Construction of a Nomogram Prediction Model for Poor Short-Term Outcome of Post-Stroke Dysphagia Based on Video Fluoroscopic Swallowing Study Temporal and Kinematic Parameters

doi:10.3969/j.issn.1673-5765.2025.09.010

Abstract

Abstract: Objective To construct a nomogram prediction model for poor short-term outcome of post-stroke dysphagia (PSD) based on video fluoroscopic swallowing study temporal and kinematic parameters, aiming to guide clinical nutritional support decisions.
Methods A total of 281 patients with PSD admitted to Cangzhou People’s Hospital from January 2021 to February 2025 were consecutively enrolled as the research subjects. Clinical data potentially associated with dysphagia were collected and statistically analyzed. Patients were divided into a training set (196 cases) and a validation set (85 cases) in a 7∶3 ratio by complete randomization. The proportion of patients with persistent dysphagia at 2 weeks after stroke (poor short-term outcome) in the training set was recorded, and its relationship with temporal and kinematic parameters of video fluoroscopic swallowing study, as well as other clinical data, was analyzed. Multivariate logistic stepwise regression analysis was used to identify independent influencing factors for poor short-term outcome of PSD, and a nomogram prediction model was constructed. ROC curves and calibration curves were plotted to evaluate the predictive efficacy of the model. Decision curve analysis was applied to assess its application value in clinical nutritional support decisions. The nomogram was validated in the validation set.
Results Among the 196 PSD patients in the training set, 86 (43.88%) had poor short-term outcomes, and 40 (47.06%) of the 85 PSD patients in the validation set showed poor short-term outcomes. There were no statistically significant differences in the rate of poor short-term outcomes and other clinical data between the training set and the validation set. Advanced age, higher NIHSS score at 24 hours post-admission, higher functional dysphagia scale score, higher penetration-aspiration scale score, prolonged oral transit time, prolonged cricopharyngeal opening time, lower pharyngeal contraction ratio, and shorter hyoid anterior displacement were independent risk factors for poor short-term outcome of PSD (all P<0.05). The nomogram prediction model based on video fluoroscopic swallowing study temporal and kinematic parameters showed good calibration and goodness-of-fit in both the training and validation sets (mean absolute errors between the predicted and actual values were 0.016 and 0.030, and the P-values of the Hosmer-Lemeshow test were 0.735 and 0.245, respectively). ROC curves showed that the AUCs of the nomogram prediction model for poor short-term outcome of PSD based on temporal and kinematic parameters were 0.945 (95%CI 0.915-0.975) in the training set and 0.944 (95%CI 0.896-0.991) in the validation set, outperforming the nomogram model based on conventional influencing factors [AUCs 0.893 (95%CI 0.846-0.939) and 0.881 (95%CI 0.805-0.956), respectively]. Decision curve analysis showed that when the threshold probability ranged from 0.05 to 0.97, the net benefit of the nomogram prediction model for poor short-term outcome of PSD (based on video fluoroscopic swallowing study temporal and kinematic parameters) was higher than that of the two extreme strategies: assuming all patients would experience poor short-term outcome of PSD or assuming no patients would experience poor short-term outcome of PSD before intervention.
Conclusions The nomogram prediction model for poor short-term outcome of PSD, constructed based on the temporal and kinematic parameters of video fluoroscopic swallowing study, is helpful for prediction of the risk of poor short-term outcome of PSD, guiding the clinical formulation of appropriate enteral feeding decisions, and optimizing the management of medical resources.

Key words: Video fluoroscopic swallowing; Post-stroke dysphagia; Outcome; Nomogram

摘要： 目的构建基于吞咽造影时间学及运动学参数的卒中后吞咽障碍（post-stroke dysphagia，PSD）短期转归不良的列线图预测模型，以指导临床营养支持决策。
方法连续纳入2021年1月—2025年2月沧州市人民医院收治的281例PSD患者为研究对象，收集并统计可能与吞咽障碍相关的临床资料。采用完全随机法按7∶3的比例将患者分为训练集（196例）和验证集（85例）。记录训练集中卒中后2周仍存在吞咽障碍（短期转归不良）的患者比例，分析其与吞咽造影时间学及运动学参数，以及其他临床资料的关系。采用多因素logistic逐步回归分析筛选PSD短期转归不良的独立影响因素，并构建列线图预测模型。通过ROC曲线及校准曲线评估模型的预测效能，应用决策曲线分析评估模型在临床营养支持决策中的应用价值，并在验证集中进行验证。
结果训练集196例PSD患者中，有86例（43.88%）短期转归不良，验证集85例PSD患者中，有40例（47.06%）短期转归不良，训练集和验证集在短期转归不良率及其他临床资料方面的差异均无统计学意义。高龄，较高的入院24 h NIHSS评分、功能性吞咽障碍量表评分和渗透-误吸量表评分，较长的口腔运送时间和环咽肌开放时间，较低的咽腔收缩率及较短的舌骨向前位移是PSD短期转归不良的独立危险因素（P＜0.05）。基于吞咽造影时间学及运动学参数的列线图预测模型在训练集和验证集中均表现出较好的校准度和拟合优度（预测值与真实值之间的平均绝对误差分别为0.016和0.030；Hosmer-Lemeshow检验的P值分别为0.735和0.245）。ROC曲线显示，在训练集和验证集中，基于吞咽造影时间学及运动学参数的PSD短期转归不良列线图预测模型的AUC分别为0.945（95%CI 0.915～0.975）和0.944（95%CI 0.896～0.991），优于基于常规影响因素的列线图预测模型[AUC分别为0.893（95%CI 0.846～0.939）和0.881（95%CI 0.805～0.956）]。决策曲线分析表明，当阈值概率在0.05～0.97时，基于吞咽造影时间学及运动学参数的PSD短期转归不良列线图预测模型的决策净收益高于治疗前认为全部患者均会发生PSD短期转归不良或全部患者均未发生PSD短期转归不良的决策净收益。
结论基于吞咽造影时间学及运动学参数构建的PSD短期转归不良列线图预测模型，有助于预测PSD短期转归不良风险，指导临床制订肠内喂养决策，并优化医疗资源管理。

