
==== Front
BMC Oral Health
BMC Oral Health
BMC Oral Health
1472-6831
BioMed Central London

4855
10.1186/s12903-024-04855-w
Research
Analysis of the potential profile and influencing factors for oral frailty in olderly patients with dental implants
Ge Wei-yan 1
Li Rui 2
Zhang Ying 1
Liang Meng-yao 2216314456@qq.com

3
1 https://ror.org/02afcvw97 grid.260483.b 0000 0000 9530 8833 Department of Planting, Affiliated Nantong Stomatological Hospital of Nantong University, Nantong, 226000 China
2 https://ror.org/02kstas42 grid.452244.1 Department of Nursing, The Second Affliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu 221000 China
3 https://ror.org/022fy9g59 grid.508280.7 Department of Nursing, The Sixth People’s Hospital of Nantong, Nantong, Jiangsu 226001 China
13 9 2024
13 9 2024
2024
24 107917 5 2024
3 9 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Objective

To investigate the current state of oral frailty in oldely patients with require dental implants, analyze influencing factors in the characteristics of oral frailty across different patient categories, and provide a reference for clinical staff to identify high-risk groups and develop proactive management strategies.

Methods

Between January 2024 and March 2024, 654 patients with dental implants were selected using convenience sampling from six secondary and tertiary stomatological hospitals in Jiangsu and Zhejiang provinces. Data were collected via a general information questionnaire and the Oral Frailty Index-8. The latent profiles of oral frailty were examined, and univariate and Logistic regression analyses were conducted to determine the impact of various factors on these profiles.

Results

In this cross-sectional study, 605 valid questionnaires were returned, yielding an effective rate of 92.58%. The mean oral frailty score was 6.64 ± 1.21, with the sample comprising 223 males and 382 females, averaging 72.54 ± 6.33 years old. Oral frailty was categorized into three latent profiles: high (20.50%), moderate (53.72%), and low (25.78%) frailty groups. Factor analysis indicated that age, gender, education level, family income, number of implants, and dyslipidemia significantly predicted the classification of these profiles (P < 0.05).

Conclusion

Oral frailty in oldely patients with dental implants exhibits heterogeneity and is influenced by age, sex, education level, family income, number of implants, and dyslipidemia. Clinical staff should recognize the characteristics of different patient categories and implement proactive measures for those at high risk of oral frailty to enhance their quality of life.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-024-04855-w.

Keywords

Dental implants
Olderly patients
Oral frailty
Influencing factors
Latent profile
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
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pmcIntroduction

The global population of individuals aged 65 and above is projected to reach 1.5 billion by 2050, with China alone accounting for approximately 365 million oldely citizens. This demographic shift accelerates the process of social aging [1]. Frailty is a clinical condition marked by impaired function, increased vulnerability, and low stress tolerance, elevating the risk of disability, falls, hospitalization, and mortality [2, 3]. Oral frailty refers to a series of phenomena and processes resulting from the gradual decline in oral health conditions with age, including the number of teeth, oral hygiene, and oral function [4]. Frailty encompasses physical, social, cognitive, and psychological dimensions [5]. Oral frailty, a subset of physical frailty, influences overall physical, cognitive, and social frailty. Studies such as Hironaka’s [6] indicate that worsening oral frailty exacerbates tooth loss, diminishes chewing function, increases nutritional deficits, and leads to general physical weakness. Additionally, facial changes like dentition loss and halitosis can cause social withdrawal, resulting in social frailty. Tooth loss also reduces chewing ability, subsequently decreasing cerebral blood flow, which diminishes brain neural activity and contributes to cognitive decline [7].

With population aging, oral health issues have become increasingly prevalent among the oldely [8]. A global systematic review indicates that the overall incidence of oral frailty in this demographic ranges from 20 to 28%, with a prevalence as high as 45.9% in China [9]. Oral health deterioration not only increases the risk of physical decline but also elevates the likelihood of mortality, disability, reduced quality of life, and hospitalization [10]. Tooth loss is the primary cause of oral frailty, accounting for approximately 30% of all cases [11]. Moreover, tooth loss adversely affects nutrition, quality of life, and overall well-being, and it increases mortality risk [12]. Dental implants, widely used to replace missing teeth, demonstrate long-term survival rates of 94-98% [13]. As an advanced method of dental restoration, dental implants play a significant role in addressing oral issues in oldely patients by effectively restoring missing teeth and enhancing both masticatory function and oral aesthetics [14].

