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Article ; Online: Identification of high likelihood of dementia in population-based surveys using unsupervised clustering: a longitudinal analysis.

Gharbi-Meliani, Amin / Husson, François / Vandendriessche, Henri / Bayen, Eleonore / Yaffe, Kristine / Bachoud-Lévi, Anne-Catherine / Cleret de Langavant, Laurent

Alzheimer's research & therapy

2023 Volume 15, Issue 1, Page(s) 209

Abstract: Background: Dementia is defined as a cognitive decline that affects functional status. Longitudinal ageing surveys often lack a clinical diagnosis of dementia though measure cognition and daily function over time. We used unsupervised machine learning ... ...

Abstract	Background: Dementia is defined as a cognitive decline that affects functional status. Longitudinal ageing surveys often lack a clinical diagnosis of dementia though measure cognition and daily function over time. We used unsupervised machine learning and longitudinal data to identify transition to probable dementia. Methods: Multiple Factor Analysis was applied to longitudinal function and cognitive data of 15,278 baseline participants (aged 50 years and more) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) (waves 1, 2 and 4-7, between 2004 and 2017). Hierarchical Clustering on Principal Components discriminated three clusters at each wave. We estimated probable or "Likely Dementia" prevalence by sex and age, and assessed whether dementia risk factors increased the risk of being assigned probable dementia status using multistate models. Next, we compared the "Likely Dementia" cluster with self-reported dementia status and replicated our findings in the English Longitudinal Study of Ageing (ELSA) cohort (waves 1-9, between 2002 and 2019, 7840 participants at baseline). Results: Our algorithm identified a higher number of probable dementia cases compared with self-reported cases and showed good discriminative power across all waves (AUC ranged from 0.754 [0.722-0.787] to 0.830 [0.800-0.861]). "Likely Dementia" status was more prevalent in older people, displayed a 2:1 female/male ratio, and was associated with nine factors that increased risk of transition to dementia: low education, hearing loss, hypertension, drinking, smoking, depression, social isolation, physical inactivity, diabetes, and obesity. Results were replicated in ELSA cohort with good accuracy. Conclusions: Machine learning clustering can be used to study dementia determinants and outcomes in longitudinal population ageing surveys in which dementia clinical diagnosis is lacking.
MeSH term(s)	Humans ; Male ; Female ; Middle Aged ; Aged ; Longitudinal Studies ; Aging/psychology ; Cognitive Dysfunction/diagnosis ; Cognition ; Dementia/epidemiology ; Dementia/diagnosis
Language	English
Publishing date	2023-11-29
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
ZDB-ID	2506521-X
ISSN	1758-9193 ; 1758-9193
ISSN (online)	1758-9193
ISSN	1758-9193
DOI	10.1186/s13195-023-01357-9
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Article ; Online: Unsupervised Machine Learning to Identify High Likelihood of Dementia in Population-Based Surveys: Development and Validation Study.

Cleret de Langavant, Laurent / Bayen, Eleonore / Yaffe, Kristine

Journal of medical Internet research

2018 Volume 20, Issue 7, Page(s) e10493

Abstract: Background: Dementia is increasing in prevalence worldwide, yet frequently remains undiagnosed, especially in low- and middle-income countries. Population-based surveys represent an underinvestigated source to identify individuals at risk of dementia.!## ...