关键词: 吞咽造影; 卒中后吞咽障碍; 转归; 列线图

CLC Number:

R743

ZHAO Dianlan, WANG Yan, ZHANG Hongjun, DONG Mengtian, HU Tao. Construction of a Nomogram Prediction Model for Poor Short-Term Outcome of Post-Stroke Dysphagia Based on Video Fluoroscopic Swallowing Study Temporal and Kinematic Parameters[J]. Chinese Journal of Stroke, 2025, 20(9): 1146-1156.

赵殿兰, 王燕, 张宏君, 董梦甜, 胡涛. 基于吞咽造影时间学及运动学参数构建卒中后吞咽障碍短期转归不良的列线图预测模型[J]. 中国卒中杂志, 2025, 20(9): 1146-1156.

References

[1] HUPPERTZ V A L，PILZ W，PILZ DA CUNHA G，et al. Malnutrition risk and oropharyngeal dysphagia in the chronic post-stroke phase[J/OL]. Front Neurol，2022，13：939735[2025-04-20]. https://doi.org/10.3389/fneur.2022.939735.
[2] 孟萍萍. rTMS对吞咽神经网络的影响及其与NMES联合对卒中后吞咽障碍的疗效观察[D]. 济南：山东大学，2021.
MENG P P. Effect of rTMS on swallowing neural network and its combination with NMES on dysphagia after stroke[D]. Ji’nan：Shandong University，2021.
[3] 卒中患者吞咽障碍和营养管理中国专家组. 卒中患者吞咽障碍和营养管理的中国专家共识（2013版）[J]. 中国卒中杂志，2013，8（12）：973-983.
Chinese Expert Group on Dysphagia and Nutritional Management in Stroke Patients. Chinese expert consensus on dysphagia and nutritional management in stroke patients（2013 edition）[J]. Chin J Stroke，2013，8（12）：973-983.
[4] WATANABE S，OH-SHIGE H，OH-IWA I，et al. Reconsideration of three screening tests for dysphagia in patients with cerebrovascular disease performed by non-expert examiners[J]. Odontology，2020，108（1）：117-123.
[5] HAN T R，PAIK N J，PARK J W. Quantifying swallowing function after stroke：a functional dysphagia scale based on videofluoroscopic studies[J]. Arch Phys Med Rehabil，2001，82（5）：677-682.
[6] SEO Z W，MIN J H，HUH S，et al. Prevalence and severity of dysphagia using videofluoroscopic swallowing study in patients with aspiration pneumonia[J]. Lung，2021，199（1）：55-61.
[7] SEO H G，OH B M，HAN T R. Swallowing kinematics and factors associated with laryngeal penetration and aspiration in stroke survivors with dysphagia[J]. Dysphagia，2016，31（2）：160-168.
[8] LEE K M，KIM H J. Practical assessment of dysphagia in stroke patients[J]. Ann Rehabil Med，2015，39（6）：1018-1027.
[9] LABEIT B，MICHOU E，HAMDY S，et al. The assessment of dysphagia after stroke：state of the art and future directions[J]. Lancet Neurol，2023，22（9）：858-870.
[10] 徐涵，吴霜. 卒中后吞咽神经功能代偿与重塑的机制研究进展[J]. 中国康复，2020，35（4）：212-216.
XU H，WU S. Research progress on the mechanism of compensation and remodeling of swallowing nerve function after stroke[J]. Chinese Journal of Rehabilitation，2020，35（4）：212-216.
[11] IKENOUCHI H，NOZUE K，YAMAGUCHI S，et al. Geriatric nutrition risk index predicts prolonged post-stroke dysphagia in acute ischemic stroke[J/OL]. J Stroke Cerebrovasc Dis，2023，32（8）：107207[2025-04-20]. https://doi.org/10.1016/j.jstrokecerebrovasdis.2023.107207.
[12] BANDA K J，CHU H，KANG X L，et al. Prevalence of dysphagia and risk of pneumonia and mortality in acute stroke patients：a meta-analysis[J/OL]. BMC Geriatr，2022，22：420[2025-04-20]. https://doi.org/10.1186/s12877-022-02960-5.
[13] 田雅琦，邱立欣，谷媛媛，等. 脑卒中吞咽困难病人吞咽造影特点及其对误吸的预测价值研究[J]. 中西医结合心脑血管病杂志，2023，21（23）：4421-4428.
TIAN Y Q，QIU L X，GU Y Y，et al. Study on the characteristics of swallowing angiography in stroke patients with dysphagia and its predictive value for aspiration[J]. Chinese Journal of Integrative Medicine on Cardio-Cerebrovascular Disease，2023，21（23）：4421-4428.