Older adults requiring dental implants constitute a high-risk group for oral frailty due to tooth loss. Oral frailty in these patients can lead to unstable implant fixation, increased risk of implant failure, and susceptibility to incision infections, thereby impeding the healing process and compromising long-term implant success [15, 16]. Given that oral frailty is reversible [17], early identification of high-risk individuals is essential for developing continuous nursing measures to enhance the success rate of dental implants in older adults and improve their quality of life.

However, research on oral frailty in China remains nascent and lacks consideration of individual heterogeneity. Latent profile analysis (LPA), an individual-centered approach, classifies individuals with similar response patterns into the same category based on their responses to external continuous variables. This method allows researchers to identify distinct characteristics within different groups that may not be evident through variable-centered approaches [18]. Consequently, this study to investigate the current state of oral frailty in oldely patients with require dental implants, analyze influencing factors in the characteristics of oral frailty across different patient categories, and provide a reference for clinical staff to identify high-risk groups and develop proactive management strategies.

Materials and methods

Ethics approval

This cross-sectional observational study adhered to the Declaration of Helsinki. Approval was granted by the Ethics Committee of Affiliated Nantong Stomatological Hospital of Nantong University (approval number: PJ 2024-014-01). Informed consent was obtained from all patients.

Subjects

Between January 2024 and March 2024, 654 patients requiring dental implants were recruited from six secondary and tertiary stomatological hospitals in Jiangsu and Zhejiang provinces. Inclusion criteria were: (1) age ≥ 60 years; (2) no contraindications to oral implantation; and (3) basic communication skills and the ability to read and provide informed consent. Exclusion criteria included a history of psychological or psychiatric diseases.

Sample size calculation

The sample size was calculated using the formula for cross-sectional studies: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:n=\frac{{{Z}_{\alpha\:}}^{2}\ast\:P\ast\:(1-P)}{{\delta\:}^{2}}$$\end{document}, with a two-sided test α of 0.05. Based on literature, the prevalence of oral diseases in oldely patients was estimated at 25%, with an allowable error of 0.04. This resulted in a required sample size of 451. Accounting for a 20% rate of invalid questionnaires, at least 541 patients were needed for the study.

Survey tools

(1) General Information Questionnaire: Relevant influencing factors were identified through a literature review [19, 20], expert group meetings, and a self-designed questionnaire. This included four sections: general demographic data (age, sex, body mass index, education, family per capita monthly income, marital status); lifestyle habits, residence, and employment status; comorbidities such as diabetes mellitus, hypertension, and dyslipidemia; and the number of implants needed.

(2) Oral Frailty Index-8 (OFI-8): Developed by Tanaka et al. [21] to assess oral frailty, this index includes five dimensions: denture use, swallowing function, social participation, oral health-related behaviors, and chewing ability. The total score ranges from 0 to 11, with higher scores indicating poorer oral conditions. A score of ≥ 4 signifies oral frailty. Chen Zongmei translated this index into Chinese [22], demonstrating good reliability and validity in olderly patients. For this study, five experts were selected: two in stomatology, two in geriatric nursing, and one in oral nursing. The content validity index of the scale was 0.92, and Cronbach’s α coefficient was 0.892.

Survey and data collection methods

The questionnaire (ID: 216758055) was designed by the researchers via WeChat, encompassing 20 questions related to general information and oral frailty. It was conducted anonymously, ensuring personal information was not disclosed, and personal factors were not individually discussed. Consistency was evaluated using the test-retest reliability method. Two questions with the same stem but different choices were included as the 8th and 12th questions. Forty-nine invalid questionnaires with inconsistent responses were excluded to ensure reliability and that each questionnaire accurately reflected the true intentions of oldely patients with dental implants. A total of 605 valid questionnaires were collected, resulting in an effective recovery rate of 92.58%.

