Effect of comprehensive geriatric assessment intervention on serum S100β levels and clinical outcomes in patients with Alzheimer's disease

Abstract

Background

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that significantly impairs cognitive function, emotional health, and daily living activities. Comprehensive Geriatric Assessment (CGA) is a multidisciplinary approach designed to optimize health outcomes in older adults, but its effectiveness in managing AD remains to be fully elucidated.

Objective

To evaluate the impact of CGA intervention on serum S100β levels and clinical outcomes in patients with AD.

Methods

In this prospective study, 120 patients diagnosed with AD were randomly assigned to either a Control group or an Intervention group. The Control group received standard treatment and routine care, while the Intervention group received individualized care plans based on CGA in addition to standard management. Primary outcomes included serum S100β levels, Alzheimer's Disease Assessment Scale–Cognitive Subscale (ADAS-Cog), Neuropsychiatric Inventory–Questionnaire (NPI-Q), Geriatric Depression Scale (GDS) scores, Mini-Nutritional Assessment (MNA) scores, Activities of Daily Living (ADLs), Instrumental Activities of Daily Living (IADLs), and Parkinson's Disease Questionnaire (PDQ-39) scores, assessed at baseline and during follow-up.

Results

Serum S100β levels remained stable in the Control group but significantly decreased in the Intervention group at 6 months. ADLs and IADLs scores were consistently higher in the Intervention group. Although ADAS-Cog and NPI-Q scores improved in both groups, the Intervention group demonstrated significantly lower NPI-Q scores at 6 months.

Conclusions

CGA intervention effectively enhances cognitive function, emotional well-being, mobility, and social interaction in patients with AD.

Keywords

Alzheimer's disease clinical outcomes comprehensive geriatric assessment serum S100β

Introduction

Alzheimer's disease (AD) is a progressive neurodegenerative disease that occurs with aging and primarily affects the elderly population.¹ Disease progresses, patients experience gradual declines in cognitive function and daily living abilities, accompanied by significant neuropsychiatric symptoms, ultimately becoming fully dependent on caregivers. As the leading type of dementia, AD accounts for approximately 33% of all dementia cases. In China, with accelerated aging, the number of AD patients has increased significantly, representing about one-quarter of the global cases.² The prevalence of AD is high among the elderly, and with the global trend of aging, it is expected that an increasing number of individuals will be affected, especially within the population aged 80 and above.³ The pathological changes of AD often remain latent in the brain for many years before clinical symptoms appear, mainly characterized by the extracellular deposition of amyloid-β plaques and intracellular neurofibrillary tangles composed of hyperphosphorylated tau protein.^4,5

The Comprehensive Geriatric Assessment (CGA) is a multidimensional, multidisciplinary assessment method widely used in community and clinical settings to systematically evaluate the overall health status of older adults. CGA can identify health needs in various areas, including physical, cognitive, emotional, nutritional, and social support, thus providing comprehensive health information for elderly patients. Through CGA, healthcare teams can develop individualized care and treatment plans based on specific assessment results, aiming to optimize health outcomes for patients.^6,7 It screens for health problems in older adults across multiple dimensions and is an important method for assessing and predicting the occurrence of geriatric syndromes.⁸ The wide range of CGA metrics, including basic information, health indicators, physical function, geriatric syndromes, environmental factors, and comorbidities, contributes to a more comprehensive assessment of older adults’ physical function and health.⁹ Studies have shown that CGA has a positive impact on various health outcomes, including reducing frailty risk, lowering mortality, and decreasing hospitalization rates, making it particularly suitable for elderly individuals requiring comprehensive health management.¹⁰ For example, CGA can significantly improve the survival of cancer patients through an optimization of the cancer treatment.¹¹ Mortality and hospitalization rates were significantly reduced in elderly patients undergoing CGA in the emergency department.¹² Armentaro et al. found that cardiac function was improved in patients with chronic heart failure managed by CGA.¹³ Although AD, is relatively common in the elderly population, current evidence on whether it can benefit from CGA remains limited.¹⁰ Therefore, the aim of this study was to investigate the effect of CGA intervention on patients with AD by comparing the difference in serum S100β levels and clinical outcomes between patients receiving CGA and conventional therapeutic care.

