Liming Su
Xue Sun1- 1School of Medicine, Huzhou University, Huzhou, China
- 2Huzhou Third Municipal Hospital, The Affiliated Hospital of Huzhou University, Huzhou, China
Introduction: Older adults with motoric cognitive risk (MCR) syndrome are at high risk of developing dementia. Although the definition of MCR is well recognized and consensus, previous studies did not reach an agreement on diagnostic criteria and measurement methods/tools for slow gait speed, which is one of four components of MCR diagnosis. The substantial heterogeneity in the methodology of slow gait speed diagnosis for MCR limits comparability and meta-analysis of studies.
Objective: The study aims to conduct systematic and standardized integration for diagnostic criteria and methods of slow gait speed diagnosis for MCR based on previous evidence that may improve comparability between future studies.
Methods: A systematic literature review will be undertaken by searching the following electronic databases (until February 1, 2022): PUBMED, EMBASE, The Cochrane Library, Web of Science. Additional studies will be identified by checking the reference lists of included studies or relevant reviews, manually searching the internet search engine Google Scholar, and searching the authors' personal files, if necessary. Two researchers will perform data extraction independently, and discrepancies will be resolved by discussion, which will include a third researcher if requires. The paper selection will perform in duplicate. Finally, a narrative account will synthesize the findings to answer the objectives of this review.
Discussion: This is the first study on systematic and standardized integration for diagnostic criteria and measurement methods/tools for slow gait speed in diagnosing MCR. The findings of this study will be convenient for medical staff to examine the intended use and applicability of each instrument/tool for evaluating the gait speed, and provide insight into developing uniform guidelines for MCR.
Systematic Review Registration: PROSPERO registration number: CRD42021232671.
Introduction
Rationale
Over 50 million people were estimated to be living with dementia globally in 2019, and this number is expected to increase to 152 million by 2050 (1, 2). However, effective treatments remain frustratingly elusive, and dementia has become an urgent challenge for the global community.
The current preclinical phase of dementia includes mild cognitive impairment (MCI) and motoric cognitive risk (MCR) syndrome (3, 4). MCR was a recently described predementia syndrome proposed by Verghese in 2013, characterized by cognitive complaints and slow gait speed without disability and dementia (5). Compared with MCI, MCR makes the assessment highly advantageous in detecting older adults at high risk of dementia (6, 7), avoiding the lengthy comprehensive neuropsychological evaluation and other time-consuming investigations (8, 9). It is more adaptable under cross-regional and cross-cultural backgrounds (5, 10, 11). Although the definition of MCR is well recognized and consensus (5, 10–15), previous studies did not reach an agreement on diagnostic criteria and measurement methods/tools for MCR, which would be a potential reason for a significant discrepancy in the prevalence of MCR in different studies, from 2–27.3% (10, 14, 16) all over the world (11, 17, 18). In general, the following four components have been proposed to be met for the diagnosis of MCR (5, 10): (a) subjective cognitive decline (SCD), (b) slow gait speed, (c) absence of dementia, and (d) independence in activities of daily living. Screening methods/tools for SCD, dementia and capability of daily living have been shown relative consistency in previous MCR studies, e.g., a question or a structured questionnaire about subjective memory loss was commonly used to screen SCD (10, 14, 19); the exclusion of dementia always refers to the diagnosis guidelines from ICD-10/11 or DSM-IV/V (5, 10, 15); the Activities of Daily Living (ADL) scale was applied to evaluate daily living capability. It is worth mentioning that slow gait speed is the critical diagnosis component of MCR; however, it always expresses controversy on diagnostic criteria and measurement methods/tools.