Statistical analysis

LTA was conducted using Mplus8.0 and SPSS software (Armonk, NY: IBM Corp). Scores from the eight items of the OFI-8 scale served as explicit variables, and 1–5 profile categories were analyzed. Fitting indexes were compared, and the optimal number of profile categories was determined based on clinical practical significance.

The fitting indices included Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and sample-size adjusted BIC (aBIC), with smaller values indicating better model fit. Entropy, ranging from 0 to 1, measured classification accuracy, with values closer to 1 denoting higher accuracy. The Likelihood Ratio Test (LMR) and Bootstrap-based Likelihood Ratio Test (BLRT) were used, where P < 0.05 indicated that the model with k categories was superior to the model with k − 1 categories. This study used a comprehensive evaluation of various models to determine the optimal one. Multiple Logistic regression analysis assessed the factors influencing oral frailty in oldely patients with dental implants, with P < 0.05 indicating statistical significance.

Results

General demographic data and oral frailty score

As shown in Tables 1 and 605 valid questionnaires were collected from participants aged 60 to 85 years, with an average age of 72.54 ± 6.33. The oral frailty scores for oldely patients with dental implants ranged from 3 to 10, with a mean score of 6.64 ± 1.21 and an average item score of 0.87 ± 0.31.

Table 1 Basic characteristics of 605 patients with oral frailty

Project	Categories	Number	Proportion (%)	
Age (years)	~ 60	329	54.38	
	~ 70	211	34.88	
	~ 80	65	10.74	
Sex	Male	223	36.86	
	Female	382	63.14	
Marital status	Married	534	88.26	
	Unmarried/divorced/widowed	71	11.74	
Monthly household income per capita (Yuan)	< 1500	158	26.11	
1500–3000	184	30.42	
> 3000	263	43.47	
Degree	Primary school and below	172	28.43	
	Middle and high school	301	49.75	
	College or above	132	21.82	
Place of residence	Cities	481	79.50	
	Rural/township	124	20.50	
Work or not	Yes	268	44.30	
	No	337	55.70	
Body mass index (kg/m2)	< 18.5	117	19.34	
	18.5–23.9	298	49.26	
	24–28	105	17.36	
	> 28	85	14.05	
Number of implants (seeds)	1	138	22.81	
	2–3	213	35.21	
	~ 4	254	41.98	
Diabetes	Yes	177	29.25	
	No	428	70.75	
Hypertension	Yes	183	30.25	
	No	422	60.75	
Dyslipidemia	Yes	280	46.28	
	No	325	53.72	

Determination of the potential profile of oral frailty in oldely patients with dental implants

Using the eight items of the Chinese Oral Frailty Index-8 scale as explicit indicators, an exploratory LPA model with 1 to 5 potential profiles was selected. Models with four or five categories were excluded based on the criterion of P < 0.05. Among the 1 to 3 latent profile models, AIC, BIC, and aBIC values decreased with the number of profiles, achieving the best fit with three latent profile categories, as detailed in Table 2.

Table 2 Comparison of oral frailty potential profile analysis indicators in elderly patients with dental implants

Model	AIC	BIC	aBIC	LMR	BLRT	Entropy	Class probability	
1	34253.731	34276.637	34235.684					
2	30865.323	30834.368	30846.853	0.006	0.000	0.876	0.41/0.59	
3	26693.546	26654.447	26643.534	0.015	0.000	0.832	0.21/0.53/0.26	
4	29615.868	29458.776	29496.368	0.059	0.000	0.913	0.21/0.36/0.17/0.26	
5	28397.138	28371.284	28353.259	0.213	0.000	0.938	0.14/0.21/0.10/0.31/0.24	
Note AIC: Akaike information criterion; BIC: Bayesian information criterion

aBIC sample-corrected BIC; LMR: LoMendell-Rubin; BLRT: Bootstrap-based likelihood ratio test

