儿童OSAHS疾病严重程度影响因素分析及临床预测价值

doi:10.6040/j.issn.1673-3770.0.2025.391

摘要/Abstract

摘要： 目的分析儿童阻塞性睡眠呼吸暂停低通气综合征(obstructive sleep apnea-hypopnea syndrome, OSAHS)疾病严重程度的影响因素,并评估其临床预测价值。方法选取2023年1月至2024年12月在石家庄人民医院就诊的OSAHS患儿182例为研究对象,采集人口学信息、多导睡眠监测及血常规检测结果,计算系统性炎症指标。采用差异性比较、Spearman等级相关、随机森林模型和logistic回归模型分析OSAHS患儿疾病严重程度的影响因素,并基于影响因素构建预测模型,通过受试者工作特征(receiver operating characteristic, ROC)曲线评价预测效能。结果轻度和中、重度OSAHS患儿在体质量指数(body mass index, BMI)、早产史及系统性炎症指标上差异有统计学意义(P<0.05)。Spearman等级相关及随机森林模型分析结果显示,中性粒细胞-淋巴细胞比值(neutrophil-lymphocyte ratio, NLR)是6种系统性炎症指标中对疾病严重程度影响最大的变量。logistic回归分析结果显示,BMI(OR=1.383,95%CI:1.201~1.592)和NLR(OR=1.575,95%CI:1.262~1.965)越大,OSAHS患儿疾病为中、重度的风险越高(P<0.05)。ROC曲线分析结果显示,构建的预测模型预测OSAHS患儿疾病严重程度的曲线下面积为0.800(95%CI:0.734~0.856)。结论 BMI和NLR是OSAHS患儿疾病严重程度的影响因素,基于二者构建的预测模型预测效能较好,有助于早期评估儿童OSAHS疾病严重程度,指导临床诊疗工作的开展。

关键词: 阻塞性睡眠呼吸暂停通气综合征, 疾病严重程度, 系统性炎症指标, 体质量指数, 预测模型

Abstract: Objective To analyze the influencing factors for disease severity in pediatric obstructive sleep apnea-hypopnea syndrome(OSAHS)and assess their clinical predictive value. Methods A total of 182 children with OSAHS treated at Shijiazhuang People's Hospital from January 2023 to December 2024 were enrolled. Demographic information, polysomnography data, and complete blood count results were collected, and systemic inflammatory indicators were calculated. Differences between groups, Spearman rank correlation, random forest model, and logistic regression analysis were used to identify factors influencing disease severity in children with OSAHS, and a prediction model was constructed based on these factors. The predictive performance was evaluated using the receiver operating characteristic(ROC)curve. Results Statistically significant differences were observed in body mass index(BMI), history of premature birth, and systemic inflammatory indicators between children with mild OSAHS and those with moderate to severe OSAHS(P<0.05). Spearman rank correlation and random forest model analysis revealed that the neutrophil-to-lymphocyte ratio(NLR)was the most influential variable among the six systemic inflammatory indicators affecting disease severity. Logistic regression analysis showed that higher BMI(OR=1.383, 95%CI: 1.201-1.592)and higher NLR(OR=1.575, 95%CI: 1.262-1.965)were associated with an increased risk of moderate to severe OSAHS(P<0.05). ROC curve analysis demonstrated that the constructed prediction model achieved an area under the curve of 0.800(95%CI: 0.734-0.856)for predicting disease severity. Conclusion BMI and NLR are influencing factors for disease severity in children with OSAHS. The prediction model based on these two factors demonstrates good predictive performance, which may facilitate early assessment of disease severity and guide clinical management.

Key words: Obstructive sleep apnea hypopnea syndrome, Disease severity, Systemic inflammation indicator, Body mass index, Prediction model

中图分类号:

R725.6

赵辉明,刘彬,陈坤,李亚非,陈姿. 儿童OSAHS疾病严重程度影响因素分析及临床预测价值[J]. 山东大学耳鼻喉眼学报, 2026, 40(5): 57-64.

ZHAO Huiming, LIU Bin, CHEN Kun, LI Yafei, CHEN Zi. Influencing factors and clinical predictive value for disease severity in pediatric obstructive sleep apnea-hypopnea syndrome[J]. Journal of Otolaryngology and Ophthalmology of Shandong University, 2026, 40(5): 57-64.