Methods

General information

In this study, 120 patients with a confirmed diagnosis of AD were prospectively included from Lianshui County People's Hospital between January 2022 to February 2023. The diagnosis of AD was made according to both DSM-5-TR criteria and the 2020 Chinese Guidelines for the Diagnosis and Treatment of Alzheimer's Disease, requiring a significant decline in memory and learning abilities, accompanied by reduced judgment or language abilities. These changes had to be gradual and progressive, with other potential causes (such as other neurodegenerative or vascular diseases) excluded. The study was approved by the Ethics Committee of Lianshui County People's Hospital (20220510-01).

Baseline data, including age and gender, were recorded for all patients. Using a simple random sampling method, the patients were equally divided into a Control group and a CGA intervention group (Intervention group).

Inclusion and exclusion criteria

Inclusion criteria: patients (1) meeting the diagnostic criteria of AD; (2) aged 60 years or above; (3) amyloid-positive as determined by Aβ₁₋₄₂ measured by positron-emission tomography (PET) or cerebrospinal fluid testing (CFS)¹⁴; (4) Montreal cognitive assessment (MoCA) score between 7 and 25, Clinical Dementia Rating (CDR) of 1–2, and Cornell Scale for Depression in Dementia (CSDD) score of 18 or less¹⁵; (5) cooperating with the completion of the test and follow-up visits; (6) signing the informed consent form.

Exclusion criteria: patients (1) not meeting the diagnostic criteria for AD; (2) younger than 60 years of age; (3) with severe neurological dysfunction and psychiatric disorders，excluded to avoid interference with cognitive assessment results and ensure data accuracy¹⁶; (4) suffering from primary diseases that could significantly impact cognitive function or study outcomes, such as advanced cardiovascular, hepatic, renal, hematopoietic diseases, and malignant tumors; (5) participating in other clinical studies within the past two months; (6) not signing the informed consent form; and (7) not able to cooperate with the completion of follow-up visits.

Comprehensive Geriatric Assessment intervention

Participants in the Intervention group received CGA intervention in addition to medication, nutritional support, general support, and psychosocial support, and an individualized care plan was developed for them based on the CGA. The CGA was evaluated by geriatricians with expertise. The evaluation indices included patient demographics such as age, gender, body mass index (BMI), education level (below junior high school, junior high school, Bachelor's degree, Master's degree, and PhD), marital status (unmarried, married, divorced, widowed), medical status (Charlson Comorbidity Index, CCI), polypharmacy assessment, MoCA score, CDR score, CSDD score, Geriatric Depression Scale-15 (GDS-15), Mini-Nutritional Assessment (MNA), Activities of Daily Living (ADLs) scale score, Instrumental Activities of Daily Living (IADLs) scale score. Participants in the Control group received the same treatment and usual care without CGA.

Outcome measures

The observational indicators included serum S100β level, Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog), Neuropsychiatric Inventory-Questionnaire (NPI-Q), ADLs score¹⁷ (Barthel Index), IADLs score, and PDQ-39 score. The above indicators were assessed at month 0 (baseline), 1, 3, and 6 after treatment.

ADAS-Cog

This scale is used to assess cognitive function in patients with AD. Scores are obtained for orientation, word list recall and recognition, object naming, ability to follow simple requirements, conceptual and structural practices, and expressive language. Scores range from 0 ∼ 70, with higher scores resulting in poorer performance.¹⁸

NPI-Q

It is a tool used to assess behavioral disturbances in dementia patients. The scoring process involves evaluating the severity and caregiver distress of various neuropsychiatric symptoms. The NPI consists of 12 domains, with symptoms rated on a scale of 1 ∼ 4 for frequency and 1 ∼ 3 for severity.¹⁹

