Xiangya Cardiopulmonary Health and Disease Cohort

1.2.1 Study objective

• Construct a cardiopulmonary holistic assessment cohort covering the full range of resting-exercise-sleep scenarios and encompassing non-cardiopulmonary disease-- cardiopulmonary hypofunction--cardiopulmonary disease populations in the longitudinal development of time.
• Explore the core indicators related to cardiopulmonary hypofunction and disease risk, and construct a joint stratification system of cardiopulmonary function.
• Map the cardiopulmonary comorbidity spectrum and describe its functional characteristics using the cardiopulmonary holistic assessment cohort, and analyze the impact of comorbidity patterns on patient's long-term prognosis and clinical outcomes.

1.2.2 Study type Bidirectional cohort design Retrospective cohort: Integrate historical hospital data(e.g., electronic medical records, imaging reports, cardiopulmonary function test records) and select the study population according to the inclusion and exclusion criteria.

Prospect cohort: patients from the retrospective cohort were screened to meet the study requirements and agreed to participate in subsequent studies for long-term follow-up(≥3years) and dynamic monitoring of cardiopulmonary function changes, 1.2.3 study content Building a cardiopulmonary cohort: build a full range of clinical cohort covering resting, exercise, and sleep scenarios with non-diseased, hypofunctional and cardiopulmonary disease populations, integrating retrospective data analysis and prospective follow-up monitoring to comprehensively reflect the cardiopulmonary performance of individuals in different physiological states, and laying the data foundation for subsequent analyses.

Constructing a joint stratification system for cardiopulmonary function: based on the data collected from the cardiopulmonary holistic assessment cohort, further in-depth feature extraction of cardiopulmonary function indicators is performed, and key indicators capable of predicting cardiopulmonary function decline and disease risk are screened out through data mining and dynamic monitoring, integrating the core indicators into a multidimensional risk indicator system, and stratifying patients by using a clustering method or based on a risk score, dividing low, medium and high risk groups, and realize the dynamic update of the stratification model.

Characterizing the cardiopulmonary comorbidity spectrum: Using the constructed cardiopulmonary cohort and the stratification system, we will deeply reveal the functional characteristics of cardiopulmonary comorbidity, analyze the functional changes and characteristics of patients with cardiopulmonary comorbidity in different scenarios (e.g., resting, exercising, or sleeping), and depict the characteristics of cardiopulmonary comorbidity spectrum; through the cardiopulmonary co-morbidity spectrum, we will deeply explore the interaction mechanism between the heart and the lungs in the progression of the disease, and analyze the impact of comorbidity on the prognosis and clinical outcomes of patients.

I1 Inclusion and exclusion criteria for retrospective cohorts 1) Inclusion criteria:

• Patients were either treated or hospitalized in the physical examination center, outpatient and emergency clinic in the Xiangya Hospital of Central South University from January 2010 to April 2025.
• Completion of cardiac function (e.g., echocardiography) and pulmonary function (e.g., pulmonary function test) assessment, with an interval of no more than 1 year between the two.
• Those who had complete clinical diagnostic and therapeutic information (e.g., medical history, medication records, laboratory test results, imaging reports) except for the cardiopulmonary function test report.

2)Exclusion criteria

• Patients with complete loss of cardiopulmonary function test reports or key data (e.g., VO2peak, FEV1/FVC, LVEF).
• Patients with loss of key clinical diagnostic and treatment data (e.g., medical history, medication records, laboratory test results).

2.1.2 Inclusion and exclusion criteria for prospective cohort

1）Inclusion criteria

• Patients who have been included in the retrospective cohort.
• Voluntarily signed informed consent form to participate in long-term follow-up for ≥3 years.
• Able to complete the baseline assessment of the prospective cohort (including cardiopulmonary function retesting, questionnaires, etc.).
• Stable conditions for follow-up (e.g., living in the local area, available valid contact information, no plans to move in the short term or go out for a long period of time).

• Exclusion Criteria.

• Patients who have been excluded from the retrospective cohort or for whom key data are missing.
• With severe cognitive impairment, psychiatric disease or verbal communication disorder, unable to cooperate with follow-up and data collection.
• Expected survival time <3 years (e.g., advanced malignancy, end-stage cardiopulmonary failure, etc.).
• Incomplete cardiopulmonary function or other clinical data during the baseline assessment.
• Those who plan to participate in other interventional clinical trials that may interfere with the assessment of cardiopulmonary function.