参考文献

[1] Picherit M, Trentesaux T, Ternisien A, et al. Management of obstructive sleep apnea-hypopnea syndrome in children: what is the role of orthodontics? A scoping review[J]. Sleep Breath, 2025, 29(2): 127. DOI:10.1007/s11325-025-03288-1
[2] 张一彤, 李青香, 石争浩, 等. 阻塞性睡眠呼吸暂停儿童睡眠结构研究及睡眠结构判读模型建立[J]. 山东大学耳鼻喉眼学报, 2023, 37(6): 126-132. DOI:10.6040/j.issn.1673-3770.0.2023.168
[3] Jalumuru A, Ramya MS, Punithavathy R, et al. Prevalence of obstructive sleep apnea in 6- to 12-year-old children in Rajanagaram Mandal - a cross-sectional study[J]. J Indian Soc Pedod Prev Dent, 2025, 43(2): 189-194. DOI:10.4103/jisppd.jisppd_145_25
[4] 王夏燕, 凌继祖, 叶新华, 等. 阻塞性睡眠呼吸暂停低通气综合征对肥胖儿童智力发育水平影响的研究进展[J]. 中国儿童保健杂志, 2025, 33(2): 203-207. DOI:10.11852/zgetbjzz2024-0616
[5] Chao Y, Chuang HH, Lin WN, et al. Interplay of weight status and sleep autonomic function in mediating and moderating the link between disease severity and blood pressure in paediatric obstructive sleep apnoea[J]. Clin Otolaryngol, 2025, 50(3): 521-527. DOI:10.1111/coa.14286
[6] Kadier K, Dilixiati D, Ainiwaer A, et al. Analysis of the relationship between sleep-related disorder and systemic immune-inflammation index in the US population[J]. BMC Psychiatry, 2023, 23(1): 773. DOI:10.1186/s12888-023-05286-7
[7] Kim M, Cho SW, Won TB, et al. Associations between systemic inflammatory markers based on blood cells and polysomnographic factors in obstructive sleep apnea[J]. Clin Exp Otorhinolaryngol, 2023, 16(2): 159-164. DOI:10.21053/ceo.2022.01368
[8] 章娜娜, 杨学森, 卢标清. 阻塞性睡眠呼吸暂停低通气综合征患者血WBC、FIB、NLR、PLR变化及其与病情的关系[J]. 临床和实验医学杂志, 2024, 23(23): 2546-2550. DOI:10.3969/j.issn.1671-4695.2024.23.021
[9] 倪鑫. 中国儿童阻塞性睡眠呼吸暂停诊断与治疗指南(2020)[J]. 中国循证医学杂志, 2020, 20(8): 883-900
[10] Yang ZP, Xue Z, Tao YJ, et al. Systemic inflammatory status of patients with obstructive sleep apnea syndrome and the predictive value of heparin-binding protein[J]. Ear Nose Throat J, 2023: 1455613231202490. DOI:10.1177/01455613231202490
[11] Gündüz Ö, Akbal Çufalı ?瘙塁. Correlation of polysomnography data and inflammatory markers after sleep surgery[J]. Acta Otolaryngol, 2025, 145(5): 457-462. DOI:10.1080/00016489.2025.247030
[12] 王照石, 刘欣, 单丽华. 儿童阻塞性睡眠呼吸暂停低通气综合征的诊断方法与标准[J]. 口腔疾病防治, 2022, 30(2): 148-152. DOI:10.12016/j.issn.2096?1456.2022.02.012
[13] Peduzzi P, Concato J, Kemper E, et al. A simulation study of the number of events per variable in logistic regression analysis[J]. J Clin Epidemiol, 1996, 49(12): 1373-1379. DOI:10.1016/S0895-4356(96)00236-3
[14] Huang GM, Wang Q, Chang L, et al. Impact of gender, age, and obesity on childhood obstructive sleep apnea: a cross-sectional study of 4, 668 children[J]. Nat Sci Sleep, 2025, 17: 1391-1404. DOI:10.2147/nss.s521415