The evaluation of slow gait speed has significant controversy on the measurement tool, cut-off value, and length of walking required in different studies, including (1) A discrepancy of measurement tools: instrumented walkway with embedded pressure sensors (such as GAITRite ®, G-WALK ®) was commonly applied to evaluate gait speed in most recent studies (20–22). Besides, gait speed (m/s) was also calculated in the specific meter at the usual gait speed by a systematic stopwatch in several previous studies (23, 24). (2) A discrepancy of measurement length of walking: gait speed has been assessed through different length paths, ranging from 2.44 to 9.72 m (15, 23, 25, 26), allowing for the acceleration and deceleration phases. (3) A discrepancy of cut-off values for the diagnosis of slow gait speed: most of the studies considered slow gait as a binary variable using the different cut-off values, e.g., 0.8 m/s (27), 20th lower percentile (28), or ≥ 1 standard deviation (SD) below mean values of gait speed established within the same study cohort (18, 24, 29). Considering that gender and age might impact the diagnostic decisions of slow gait speed in the same cohort, some studies proposed that the diagnosis of slow gait speed should have age- and sex-appropriate cut-off value (27, 30). It is worth noting that a few studies have shown that gait speed might be difficult to assess during a primary care visit because of consultation rooms/space and consult time constraints (31, 32). In this context, a substitutive diagnosis component of MCR has been recommended, such as mobility performance using the five-times-sit-to-stand (FSTT) test (7, 33). Therefore, the most common measurement tool, length of walking, and cut-off value, for diagnosing slow gait speed in MCR individuals are unclear. In addition, whether better surrogate criteria for superseding slow gait speed remains to be elucidated.
The diagnostic criteria and measurement methods/tools for MCR are constantly evolving. There are no current uniform guidelines for MCR diagnosis, which impedes clinical practice and comparability of research on MCR across countries. Therefore, uniform diagnostic criteria and measurement methods/tools for MCR are needed. Given the scanty of studies on MCR diagnosis and the significant controversy on the diagnosis of slow gait speed, this study will conduct a systematic review to explore the ways used to diagnose MCR cases in all studies, using Verghese's criteria. It will focus on the variation of operationalization in the diagnosis component of slow gait speed for MCR.
Objectives
This study aims to perform a systematic review and narrative synthesis of evidence on the methodology of measuring slow gait speed in diagnosing MCR.
Methods
Review Method
The protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) database (registration number CRD42021232671) (34) on 22 February 2021, which is reported following the reporting guidance provided in the PRISMA-P statement (35, 36) (see PRISMA-P checklist in Supplementary Material 1).
Patient and Public Involvement
No patients or the public will be involved in this study.
Eligibility Criteria
Any original studies reporting the diagnostic criteria and measurement methods/tools for participants with MCR will be considered for inclusion in the final analysis.
Inclusion criteria will include the following: (1) The participant population included MCR; (2) Full text include MCR diagnostic criteria and measurement methods/tools.
Exclusion criteria will exclude the following: (1) Not relevant; (2) Not in English; (3) Inadequate description of slow gait speed methodology; (4) The full text does not include diagnostic criteria and measurement methods/tools for slow gait speed; (5) Duplicate analyses conducted on the same cohorts with the same assessment methods of slow gait speed; (6) Commentaries; (7) Methodology papers; (8) Conference abstracts; (9) Full text not available; (10) Animal or laboratory studies. Protocols, editorials, and letters will be excluded, but relevant references will be screened.
Information Sources and Search Strategy
According to key terms from previous literature reviews and Medical Subject Headings (MeSH), the following electronic bibliographic databases will be searched (until February 1, 2022): PUBMED, EMBASE, The Cochrane Library, Web of Science. The literature search will be limited to the English language and human subjects. A detailed search strategy of PUBMED was built (see Table 1 in Supplementary Material 2), similar search strategies will be adapted to other electronic databases. The searches will be re-run before the final analysis, and additional studies will be retrieved.
To ensure literature saturation, we will check the reference lists of relevant studies, reviews, protocols, editorials, and letters identified by the search, and conduct a manual search of the internet search engine Google Scholar. In addition, if necessary, we will also search the authors' personal files to make sure that all relevant material has been captured. Finally, we will circulate a bibliography of the included studies to the systematic review team and experts identified by the team.
Study Records
Data Management
The abstracts and full-text articles retrieved from the search strategy will be imported into Endnote X9, and duplicates will be removed.
Screening and Data Collection
Two researchers will independently examine (1) titles and abstracts, and (2) full texts of relevant articles in two separate stages. Any study not meeting the inclusion criteria will be removed, and two researchers will resolve the disagreements by discussion or by a third researcher. Neither of the two researchers will be blind to the journal titles, the study authors, or institutions. According to the PRISMA, we will present the diagram of the selection process (37) (see Figure 1).
