Frailty and Cognitive Decline in Hospitalized Elderly Patients: Associations with Clinical and Laboratory Parameters

Introduction

Elderly patients frequently have multimorbidity, in which several health conditions coexist. These include issues known as the “geriatric giants,” such as frailty syndrome (FS) and dementia. Both conditions are increasingly prevalent in hospitalized older adults and contribute significantly to functional decline and adverse clinical outcomes [1]. This growing burden of frailty and cognitive disorders places considerable strain on healthcare systems, especially in aging societies. In light of demographic shifts and the increasing proportion of older adults worldwide, frailty and cognitive decline have emerged as interconnected syndromes of critical importance in geriatric medicine. Frailty is defined as a reduction in homeostatic reserve and increased vulnerability to stressors, leading to a higher risk of developing disability, poorer prognosis, and death [1,2]. Clinical features of FS are commonly observed in patients hospitalized in various departments, with some also exhibiting cognitive impairment. However, not all patients with FS have dementia, nor do all those with cognitive impairment present with FS. Research suggests that frailty may be a risk factor for developing dementia. Conversely, individuals with Alzheimer disease and other dementias tend to exhibit more severe frailty symptoms. While the exact mechanisms linking frailty and cognitive impairment remain unclear, they likely involve abnormalities in biological processes associated with aging [3]. Recent studies have also highlighted the role of nutritional deficiencies, including vitamin D, B6, and B12, in the development of cognitive dysfunction in aging populations, suggesting an additional pathway linking biological and functional deterioration [4]. The co-occurrence of these conditions is associated with worse prognosis, prolonged hospitalization, and increased care dependency [5]. Both FS and dementia contribute to functional decline. Their interaction can exacerbate cognitive and physical deterioration, increasing the risk of institutionalization and mortality [6,7].

Three models for defining frailty can be distinguished [8,9]:

In clinical practice, a variety of testing tools can be used to diagnose FS [10]. The most widely used model is the frailty phenotype model, described in 2001 by Linda Fried and colleagues. Frailty is diagnosed if 3 out of the following 5 criteria are met: unintentional weight loss (more than 4.5 kg in the last 6 months), low physical activity (assessed through a physical activity questionnaire), muscle weakness (measured by a handgrip strength dynamometer, adjusted for sex and body mass index [BMI]), slow walking speed (measured over a distance of 3 m), and exhaustion (assessed using the Center for Epidemiologic Studies Depression Scale – Revised, or CESD-R) [11].

Another tool for diagnosing FS is the Edmonton Frail Scale, which consists of 10 items: balance, medication use, mobility, nutrition, social support, mood, quality of life, health-oriented attitudes, functional independence, and cognitive functions [12]. A simple tool based on clinical observation is the Clinical Frailty Scale (CFS), which assesses the severity of FS using pictograms that reflect functional status. The CFS distinguishes 9 grades of severity [13]. It is a useful screening tool for FS and can be effectively administered by various healthcare professionals [14]. Additionally, the CFS is a proven prognostic factor, correlating with the risks of hospitalization and mortality, and is useful in emergency medicine [15]. It has also proven effective in predicting mortality among hospitalized COVID-19 patients [16]. Given its simplicity, strong predictive power, and adaptability across clinical settings, the CFS has become one of the most practical and validated tools for real-time frailty stratification. The CFS scale is now widely used as a triage tool to guide critical clinical decisions in situations where healthcare resources are limited [17]. In a systematic review, a team of Italian researchers found that CFS scores were linked to clinical outcomes, disease presence, risk of re-admissions, and life expectancy in patients [18].

Patients hospitalized in geriatric departments undergo a comprehensive geriatric assessment (CGA) to evaluate their functional, physical, and cognitive status using a set of standardized scales [19]. Functional status in activities of daily living is assessed using the Katz Index of Independence in Activities of Daily Living (ADL) [20], the Lawton Instrumental Activities of Daily Living Scale (IADL) [21], and the Barthel Index [22]. Cognitive function is evaluated using the Mini-Mental State Examination (MMSE) developed by Folstein [23]. The presence and severity of depressive symptoms are assessed with the Geriatric Depression Scale (GDS) developed by Yesavage [24].