ADLs scale

It is used to assess the ability of patients to perform ADLs. The activities involved eating, bathing, grooming (washing, brushing, shaving, combing, etc.), dressing (including tying shoelaces), bowel control, urination control, toileting (including wiping, arranging clothes, and flushing), wheelchair transfer, walking on a flat ground for 45 meters, and walking up and down stairs. The level of assessment was categorized as independent, partially independent with partial assistance, needy of great assistance, and not independent at all. Scoring was based on the Barthel Index, with a total score of 100; a score of 60 or more indicated that the patient was basically independent who was mildly dysfunctional and able to perform some daily activities independently; a score of 60–41 indicted that the patient needed help in living; a score of 40–20 indicted that the patient needed great help in living; a score of 20 indicted that the patient had no independence in daily life at all.

IADLs scale

It is used to assess instrumental activities of daily living, with 8 items including making phone calls, shopping, meal preparation, housework, washing clothes, use of transportation, medication, and money management. Its score reflects the current functional status of the patient. A minimum total score of 14 is considered completely normal function; a total score of over 14 indicates varying degrees of functional decline; a total score of over 22 is considered a significant impairment of function.

PDQ-39 scale

The PDQ-39 is a multifunctional tool for assessing the quality of life and health status of PD patients, with a total of 39 items distributed across 8 question scales, i.e., mobility (10 items), ADL (6 items), emotional well-being (6 items), stigma (4 items), social support (3 items), cognition (4 items), communication (3 items), and bodily pain (3 items). The total score ranged from 0 to 100. Lower scores represented better status of the patient, while higher scores indicated poorer status and more difficulty in taking care of themselves.²⁰

Measurement of serum S100β level

Serum S100β levels in AD patients were determined by enzyme linked immunosorbent assay (ELISA) before treatment and at 1, 3, and 6 months after treatment. Specifically, 3 mL of peripheral venous blood was drawn from patients at each test time point, and the upper serum was collected after centrifugation and set aside. The dilution solution was diluted to the appropriate concentration. Later, 100 μL of antigen was added to each well, which was then placed at 37°C for 4 h. Subsequently, the liquid in the wells was discarded. 5% calf serum was blocked at 37°C for 40 min. During the blocking, blocking buffer was added to fill up the reaction wells, and air bubbles were removed from the wells. After the blocking was finished, each well was washed with the washing solution for 3 times, and 3 min for each time. Next, the diluted sample was added into the enzyme reaction wells, with 100 μL for each well, and two duplicate wells were set up for each sample. Following that, these wells were incubated at 37°C for 40–60 min. Again, the wells were washed for 3 times, and 3 min for each time. Then, the enzyme-labeled antibody was added for a 60-min incubation at 37°C. The wells were later incubated with TMB substrate solution at 100 μL per well at 37°C away from light for 3–5 min. Finally, the termination solution was introduced to develop the color, and the experimental results were obtained within 20 min.

Statistical methods

Measurement data were expressed as mean ± standard deviation (SD). Count data were expressed as percentage (%). The t-test was used for comparison of measurement data. Comparisons of categorical variables were performed using the chi-square χ² test. All hypotheses were tested with a p-value of 0.05. Statistical analysis was performed using SPSS v25.

Results

Baseline information

Patient selection and index testing were performed in this study according to the inclusion and exclusion processes shown in Figure 1. A total of 146 AD patients were examined for eligibility, 26 patients were excluded due to non-signing of informed consent, and 120 patients were enrolled. No patient was lost during the 6-month follow-up period. Finally, 60 patients were assigned to the Control group and 60 patients to the Intervention group. Baseline data of AD patients in the two groups, including age, gender, BMI, education level, marital status, CCI, polypharmacy, MoCA score, CDR score, CSDD score, GDS-15 score, MNA score, ADL score, IADL score, and PDQ-39 score, did not have statistically significant differences; as a result, these patients were ready for the next step of the study (Table 1, p > 0.05).

Figure 1.