Abstract	Background: Dementia is increasing in prevalence worldwide, yet frequently remains undiagnosed, especially in low- and middle-income countries. Population-based surveys represent an underinvestigated source to identify individuals at risk of dementia. Objective: The aim is to identify participants with high likelihood of dementia in population-based surveys without the need of the clinical diagnosis of dementia in a subsample. Methods: Unsupervised machine learning classification (hierarchical clustering on principal components) was developed in the Health and Retirement Study (HRS; 2002-2003, N=18,165 individuals) and validated in the Survey of Health, Ageing and Retirement in Europe (SHARE; 2010-2012, N=58,202 individuals). Results: Unsupervised machine learning classification identified three clusters in HRS: cluster 1 (n=12,231) without any functional or motor limitations, cluster 2 (N=4841) with walking/climbing limitations, and cluster 3 (N=1093) with both functional and walking/climbing limitations. Comparison of cluster 3 with previously published predicted probabilities of dementia in HRS showed that it identified high likelihood of dementia (probability of dementia >0.95; area under the curve [AUC]=0.91). Removing either cognitive or both cognitive and behavioral measures did not impede accurate classification (AUC=0.91 and AUC=0.90, respectively). Three clusters with similar profiles were identified in SHARE (cluster 1: n=40,223; cluster 2: n=15,644; cluster 3: n=2335). Survival rate of participants from cluster 3 reached 39.2% (n=665 deceased) in HRS and 62.2% (n=811 deceased) in SHARE after a 3.9-year follow-up. Surviving participants from cluster 3 in both cohorts worsened their functional and mobility performance over the same period. Conclusions: Unsupervised machine learning identifies high likelihood of dementia in population-based surveys, even without cognitive and behavioral measures and without the need of clinical diagnosis of dementia in a subsample of the population. This method could be used to tackle the global challenge of dementia.
MeSH term(s)	Dementia/diagnosis ; Dementia/pathology ; Female ; Humans ; Longitudinal Studies ; Male ; Middle Aged ; Prevalence ; Unsupervised Machine Learning/trends ; Validation Studies as Topic
Language	English
Publishing date	2018-07-09
Publishing country	Canada
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2028830-X
ISSN	1438-8871 ; 1438-8871
ISSN (online)	1438-8871
ISSN	1438-8871
DOI	10.2196/10493
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Article ; Online: The direct health care cost to Medicare of Down syndrome dementia as compared with Alzheimer's disease among 2015 Californian beneficiaries.

Bayen, Eleonore / Yaffe, Kristine / Cleret de Langavant, Laurent / Chen, Yingjia / Possin, Katherine L

Annals of physical and rehabilitation medicine

2020 Volume 64, Issue 1, Page(s) 101430

Abstract: Background: Aging individuals with Down syndrome (DS) are at increased risk of dementia due to trisomy of chromosome 21 on which the amyloid precursor protein gene is located and with increased life expectancy. Yet, little is known about the costs ... ...

Abstract	Background: Aging individuals with Down syndrome (DS) are at increased risk of dementia due to trisomy of chromosome 21 on which the amyloid precursor protein gene is located and with increased life expectancy. Yet, little is known about the costs associated with DS dementia and how this compares to Alzheimer's disease (AD). Objective: To better understand direct healthcare costs and care consumption in DS dementia, we compared the total cost of care to US Medicare and the drivers of these medical expenditures in individuals with DS with and without dementia, and in those with AD without DS. Methods: The effect of dementia in DS on costs and care utilization was estimated with 2015 California Medicare fee-for-service data (parts A and B). Among 3,001,977 Californian Medicare beneficiaries, 353 individuals had DS with dementia (age 45-89 years). We compared their number of chronic comorbidity conditions among 27 and their care and Medicare costs to those of age- and sex-matched individuals with DS without dementia and those with AD without DS. Results: Medicare annual cost per beneficiary was a mean of 43.5% and 82.2% higher with DS dementia (mean $35,011) than DS without dementia (mean $24,401) and AD without dementia (mean $19,212), related to greater utilization of inpatient services. DS dementia was associated with increased level of multimorbidity (mean of 3.4 conditions in addition to dementia vs. 2.7 and 2.2 conditions for DS without dementia and AD, respectively), with more emergency room visits (88% vs. 76.5% and 54.4%) and with more primary care physician visits (91.2% vs. 87.3% and 81.3%). Conclusion: DS adults with dementia have higher health care costs than DS adults without dementia and adults with AD. Understanding costs and complex health care needs in DS dementia could facilitate management of adult and geriatric care resources for these high-need high-cost individuals.
MeSH term(s)	Aged ; Aged, 80 and over ; Alzheimer Disease/economics ; California ; Dementia/economics ; Dementia/etiology ; Down Syndrome/complications ; Down Syndrome/economics ; Fee-for-Service Plans ; Health Care Costs ; Humans ; Medicare/economics ; Middle Aged ; United States
Language	English
Publishing date	2020-10-15
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2480363-7
ISSN	1877-0665 ; 1877-0657
ISSN (online)	1877-0665
ISSN	1877-0657
DOI	10.1016/j.rehab.2020.07.011
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Article ; Online: Approximating dementia prevalence in population-based surveys of aging worldwide: An unsupervised machine learning approach.