Average attribution rate and identification of the three potential profiles of oral frailty in oldely patients with dental implants

The three latent profiles were: C1, comprising 124 cases (20.50%); C2, comprising 325 cases (53.72%); and C3, comprising 156 cases (25.78%). Based on the response probabilities of the eight items in the oral frailty scale, C1 was identified as the “high oral frailty group,” C2 as the “moderate oral frailty group,” and C3 as the “low oral frailty group” (illustrated in Fig. 1). The average probabilities of oral frailty in oldely patients with implants belonging to the three profiles were 0.943, 0.952, and 0.962, respectively, confirming the reliability of the three-profile model (Table 3).

Fig. 1 Line chart depicting oral frailty across each latent category

Table 3 Average attribution rate of the three oral frailty categories in olderly patients with dental implants (n = 605)

Model	C1	C2	C3	
C1	0.943	0.018	0.044	
C2	0.032	0.952	0.016	
C3	0.015	0.023	0.962	

Univariate analysis of oral Frailty profiles in oldely patients with dental implants

The general demographic and health-related characteristics of oldely patients with dental implants across three potential oral frailty profiles were compared. Statistically significant differences were noted in age, sex, education, family per capita monthly income, number of implants, and dyslipidemia among the profiles (P < 0.05) (Table 4).

Table 4 Influencing factors for the three potential oral frailty profiles in oldely patients with dental implants (n = 605)

Variables	Low oral failure group (n = 156)	Middle oral failure group (n = 325)	High oral failure group (n = 124)	χ2	P	
Age (years)				75.383	<0.001	
~ 60	107	159	46			
~ 70	45	126	40			
~ 80	4	40	38			
Sex				7.761	0.021	
Male	52	112	59			
Female	104	213	65			
Marital status				0.675	0.714	
Married	135	288	111			
Unmarried/divorced/widowed	21	37	13			
Degree				58.962	<0.001	
Primary school and below	19	108	45			
Middle and high school	72	165	64			
College or above	65	52	15			
Place of residence				4.571	0.102	
Cities	115	263	103			
Rural/township	41	62	21			
Monthly household income per capita (Yuan)				12.318	0.015	
< 1500	44	84	30			
1500–3000	40	91	53			
> 3000	72	150	41			
Body mass index (kg/cm2)				2.907	0.802	
< 18.5	28	59	30			
18.5–23.9	77	166	55			
24–28	28	56	21			
> 28	23	44	18			
Work or not				10.069	0.507	
Yes	81	146	41			
No	75	179	83			
Number of implants (seeds)				35.756	<0.001	
1	47	73	18			
2–3	63	123	27			
~ 4	46	129	79			
Diabetes				1.806	0.405	
Yes	52	89	36			
No	104	236	88			
Hypertension				5.889	0.053	
Yes	47	109	27			
No	109	216	97			
Dyslipidemia				8.455	0.015	
Yes	98	170	67			
No	58	155	57			

Multivariate analysis of oral Frailty profiles in oldely patients with dental implants

Logistic regression analysis was conducted, utilizing the oral frailty score of oldely patients with dental implants as the dependent variable, and incorporating variables that showed statistical significance in the univariate analysis as independent variables. In comparison to the C3 group, age (categorization: 60 years = 0, 70 years = 1, 80 years = 2, with 60 years as the reference), sex (female = 0, male = 1, with female as the reference), education level (primary school and below = 0, junior and senior high school = 1, junior college and above = 2, with primary school and below as the reference), family per capita income (< 1500 yuan = 0, 1500–3000 yuan = 1, > 3000 yuan = 2, with < 1500 yuan as the reference), and number of implants (1 implant = 0, 2–3 implants = 1, 4–2 implants = 2, with 1 implant as the reference) were identified as influencing factors for oral frailty (all P < 0.05).

Regression analysis results indicated that age, gender, education level, family income per capita, and the necessity for growth significantly predicted higher oral failure rates (P < 0.05) compared to the low oral failure group. Additionally, age, gender, growth necessity, and dyslipidemia were significant predictors of oral failure (all P < 0.05), as demonstrated in Table 5.