Figure 1. Systematic review flow-chart.
Data Extraction
According to the previously designed and standardized sheet, two researchers will independently perform the data extraction from each eligible study. We will conduct calibration exercises before starting the review to ensure consistency across reviewers. The following data will be collected in the included studies: publication information, including the first author's name, publication year; study characteristics, such as country, research type, measurement setting, total study sample size; participant information, like age, number of the target population, prevalence, and inclusion and exclusion criteria; and screening information of MCR: except for SCD, dementia, and capability of daily living, the screening method of slow gait speed will be critical information for collection. This study will extract the cut-off values of slow gait in different age groups based on the gender stratification of the participants, and the cut-off value with the highest frequency of use will be considered “the most common cut-off value” for slow gait to match the particular gender and age. In cases where a publication characterized subjects using different MCR criteria, these criteria will be extracted separately and treated as separate entries for analysis (detail see Tables 2, 3 in Supplementary Material 2).
Outcomes
This study will systematically review the differences in usage number of measurement methods/tools for screening slow gait speed or other potential surrogate criteria in diagnosing MCR, and further clarify the operationalization of slow gait speed criteria and the sex- and age-appropriate cut-off values to define gait slow in different countries and cohorts.
Assessment of Risk of Bias
We are interested in the diagnostic criteria and measurement methods/tools of slow gait speed in diagnosing MCR in different studies, not the results of disease risk or treatment efficacy. Meanwhile, in terms of the scanty of studies on MCR diagnosis, we will conduct a purely narrative systematic literature review without an actual meta-analysis.
Data Synthesis
A narrative synthesis will be conducted using tools and techniques informed by the Guidance on the Conduct of Narrative Synthesis in Systematic Reviews (38). We will comprehensively describe these research results and summarize the measurement methods/tools for slow gait speed or other potential surrogate criteria. A quantitative analysis will also be conducted to assess the difference in usage number of each diagnostic criteria/method and cut-off value, where appropriate, including the differences in the usage number of measurement tools for slow gait between measurement sites (clinical and community setting), and the differences in the usage number of cut-off values for slow gait based on the different characteristics of participants, like countries, genders, age groups. A chi-squared test or Fisher's exact test will be applied to verify the statistical significance of differences (P-value of < 0.05).
Discussion
This study protocol follows the recommendations by the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. Previous studies have shown that older adults with MCR are at high risk of developing dementia, including Alzheimer's disease with a two-fold increased risk and vascular dementia with a 12-fold increased risk (10, 27). One multicenter prevalence study reported that 20.3% of individuals with MCR could be reverted to non-MCR (11). Therefore, a rapid diagnosis of MCR is essential for dementia ultra-early prevention and intervention. Currently, there are inconsistent conclusions on diagnostic/measurement methods for MCR, especially for its important diagnosis component, i.e., gait slow speed, and no systematic review focusing on this topic. To the best of our knowledge, this is the first systematic review protocol on the comprehensive analysis of the methodology of measuring slow gait speed in diagnosing MCR. The findings of this review will provide the conceptual framework for the future development of MCR standardized diagnostic criteria and facilitate its consistent use in clinical practice and research.
Certain limitations in the design of this study should be noted. Language restriction to English might exclude additional studies published in other first languages, potentially introducing language and cultural biases. Furthermore, the scanty studies on MCR diagnosis will make meta-analysis difficult and sometimes impossible.
This protocol describes the integration framework of the diagnostic criteria and measurement methods/tools of slow gait speed in diagnosing MCR. The findings of this study will elaborate on the most common measurement tool, length of walking, and cut-off value, for diagnosing slow gait speed in MCR individuals. This study will provide critical clinical implications for the MCR screening practice. According to individual-level characteristics and screening space, medical staff will choose the appropriate measurement methods/tools of slow gait speed or better surrogate criteria for superseding slow gait speed. These matched-conditions measurement methods/tools of slow gait speed may provide insight into developing uniform guidelines for MCR.
Amendments
Protocol amendments will be listed and made available on the PROSPERO registration. Any modifications to this protocol will be documented and published alongside the systematic review results.