Cleret de Langavant, Laurent / Bayen, Eléonore / Bachoud-Lévi, Anne-Catherine / Yaffe, Kristine

Alzheimer's & dementia (New York, N. Y.)

2020 Volume 6, Issue 1, Page(s) e12074

Abstract: Introduction: Ability to determine dementia prevalence in low- and middle-income countries (LMIC) remains challenging because of frequent lack of data and large discrepancies in dementia case ascertainment.: Methods: High likelihood of dementia was ... ...

Abstract	Introduction: Ability to determine dementia prevalence in low- and middle-income countries (LMIC) remains challenging because of frequent lack of data and large discrepancies in dementia case ascertainment. Methods: High likelihood of dementia was determined with hierarchical clustering after principal component analysis applied in 10 population surveys of aging: HRS (USA, 2014), SHARE (Europe and Israel, 2015), MHAS (Mexico, 2015), ELSI (Brazil, 2016), CHARLS (China, 2015), IFLS (Indonesia, 2014-2015), LASI (India, 2016), SAGE-Ghana (2007), SAGE-South Africa (2007), SAGE-Russia (2007-2010). We approximated dementia prevalence using weighting methods. Results: Estimated numbers of dementia cases were: China, 40.2 million; India, 18.0 million; Russia, 5.2 million; Europe and Israel, 5.0 million; United States, 4.4 million; Brazil, 2.2 million; Mexico, 1.6 million; Indonesia, 1.3 million; South Africa, 1.0 million; Ghana, 319,000. Discussion: Our estimations were similar to prior ones in high-income countries but much higher in LMIC. Extrapolating these results globally, we suggest that almost 130 million people worldwide were living with dementia in 2015.
Language	English
Publishing date	2020-08-27
Publishing country	United States
Document type	Journal Article
ZDB-ID	2832891-7
ISSN	2352-8737 ; 2352-8737
ISSN (online)	2352-8737
ISSN	2352-8737
DOI	10.1002/trc2.12074
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Article ; Online: The specific role of the striatum in interval timing: The Huntington's disease model.

Lemoine, Laurie / Lunven, Marine / Bapst, Blanche / Cleret de Langavant, Laurent / de Gardelle, Vincent / Bachoud-Lévi, Anne-Catherine

NeuroImage. Clinical

2021 Volume 32, Page(s) 102865

Abstract: Time processing over intervals of hundreds of milliseconds to minutes, also known as interval timing, is associated with the striatum. Huntington's disease patients (HD) with striatal degeneration have impaired interval timing, but the extent and ... ...

Abstract	Time processing over intervals of hundreds of milliseconds to minutes, also known as interval timing, is associated with the striatum. Huntington's disease patients (HD) with striatal degeneration have impaired interval timing, but the extent and specificity of these deficits remain unclear. Are they specific to the temporal domain, or do they extend to the spatial domain too? Do they extend to both the perception and production of interval timing? Do they appear before motor symptoms in Huntington's disease (Pre-HD)? We addressed these issues by assessing both temporal abilities (in the seconds range) and spatial abilities (in the cm range) in 20 Pre-HD, 25 HD patients, and 25 healthy Controls, in discrimination, bisection and production paradigms. In addition, all participants completed a questionnaire assessing temporal and spatial disorientation in daily life, and the gene carriers (i.e., HD and Pre-HD participants) underwent structural brain MRI. Overall, HD patients were more impaired in the temporal than in the spatial domain in the behavioral tasks, and expressed a greater disorientation in the temporal domain in the daily life questionnaire. In contrast, Pre-HD participants showed no sign of a specific temporal deficit. Furthermore, MRI analyses indicated that performances in the temporal discrimination task were associated with a larger striatal grey matter volume in the striatum in gene carriers. Altogether, behavioral, brain imaging and questionnaire data support the hypothesis that the striatum is a specific component of interval timing processes. Evaluations of temporal disorientation and interval timing processing could be used as clinical tools for HD patients.
MeSH term(s)	Brain ; Corpus Striatum/diagnostic imaging ; Gray Matter ; Humans ; Huntington Disease/genetics ; Neuropsychological Tests
Language	English
Publishing date	2021-10-27
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2701571-3
ISSN	2213-1582 ; 2213-1582
ISSN (online)	2213-1582
ISSN	2213-1582
DOI	10.1016/j.nicl.2021.102865
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Article ; Online: Mild encephalopathy with reversible splenial lesion: Description of nine cases and review of the literature.