FS is commonly observed among these patients. While the existing literature offers extensive information on frailty syndrome, there is little information on its impact on the course and duration of hospitalization, as well as methods of assessment. Despite growing interest, there remains a scarcity of data specifically addressing the co-occurrence of cognitive impairment and frailty syndrome, and their combined associations with clinical indicators in hospitalized elderly patients [25]. Particularly lacking are studies that correlate FS and cognitive impairment with clinical scales and biochemical parameters obtained during routine hospital care [5,26]. Among these factors are laboratory indicators such as serum albumin, hemoglobin, sodium, thyroid-stimulating hormone (TSH), and lymphocyte count. These biomarkers are considered important prognostic indicators in geriatric patients [27]. Hypoalbuminemia, anemia, and lymphopenia have been identified as significant risk factors for malnutrition in the elderly population [27]. Hyponatremia, frequently observed in older adults, is associated with an increased risk of altered mental status and delirium [28,29]. In patients presenting with cognitive impairment, thyroid dysfunction must always be excluded as a potential contributing factor [30]. Furthermore, functional decline in frail elderly individuals may be exacerbated by sensory deficits, depression, pain, sleep disturbances, and fall risk – factors that often co-occur with cognitive changes [1,31–33].

The primary aim of this study was to evaluate the co-occurrence of FS and cognitive impairment in hospitalized geriatric patients. Additionally, the study analyzed the associations between these syndromes and various clinical factors, including functional status, fall risk, sensory deficits, depressive symptoms, and selected prognostic laboratory parameters: serum albumin, hemoglobin, lymphocyte count, sodium, and TSH levels.

The research hypothesis posited that increased frailty severity would be positively associated with worse cognitive impairment in hospitalized older adults.

Material and Methods

STUDY DESIGN:

This retrospective study analyzed the medical records of 265 patients who were consecutively admitted between January 1 and December 31, 2022, to the Internal Medicine and Geriatrics Ward of the Clinic of Internal Medicine and Cardiology at the University Clinical Centre of the Medical University of Warsaw (UCK WUM). All patients underwent routine CGA during hospitalization. Patients were eligible for inclusion if they met the following criteria: age ≥60 years, presence of multimorbidity (defined as 3 or more chronic conditions), and a score of ≥3 on the Vulnerable Elders Survey-13 (VES-13) [34]. Medical records were selected consecutively, and no randomization was used. Patients were excluded if their documentation was incomplete or if CGA was not performed during hospitalization. The CGA was conducted within 24 to 48 hours prior to hospital discharge by trained physicians, following a standardized protocol. The STROBE guidelines (Strengthening the Reporting of Observational Studies in Epidemiology) were followed.

METHODS:

Functional status in activities of daily living was assessed using 3 validated tools: ADL [20], IADL [21] and the Barthel Index [22]. Cognitive function was evaluated using the MMSE, with the following interpretation of scores based on established criteria: 27–30 points: no cognitive impairment; 24–26 points: mild cognitive impairment (MCI); 19–23 points: mild dementia; 11–18 points: moderate dementia; and 0–10 points: severe dementia [23].

Depressive symptoms were assessed using the 15-item version of the GDS [24]. As part of the CGA, fall risk was assessed using the Short Tinetti Test [35] and the risk of developing pressure ulcers was evaluated using the Norton Scale [36].

Additional variables obtained through patient interviews and clinical observation were also included in the analysis: living alone; number of years of formal education; and use of eyeglasses, hearing aids, walking aids, or incontinence products (eg, adult diapers). BMI was also calculated.

Frailty and its severity were assessed using the CFS [37], which categorizes frailty into 9 grades: grade 1 – healthy, very active individuals; grade 2 – individuals in good physical condition; grade 3 – individuals with well-controlled medical conditions who are occasionally active; grade 4 – prefrailty, characterized by limited physical activity and increased susceptibility to frailty; grade 5 – mild frailty where individuals require assistance in IADLs; grade 6 – moderate frailty, where individuals need assistance in ADLs and IADLs; grade 7 – severe frailty, where individuals are dependent on caregivers but remain stable; grade 8 – very severe frailty, with individuals dependent on caregivers and approaching the end of life; and grade 9 – terminally ill individuals with a life expectancy of less than 6 months. For the purposes of the study, the following FS severity ranges were defined according to the CFS scores: Group 1 – patients without frailty, corresponding to CFS grades 1, 2 and 3; group 2 – patients in the prefrailty phase, corresponding to CFS grade 4; group 3 – patients with mild frailty, corresponding to CFS grade 5; group 4 – patients with moderate frailty, corresponding to CFS grade 6; group 5 – patients with severe frailty, corresponding to CFS grade 7; and group 6 – patients with very severe frailty and terminally ill patients, corresponding to CFS grades 8 and 9. Baseline demographic and clinical characteristics were compared between frailty groups to assess significant group-level differences.

