being in an intermittent hypoxic state and fragmented sleep\u003csup\u003e[18]\u003c/sup\u003e. CPAP is the first-line solution for the treatment of OSAS, and the efficacy evaluation of this technology has always been a key issue of concern to clinical physicians.\u003c/p\u003e \u003cp\u003eWith the deepening of research, some scholars have found in recent years that OSAS patients have a higher risk of developing central serous retinochoroidopathy; continuous hypoventilation may activate the body's hypoxia-inducible factor, promote the high expression of angiogenic factors, damage vascular endothelial tissue, and change vascular permeability, ultimately leading to thinning of the choroid and abnormal vascular structure\u003csup\u003e[19]\u003c/sup\u003e. Related reports point out that the mechanism of recurrent central serous retinochoroidopathy in OSAS patients may be related to a series of pathophysiological changes (including choroidal vasoconstriction, local blood flow reduction, etc.) caused by direct stimulation of the choroid by long-term secondary hypoxemia and hypercapnia\u003csup\u003e[20]\u003c/sup\u003e. Studies have confirmed that hypoxemia and hypercapnia can lead to choroidal vasodilation and increased blood flow in the early stages. The hypoxic state of patients with severe OSAS lasts for a long period of time, which can easily lead to choroidal vascular autoregulation dysfunction, increase vascular resistance, aggravate local blood hyperviscosity and trigger metabolic disturbance, ultimately causing endothelial cell damage and increasing the risk of local thrombosis. At the same time, local blood flow stagnation can also increase red blood cell aggregation, leading to shortening of microvilli and aggravation of choroidal vascular deformation\u003csup\u003e[21]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe retina has a high oxygen demand and the choroid has a relatively rich vascular tissue structure. The photoreceptors are most densely populated in the fovea, and their blood supply mainly comes from the choroid, which is the thickest in this area, and the thickness of the choroid gradually becomes thinner from the fovea to the periphery. SF-CT is an important indicator for evaluating eye diseases and systemic diseases (caused by ischemia, hypoxia, etc.). Changes in SF-CT values ​​can provide a reliable basis for the early diagnosis of central serous retinal choroidopathy. Related studies have also pointed out that the SF-CT of patients with moderate to severe OSAS is significantly thinner, and the degree of thinning is related to the oxygen depletion index. The frequency of intermittent nocturnal hypoxia in OSAS patients has a greater impact on SF-CT\u003csup\u003e[22]\u003c/sup\u003e. Other scholars have pointed out that changes in SF-CT values ​​are correlated with circadian rhythms, which may directly reflect the improvement of the condition of patients with severe OSAS\u003csup\u003e[23]\u003c/sup\u003e. The unique physiological characteristics of the choroid (fast blood flow and small oxygen partial pressure difference between arteries and veins) make it insensitive to changes in blood oxygen saturation, but the choroid is highly sensitive to changes in blood carbon dioxide partial pressure (i.e., an increase in blood carbon dioxide partial pressure in the human body by 1 mmHg, choroidal blood flow increases by 1.5%)\u003csup\u003e[24]\u003c/sup\u003e. Therefore, strengthening CC-VD monitoring is of great significance to evaluate the improvement of choroidal lesions. Alternating hypoxia may stimulate patients' sympathetic nervous system, resulting in damage to the nerve tissue distributed in the choroidal vascular layer, persistent hypoxia of local tissue, and ultimately causing changes in the choroidal vascular structure. As a new biological indicator of the choroid, CVI can accurately reflect the dynamic changes of the choroidal matrix and vascular structure, and the measurement of this indicator is not easily affected by external factors (such as patient age, axial length, disease status, etc.). The data of this study showed that the SF-CT and CVI values ​​of patients in