Author's Note
The study is currently preparing to search the literature. We will limit the date of the last literature retrieval to February 1, 2022, and we will re-run the literature search before the final analysis. This study will be completed in June 2022, and the timeline of the work is in detail as below:
- Complete the data extract at the end of Mar 2022;
- Complete the data analysis at the end of Apr 2022;
- Finish the manuscript and submit it at the end of June 2022.
Ethics Statement
Ethical approval is not required for this systematic review as no primary data are collected. However, the findings of this study will be published in an open-access journal to ensure access for all stakeholders and disseminated during various scientific conferences.
Author Contributions
LW and LS conceptualized the review. LS wrote the draft manuscript of this study. XS drafted the search strategies, CH and ZW will conduct article screening and data extraction. XS critically reviewed the protocol. LW is the guarantor. All authors contributed to the revision of the protocol. All authors have read and approved the final manuscript.
Funding
This work was supported by the National Natural Science Foundation of China (Nos. 72174061 and 71704053), the China Scholarship Council Foundation (No. 201908330251), Zhejiang Provincial Natural Science Foundation of China (No. LQ17G030002), the General Scientific Research Project of Zhejiang Education Department (Y201942543), and the Zhejiang Provincial College Students Scientific and Technological Innovation Activities–Zhejiang Xinmiao Talents Program (No. 2021R431031).
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary Material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2022.858950/full#supplementary-material
Abbreviations
MCR, Motoric Cognitive Risk Syndrome.
References
1. United Nations. World population prospects 2019: highlights. Department of Economic and Social Affairs, Population Division (2019).
2. Alzheimer's Disease International. (2019). World Alzheimer Report 2019: Attitudes to Dementia. Available online at: https://www.alzint.org/resource/world-alzheimer-report-2019/ (accessed September 20, 2019).
3. Sekhon H, Allali G, Launay CP, Barden J, Szturm T, Liu-Ambrose T, et al. Motoric cognitive risk syndrome, incident cognitive impairment and morphological brain abnormalities: systematic review and meta-analysis. Maturitas. (2019) 123: 45–54. doi: 10.1016/j.maturitas.2019.02.006
4. Beauchet O, Sekhon H, Launay CP, Gaudreau P, Morais JA, Allali G. Relationship between motoric cognitive risk syndrome, cardiovascular risk factors and diseases, and incident cognitive impairment: results from the “NuAge” study. Maturitas. (2020) 138: 51–7. doi: 10.1016/j.maturitas.2020.05.007
5. Verghese J, Wang C, Lipton RB, Holtzer R. Motoric cognitive risk syndrome and the risk of dementia. J Gerontol A Biol Sci Med Sci. (2013) 68:412–8. doi: 10.1093/gerona/gls191
6. Capistrant BD, Glymour MM, Berkman LF. Assessing mobility difficulties for cross-national comparisons: results from the World Health Organization Study on Global AGEing and Adult Health. J Am Geriatr Soc. (2014) 62:329–35. doi: 10.1111/jgs.12633
7. Sekhon H, Launay CP, Chabot J, Allali G, Beauchet O. Motoric cognitive risk syndrome: Could it be defined through increased five-times-sit-to-stand test time, rather than slow walking speed?. Front Aging Neurosci. (2019) 10: 434. doi: 10.3389/fnagi.2018.00434
8. Sekhon H, Allali G, Beauchet O. The association of anxio-depressive disorders and depression with motoric cognitive risk syndrome: results from the baseline assessment of the Canadian longitudinal study on aging. Geroscience. (2019) 41:409–18. doi: 10.1007/s11357-019-00093-z