Table 5 Multivariate analysis of the three potential oral frailty profiles in oledely patients with dental implants (n = 605)

Project	B	SE	Walds χ2	P	OR	95% CI	
C1 group vs. C3 group							
Constant	2.132	0.418	26.01	<0.001	8.310	-	
Age (years)							
~ 70	0.574	0.315	3.320	0.034	1.772	1.321–2.142	
~ 80	1.037	0.164	39.981	<0.001	2.811	1.541–3.870	
Sex							
Female	0.713	0.211	22.460	0.001	2.033	1.832–2.832	
Degree							
Middle and high school	-0.154	0.076	4.093	0.029	0.859	0.432–0.899	
College or above	-0.312	0.262	1.418	<0.001	0.877	0.511–0.923	
Monthly household income per capita (Yuan)							
1500–3000	-0.231	0.088	4.510	0.024	0.794	0.638–0.893	
> 3000	-0.211	0.201	11.021	0.008	0.734	0.598–0.921	
Number of implants (seeds)							
2–3	0.378	0.133	8.077	0.011	1.466	1.214–1.876	
~ 4	1.122	0.411	7.453	0.009	3.055	1.675–5.321	
Dyslipidemia							
Yes	0.798	0.119	44.969	<0.001	2.211	1.833–2.907	
C2 group vs. C3 group							
Constant	1.661	0.155	114.83	<0.001	5.213	-	
Age (years)							
~ 70	0.234	0.112	4.365	0.024	1.262	1.078–2.376	
~ 80	0.387	0.087	19.785	<0.001	1.471	1.145–3.287	
Sex							
Female	0.174	0.074	5.528	0.018	1.194	1.077–1.977	
Number of implants (seeds)							
~ 4	0.241	0.112	4.630	0.023	1.270	1.002–2.134	
Monthly household income per capita (Yuan)							
> 3000	-0.421	0.143	8.663	0.009	0.658	0.213–0.976	
Dyslipidemia							
Yes	0.299	0.125	5.721	0.015	1.359	1.089–2.181	
Note C1 represents “high oral failure group,” C2 represents “moderate oral failure group,” and C3 represents “low oral failure group”

Discussion

Oral frailty in oldely patients with dental implants can be categorized into three distinct groups, with an overall high level of frailty. This study utilized LPA to identify three categories of oral decline: high oral failure, moderate oral failure, and low oral failure groups, constituting 20.5%, 53.72%, and 25.78% of the sample, respectively. The study confirmed heterogeneity within the weak oral group. The oral frailty score averaged 6.64 ± 1.21, with scores above 4 indicating significant frailty, thereby highlighting the elevated frailty levels among olderly dental implant patients. Most domestic research focuses on oldely individuals in communities or nursing homes [23, 24], while international studies predominantly examine post-implantation oral health without specifically addressing oral frailty in this demographic [25, 26]. Notably, 20.50% of patients demonstrated severe oral frailty prior to implant placement. Scores for item 2, “Can you eat hard food, including hard candy or raw sweet potatoes?” and “Do you see a dentist at least once a year?” exceeded 0.82, indicating both low chewing ability and poor oral health care practices. Additionally, 53.72% of patients exhibited moderate frailty, representing the largest group, which suggests that most oldely patients with dental implants fall into this category. Future efforts should focus on addressing oral frailty, identifying modifiable factors, and implementing strategies to reverse frailty, thereby enhancing quality of life and the longevity of dental implants. Finally, 25.78% of patients exhibited low-level frailty, often due to poor chewing caused by missing teeth. Post-implantation follow-ups are necessary to assess whether oral weakness improves after implantation.

The study identified significant differences in age, sex, education, family per capita income, number of implants, and dyslipidemia. Prior research has established age as a risk factor for oral frailty [24, 27], with the prevalence of oral debilitating conditions increasing with age. This may be attributed to decreased alkaline phosphatase enzyme activity in periodontal ligament cells, diminished regeneration and osteogenic activity of periodontal ligament stem cells, physiological atrophy, and bone demineralization, leading to conditions such as periodontitis, caries, and general oral weakness [28]. Additionally, due to the limited scope of reimbursement for oral treatment costs in China, oldely individuals often avoid seeking dental care due to the financial burden, resulting in delayed treatment of oral diseases.

