Multimorbidity in elderly patients with or without T2DM: A real-world cross-sectional analysis based on primary care and hospitalisation data
2024

Multimorbidity in Elderly Patients with Type 2 Diabetes

Sample size: 36024 publication 10 minutes Evidence: high

Author Information

Author(s): Li Yang, Geng Shasha, Yuan Huixiao, Ge Jianli, Li Qingqing, Chen Xin, Zhu Yingqian, Liu Yue, Guo Xiaotong, Wang Xiaoli, Jiang Hua

Primary Institution: Shanghai East Hospital, Tongji University School of Medicine

Hypothesis

The study aims to determine the prevalence of multimorbidity in elderly T2DM patients and evaluate current guidelines' inclusiveness in addressing major comorbidities.

Conclusion

Multimorbidity in elderly patients with T2DM needs broader acknowledgment, as current guidelines inadequately address COPD management.

Supporting Evidence

  • More than 90% of elderly T2DM patients had at least one additional chronic disease.
  • Multimorbidity was more frequent in women and older patients.
  • Hyperlipidemia, hypertension, and ischaemic heart disease were the most prevalent comorbidities.
  • T2DM diagnosis was significantly associated with cardiovascular-kidney-metabolic and neuropsychiatric diseases.
  • A higher prevalence of COPD was consistently detected in elderly patients with T2DM.

Takeaway

Most older people with diabetes have other health problems too, and doctors need to pay more attention to these issues.

Methodology

The study used electronic health records from the Shanghai Health Cloud platform to analyze elderly patients with T2DM and their comorbidities from 2019 to 2022.

Potential Biases

Potential biases may arise from the reliance on electronic health records and the subjective interpretation of diagnostic imaging.

Limitations

The study is limited by the quality of diagnostic data across different medical institutions and the potential for misclassification of undiagnosed conditions.

Participant Demographics

Elderly patients (≥60 years) from the Pudong New Area community in Shanghai, China.

Statistical Information

Confidence Interval

95% CI = 38.9–46.0%

Digital Object Identifier (DOI)

10.7189/jogh.14.04263

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