9. Sathyan S, Ayers E, Gao T, Milman S, Barzilai N, Rockwood K, et al. Frailty and risk of incident motoric cognitive risk syndrome. J Alzheimers Dis. (2019) 71(s1):S85–S93. doi: 10.3233/JAD-190517
10. Verghese J, Annweiler C, Ayers E, Barzilai N, Beauchet O, Bennett DA, et al. Motoric cognitive risk syndrome: multicountry prevalence and dementia risk. Neurology. (2014) 83:718–26. doi: 10.1212/WNL.0000000000000717
11. Verghese J, Ayers E, Barzilai N, Bennett DA, Buchman AS, Holtzer R, et al. Motoric cognitive risk syndrome: multicenter incidence study. Neurology. (2014) 83:2278–84. doi: 10.1212/WNL.0000000000001084
12. Ayers E, Verghese J. Motoric cognitive risk syndrome and risk of mortality in older adults. Alzheimers Dement. (2016) 12:556–64. doi: 10.1016/j.jalz.2015.08.167
13. Ayers E, Verghese J. Diagnosing motoric cognitive risk syndrome to predict progression to dementia. Neurodegener Dis Manag. (2014) 4:339–42. doi: 10.2217/nmt.14.39
14. Callisaya ML, Ayers E, Barzilai N, Ferrucci L, Guralnik JM, Lipton RB, et al. Motoric cognitive risk syndrome and falls risk: a multi-center study. J Alzheimers Dis. (2016) 53:1043–52. doi: 10.3233/JAD-160230
15. Doi T, Shimada H, Makizako H, Tsutsumimoto K, Verghese J, Suzuki T. Motoric cognitive risk syndrome: association with incident dementia and disability. J Alzheimers Dis. (2017) 59:77–84. doi: 10.3233/JAD-170195
16. Wang N, Allali G, Kesavadas C, Noone ML, Pradeep VG, Blumen HM, et al. Cerebral small vessel disease and motoric cognitive risk syndrome: results from the Kerala-Einstein study. J Alzheimers Dis. (2016) 50:699–707. doi: 10.3233/JAD-150523
17. Sosa AL, Albanese E, Stephan BC, Dewey M, Acosta D, Ferri CP, et al. Prevalence, distribution, and impact of mild cognitive impairment in Latin America, China, and India: a 10/66 population-based study. PLoS Med. (2012) 9:e1001170. doi: 10.1371/journal.pmed.1001170
18. van der Leeuw G, Ayers E, Blankenstein AH, van der Horst HE, Verghese J. The association between pain and prevalent and incident motoric cognitive risk syndrome in older adults. Arch Gerontol Geriatr. (2020) (87): 103991. doi: 10.1016/j.archger.2019.103991
19. Meiner Z, Ayers E, Verghese J. Motoric cognitive risk syndrome: a risk factor for cognitive impairment and dementia in different populations. Annals Geriatric Med Res. (2020) 24:3. doi: 10.4235/agmr.20.0001
20. Verghese J, Wang C, Bennett DA, Lipton RB, Katz MJ, Ayers E. Motoric cognitive risk syndrome and predictors of transition to dementia: a multicenter study. Alzheimers Dement. (2019) 15:870–877. doi: 10.1016/j.jalz.2019.03.011
21. Van Uden CJT, Besser MP. Test-retest reliability of temporal and spatial gait characteristics measured with an instrumented walkway system (GAITRite). BMC Musculoskelet Disord. (2004) (5): 13. doi: 10.1186/1471-2474-5-13
22. Cheng FY, Chang Y, Cheng SJ, Shaw JS, Lee CY, Chen PH. Do cognitive performance and physical function differ between individuals with motoric cognitive risk syndrome and those with mild cognitive impairment? BMC Geriatr. (2021) 21:36. doi: 10.1186/s12877-020-01992-z
23. Beauchet O, Sekhon H, Launay CP, Chabot J, Rolland Y, Schott AM, et al. Motoric cognitive risk syndrome and mortality: results from the EPIDOS cohort. Eur J Neurol. (2019) 26:794–e56. doi: 10.1111/ene.13891
24. Lord S, Moyes S, Teh R, Port W, Muru-Lanning M, Bacon CJ, et al. Gait, cognition and falls over 5 years, and motoric cognitive risk in New Zealand octogenarians: Te Puāwaitanga o Nga Tapuwae Kia Ora Tonu, LiLACS NZ. BMC Geriatr. (2020) 20:43. doi: 10.1186/s12877-020-1420-8