Patient inclusion and exclusion. AD: Alzheimer's disease; MoCA: Montreal Cognitive Assessment; CDR: Clinical Dementia Rating; CSDD: Cornell Scale for Depression in Dementia.

Table 1.

Comparison of baseline information of patients between the two groups.

Characteristics	Intervention group(n = 60)	Control group(n = 60)	p
Age (y)	67 (63.25–72)	68 (63–72)	0.839
Gender	33/27	40/20	0.190
BMI	22.11 (21.01–23.68)	21.92 (20.69–22.88)	0.178
Educational level			0.614
Below junior high school	34 (56.7)	38 (63.3)
Junior high school	24 (40.0)	19 (31.7)
Bachelor's degree	2 (3.3)	2 (3.3)
Master or above	0 (0.0)	1 (1.7)
Marital status			0.537
Unmarried	6 (10.0)	2 (3.3)
Married	44 (73.3)	48 (80.0)
Divorced	5 (8.3)	5 (8.3)
Widowed	5 (8.3)	5 (8.3)
CCI	3 (2–4)	3 (2–4)	0.093
MoCA	14 (12.25–17)	15 (13–17)	0.718
CDR	1 (1–2)	1 (1–2)	0.451
CSDD	17 (16–18)	17 (15.25–17)	0.443
GDS-15	7 (5–8)	7 (5.25–8)	0.595
MNA	21 (19–24)	22 (20–24)	0.311
ADL	48 (44–50)	46 (44–50)	0.513
IADL	1 (0–2)	1 (0–2)	0.536
PDQ-39	69 (63–72)	68.5 (64.25–73.75)	0.432

BMI: body mass index; CCI: Charlson Comorbidity Index; PIM: potentially inappropriate medication; MoCA: Montreal Cognitive Assessment; CDR: Clinical Dementia Rating; CSDD: Cornell Scale for Depression in Dementia; GDS-15: Geriatric Depression Scale-15; MNA: Mini-Nutritional Assessment; ADL: activities of daily living; IADL, instrumental activities of daily living; PDQ-39: Parkinson's Disease Questionnaire 39.

Effect of comprehensive geriatric assessment on serum S100β levels in AD patients

We tested the serum S100β levels of two groups of patients at different times by ELISA, and the results are shown in Figure 2. Serum S100β levels before and after treatment in the Control group remained relatively stable, while they showed a decreasing trend in the Intervention group. There was no significant difference in serum S100β levels between the two groups of AD patients before treatment. At 1 and 3 months after treatment, serum S100β levels in the Intervention group were lower than those in the Control group, but the difference was not statistically significant; at 6 months after treatment, serum S100β levels in the Intervention group were significantly lower than those in the Control group (p < 0.01).

Figure 2.

Serum S100β levels measured in two groups of AD patients at different time points. ELISA was used to determine serum S100β levels in two groups of AD patients, **p < 0.01 versus Control.

Effect of comprehensive geriatric assessment on the mental status and mobility of AD patients

Subsequently, we assessed the activity ability and mental state of the two groups of patients based on ADL score and IADL score, ADAS-Cog and NPI-Q. The ADL scores and IADL scores of the two groups before and after treatment were slightly higher than those of the Control group, but the difference was not statistically significant (p > 0.05); compared with the pre-treatment period, the ADL scores and IADL scores of the two groups of AD patients at 1, 3, and 6 months after treatment had small fluctuations, but they showed an overall upward trend (Figure 3A, B). ADAS-Cog and NPI-Q scores were slightly lower in both groups than in the control group before and after treatment, but the difference was not statistically significant (p > 0.05). After treatment, the ADAS-Cog and NPI-Q scores of both patients showed an overall decreasing trend; and at 6 months after treatment, the NPI-Q scores of the Intervention group were significantly lower than those of the Control group (p < 0.05) (Figure 3C, D).

Figure 3.

The activity ability and mental state scale scores measured in both groups of patients at different time points. The ADL (A), IADL (B), ADAS-Cog (C), and NPI-Q (D) scores of the two groups of patients were analyzed by the corresponding scales. *p < 0.05 versus Control.

