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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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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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Aging Clinical and Experimental Research (2023) 35:3189–3203
https://doi.org/10.1007/s40520-023-02608-3
ORIGINAL ARTICLE
Network analysis offrailty indicators inhospitalized elderly patients:
unveiling therole ofdepression andhemoglobin ascore factors
RuxiaQiu1,2,3 · YanhongGu1,2,3
Received: 19 July 2023 / Accepted: 23 October 2023 / Published online: 30 November 2023
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023
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, fol-
lowed 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.
Keywords Frailty· Factors· Hospitalized elderly patients· Network approach
Introduction
The global population is experiencing unprecedented aging,
particularly in low- and middle-income countries [1]. How-
ever, not all individuals age at the same rate, and those who
experience accelerated aging are referred to as “frail” [2].
Frailty has gained international attention [3]. It is a complex
and multidimensional state characterized by reduced physi-
ological reserve, particularly among older adults, resulting
from diminished capacity in neuromuscular, metabolic, and
immune systems, leading to heightened vulnerability to cope
with stressors [4, 5]. This condition is accompanied by a
multidimensional decline in physical abilities, cognition,
and social roles [6]. Although the concept of frailty remains
evolving and controversial, its association with adverse out-
comes such as hospitalization, long-term care, and mortal-
ity is well-established [7], imposing a substantial burden on
individuals, families, caregivers, and healthcare systems [8].
While considerable research has focused on investigating
frailty prevalence and influencing factors among community
and nursing home residents [9, 10], the prevalence of frailty
is notably high among elderly hospitalized patients [11],
ranging from 27% to 94% [12], surpassing rates observed
within the community (5.9–17.4%) [9]. Frailty significantly
* Yanhong Gu
reddy_gu@163.com
1 Department ofNursing, Shanghai Fifth People’s Hospital,
Fudan University, No.801, Heqing Road, Minhang District,
Shanghai, China
2 Center forCommunity Health Research ofFudan University,
No.801, Heqing Road, Minhang District, Shanghai, China
3 School ofNursing, Fudan University, No.305, Fenglin Road,
Xuhui District, Shanghai, China
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