Women exhibit higher levels of oral frailty compared to men. Nagatani [7] found that oldely women are more susceptible to oral weakness. Possible reasons include the gradual decrease in estrogen levels with age [29], which thins the oral mucosa and leads to dry mouth, thereby increasing the risk of oral frailty. Despite a greater focus on oral hygiene among women [30], they are more prone to conditions such as gingivitis and periodontitis. This increased susceptibility may be attributed to their thinner, more sensitive oral mucosa, which is more vulnerable to external stimuli and bacterial infections. Higher education and better economic conditions serve as protective factors against oral frailty. Individuals with higher education levels typically have greater health awareness and prioritize their health [31]. They are also more likely to proactively seek information on oral health and adopt preventive measures, such as regular dental check-ups, good oral hygiene practices, and a healthier lifestyle. Habits like not smoking, moderate alcohol consumption, and a balanced diet contribute to maintaining oral health. Additionally, better economic conditions enable individuals to afford oral health care costs, including regular examinations, dental cleanings, and restorations.

The number of implants required serves as a risk factor for oral frailty, with a direct correlation between the number of missing teeth and oral frailty. Tooth loss significantly impairs chewing function [32], thereby hindering the thorough mastication and digestion of food, which adversely affects nutrient absorption. Additionally, prolonged tooth loss leads to atrophy and dysfunction of perioral tissues, exacerbating oral frailty. The loss of teeth also compromises gum support [33], making the gums more susceptible to atrophy, gingivitis, and other related issues. This susceptibility heightens the risk of oral infection and further weakens oral health. Furthermore, tooth loss disrupts the balance of the oral microbial community, increasing the risk of infections and diseases.

Dyslipidemia poses a risk factor due to its potential to impair blood circulation [34], compromising the blood supply and nutrition to oral tissues and making them susceptible to damage. Additionally, dyslipidemia can impair immune function [35], reducing resistance to oral bacteria and elevating the risk of infection, ultimately contributing to oral frailty.

The study’s sample representation was limited to stomatological hospitals in Jiangsu and Zhejiang Provinces, which restricts the generalizability of the results. Future research should aim to broaden the evidence base and verify findings across diverse populations. Additionally, the potential for reversing oral frailty post-implantation was not explored. Longitudinal studies are recommended to investigate the mechanisms by which dental implants affect oral frailty in oldely patients.

Enlightenment to clinical work

Addressing oral frailty in oldely patients with dental implants requires significant attention from clinical staff. To enhance the success rate and longevity of dental implants in this demographic, individualized treatment plans should be tailored to each patient’s specific oral frailty condition. Factors such as age, overall health status, and oral condition must be taken into account to determine appropriate treatment strategies and implant plans.

Conclusions

Latent Profile Analysis (LPA) categorized oral frailty in oldely patients with implants into three distinct profiles: high(20.50%), moderate(53.72%), and low(25.78%) oral failure groups. Significant differences in these profiles were influenced by age, sex, education level, family income, number of implants, and dyslipidemia. Clinical staff should recognize the characteristics of different patient categories and implement proactive measures for those at high risk of oral frailty to enhance their quality of life.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Author contributions

ML designed this study.RL and YZ built the study framework, WG wrote the manuscript, contributed to the article, and approved the submitted version.All authors reviewed the manuscript.

Funding

No funds, grants, or other support were received during the preparation of this manuscript.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The Ethics Committee of Affiliated Nantong Stomatological Hospital of Nantong University approved the study (approval number: PJ 2024-014-01). Informed consent was obtained from all patients. All methods and procedures were performed in accordance with relevant guidelines and regulations, including the Declaration of Helsinki.

Informed consent

All patients provided informed consent.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Wei-yan Ge, Rui Li and Ying Zhang contributed equally to this work.
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