Parkinson's Disease Questionnaire scores

We assessed the mobility, ADL, emotional well-being, social support, cognitive status, pain condition and communication ability of AD patients using the PDQ-39. The results, as displayed in Table 2, showed that there were no significant differences between the two groups in mobility, activities of daily living, cognitive status, and pain before and at 1, 3, and 6 months after treatment. Compared with the Control group, the patients in the Intervention group showed a significant difference in emotional well-being (7 (6–10) versus 10 (8–12.75), p < 0.0001), social support (3 (2–3.75) versus 3 (3–5.75), p = 0.001), and communication skills (3 (2–5) versus 3 (2–5), p < 0.0001) showed significant improvement at 6 months after treatment. In addition, although there was no statistical difference in PDQ-39 scores between the two groups of patients at 1 and 3 months after treatment, patients in the Intervention group had smaller scores than those in the Control group. At 6 months after treatment, patients in the Intervention group exhibited much lower scores than those in the Control group (55 (49.5–60) versus 61 (55.5–66), 61 (55.5–66)).

Table 2.

Parkinson's Disease Questionnaire assessment of patients in both groups at different time points.

Characteristic	Intervention (n = 60)	Control (n = 60)	statistic	p
Mobility
Baseline	19 (18–21)	20.5 (17–23.75)	−1.703	0.089
1M	19.5 (18–22)	20 (17–23)	−0.617	0.537
3M	19 (18–22)	20.5 (17.25–23)	−1.057	0.290
6M	20 (18–21.75)	20 (16.25–24)	−0.309	0.758
ADL
Baseline	11 (10–14)	12 (9.25–13)	−0.156	0.876
1M	9 (7–12.75)	11 (9–12)	−1.045	0.296
3M	8.5 (7–11)	10 (8–11)	−1.363	0.173
6M	8 (6–10)	9 (7–10.75)	−0.935	0.350
EMO
Baseline	12 (11–14)	12 (10–14.75)	−0.848	0.397
1M	11 (10–13)	12 (8–14.75)	−0.113	0.910
3M	11 (8–13.75)	11 (9–14)	−0.638	0.524
6M	7 (6–10)	10 (8–12.75)	−4.473	0.000
Social support
Baseline	5 (3–7)	5 (3–6)	−0.114	0.909
1M	3.5 (2–6)	4 (3–6)	−0.904	0.366
3M	4 (2–5.75)	4 (2–6)	−0.702	0.483
6M	3 (2–3.75)	3 (3–5.75)	−3.268	0.001
Stigma
Baseline	5 (4–6.75)	5 (4–7)	−0.402	0.688
1M	5 (4–6)	5 (3.25–7)	−0.037	0.970
3M	4.5 (2.25–7)	5 (3–7)	−0.363	0.716
6M	4 (2.25–6)	4 (3–6)	−0.256	0.798
Communication
Baseline	5 (4–6.75)	5 (4–7)	−0.101	0.919
1M	5 (4–7)	5 (4–7)	−0.269	0.788
3M	6 (4–7)	5 (4–6.75)	−0.996	0.319
6M	3 (2–5)	5 (4–6)	−5.312	0.000
Cognition
	6.5 (5–8)	7 (5–8)	−0.314	0.753
1M	6 (4–7)	6 (4.25–7)	−0.982	0.326
3M	6 (4.25–7)	6 (4.25–8)	−1.031	0.303
6M	5 (4–6.75)	6 (4–7)	−0.908	0.364
Bodily pain
Baseline	3 (2–4)	3 (2–4)	−0.903	0.366
1M	3 (2–4)	3.5 (2–5)	−0.830	0.406
3M	3 (2–4)	3.5 (3–5)	−0.387	0.698
6M	4 (2–5)	4 (3–5)	−0.223	0.824
PDQ-39
Baseline	69 (63–72)	68.5 (64.25–73.75)	-0.786	0.432
1M	64.5 (59.25–69)	68 (61–71)	-1.853	0.064
3M	63 (57.25–67)	63.5 (60–70)	-1.432	0.152
6M	55 (49.5–60)	61 (55.5–66)	-4.010	0.000

M: month; ADL: activities of daily living; EMO: emotional well-being; PDQ-39: Parkinson's Disease Questionnaire-39.