the Poor response group were higher than those in the Good response group after treatment, and their CC-VD values ​​were significantly lower than those in the Good response group; suggesting that various choroidal vascular indicators may play a certain role in the evaluation of the efficacy of CPAP treatment in patients with severe OSAS, which maybe based on the fact that the vascular network distributed in the choroid is relatively loose, therefore it can intuitively reflect the vascular spasm state of patients with severe OSAS. After CPAP treatment intervention, patients' systemic hypoxia condition was improved, and the symptoms of choroidal vasospasm were significantly alleviated.\u003c/p\u003e \u003cp\u003eUpper airway stenosis caused by physiological factors (such as tongue root retardation caused by excessive supine lying) and pathological factors (such as nasal polyps, allergic rhinitis, loose soft palate, excessively long and thick uvula, temporomandibular joint dysfunction, and abnormal muscle control caused by brain nerve tissue damage) is the main pathological basis of OSAS\u003csup\u003e[25]\u003c/sup\u003e. Respiratory apnea and/or hypopnea caused by collapse of upper airway soft tissue during sleep can lead to long-term chronic hypoxia in patients, which can progress to hypoxemia and hypercapnia in severe cases\u003csup\u003e[26]\u003c/sup\u003e. Oropharyngeal morphological indicators directly reflect the abnormal anatomical structure of the upper airway, providing a reliable basis for clinical timely detection of upper airway muscle relaxation and collapse. HMD is one of the anatomical features of the upper airway, and changes in this indicator indicate abnormal oropharyngeal function. PNS-P1 is an objective indicator for evaluating the downward movement of the soft palate. The larger the PNS-P1, the more severe the soft palate ptosis and the higher the risk of respiratory disorders in patients\u003csup\u003e[27]\u003c/sup\u003e. In this study, the PNS-Me and HMD values ​​of the patients in the Poor response group after treatment were lower than those in the Good response group, and their PNS-P1 values ​​were significantly higher than those in the other group. The results showed that CPAP treatment had a good regulatory effect on oropharyngeal muscle tension, which can improve the upper airway stenosis in patients with severe OSAS to a certain extent. Through ROC analysis, it was found that the oropharyngeal morphology indicators had a high predictive value for the efficacy of CPAP treatment in patients with severe OSAS, which fully demonstrated that oropharyngeal morphology indicators can be used as reliable indicators to evaluate the outcome of CPAP treatment.\u003c/p\u003e \u003cp\u003eThis study still has some limitations: for example, the sample size is small and relatively single (i.e., the representativeness of the sample may vary due to different regions and races); the objective analysis is not comprehensive (such as the correlation between sleep breathing parameters and choroidal vascular indicators and oropharyngeal morphological indicators is not analyzed, etc.); other factors (such as the examination results may be limited by individual differences in patients, the technical level of physicians, image clarity, etc.) that may affect the accuracy of the prediction model results are not considered. Therefore, in future clinical trials, it may be beneficial to analyze objective indicators from multiple perspectives, appropriately increase the sample size, select more representative samples, and reasonably avoid factors that may influence the research outcomes so as to help improve the stability and reliability of the model and provide a deeper analysis of the predictive efficacy of choroidal vascular and oropharyngeal morphological indicators for the CPAP treatment efficacy in severe OSAS patients.