LABORATORY ANALYSIS:

All patients underwent standard laboratory testing as part of routine clinical practice, typically within the first 24 hours of hospitalization. Parameters analyzed included serum albumin, hemoglobin, lymphocyte count, sodium, and TSH. All laboratory measurements were performed at the Clinical Hospital Laboratory using validated, calibrated, and quality-controlled methods in accordance with established laboratory diagnostic procedures [27]. A comparative analysis was then performed on the results of the CGA scales, clinical parameters, and selected laboratory findings according to MMSE and CFS scores.

ETHICS STATEMENT:

The study was approved by the Research Ethics Committee at the Medical University of Warsaw (No. AKBE/65/2022). Due to the retrospective nature of the study and the use of anonymized data, the requirement for informed consent was waived. The research was carried out under the guidelines of the Declaration of Helsinki, Good Clinical Practice and the General Data Protection Regulation (GDPR).

STATISTICAL ANALYSIS:

Results are presented as median and interquartile range (IQR) or absolute numbers and percentages where appropriate. The Kolmogorov-Smirnov test was used to assess the normality of the distributions. Qualitative variables are presented as quantities (n) and percentage values of the whole group (%), while proportions in groups were assessed with a chi-squared test. In the comparative analysis of clinical data, Kruskal-Wallis ANOVA by ranks was used. Correlation analysis was performed using the Spearman test. In the multivariable linear regression, ANOVA was applied with CFS scale as dependable variables. Missing data as a missing completely at random (MCAR) handling was done by complete-case analysis (CCA) and affected 0.3% of results. Sample size calculation used confidence level 95% and maximum error 7%. Statistica 13.0 (StatSoft, Tulsa, OK, USA) was used for statistical analysis. P<0.05 was considered as the significance level.

Results

DESCRIPTIVE DATA:

The medical records of 265 patients (62% women (N=163)) were analyzed. The median age of the patients was 82 years (75–88). The median MMSE score in the study group was 19 points (15–24). On the CFS, grade 5 severity was the most common: N=64/264 (24%). Eyeglasses were used by 210 individuals (80%), while hearing aids were used by 54 individuals (21%).

MAIN RESULTS:

We found a statistically significant effect of clinical factors, such as age (P<0.001) and albumin level (P=0.001), on MMSE scores. Baseline demographic and clinical characteristics were compared between frailty groups to assess significant group-level differences. Other factors, including the use of eyeglasses (P<0.001), hearing aids (P=0.004), the presence of pressure ulcers (P=0.021), living alone (P=0.042), patient mobility (P<0.001), and the need for incontinence briefs (P<0.001), were significantly related to the MMSE scale categories. The relevance of sensory deficits such as vision and hearing loss aligns with the study’s focus on cognitive decline, as these factors can contribute to or exacerbate cognitive impairment in older adults. No statistically significant impact was found for GDS (P=0.629), sodium level (P=0.540), or TSH level (P=0.618) on MMSE scores (Table 1). In contrast, CFS (R=−0.531), ADL (R=0.525), IADL (R=0.570), Norton (R=0.450), Barthel (R=0.523), VES-13 (R=−0.444), and Tinetti (R=0.446) had statistically significant correlations (P<0.05) with MMSE scores. No statistically significant relationship was found between education level (R=0.095) and MMSE scores (Table 2).

Clinical factors such as age (P<0.001), albumin level (P<0.001), hemoglobin level (P=0.002), and MMSE scale score (P<0.001) had a statistically significant impact on CFS scores (Figure 1). A clinically significant correlation was observed between the CFS score and lymphocyte count in the sample group (P=0.292). Other factors, including the use of hearing aids (P=0.011), patient mobility (P<0.001), the presence of pressure ulcers (P<0.001), and the need for incontinence briefs (P<0.001), were significantly associated with CFS categories. The clinically significant effect of GDS scores on CFS ranges was observed, nearing statistical significance (P=0.064). No statistically significant impact was found for sodium level (P=0.308) or TSH level (P=0.486) on CFS ranges (Table 3). In contrast, other scales such as MMSE (R=−0.531), ADL (R=−0.811), IADL (R=−0.823), Norton (R=0.781), Barthel (R=0.850), VES-13 (R=0.645), and Tinetti (R=0.743) demonstrated statistically significant correlations (P<0.05) with CFS scores. No statistically significant relationship was found between education level (R=0.020) and FS severity on CFS (Table 3).