Discussion

The number of AD patients is growing as the population ages, which will put a significant financial strain on society and the families of the affected individuals.²¹ The problem of precisely, thoroughly, and promptly identifying older people with high-risk variables has emerged as a pressing one. CGA is a clinical assessment method widely used in the elderly based on the extensive practice and experience of clinical experts.²² This method not only raises awareness of existing problems that the elderly confront, but also sheds light on some underlying problems.²³ Currently, CGA has been applied to a variety of geriatric diseases, such as diabetes, hypertension, and chronic malnutrition. It has achieved satisfactory results, such as stable control of blood pressure and blood glucose, and significant improvement in nutritional status.^24,25 However, there are no studies on whether AD patients can benefit from CGA.

S100β is an acidic calcium-binding protein that is mainly produced by astrocytes, oligodendrocytes and Schwann cells of the peripheral nervous system.^26,27 S100β is believed to have a trophic impact on neural tissues at physiological concentrations; nevertheless, excess S100β has severe neurotoxicity, which can cause neurodegeneration and impair cognitive function.²⁸ S100β plays an important role in maintaining the normal morphology of nerve fibers, promoting neuronal growth, and encouraging neurotransmitter secretion.²⁹ After the damage of the nervous system, S100β protein can enter into the blood circulation through the damaged blood-brain barrier, so the changes of S100β protein in peripheral blood can specifically reflect the damage of brain tissue.³⁰ At present, S100β has been widely involved in the study of neurological diseases, especially nerve injury diseases.³¹ Prior research has revealed the elevated serum levels of S100β in AD patients.³² In this study, by determining the S100β level in serum of patients at different time points, we found that the serum S100β level kept stable at a higher level in the Control group before treatment. At 1, 3, and 6 after treatment, the serum S100β level tended to decrease in the Intervention group. In addition, the serum S100β level in AD patients in the Intervention group was much lower at 6 months after CGA intervention. To the best of our knowledge, this study is the first to report that CGA Intervention has a significant effect on serum S100β levels in AD patients.

In this study, we compared the prognostic difference between AD patients in the CGA intervention group and those in the conventional therapeutic care group by means of multiple assessment scales. PDQ-39 is the most popular self-assessment scale for evaluating the quality of life of patients with Parkinson's disease in the clinical setting, with higher scores indicating poorer quality of life. The PDQ-39 scale scores of the two groups of patients were compared at different time points before and after treatment, and the results showed that there was no significant difference between the two groups of patients in mobility, ADL, cognitive status, and pain before treatment and 6 months after treatment; however, at 6 months after treatment, the patients in the Intervention group had significant improvements in their emotional well-being, social support, communication ability, and total PDQ-39 scores. There was no statistically significant difference in the ADL and IADL scores, which reflect the activity ability to perform ADLs, between the two groups at 6 months after treatment. However, the scores of patients in the Intervention group were lower than those in the Control group at all-time points, and even showed a downward trend. ADAS-Cog and NPI-Q scores in response to mental status showed a significant decrease in both groups after treatment, but there was no significant difference between the two groups. But after 6 months of treatment, NPI-Q scores were significantly lower in the intervention group than in the control group. This responds to the fact that the degree of improvement in the psychological state of the patients in the intervention group was significantly better than that of the control group. More research is needed to demonstrate whether CGA intervention over a longer period of time can lead to significant improvements in patients in the Intervention group compared with the Control group. Collectively, CGA intervention can improve the mobility and mental status of AD patients.