25. Sekhon H, Allali G, Launay CP, Chabot J, Beauchet O. The spectrum of pre-dementia stages: cognitive profile of motoric cognitive risk syndrome and relationship with mild cognitive impairment. Eur J Neurol. (2017) 24:1047–54. doi: 10.1111/ene.13331
26. Blumen HM, Allali G, Beauchet O, Lipton RB, Verghese J. A gray matter volume covariance network associated with the motoric cognitive risk syndrome: a multicohort MRI study. J Gerontol A Biol Sci Med Sci. (2019) 74:884–9. doi: 10.1093/gerona/gly158
27. Jung HW, Jang IY, Lee CK, Yu SS, Hwang JK, Jeon C, et al. Usual gait speed is associated with frailty status, institutionalization, and mortality in community-dwelling rural older adults: a longitudinal analysis of the Aging Study of Pyeongchang Rural Area. Clin Interv Aging. (2018) (13): 1079-1089. doi: 10.2147/CIA.S166863
28. Willey JZ, Moon YP, Kulick ER, Cheung YK, Wright CB, Sacco RL, et al. Physical inactivity predicts slow gait speed in an elderly multi-ethnic cohort study: the northern Manhattan study. Neuroepidemiology. (2017) 49:24–30. doi: 10.1159/000479695
29. Ayers E, Verghese J. Gait dysfunction in motoric cognitive risk syndrome. J Alzheimers Dis. (2019) 71:S95–S103. doi: 10.3233/JAD-181227
30. Lau LK, Wee SL, Pang WJB, Chen KK, Jabbar KA, Yap PLK, et al. Reference values of gait speed and gait spatiotemporal parameters for a South East Asian population: The Yishun study. Clin Interv Aging. (2020) 15: 1753–65. doi: 10.2147/CIA.S270407
31. Van Kan GA, Rolland Y, Andrieu S, Bauer J, Beauchet O, Bonnefoy M, et al. Gait speed at usual pace as a predictor of adverse outcomes in community-dwelling older people an International Academy on Nutrition and Aging (IANA) Task Force. J Nutr Health Aging. (2009) 13:881–9. doi: 10.1007/s12603-009-0246-z
32. Petek Ster M, Svab I, Zivcec Kalan G. Factors related to consultation time: experience in Slovenia. Scand J Prim Health Care. (2008) 26:29–34. doi: 10.1080/02813430701760789
33. Whitney SL, Wrisley DM, Marchetti GF, Gee MA, Redfern MS, Furman JM. Clinical measurement of sit-to-stand performance in people with balance disorders: validity of data for the Five-Times-Sit-to-Stand Test. Phys Ther. (2005) 85:1034–45. doi: 10.1093/ptj/85.10.1034
34. Liming S, Lina W, Xue S, Cheng H, Zhuqin W. A systematic review of diagnostic criteria and methods for motoric cognitive risk syndrome (MCR). PROSPERO 2021 CRD42021232671. Available online at: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021232671 (accessed February 22, 2021).
35. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. PRISMA-P Group. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst Rev. (2015) 41: 1. doi: 10.1186/2046-4053-4-1
36. Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. PRISMA-P Group. preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. BMJ. (2015) 350:g7647. doi: 10.1136/bmj.g7647
37. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. (2021) 372:n71. doi: 10.1136/bmj.n71
Keywords: motoric cognitive risk syndrome, diagnostic criteria, subjective cognitive decline, slow gait speed, systematic review
Citation: Su L, Sun X, Huang C, Wei Z, Shen X and Wang L (2022) Methodology of Measuring Motoric Cognitive Risk Syndrome—Focusing on Slow Gait Speed: Protocol for a Systematic Review. Front. Psychiatry 13:858950. doi: 10.3389/fpsyt.2022.858950
Received: 20 January 2022; Accepted: 21 February 2022;
Published: 23 March 2022.
Edited by:
Francesco Panza, University of Bari Aldo Moro, ItalyReviewed by:
Ahmet Turan ISIK, Dokuz Eylül University, TurkeyEmmeline Ayers, Albert Einstein College of Medicine, United States
Copyright © 2022 Su, Sun, Huang, Wei, Shen and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Lina Wang, YXJpbmcyMDAwJiN4MDAwNDA7MTYzLmNvbQ==
†These authors have contributed equally to this work