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, the patients in the Good response group underwent OCT and oral CT examinations, and their choroidal vascular indicators (SF-CT, CC-VD and CVI) and oropharyngeal morphological indicators were significantly different from those in the Poor response group. The ophthalmic parameters and oral indicators have good predictive value for the efficacy of CPAP treatment in patients with severe OSAS, and have good application prospects in the evaluation of OSAS disease severity an outcome, being worthy of clinical reference.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot appliance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChenxu Wang\u003csup\u003e*\u003c/sup\u003e and Jingjing Yu\u003csup\u003e*\u003c/sup\u003e: Co-first authors, contributed equally to study design, data collection, analysis, etc.\u003c/p\u003e\n\u003cp\u003eYue Gu: Specific role, performed experiments, methodology development.\u003c/p\u003e\n\u003cp\u003eZhen Wu\u003csup\u003e#\u003c/sup\u003e and Yimin Xia\u003csup\u003e#\u003c/sup\u003e: Co-corresponding authors, supervised the research, provided critical revisions, and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e* These authors contributed equally to this work. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Ethics Committee of Affiliated Changshu Hospital of Nantong University. Written informed consent was obtained from all participants, and all procedures followed the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eClinical trial number: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsent for participant is not applicable as this study did not involve human participants or personal data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHuman Ethics and Consent to Participate declarations: not applicable. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsent for publication is not applicable as this study did not involve human participants or personal data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLV R, LIU X, ZHANG Y, et al. Pathophysiological mechanisms and therapeutic approaches in obstructive sleep apnea syndrome [J]. Signal Transduct Target Ther, 2023, 8(1): 218.\u003c/li\u003e\n\u003cli\u003eLEE J J, SUNDAR K M. Evaluation and Management of Adults with Obstructive Sleep Apnea Syndrome [J]. Lung, 2021, 199(2): 87-101.\u003c/li\u003e\n\u003cli\u003eIANNELLA G, MAGLIULO G, GRECO A, et al. Obstructive Sleep Apnea Syndrome: From Symptoms to Treatment [J]. Int J Environ Res Public Health, 2022, 19(4):2459 \u003c/li\u003e\n\u003cli\u003eTEIGA P, CHATELAIN S, HEINZER R, et al. [Obstructive sleep apnea syndrome : CPAP or Mandibular Advancement Device?] [J]. Rev Med Suisse, 2020, 16(709): 1865-9.\u003c/li\u003e\n\u003cli\u003eSANTILLI M, MANCIOCCHI E, D\u0026apos;ADDAZIO G, et al. Prevalence of Obstructive Sleep Apnea Syndrome: A Single-Center Retrospective Study [J]. Int J Environ Res Public Health, 2021, 18(19):10277 \u003c/li\u003e\n\u003cli\u003eCAPORALE M, PALMERI R, CORALLO F, et al. Cognitive impairment in obstructive sleep apnea syndrome: a descriptive review [J]. Sleep Breath, 2021, 25(1): 29-40.\u003c/li\u003e\n\u003cli\u003eKEMSTACH V V, KOROSTOVTSEVA L S, GOLOVKOVA-KUCHERIAVAIA M S, et al. [Obstructive sleep apnea syndrome and cognitive impairment] [J]. Zh Nevrol Psikhiatr Im S S Korsakova, 2020, 120(1): 90-5.\u003c/li\u003e\n\u003cli\u003eNOKES B, COOPER J, CAO M. Obstructive sleep apnea: personalizing CPAP alternative therapies to individual physiology [J]. Expert Rev Respir Med, 2022, 16(8): 917-29.\u003c/li\u003e\n\u003cli\u003eTONDO P, SCIOSCIA G, SABATO R, et al. Mortality in obstructive sleep apnea syndrome (OSAS) and overlap syndrome (OS): The role of nocturnal hypoxemia and CPAP compliance [J]. Sleep Med, 2023, 112(Dec)96-103.\u003c/li\u003e\n\u003cli\u003eKIM J, LEE H J, LEE D A, et al. Choroid plexus enlargement in patients with obstructive sleep apnea [J]. Sleep Med, 2024, 121(Sep)179-83.\u003c/li\u003e\n\u003cli\u003eOZCAN G, TEMEL E, ORNEK K, et al. Choroidal vascularity index in obstructive sleep apnea syndrome [J]. Sleep Breath, 2022, 26(4): 1655-9.\u003c/li\u003e\n\u003cli\u003eKUO C J, LIN C S, CHUANG C H, et al. Quantitative Morphometric Measurements of the Oropharynx in Obstructive Sleep Apnea Syndrome Using a Laser Depth Measurement Module [J]. Nat Sci Sleep, 2020, 12(14)1181-90.