This study has some limitations. First, this study is a single-center study, and the patients included were only limited to a specific region, so there is a certain selection bias; second, the number of patients included in this study is small; finally, this study has a follow-up deadline of 6 months after treatment, and the long-term prognosis of the patients is not yet known. In order to address the above shortcomings, future studies should be based on a multicenter and large-sample study with a long-term follow-up to evaluate the role of CGA in reducing the social, family, and economic burdens of AD patients as well as improving their quality of life and mental status.

In conclusion, CGA intervention significantly improved mental status, mobility, emotional well-being, social support, and communication skills in people with AD. It is suggested that CGA intervention can improve the mobility and mental status of AD patients.

Footnotes

ORCID iD

Bin Liu

Ethical considerations

The study was approved by the Ethics Committee of Lianshui County People's Hospital (20220510-01). All methods were carried out in accordance with the Declaration of Helsinki.

Consent to participate

This study obtained the informed consent of the patient for publication, and the researcher will protect the patient's privacy when publishing the article.

Author contributions

Da-wei Wang (Conceptualization; Data curation; Formal analysis; Visualization; Writing – original draft; Writing – review & editing); Xue-ting Qin (Conceptualization; Data curation; Formal analysis; Visualization; Writing – original draft; Writing – review & editing); Gang Wang (Data curation; Formal analysis); Juan Liu (Data curation; Formal analysis); Yu-ping Xu (Data curation; Formal analysis); Yuan Tian (Data curation; Formal analysis); Bin Liu (Conceptualization; Data curation; Formal analysis; Funding acquisition; Visualization; Writing – original draft; Writing – review & editing).

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is supported by Intervention of elderly dementia patients using comprehensive elderly assessment and observation of serum S100β The influence of proteins (LKM2022072).

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

The data used to support the findings of this study are available from the corresponding author upon request.

References

Emre

Mecocci

Stender

. Pooled analyses on cognitive effects of memantine in patients with moderate to severe Alzheimer's disease. J Alzheimers Dis 2008; 14: 193–199.

Zhang

. Recent advances in research on Alzheimer's disease in China. J Clin Neurosci 2020; 81: 43–46.

Jucker

Walker

. Alzheimer's disease: from immunotherapy to immunoprevention. Cell 2023; 186: 4260–4270.

Jack

Jr ., Bennett

Blennow

, et al. NIA-AA Research framework: toward a biological definition of Alzheimer's disease. Alzheimers Dement 2018; 14: 535–562.

Grundke-Iqbal

Iqbal

Tung

, et al. Abnormal phosphorylation of the microtubule-associated protein tau (tau) in Alzheimer cytoskeletal pathology. Proc Natl Acad Sci U S A 1986; 83: 4913–4917.

Salis

Loddo

Zanda

, et al. Comprehensive Geriatric Assessment: application and correlations in a real-life cross-sectional study. Front Med (Lausanne) 2022; 9: 984046.

Zhang

Tian

Wang

, et al. The epidemiology of Alzheimer's disease modifiable risk factors and prevention. J Prev Alzheimers Dis 2021; 8: 313–321.

Chen

Yan

Wang

, et al. Chinese Expert consensus on the application of comprehensive geriatric assessment for the elderly. Aging Med (Milton) 2018; 1: 100–105.

Choi

Rajaguru

Shin

, et al. Comprehensive geriatric assessment and multidisciplinary team interventions for hospitalized older adults: a scoping review. Arch Gerontol Geriatr 2023; 104: 104831.

10.

Ambagtsheer

Thompson

Tucker

, et al. Does CGA improve health outcomes in the community? An umbrella review. J Am Med Dir Assoc 2023; 24: 782–789.e715.

11.

Banh Chong

Grosclaude

Chabrillac

, et al. Outcomes of comprehensive geriatric assessment and surgical management in head and neck cancers of the elderly: an observational study. Eur Arch Otorhinolaryngol 2023; 280: 329–338.

12.

Lee

Huang

, et al. Post-acute care for frail older people decreases 90-day emergency room visits, readmissions and mortality: an interventional study. PLoS One 2023; 18: e0279654.

13.

