Multivariate predictive model of the therapeutic effects of metoprolol in paediatric vasovagal syncope: a multi-centre studyResearch in context
Summary: Background: Metoprolol therapy for paediatric vasovagal syncope (VVS) has yielded inconsistent results, necessitating predictive markers. We aimed to develop and validate models to identify paediatric VVS patients likely to benefit from metoprolol. Methods: 478 metoprolol-treated paediatri...
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Elsevier
2025-03-01
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| author | Yaxi Cui Jing Zhang Yuwen Wang Ying Liao Keyu Liu Wenrui Xu Shu Wu Chufan Sun Chunyu Zhang Qingyou Zhang Ping Liu Yuli Wang Yanjun Deng Chen Shen Yao Lin Hong Cai Juan Zhang Runmei Zou Ping Liu Shuo Wang Hongfang Jin Lin Shi Cheng Wang Junbao Du |
| author_facet | Yaxi Cui Jing Zhang Yuwen Wang Ying Liao Keyu Liu Wenrui Xu Shu Wu Chufan Sun Chunyu Zhang Qingyou Zhang Ping Liu Yuli Wang Yanjun Deng Chen Shen Yao Lin Hong Cai Juan Zhang Runmei Zou Ping Liu Shuo Wang Hongfang Jin Lin Shi Cheng Wang Junbao Du |
| author_sort | Yaxi Cui |
| collection | DOAJ |
| description | Summary: Background: Metoprolol therapy for paediatric vasovagal syncope (VVS) has yielded inconsistent results, necessitating predictive markers. We aimed to develop and validate models to identify paediatric VVS patients likely to benefit from metoprolol. Methods: 478 metoprolol-treated paediatric patients with VVS were enrolled from three syncope units and divided into retrospective training (March 2017–March 2023, n = 323) and prospective validation cohorts (April 2023–March 2024, n = 155). Fourteen patients (2.9%) were excluded for lacking follow-up data. Patients were classified as responders or non-responders based on symptom improvement after 1–3 months of metoprolol therapy. Univariate analysis and logistic regression were used to select the candidate predictors. A nomogram and a scoring model were established to predict treatment efficacy. The model values were analysed using a receiver operating characteristic (ROC) curve. Consistency was evaluated using the Hosmer–Lemeshow (H-L) test, calibration curve, and concordance index (C-index). The clinical utility of model was assessed through the decision curve analysis (DCA). Internal validation was performed using the bootstrap approach. The predictive model derived from the training cohort was validated in the validation cohort to assess its accuracy and feasibility. Findings: Increased heart rate during positive response in head-up tilt test (ΔHR), corrected QT interval dispersion (QTcd), and standard deviation of all normal-to-normal intervals (SDNN) were selected as independent predictors to develop a predictive model. A nomogram model was built (AUC: 0.900, 95% CI: 0.867–0.932); the H-L test and calibration curves showed a strong alignment between predicted and actual results. The scoring model was established in the training cohort (AUC: 0.941, 95% CI: 0.897–0.985), yielding a sensitivity of 82.8% and a specificity of 96.5%, with a cut-off value of 2.5 points. In the external validation cohort, the scoring model achieved a sensitivity, specificity, and accuracy of 93.6%, 80.9%, and 87.7%, respectively. Interpretation: The nomogram and scoring model were constructed to predict the efficacy of metoprolol for children with VVS, which will greatly assist paediatricians in the individual management of VVS in children and adolescents. Funding: This research was funded by National High-Level Hospital Clinical Research Funding (Clinical Research Project of Peking University First Hospital, grant number 2022CR59). |
| format | Article |
| id | doaj-art-9f1a6850632f407b97fdb1106e5d18fc |
| institution | OA Journals |
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| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
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| spelling | doaj-art-9f1a6850632f407b97fdb1106e5d18fc2025-08-20T02:13:27ZengElsevierEBioMedicine2352-39642025-03-0111310559510.1016/j.ebiom.2025.105595Multivariate predictive model of the therapeutic effects of metoprolol in paediatric vasovagal syncope: a multi-centre studyResearch in contextYaxi Cui0Jing Zhang1Yuwen Wang2Ying Liao3Keyu Liu4Wenrui Xu5Shu Wu6Chufan Sun7Chunyu Zhang8Qingyou Zhang9Ping Liu10Yuli Wang11Yanjun Deng12Chen Shen13Yao Lin14Hong Cai15Juan Zhang16Runmei Zou17Ping Liu18Shuo Wang19Hongfang Jin20Lin Shi21Cheng Wang22Junbao Du23Department of Pediatrics, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Pediatric Cardiology, Children's Hospital, Capital Institute of Pediatrics, Beijing, 100020, ChinaDepartment of Pediatric Cardiovasology, Children's Medical Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, ChinaDepartment of Pediatrics, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Pediatrics, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Pediatrics, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Pediatrics, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Pediatrics, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Pediatrics, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Pediatrics, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Pediatrics, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Pediatrics, Peking University First Hospital, Beijing, 100034, ChinaDepartment of Pediatric Cardiology, Children's Hospital, Capital Institute of Pediatrics, Beijing, 100020, ChinaDepartment of Pediatric Cardiology, Children's Hospital, Capital Institute of Pediatrics, Beijing, 100020, ChinaDepartment of Pediatric Cardiology, Children's Hospital, Capital