Derivation and Internal Validation of Prediction Models for Pulmonary Hypertension Risk Assessment in a Cohort Inhabiting Tibet, China

Abstract

Abstract

Background: Due to exposure to hypoxic environments, individuals residing in plateau regions are susceptible to pulmonary hypertension (PH). Consequently, there is an urgent need for a simple and efficient nomogram to assess the risk of PH in this population.

Methods: This study included a total of 6,603 subjects, who were randomly divided into a validation set and a derivation 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.

Results: 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 (RAD), high voltage in the right ventricle (HVRV), 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.

Conclusions: A reliable and straightforward nomogram was developed to predict the risks of PH in the plateau population.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This study was funded by the Talent Program of Army Medical University (No. 2019R038). It includes grants such as paper language editing fees and publication fees

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

the Ethics Committee of the General Hospital of Tibet Military Area Command (APPROVAL NUMBER: 2024-KD002-01)

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

Data Availability

Source data files have been provided as additional files.

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