[14] SUZUKI M，KOYAMA S，KIMURA Y，et al. Relationship between tongue muscle quality and swallowing speed in community-dwelling older women[J]. Aging Clin Exp Res，2020，32（10）：2073-2079.
[15] 孙彩杰，占婷婷，王丽丽，等. 基于logistic回归构建脑卒中后吞咽障碍的预测模型[J]. 承德医学院学报，2022，39（6）：494-498.
SUN C J，ZHAN T T，WANG L L，et al. Construction of a predictive model for dysphagia after stroke based on logistic regression[J]. Journal of Chengde Medical University，2022，39（6）：494-498.
[16] WANG C M，CHEN J Y，CHUANG C C，et al. Aging-related changes in swallowing，and in the coordination of swallowing and respiration determined by novel non-invasive measurement techniques[J]. Geriatr Gerontol Int，2015，15（6）：736-744.
[17] LEITE K K A，SASSI F C，MEDEIROS G C，et al. Clinical swallowing prognostic indicators in patients with acute ischemic stroke[J]. Arq Neuropsiquiatr，2019，77（7）：501-508.
[18] LI P，ZHANG Q L，LI S Y. The relationship between acute inflammatory cytokines，nerve function defect，daily living ability and PSD[J]. Chin J Appl Physiol，2017，33（2）：121-123.
[19] ROFES L，MURIANA D，PALOMERAS E，et al. Prevalence，risk factors and complications of oropharyngeal dysphagia in stroke patients：a cohort study[J/OL]. Neurogastroenterol Motil，2018：e13338[2025-04-20]. https://doi.org/10.1111/nmo.13338.
[20] OKUBO P C M I，FÁBIO S R C，DOMENIS D R，et al. Using the National Institute of Health stroke scale to predict dysphagia in acute ischemic stroke[J]. Cerebrovasc Dis，2012，33（6）：501-507.
[21] 戴萌，张耀文，安德连，等. 吞咽造影检查在脑卒中患者口服胶囊吞咽功能评估中的应用研究[J]. 中华物理医学与康复杂志，2019，41（9）：647-650.
DAI M，ZHANG Y W，AN D L，et al. Videofluoroscopy for assessing the capsule swallowing capability of stroke survivors[J]. Chin J Phys Med Rehabil，2019，41（9）：647-650.
[22] 麦艺颖，戴萌，谢纯青，等. 电视透视吞咽检查定量评价脑干梗死患者吞咽障碍特点的临床研究[J]. 中华物理医学与康复杂志，2018，40（2）：87-90.
MAI Y Y，DAI M，XIE C Q，et al. Dysphagia after brain stem infarction：a quantitative analysis of videofluoroscopic observations[J]. Chin J Phys Med Rehabil，2018，40（2）：87-90.
[23] 张茜，代欣，贺媛，等. 吞咽造影数字化分析咽腔电刺激对吞咽康复的作用[J]. 河北医药，2024，46（4）：547-550，554.
ZHANG Q，DAI X，HE Y，et al. Effectiveness of digital analysis of swallowing radiography and the electrical stimulation of pharyngeal cavity on swallowing rehabilitation[J]. Hebei Medical Journal，2024，46（4）：547-550，554.
[24] STEELE C M，BAILEY G L，CHAU T，et al. The relationship between hyoid and laryngeal displacement and swallowing impairment[J]. Clin Otolaryngol，2011，36（1）：30-36.
[25] UEDA N，NOHARA K，KOTANI Y，et al. Effects of the bolus volume on hyoid movements in normal individuals[J]. J Oral Rehabil，2013，40（7）：491-499.
[26] SIA I，CARVAJAL P，LACY A A，et al. Hyoid and laryngeal excursion kinematics-magnitude，duration and velocity-changes following successful exercise-based dysphagia rehabilitation：MDTP[J]. J Oral Rehabil，2015，42（5）：331-339.
[27] TANG A L，CHEN X X，MA J J，et al. Characteristics of submental muscles function and hyoid bone movement in patients with dysphagia after stroke[J/OL]. Clin Biomech（Bristol），2022，100：105772[2025-04-20]. https://doi.org/10.1016/j.clinbiomech.2022.105772.
[28] CABIB C，ORTEGA O，KUMRU H，et al. Neuroreha-bilitation strategies for poststroke oropharyngeal dysphagia：from compensation to the recovery of swallowing function[J]. Ann N Y Acad Sci，2016，1380（1）：121-138.