Armentaro

Condoleo

Pelaia

, et al. Short term effect of sacubitril/valsartan on comprehensive geriatric assessment in chronic heart failure: a real life analysis. Intern Emerg Med 2023; 18: 113–125.

14.

van Dyck

Swanson

Aisen

, et al. Lecanemab in early Alzheimer's disease. N Engl J Med 2023; 388: 9–21.

15.

Moussavi

Uehara

Rutherford

, et al. Repetitive transcranial magnetic stimulation as a treatment for Alzheimer's disease: a randomized placebo-controlled double-blind clinical trial. Neurotherapeutics 2024; 21: e00331.

16.

First

Clarke

Yousif

, et al. DSM-5-TR: rationale, process, and overview of changes. Psychiatr Serv 2023; 74: 869–875.

17.

Chevalley

Truijen

Opsommer

, et al. Physical functioning factors predicting a return home after stroke rehabilitation: a systematic review and meta-analysis. Clin Rehabil 2023; 37: 1698–1716.

18.

Munro

Longmire

Drye

, et al. Cognitive outcomes after sertaline treatment in patients with depression of Alzheimer disease. Am J Geriatr Psychiatry 2012; 20: 1036–1044.

19.

Garcia-Alberca

Gris

de la Guia

, et al. Efficacy of Souvenaid(R) combined with acetylcholinesterase inhibitors in the treatment of mild Alzheimer's disease. J Alzheimers Dis 2023; 91: 1459–1469.

20.

Hou

, et al. The impact of Tai Chi on motor function, balance, and quality of life in Parkinson's disease: a systematic review and meta-analysis. Evid Based Complement Alternat Med 2021; 2021: 6637612.

21.

Bartley

Geda

Christianson

, et al. Frailty and mortality outcomes in cognitively normal older people: sex differences in a population-based study. J Am Geriatr Soc 2016; 64: 132–137.

22.

Xiao

Yang

, et al. Analysis of the incidence of falls and related factors in elderly patients based on comprehensive geriatric assessment. Aging Med (Milton) 2023; 6: 245–253.

23.

De Witte

Gobbens

De Donder

, et al. The comprehensive frailty assessment instrument: development, validity and reliability. Geriatr Nurs 2013; 34: 274–281.

24.

Yao

Zheng

, et al. The effect of comprehensive assessment and multi-disciplinary management for the geriatric and frail patient: a multi-center, randomized, parallel controlled trial. Medicine (Baltimore) 2020; 99: e22873.

25.

Kitamura

Nakazawa

Nagashima

, et al. The prognostic utility of a geriatric assessment for patients with pancreatic cancer receiving gemcitabine-based chemotherapy: a prospective observational study. Intern Med 2023; 62: 1573–1580.

26.

Hachem

Aguirre

Vives

, et al. Spatial and temporal expression of S100B in cells of oligodendrocyte lineage. Glia 2005; 51: 81–97.

27.

Vives

Alonso

Solal

, et al. Visualization of S100B-positive neurons and glia in the central nervous system of EGFP transgenic mice. J Comp Neurol 2003; 457: 404–419.

28.

Soldozy

Yagmurlu

Norat

, et al. Biomarkers predictive of long-term outcome after ischemic stroke: a meta-analysis. World Neurosurg 2022; 163: e1–e42.

29.

Koh

Lee

. S100b as a marker for brain damage and blood-brain barrier disruption following exercise. Sports Med 2014; 44: 369–385.

30.

Hov

Bolstad

Idland

, et al. Cerebrospinal fluid S100B and Alzheimer's disease biomarkers in hip fracture patients with delirium. Dement Geriatr Cogn Dis Extra 2017; 7: 374–385.

31.

van Munster

Korevaar

Korse

, et al. Serum S100B in elderly patients with and without delirium. Int J Geriatr Psychiatry 2010; 25: 234–239.

32.

D'Cunha

McKune

Panagiotakos

, et al. Evaluation of dietary and lifestyle changes as modifiers of S100beta levels in Alzheimer's disease. Nutr Neurosci 2019; 22: 1–18.