\u003c/li\u003e\n\u003cli\u003eCHUNG F, MEMTSOUDIS S G, RAMACHANDRAN S K, et al. Society of Anesthesia and Sleep Medicine Guidelines on Preoperative Screening and Assessment of Adult Patients With Obstructive Sleep Apnea [J]. Anesth Analg, 2016, 123(2): 452-73.\u003c/li\u003e\n\u003cli\u003eCOSENTINO F, GRANT P J, ABOYANS V, et al. 2019 ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD [J]. Eur Heart J, 2020, 41(2): 255-323.\u003c/li\u003e\n\u003cli\u003eFLACK J M, ADEKOLA B. Blood pressure and the new ACC/AHA hypertension guidelines [J]. Trends Cardiovasc Med, 2020, 30(3): 160-4.\u003c/li\u003e\n\u003cli\u003eMARINO A V, COSTIGLIOLA R, FIORETTO I. Choroidal vascularity index in obstructive sleep apnea syndrome [J]. Sleep Breath, 2023, 27(2): 771.\u003c/li\u003e\n\u003cli\u003eAKASHIBA T, INOUE Y, UCHIMURA N, et al. Sleep Apnea Syndrome (SAS) Clinical Practice Guidelines 2020 [J]. Respir Investig, 2022, 60(1): 3-32.\u003c/li\u003e\n\u003cli\u003eHUANG H H, TSAO C H, WEI J C. Voice Assessment in Patients With Obstructive Sleep Apnea Syndrome After Transoral Robotic Surgery [J]. Front Surg, 2021, 8(17)647792.\u003c/li\u003e\n\u003cli\u003eBAI X Q, SUN X G. [Sleep apnea and ocular diseases] [J]. Zhonghua Yan Ke Za Zhi, 2024, 60(3): 296-302.\u003c/li\u003e\n\u003cli\u003eNARANJO-BONILLA P, MUNOZ-VILLANUEVA M C, GIMENEZ-GOMEZ R, et al. Retinal and choroidal thickness measurements in obstructive sleep apnea: impacts of continuous positive airway pressure treatment [J]. Graefes Arch Clin Exp Ophthalmol, 2021, 259(11): 3381-93.\u003c/li\u003e\n\u003cli\u003eMAVIGOK E, OZCAN A A, ULAS B. Obsructive sleep apnea syndrome: is it a risk factor for ocular surface disease and ocular comorbidities? [J]. Int Ophthalmol, 2023, 43(7): 2329-34.\u003c/li\u003e\n\u003cli\u003eCOLAK M, OZEK D, OZCAN K M, et al. Evaluation of retinal vessel density and foveal avascular zone measurements in patients with obstructive sleep apnea syndrome [J]. Int Ophthalmol, 2021, 41(4): 1317-25.\u003c/li\u003e\n\u003cli\u003eALTINEL M G, USLU H, KANRA A Y, et al. Effect of obstructive sleep apnoea syndrome and continuous positive airway pressure treatment on choroidal structure [J]. Eye (Lond), 2022, 36(10): 1977-81.\u003c/li\u003e\n\u003cli\u003eAZAD A D, DAVILA J R, RAYESS N, et al. The Effect of Obstructive Sleep Apnea Treatment and Severity on Choroidal Thickness in Patients With Central Serous Chorioretinopathy [J]. J Vitreoretin Dis, 2022, 6(1): 22-30.\u003c/li\u003e\n\u003cli\u003eXU Q, WANG X, LIU P, et al. Correlation of cephalometric variables with obstructive sleep apnea severity among children: a hierarchical regression analysis [J]. Cranio, 2022, 26(Aug):1-8.\u003c/li\u003e\n\u003cli\u003eGOVINDAGOUDAR M B, LALWANI L K, SINGH P K, et al. Dynamic assessment of oropharynx with ultrasonography as a screening tool for obstructive sleep apnea [J]. J Sleep Res, 2023, 32(1): e13712.\u003c/li\u003e\n\u003cli\u003eLUN H M, LIU R C, HU Q, et al. Potential ultrasonic anatomical markers of obstructive sleep apnoea-hypopnoea syndrome [J]. Clin Radiol, 2023, 78(2): e137-e42.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"head-and-face-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hafm","sideBox":"Learn more about [Head \u0026 Face Medicine](http://head-face-med.biomedcentral.com)","snPcode":"13005","submissionUrl":"https://submission.nature.com/new-submission/13005/3","title":"Head \u0026 Face Medicine","twitterHandle":"@HeadNeckMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Choroidal vascular indicators, Oropharyngeal morphological indicators, Severe OSAS patients, CPAP, Treatment efficacy","lastPublishedDoi":"10.21203/rs.3.rs-6389207/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6389207/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThe goal of this paper is to explore the value of choroidal vascular and oropharyngeal morphological indicators in predicting the efficacy of Continuous Positive Airway Pressure (CPAP) treatment in patients with severe Obstructive Sleep Apnea Syndrome (OSAS).