Grosset, Lina / Hosseini, Hassan / Bapst, Blanche / Hodel, Jérôme / Cleret De Langavant, Laurent / Faugeras, Frédéric / Bachoud-Lévi, Anne-Catherine / Seddik, Lilia

Seizure

2021 Volume 88, Page(s) 83–86

Abstract: Mild encephalopathy/encephalitis with reversible splenial lesion (MERS) is a transient clinico-radiological syndrome characterized by non-specific encephalopathy and specific magnetic resonance imaging (MRI) pattern. MRI shows an ovoid lesion in the mid- ... ...

Abstract	Mild encephalopathy/encephalitis with reversible splenial lesion (MERS) is a transient clinico-radiological syndrome characterized by non-specific encephalopathy and specific magnetic resonance imaging (MRI) pattern. MRI shows an ovoid lesion in the mid-splenium of the corpus callosum (SCC), with signal-intensity anomaly similar to stroke but vanishing within few weeks. Although there are a lot of child MERS cases descriptions, there are just a few adult-onset reported. Our goal is to provide a better clinical and radiological description of this entity. We reported nine adult-onset cases of MERS managed in our stroke unit between 2017 and 2019. The study of our adult series suggests that epilepsy and the context of an infection are very common in MERS. Adult cases show frequent focal neurological deficits and few encephalopathies compared to children. The measurement of very low ADC values in SCC lesion is a new radiological feature of MERS that should be systematically assessed in suspected cases to differentiate this complex syndrome from SCC strokes.
MeSH term(s)	Adult ; Brain Diseases/complications ; Brain Diseases/diagnostic imaging ; Child ; Corpus Callosum/diagnostic imaging ; Encephalitis/complications ; Encephalitis/diagnostic imaging ; Humans ; Magnetic Resonance Imaging ; Stroke/complications ; Stroke/diagnostic imaging ; Syndrome
Language	English
Publishing date	2021-04-03
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	1137610-7
ISSN	1532-2688 ; 1059-1311
ISSN (online)	1532-2688
ISSN	1059-1311
DOI	10.1016/j.seizure.2021.03.032
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Article: Self-Reported Social Relationship Capacities Predict Motor, Functional and Cognitive Decline in Huntington's Disease.

Lemercier, Pablo / Cleret de Langavant, Laurent / Hamet Bagnou, Jennifer / Youssov, Katia / Lemoine, Laurie / Audureau, Etienne / Massart, Renaud / Bachoud-Lévi, Anne-Catherine

Journal of personalized medicine

2022 Volume 12, Issue 2

Abstract: Huntington's Disease (HD) is an inherited neurodegenerative disease characterized by a combination of motor, cognitive, and behavioral disorders. The social and behavioral symptoms observed in HD patients impact their quality of life and probably explain ...

Abstract	Huntington's Disease (HD) is an inherited neurodegenerative disease characterized by a combination of motor, cognitive, and behavioral disorders. The social and behavioral symptoms observed in HD patients impact their quality of life and probably explain their relational difficulties, conflicts, and social withdrawal. In this study, we described the development of the Social Relationship Self-Questionnaire (SRSQ), a self-reporting questionnaire that assesses how HD patients perceived their social relationships. The scale was proposed for 66 HD patients at an early stage of the disease, 32 PreHD patients (individuals carrying the mutant gene without motor symptoms), and 66 controls. The HD patients were included in a prospective longitudinal follow-up for an average of 1.07 years with motor, functional, cognitive, and behavioral assessments. Based on the HD patients' answers at baseline, we identified two domains in the SRSQ. The first domain was related to social motivation and correlated with cognitive performance. The second domain was related to emotional insight and correlated with behavioral symptoms such as apathy, anxiety, and irritability. We discovered that both SRSQ domain scores at baseline predicted future motor, functional, and cognitive decline in HD.
Language	English
Publishing date	2022-01-27
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662248-8
ISSN	2075-4426
ISSN	2075-4426
DOI	10.3390/jpm12020174
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Article ; Online: Annonaceae Consumption Worsens Disease Severity and Cognitive Deficits in Degenerative Parkinsonism.