The independent predictors retained in the final regression model were Norton and IADL scales. The remaining factors were eliminated (sex, age, BMI, Tinetti Test, Barthel scale, ADL scale, VES-13 scale, GDS scale) (Table 4). A Norton Scale increase of 2 points caused a decrease of CFS scale of 1 grade, while an IADL scale rise of 2 points caused a decrease of CFS scale of 1 grade. Table 5 presents the distribution of participants across the CFS and MMSE groups.

A comparative analysis of men and women revealed that women were significantly more likely to have bone fractures (42% vs 21%; P<0.001), to use a cane/walking frame (40% vs 25%; P=0.010), and to require incontinence briefs (64% vs 38%; P<0.001). It was observed, at the limit of statistical significance, that men were more likely to walk unaided (61% vs 49%; P=0.049). None of the evaluated laboratory parameters and geriatric scales showed statistically significant differences between males and females (Table 6).

Discussion

ASSOCIATION BETWEEN CFS SCORES AND PROGNOSTIC LABORATORY PARAMETERS:

Laboratory tests play a key role in the diagnosis and monitoring of frailty syndrome. In the present study, lower albumin and lymphocyte levels were associated with greater severity of FS and cognitive impairment. These findings are in line with a growing body of literature emphasizing the prognostic value of routine biomarkers in geriatric patients. Similarly, Rudy et al found a strong correlation between serum albumin levels and FS in elderly patients admitted to the hospital. The lower the serum albumin level, the higher the likelihood of developing FS [38]. In a study by Yangita et al involving individuals aged 65 and older with type 2 diabetes, hypoalbuminemia, low AspAT levels, and low BMI were identified as independent risk factors for frailty syndrome, as assessed by the CFS [39]. Japanese researchers also found that lower albumin levels, even within the normal range, were linked to a frailty indicator (handgrip strength) and an inflammation marker (high-sensitivity C-reactive protein) [40]. Lymphocyte counts and inflammation indicators serve as prognostic factors in the evaluation of geriatric patients [41]. Other immunological markers associated with FS include interleukin-17 (IL-17) [42].

In their study assessing frailty with the CFS, Okyar Baş et al demonstrated a link between the Pan-immune-inflammation value (PIV) and frailty syndrome. PIV is a biomarker that combines neutrophil, platelet, monocyte, and lymphocyte measurements [43]. A meta-analysis by Chinese researchers on inflammatory biomarkers found that elderly adults with FS tend to have lower lymphocyte levels [44]. Spanish researchers reviewed studies analyzing changes in lymphocyte counts in patients with frailty syndrome, revealing a relation between FS and lower lymphocyte counts. The authors emphasize the need for further research to determine the sensitivity of lymphocyte counts and lymphocyte subtypes in diagnosing and monitoring frailty syndrome, suggesting that this measure could be used as a biomarker for frailty status [45]. The association between immune system markers and FS has also been demonstrated across different populations, reinforcing the importance of inflammation and nutritional status in the aging process.

CFS AND COGNITIVE STATUS:

In the present study, among hospitalized geriatric patients assessed using the CFS, 13.63% (36/264) showed no signs of frailty syndrome, 21.59% (57/264) were classified as pre-frail, and the vast majority, nearly 65% (171/264), exhibited symptoms of frailty. Of the frail patients, 24.24% (64/264) had mild frailty, 21.96% (58/264) had moderate frailty, 10.98% (29/264) had severe frailty, and 7.57% (20/264) were in the terminal stage. All participants without FS exhibited normal cognitive function. Those with prefrailty and mild frailty had mild cognitive impairment (MCI). Participants with moderate FS displayed slight cognitive impairment (dementia), while those with severe FS predominantly had moderate cognitive impairment (dementia). The severity of FS was correlated with worse cognitive impairment. This proves our research hypothesis and aligns with studies that have proposed a bidirectional relationship between physical and cognitive decline in aging.