Institute of Pediatrics, Beijing, 100020, ChinaDepartment of Pediatric Cardiovasology, Children's Medical Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, ChinaDepartment of Pediatric Cardiovasology, Children's Medical Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, ChinaDepartment of Pediatric Cardiovasology, Children's Medical Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, ChinaDepartment of Pediatric Cardiovasology, Children's Medical Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, ChinaDepartment of Pediatric Cardiovasology, Children's Medical Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, ChinaDepartment of Pediatrics, Peking University First Hospital, Beijing, 100034, China; Corresponding author.Department of Pediatric Cardiology, Children's Hospital, Capital Institute of Pediatrics, Beijing, 100020, China; Corresponding author.Department of Pediatric Cardiovasology, Children's Medical Center, The Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China; Corresponding author.Department of Pediatrics, Peking University First Hospital, Beijing, 100034, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, 100191, China; Corresponding author. Department of Pediatrics, Peking University First Hospital, Beijing, 100034, China.Summary: Background: Metoprolol therapy for paediatric vasovagal syncope (VVS) has yielded inconsistent results, necessitating predictive markers. We aimed to develop and validate models to identify paediatric VVS patients likely to benefit from metoprolol. Methods: 478 metoprolol-treated paediatric patients with VVS were enrolled from three syncope units and divided into retrospective training (March 2017–March 2023, n = 323) and prospective validation cohorts (April 2023–March 2024, n = 155). Fourteen patients (2.9%) were excluded for lacking follow-up data. Patients were classified as responders or non-responders based on symptom improvement after 1–3 months of metoprolol therapy. Univariate analysis and logistic regression were used to select the candidate predictors. A nomogram and a scoring model were established to predict treatment efficacy. The model values were analysed using a receiver operating characteristic (ROC) curve. Consistency was evaluated using the Hosmer–Lemeshow (H-L) test, calibration curve, and concordance index (C-index). The clinical utility of model was assessed through the decision curve analysis (DCA). Internal validation was performed using the bootstrap approach. The predictive model derived from the training cohort was validated in the validation cohort to assess its accuracy and feasibility. Findings: Increased heart rate during positive response in head-up tilt test (ΔHR), corrected QT interval dispersion (QTcd), and standard deviation of all normal-to-normal intervals (SDNN) were selected as independent predictors to develop a predictive model. A nomogram model was built (AUC: 0.900, 95% CI: 0.867–0.932); the H-L test and calibration curves showed a strong alignment between predicted and actual results. The scoring model was established in the training cohort (AUC: 0.941, 95% CI: 0.897–0.985), yielding a sensitivity of 82.8% and a specificity of 96.5%, with a cut-off value of 2.5 points. In the external validation cohort, the scoring model achieved a sensitivity, specificity, and accuracy of 93.6%, 80.9%, and 87.7%, respectively. Interpretation: The nomogram and scoring model were constructed to predict the efficacy of metoprolol for children with VVS, which will greatly assist paediatricians in the individual management of VVS in children and adolescents. Funding: This research was funded by National High-Level Hospital Clinical Research Funding (Clinical Research Project of Peking University First Hospital, grant number 2022CR59).http://www.sciencedirect.com/science/article/pii/S2352396425000398ChildrenMulti-centre studyVasovagal syncopeMetoprololEffectivenessPredictive model |
| spellingShingle | Yaxi Cui Jing Zhang Yuwen Wang Ying Liao Keyu Liu Wenrui Xu Shu Wu Chufan Sun Chunyu Zhang Qingyou Zhang Ping Liu Yuli Wang Yanjun Deng Chen Shen Yao Lin Hong Cai Juan Zhang Runmei Zou Ping Liu Shuo Wang Hongfang Jin Lin Shi Cheng Wang Junbao Du Multivariate predictive model of the therapeutic effects of metoprolol in paediatric vasovagal syncope: a multi-centre studyResearch in context EBioMedicine Children Multi-centre study Vasovagal syncope Metoprolol Effectiveness Predictive model |
| title | Multivariate predictive model of the therapeutic effects of metoprolol in paediatric vasovagal syncope: a multi-centre studyResearch in context |
| title_full | Multivariate predictive model of the therapeutic effects of metoprolol in paediatric vasovagal syncope: a multi-centre studyResearch in context |
| title_fullStr | Multivariate predictive model of the therapeutic effects of metoprolol in paediatric vasovagal syncope: a multi-centre studyResearch in context |
| title_full_unstemmed | Multivariate predictive model of the therapeutic effects of metoprolol in paediatric vasovagal syncope: a multi-centre studyResearch in context |
| title_short | Multivariate predictive model of the therapeutic effects of metoprolol in paediatric vasovagal syncope: a multi-centre studyResearch in context |
| title_sort | multivariate predictive model of the therapeutic effects of metoprolol in paediatric vasovagal syncope a multi centre studyresearch in context |
| topic | Children Multi-centre study Vasovagal syncope Metoprolol Effectiveness Predictive model |
| url | http://www.sciencedirect.com/science/article/pii/S2352396425000398 |
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