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Network analysis of frailty indicators in hospitalized elderly patients: unveiling the role of depression and hemoglobin as core factors

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Abstract

Background

Frailty is a significant concern among hospitalized older adults, influenced by multiple factors. Understanding the complex interactions between these variables can be facilitated through a network perspective.

Aim

This study aimed to identify the core factor and physiological indicator of frailty in hospitalized elderly patients and visualize their interactions within the network structure.

Methods

Frailty was assessed using the Tilburg Frailty Indicators, with a score of 5 or higher indicating frailty. Additional variables related to sociodemographic, physical and clinical, psychological and cognitive aspects, as well as physiological indicators, were extracted from electronic health records. A partial correlation network analysis was conducted using an adaptive LASSO algorithm, based on univariate correlation and logistic regression, to examine the network structure and identify influential nodes.

Results

The average age of participants was 70.74 ± 7.52 years, with 24.27% classified as frail. Frailty was associated with 38 of 145 initially included variables (P < 0.05). The network analysis revealed depression as the most central node, followed by drugs used, sleep disorders, loneliness, masticatory obstacles, drinking, and number of teeth missing. Hemoglobin emerged as the most central biochemical indicator in the network, based on network center index analysis (Strength = 4.858, Betweenness = 223, Closeness = 0.034).

Conclusions

Frailty in hospitalized older adults is influenced by various social, physical, and psychological factors, with depression as the core factor of utmost importance. Changes in hemoglobin levels could serve as an essential indicator. This innovative network approach provides insights into the multidimensional structure and relationships in real-world settings.

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Availability of data and materials

The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.

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Funding

Key Medical Specialty funded by Shanghai Fifth People’s Hospital, Fudan University (No.2020WYZDZK10). Scientific Research Project funded by Shanghai Fifth People’s Hospital, Fudan University (No.2022WYHLZD01). Natural Science Research Funds of Minhang District, Shanghai ( No.2023MHZ031).

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Authors and Affiliations

  1. Department of Nursing, Shanghai Fifth People’s Hospital, Fudan University, No.801, Heqing Road, Minhang District, Shanghai, China

    Ruxia Qiu & Yanhong Gu

  2. Center for Community Health Research of Fudan University, No.801, Heqing Road, Minhang District, Shanghai, China

    Ruxia Qiu & Yanhong Gu

  3. School of Nursing, Fudan University, No.305, Fenglin Road, Xuhui District, Shanghai, China

    Ruxia Qiu & Yanhong Gu

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  1. Ruxia Qiu
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  2. Yanhong Gu
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Contributions

RQ: methodology, validation, investigation, data curation, writing—original draft, writing—review and editing. YG: conceptualization, methodology, resources, supervision, project administration, funding acquisition, writing—review and editing.

Corresponding author

Correspondence to Yanhong Gu.

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Conflict of interest

All authors declare that there are no conflicts of interest. We would like to thank the participating elderly patients for their help and efforts in the data collection process.

Statement of human and animal rights

All data analysed here were collected as part of routine diagnosis and treatment. We informed our local ethical committee of this observational research. No animal was used for this study.

Ethical approval and consent to participate

The study protocol was approved by the Institutional Ethics Committee (Ethical Approval Form no. 2022-130) and adhered to the principles of the Declaration of Helsinki. Written informed consent was obtained from each patient before data collection.

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Qiu, R., Gu, Y. Network analysis of frailty indicators in hospitalized elderly patients: unveiling the role of depression and hemoglobin as core factors. Aging Clin Exp Res 35, 3189–3203 (2023). https://doi.org/10.1007/s40520-023-02608-3

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