In our study, cognitive function assessed with the MMSE revealed that more than 40% (109/264) of patients had no cognitive impairment, 24.62% (65/264) showed signs of mild cognitive impairment, and 34.09% (90/264) had test results consistent with dementia. Those without cognitive impairment were, at most, mildly frail, whereas those with moderate dementia were at least moderately frail. All patients with severe dementia had severe frailty syndrome. As cognitive impairment worsened, the severity of FS also increased.

A study by Chinese researchers, which assessed over 300 hospitalized patients aged 60 and above, using the CFS and MMSE scales, reported prevalence rates of 29.9% for frailty, 28% for cognitive impairment, and 15.8% for the co-occurrence of both conditions [5].

In a study conducted by Japanese researchers on elderly outpatients with cardiometabolic diseases, the prevalence of FS was significantly lower, at 24%, while cognitive impairment was observed in 41% of the patients. Most frail patients had cognitive impairment, with 20% of them showing signs suggestive of dementia [46].

A study of elderly women living in a Japanese community found that frail individuals were more likely to experience cognitive decline, establishing a link between cognitive decline and frailty [47].

Research by Shimada indicates that cognitive impairment and cognitive frailty are significant risk factors for dementia. However, the strength of the association between dementia and physical frailty remains inconsistent across studies. Future longitudinal studies are needed to determine the directionality and potential causality of this relationship. Individuals with both physical frailty and cognitive impairment may be at a higher risk of developing dementia compared to those who are healthy or those with only physical disability or cognitive impairment [48,49].

The highest prevalence of FS is observed among elderly residents of nursing homes. In a study by Polish researchers involving 86 nursing home residents, 75.6% of participants exhibited signs of FS as assessed by the CSHA-CFS, with 34.9% having severe FS. The study demonstrated that evaluating the severity of FS and cognitive impairment holds prognostic significance. The co-existence of FS and cognitive impairment is associated with increased mortality, emphasizing the need to evaluate both conditions in the elderly and to consider them together [7].

Studies assessing the prevalence of FS in patients with dementia have been systematically reviewed. British researchers found that the studies reviewed were heterogeneous, employing various protocols, but suggest that patients with dementia are at higher risk of developing FS [50].

A review by Australian authors revealed a wide range in the prevalence of FS among individuals aged 65 and older with dementia, in both acute care settings (50.8% to 91.8%) and outpatient settings (24.3% to 98.9%) [51].

Numerous studies highlight the significant link between FS and cognitive impairment, suggesting that their co-existence can increase the risk of adverse health outcomes in the elderly [26].

The observed co-occurrence of frailty and cognitive decline in our cohort is consistent with findings from cluster analyses that reveal overlapping trajectories of physical, cognitive, and psychiatric impairment in elderly patients [52].

CFS AND FUNCTIONAL STATUS:

The study examined the impact of FS on the functional status of patients. As the severity of FS increased, the number of individuals walking unaided dropped significantly, while the need for canes or walking frames grew. With increasing severity of frailty syndrome, patients’ ability to perform basic and complex activities of daily living declined. The Barthel Index scores also decreased, and the risk of pressure ulcers and the need for incontinence briefs increased. Those with severe and terminal FS were predominantly confined to bed and chair or were completely bed-bound. These functional limitations directly reflect the decline in physiological reserve and support the CFS as a dynamic tool to assess patients’ dependency progression. No correlation was found between living alone and FS and cognitive impairment. The number of individuals living alone was lowest among patients with severe and terminal FS, as well as those with moderate and severe dementia. These patients require the care of another person. With increasing severity of frailty syndrome, the need for care and nursing support grows. Several studies confirm the relationship between FS and functional deterioration, particularly in IADLs [53,54].

Chinese researchers found that elderly hospitalized patients with both frailty and cognitive impairment at admission faced a higher risk of new ADL dependence, while frailty or cognitive impairment alone were not associated with new ADL dependence at a one-year follow-up [5]. Studies highlight the importance of early diagnosis of FS and cognitive impairment, along with the effective interventions to prevent functional decline and dependence [55]. Particular importance should be placed on interventions implemented in older adults during the prefrailty stage. This geriatric subgroup was the focus of a study by Lee, which demonstrated the positive effects of remote exercise programs on physical functioning. These findings provide valuable insights into non-pharmacological interventions that can enhance functional status and potentially alleviate frailty symptoms [56].