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 245 patients with severe OSAS between January 2022 and June 2024 from a hospital, treated with CPAP, were enrolled. Patients were divided into two groups based on treatment efficacy: the Good response group and the Poor response group. Choroidal vascular indicators [subfoveal choroidal thickness (SF-CT), choriocapillaris vessel density (CC-VD), choroidal vascularity index (CVI)] and oropharyngeal morphological indicators [posterior nasal spine to menton distance (PNS-Me), hyoid-mental distance (HMD), soft palate length (posterior nasal spine to uvular tip point, PNS-P1)] were compared between the two groups. Receiver Operating Characteristic (ROC) curves were drawn to analyze the predictive efficacy of these indicators for CPAP treatment in severe OSAS patients. A nomogram and calibration curve were created to develop a prediction model for CPAP treatment efficacy in severe OSAS patients.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn the Poor response group, the longest apnea duration (LAD), percentage of time with oxygen saturation\u0026thinsp;\u0026lt;\u0026thinsp;90% (TS90%), and apnea-hypopnea index (AHI) were all significantly higher than those in the Good response group. The lowest arterial oxygen saturation (LSaO2) was notably lower in the Poor response group compared to the other one (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The area under the curve (AUC) values ​​of SF-CT, CC-VD, and CVI for predicting the outcome of IBD patients were 0.835, 0.805, and 0.910, respectively. The AUC values ​​of PNS-Me, HMD, and PNS-P1 were 0.897, 0.937, and 0.898, respectively. In addition, the nomogram prediction model constructed with choroidal vascular and oropharyngeal morphology indicators had high accuracy.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eChoroidal vascular and oropharyngeal morphological indicators have a good predictive effect on CPAP treatment efficacy in patients with severe OSAS.\u003c/p\u003e","manuscriptTitle":"Choroidal Vascular and Oropharyngeal Morphological Indicators in Predicting CPAP Treatment Efficacy in Severe OSAS Patients: A Prospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 07:12:03","doi":"10.21203/rs.3.rs-6389207/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-12T08:08:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-11T05:44:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-06T08:46:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"266292585025685984759651973864466342493","date":"2025-05-05T10:31:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-01T08:58:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"92460245752515466964315151974265290161","date":"2025-05-01T08:56:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"278646193805588092986133608280134265953","date":"2025-04-29T11:26:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-29T06:14:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-09T09:11:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-09T09:10:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Head \u0026 Face Medicine","date":"2025-04-07T01:45:43+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"head-and-face-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hafm","sideBox":"Learn more about [Head \u0026 Face Medicine](http://head-face-med.biomedcentral.com)","snPcode":"13005","submissionUrl":"https://submission.nature.com/new-submission/13005/3","title":"Head \u0026 Face Medicine","twitterHandle":"@HeadNeckMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4e01deab-a096-4f17-9ee2-f452663fef50","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-06T16:04:20+00:00","versionOfRecord":{"articleIdentity":"rs-6389207","link":"https://doi.org/10.1186/s13005-025-00523-8","journal":{"identity":"head-and-face-medicine","isVorOnly":false,"title":"Head \u0026 Face Medicine"},"publishedOn":"2025-10-02 15:58:09","publishedOnDateReadable":"October 2nd, 2025"},"versionCreatedAt":"2025-05-07 07:12:03","video":"","vorDoi":"10.1186/s13005-025-00523-8","vorDoiUrl":"https://doi.org/10.1186/s13005-025-00523-8","workflowStages":[]},"version":"v1","identity":"rs-6389207","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6389207","identity":"rs-6389207","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}