Derivation and internal validation of prediction models for pulmonary hypertension risk assessment in a cohort inhabiting Tibet, China
Individuals residing in plateau regions are susceptible to pulmonary hypertension (PH) and there is an urgent need for a prediction nomogram to assess the risk of PH in this population. A total of 6603 subjects were randomly divided into a derivation set and a validation set at a ratio of 7:3. Optim...
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eLife Sciences Publications Ltd
2024-11-01
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| author | Junhui Tang Rui Yang Hui Li Xiaodong Wei Zhen Yang Wenbin Cai Yao Jiang Ga Zhuo Li Meng Yali Xu |
| author_facet | Junhui Tang Rui Yang Hui Li Xiaodong Wei Zhen Yang Wenbin Cai Yao Jiang Ga Zhuo Li Meng Yali Xu |
| author_sort | Junhui Tang |
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| description | Individuals residing in plateau regions are susceptible to pulmonary hypertension (PH) and there is an urgent need for a prediction nomogram to assess the risk of PH in this population. A total of 6603 subjects were randomly divided into a derivation set and a validation set at a ratio of 7:3. Optimal predictive features were identified through the least absolute shrinkage and selection operator regression technique, and nomograms were constructed using multivariate logistic regression. The performance of these nomograms was evaluated and validated using the area under the curve (AUC), calibration curves, the Hosmer–Lemeshow test, and decision curve analysis. Comparisons between nomograms were conducted using the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices. NomogramI was established based on independent risk factors, including gender, Tibetan ethnicity, age, incomplete right bundle branch block (IRBBB), atrial fibrillation (AF), sinus tachycardia (ST), and T wave changes (TC). The AUCs for NomogramI were 0.716 in the derivation set and 0.718 in the validation set. NomogramII was established based on independent risk factors, including Tibetan ethnicity, age, right axis deviation, high voltage in the right ventricle, IRBBB, AF, pulmonary P waves, ST, and TC. The AUCs for NomogramII were 0.844 in the derivation set and 0.801 in the validation set. Both nomograms demonstrated satisfactory clinical consistency. The IDI and NRI indices confirmed that NomogramII outperformed NomogramI. Therefore, the online dynamic NomogramII was established to predict the risks of PH in the plateau population. |
| format | Article |
| id | doaj-art-d454dcbb0bc944f8a9a360426482d36e |
| institution | Kabale University |
| issn | 2050-084X |
| language | English |
| publishDate | 2024-11-01 |
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| spelling | doaj-art-d454dcbb0bc944f8a9a360426482d36e2024-11-11T13:40:34ZengeLife Sciences Publications LtdeLife2050-084X2024-11-011310.7554/eLife.98169Derivation and internal validation of prediction models for pulmonary hypertension risk assessment in a cohort inhabiting Tibet, ChinaJunhui Tang0https://orcid.org/0000-0001-6215-2913Rui Yang1https://orcid.org/0000-0002-6949-7428Hui Li2Xiaodong Wei3Zhen Yang4Wenbin Cai5Yao Jiang6Ga Zhuo7Li Meng8Yali Xu9https://orcid.org/0000-0002-6311-8757Department of Ultrasound, the General Hospital of Tibet Military Command, Tibet, ChinaDepartment of High Mountain Sickness, the General Hospital of Tibet Military Command, Tibet, ChinaDepartment of Ultrasound, the General Hospital of Tibet Military Command, Tibet, ChinaDepartment of Ultrasound, the General Hospital of Tibet Military Command, Tibet, ChinaDepartment of Ultrasound, the General Hospital of Tibet Military Command, Tibet, ChinaDepartment of Ultrasound, the General Hospital of Tibet Military Command, Tibet, ChinaDepartment of Ultrasound, the General Hospital of Tibet Military Command, Tibet, ChinaDepartment of Ultrasound, the General Hospital of Tibet Military Command, Tibet, ChinaDepartment of Ultrasound, the General Hospital of Tibet Military Command, Tibet, ChinaDepartment of Ultrasound, Xinqiao Hospital, Army Medical University, Chongqing, ChinaIndividuals residing in plateau regions are susceptible to pulmonary hypertension (PH) and there is an urgent need for a prediction nomogram to assess the risk of PH in this population. A total of 6603 subjects were randomly divided into a derivation set and a validation set at a ratio of 7:3. Optimal predictive features were identified through the least absolute shrinkage and selection operator regression technique, and nomograms were constructed using multivariate logistic regression. The performance of these nomograms was evaluated and validated using the area under the curve (AUC), calibration curves, the Hosmer–Lemeshow test, and decision curve analysis. Comparisons between nomograms were conducted using the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices. NomogramI was established based on independent risk factors, including gender, Tibetan ethnicity, age, incomplete right bundle branch block (IRBBB), atrial fibrillation (AF), sinus tachycardia (ST), and T wave changes (TC). The AUCs for NomogramI were 0.716 in the derivation set and 0.718 in the validation set. NomogramII was established based on independent risk factors, including Tibetan ethnicity, age, right axis deviation, high voltage in the right ventricle, IRBBB, AF, pulmonary P waves, ST, and TC. The AUCs for NomogramII were 0.844 in the derivation set and 0.801 in the validation set. Both nomograms demonstrated satisfactory clinical consistency. The IDI and NRI indices confirmed that NomogramII outperformed NomogramI. Therefore, the online dynamic NomogramII was established to predict the risks of PH in the plateau population.https://elifesciences.org/articles/98169pulmonary hypertensionprediction modelnomogramtransthoracic echocardiographyelectrocardiogramhigh altitude |
| spellingShingle | Junhui Tang Rui Yang Hui Li Xiaodong Wei Zhen Yang Wenbin Cai Yao Jiang Ga Zhuo Li Meng Yali Xu Derivation and internal validation of prediction models for pulmonary hypertension risk assessment in a cohort inhabiting Tibet, China eLife pulmonary hypertension prediction model nomogram transthoracic echocardiography electrocardiogram high altitude |
| title | Derivation and internal validation of prediction models for pulmonary hypertension risk assessment in a cohort inhabiting Tibet, China |
| title_full | Derivation and internal validation of prediction models for pulmonary hypertension risk assessment in a cohort inhabiting Tibet, China |
| title_fullStr | Derivation and internal validation of prediction models for pulmonary hypertension risk assessment in a cohort inhabiting Tibet, China |
| title_full_unstemmed | Derivation and internal validation of prediction models for pulmonary hypertension risk assessment in a cohort inhabiting Tibet, China |
| title_short | Derivation and internal validation of prediction models for pulmonary hypertension risk assessment in a cohort inhabiting Tibet, China |
| title_sort | derivation and internal validation of prediction models for pulmonary hypertension risk assessment in a cohort inhabiting tibet china |
| topic | pulmonary hypertension prediction model nomogram transthoracic echocardiography electrocardiogram high altitude |
| url | https://elifesciences.org/articles/98169 |
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