OTHER GERIATRIC GIANTS INCLUDE SENSORY DISORDERS, FALLS AND FRACTURES:

In the study population, the use of eyeglasses decreased significantly among patients with worsening cognitive impairment and frailty syndrome. Conversely, the use of hearing aids significantly increased, and it was lowest among those with terminal frailty. These sensory deficits may contribute to reduced cognitive stimulation, social withdrawal, and increased care dependency. Although discussed briefly, their inclusion reflects the multidimensional nature of frailty and highlights the importance of addressing correctable sensory impairments in geriatric care.

A prospective study by Mexican researchers showed that individuals with progressive visual impairment have a higher risk of developing FS [57]. A study by Chinese researchers found that elderly adults with dual sensory impairment were more likely to be frail compared to those without sensory impairment [31]. Furthermore, Japanese researchers observed that visual impairment, but not hearing impairment, is an independent risk factor for FS [58]. Interventions to improve sensory function could potentially reduce the risk of frailty in elderly adults.

Our study found that the risk of falling, as measured by the Short Tinetti Test, rose significantly with increasing FS severity and cognitive impairment. However, no correlation was detected between the rate of bone fractures after age 60 and the prevalence or severity of FS and cognitive impairment. Studies and meta-analyses suggest that elderly individuals with FS have a significantly higher risk of falling than those without FS [32]. Additionally, cognitive impairment has been identified as a significant predictor of falls in the elderly [33].

VES-13 VS CFS:

Our study included patients who scored 3 or more points out of a possible 10 on the VES-13 scale. The VES-13 scale is a simple and functional tool for dynamic screening of individuals over 60 to identify those at risk of deterioration. A VES-13 score of ≥3 is associated with an increased risk of death and functional decline [34].

We analyzed the VES-13 scores of patients as FS progressed. Patients without FS had scores below 6, whereas those with FS all scored 6 or higher. It is important to focus on pre-frail patients scoring >6 points on the VES-13 scale, as they are at greater risk of developing frailty syndrome. The VES-13 scale with a cutoff of 6 points is a reliable indicator of frailty syndrome. This is supported by research on screening tools for elderly patients, which suggest that a cutoff of 6 points is optimal for evaluating functional status [59,60].

In summary, FS is recognized as one of the “geriatric giants,” with its prevalence increasing progressively in the oldest age groups [61]. The CFS scale should play an essential role in assessing chronically ill elderly patients. The need to identify patients with FS stems from standards that define specific diagnostic and therapeutic approaches for these individuals. The assessment of FS is already incorporated into cardiology, diabetes, and oncology standards [62–64] for FS and cognitive impairment in hospitalized older adults and should be considered a standard component of clinical practice.

LIMITATIONS:

The present analysis did not account for the potential influence of renal and hepatic function on serum albumin levels. This was because hypoalbuminemia is an independent risk factor for malnutrition, which is closely associated with frailty syndrome. The aim of the study was not to investigate the underlying causes of hypoalbuminemia, but rather to examine its consequences and clinical implications. Moreover, as a retrospective study based on medical records, our analysis is subject to potential selection bias and information bias due to missing or incomplete data. Additionally, the study was conducted at a single clinical center, which may limit the generalizability of the findings to broader, more diverse populations. The reliance on cross-sectional data also limits the ability to establish causal relationships between frailty, cognitive impairment, and associated clinical parameters. Future research should employ prospective, multicenter designs to validate our findings and explore mechanistic pathways underlying the relationship between frailty and cognitive decline.

Conclusions

Most hospitalized elderly patients display clinical signs of frailty syndrome, and cognitive disorders (dementia) are expected in 1 out of every 3 of them. This supports the study hypothesis that frailty and cognitive impairment often coexist and become more prevalent with age.

The severity of FS in hospitalized geriatric patients is correlated with worse cognitive impairment. This co-occurrence underscores the importance of routine screening for both cognitive decline and frailty in geriatric care settings.

With increasing severity of frailty syndrome, there is a decline in the ability to perform basic and complex daily activities, an elevated risk of falls, and a greater prevalence of sensory disturbances, all of which result in heightened care and nursing requirements. These findings emphasize the clinical value of identifying frailty at early stages to prevent further deterioration.

Lower albumin and lymphocyte levels were associated with greater severity of FS and cognitive impairment. These biomarkers may be useful in the early identification of patients at higher risk of functional decline. Given the retrospective design and reliance on medical records, our results should be interpreted with caution. Nevertheless, our findings offer clinically meaningful insights that may inform future research directions and support the refinement of targeted strategies for mitigating frailty and cognitive decline in geriatric populations.