[15] Ramírez-Contreras C, Elgueta VP, Briones-Suárez L. Childhood OSAS and obesity: prospective associations of anthropometric markers with objective sleep outcomes in the CHAT trial[J]. J Sleep Res, 2026, 35(2): e70156. DOI:10.1111/jsr.70156
[16] 于悦, 谭慧文, 刘奕姝, 等. 阻塞性睡眠呼吸暂停低通气综合征病情严重程度的影响因素及代谢相关激素与临床相关指标的关系研究[J]. 中国全科医学, 2021, 24(8): 947-953. DOI:10.12114/j.issn.1007-9572.2021.00.142
[17] 文艺, 谢世麒, 周建荣, 等. 阻塞性睡眠呼吸暂停低通气综合征合并超重或肥胖的临床特征及影响因素研究[J]. 重庆医科大学学报, 2023, 48(11): 1387-1392. DOI:10.13406/j.cnki.cyxb.003372
[18] 董世佳. 儿童阻塞性睡眠呼吸暂停低通气综合征的多导睡眠监测特点及病情严重程度的影响因素分析[D]. 南充: 川北医学院, 2023: 29
[19] 窦海艳, 纪海辉, 张晓波. OSAHS患者病因及疾病严重度相关性研究[J]. 世界最新医学信息文摘(连续型电子期刊), 2021, 21(24): 115-116. DOI:10.3969/j.issn.1671-3141.2021.24.05
[20] Dong N, Yue HM. Advances in immunology of obstructive sleep apnea: mechanistic insights, clinical impact, and therapeutic perspectives[J]. Front Immunol, 2025, 16: 1654450. DOI:10.3389/fimmu.2025.1654450
[21] Kayali Dinç AS, Gülhan Ya?瘙塂ar N, Yeniçeri A, et al. Role of hematological parameters and inflammatory indices in determining the severity of obstructive sleep apnea syndrome: reality or myth?[J]. Eur Arch Otorhinolaryngol, 2025, 282(8): 4343-4348. DOI:10.1007/s00405-025-09528-0
[22] Güne?瘙塂 ZY, Günaydın FM. The relationship between the systemic immune-inflammation index and obstructive sleep apnea[J]. Sleep Breath, 2024, 28(1): 311-317. DOI:10.1007/s11325-023-02913-1
[23] 牟嘉砾, 沈蓓. NLR、 PLR与儿童OSAHS的相关性研究[J]. 临床耳鼻咽喉头颈外科杂志, 2017, 31(22): 1732-1734, 1739. DOI:10.13201/j.issn.1001-1781.2017.22.007
[24] 米尔吾提·布尔勒克. 中性粒细胞/淋巴细胞比值、血小板/淋巴细胞比值在儿童OSAHS中的变化研究[D]. 乌鲁木齐: 新疆医科大学, 2024: 27
[25] 高俊康, 万玉峰. 阻塞性睡眠呼吸暂停低通气综合征患者病情严重程度与血液学指标的相关性分析[J]. 医学信息, 2021, 34(4): 84-87, 91. DOI:10.3969/j.issn.1006-1959.2021.04.022
[26] 张梁, 吴峰, 徐光辉. NLR和PLR及PDW与OSAHS患者严重程度的相关性研究[J]. 当代医学, 2021, 27(21): 89-91. DOI:10.3969/j.issn.1009-4393.2021.21.036
[27] 冯媛. NLR、 PLR和SII在阻塞性睡眠呼吸暂停低通气综合征患者中的变化及其临床意义[D]. 石家庄: 河北医科大学, 2023: 23
[28] Zorlu D, Ozyurt S, Bırcan HA, et al. Do complete blood count parameters predict diagnosis and disease severity in obstructive sleep apnea syndrome?[J]. Eur Rev Med Pharmacol Sci, 2021, 25(11): 4027-4036
[29] Hou ZW, Chen C, Liu H, et al. Predictive value of neutrophil-to-lymphocyte ratio for cerebral infarction in obstructive sleep apnea: a nomogram-based analysis[J]. Nat Sci Sleep, 2025, 17: 1777-1787. DOI:10.2147/NSS.S536799
[30] Yu B, Wei J, Zhao JQ, et al. The neutrophil-to-lymphocyte ratio is a potential biomarker for the occurrence of atrial fibrillation in patients with obstructive sleep apnea: a BIOMARKER OF AF IN OSA PATIENTS[J]. Sleep Med, 2023, 110: 259-267. DOI:10.1016/j.sleep.2023.08.004
[31] Düger M, Seyhan EC, Günlüo glu MZ, et al. Does ischemia-modified albumin level predict severity of obstructive sleep apnea?[J]. Sleep Breath, 2021, 25(1): 65-73. DOI:10.1007/s11325-020-02038-9

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