Automated cohort database system for cardiopulmonary physiotherapy: A comprehensive tool supporting research on cardiac surgery patients-framework design, development and validation

Comput Methods Programs Biomed. 2025 May 2;268:108825. doi: 10.1016/j.cmpb.2025.108825. Online ahead of print.

ABSTRACT

BACKGROUND: The shared goal of clinical physicians and cardiopulmonary physiotherapists is to tailor optimal comprehensive rehabilitation strategies for each patient undergoing cardiac surgery to improve outcomes. The sustained and large-scale acquisition of patient course and rehabilitation treatment-related data faces numerous challenges. This necessitates research and analysis based on large sample size data from cardiac surgery patients.

OBJECTIVE: The Cardiopulmonary Physiotherapists Database System (CPPTherapists-DBS) was developed to enhance the management and analysis of data for researching risk factors associated with postoperative pulmonary complications (PPCs) in cardiac surgery patients. This system aims to establish comprehensive system design standards, frameworks, and validation procedures to support research in both cardiac surgery and cardiopulmonary physiotherapy.

METHODS: The development of the CPPTherapists-DBS involved: (1) establishing system design standards and frameworks through a detailed software engineering requirements analysis, where clinical researchers defined data collection standards, business scope, and identification rules based on international guidelines and previous research; (2) designing and developing the system to integrate advanced functionalities for data management and analysis within the established frameworks; (3) validating the system by constructing a retrospective cohort for PPCs and developing and evaluating a predictive model based on the collected data.

RESULTS: The CPPTherapists-DBS successfully established design standards and frameworks for system development. It has collected clinical data from 27,027 cardiac surgery patients across multiple medical centers from 2010 to 2021. Since January 2022, it has also included physical rehabilitation treatment records for 5,335 patients. The system's CCVPRA tool provides advanced visualization capabilities, enabling rapid data modeling for 6,608 patients and development of a predictive model for PPCs. The model demonstrated strong performance with an AUC of 0.78 in the training set and 0.76 in the testing set.

CONCLUSIONS: The CPPTherapists-DBS effectively automates the collection and management of clinical and rehabilitation data, adhering to established system design standards and frameworks. It offers powerful tools for data visualization and modeling, representing a significant advancement in cohort database systems and providing a replicable model for supporting research on cardiac surgery patients and cardiopulmonary physiotherapy.

PMID:40347620 | DOI:10.1016/j.cmpb.2025.108825