Cleret de Langavant, Laurent / Roze, Emmanuel / Petit, Aimée / Tressières, Benoit / Gharbi-Meliani, Amin / Chaumont, Hugo / Michel, Patrick Pierre / Bachoud-Lévi, Anne-Catherine / Remy, Philippe / Edragas, Régine / Lannuzel, Annie

Movement disorders : official journal of the Movement Disorder Society

2022 Volume 37, Issue 12, Page(s) 2355–2366

Abstract: Background: High consumption of Annona muricata fruit has been previously identified as a risk factor for atypical parkinsonism in the French Caribbean islands.: Objective: We tested whether consumption of Annonaceae products could worsen the ... ...

Abstract	Background: High consumption of Annona muricata fruit has been previously identified as a risk factor for atypical parkinsonism in the French Caribbean islands. Objective: We tested whether consumption of Annonaceae products could worsen the clinical phenotype of patients with any form of degenerative parkinsonism. Methods: We analyzed neurological data from 180 Caribbean parkinsonian patients and specifically looked for dose effects of lifelong, cumulative Annonaceae consumption on cognitive performance. Using unsupervised clustering, we identified one cluster with mild/moderate symptoms (N = 102) and one with severe symptoms including cognitive impairment (N = 78). Results: We showed that even low cumulative consumption of fruits/juices (>0.2 fruit-years) or any consumption of herbal tea from Annonaceae worsen disease severity and cognitive deficits in degenerative parkinsonism including Parkinson's disease (OR fruits-juices: 3.76 [95% CI: 1.13-15.18]; OR herbal tea: 2.91 [95% CI: 1.34-6.56]). Conclusion: We suggest that more restrictive public health preventive recommendations should be made regarding the consumption of Annonaceae products. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
MeSH term(s)	Annonaceae/adverse effects ; Teas, Herbal ; Parkinsonian Disorders/complications ; Parkinsonian Disorders/epidemiology ; Patient Acuity ; Cognitive Dysfunction/complications ; Cognition
Chemical Substances	Teas, Herbal
Language	English
Publishing date	2022-10-10
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	607633-6
ISSN	1531-8257 ; 0885-3185
ISSN (online)	1531-8257
ISSN	0885-3185
DOI	10.1002/mds.29222
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Article ; Online: Predicting clinical scores in Huntington's disease: a lightweight speech test.

Riad, Rachid / Lunven, Marine / Titeux, Hadrien / Cao, Xuan-Nga / Hamet Bagnou, Jennifer / Lemoine, Laurie / Montillot, Justine / Sliwinski, Agnes / Youssov, Katia / Cleret de Langavant, Laurent / Dupoux, Emmanuel / Bachoud-Lévi, Anne-Catherine

Journal of neurology

2022 Volume 269, Issue 9, Page(s) 5008–5021

Abstract: Objectives: Using brief samples of speech recordings, we aimed at predicting, through machine learning, the clinical performance in Huntington's Disease (HD), an inherited Neurodegenerative disease (NDD).: Methods: We collected and analyzed 126 ... ...

Abstract	Objectives: Using brief samples of speech recordings, we aimed at predicting, through machine learning, the clinical performance in Huntington's Disease (HD), an inherited Neurodegenerative disease (NDD). Methods: We collected and analyzed 126 samples of audio recordings of both forward and backward counting from 103 Huntington's disease gene carriers [87 manifest and 16 premanifest; mean age 50.6 (SD 11.2), range (27-88) years] from three multicenter prospective studies in France and Belgium (MIG-HD (ClinicalTrials.gov NCT00190450); BIO-HD (ClinicalTrials.gov NCT00190450) and Repair-HD (ClinicalTrials.gov NCT00190450). We pre-registered all of our methods before running any analyses, in order to avoid inflated results. We automatically extracted 60 speech features from blindly annotated samples. We used machine learning models to combine multiple speech features in order to make predictions at individual levels of the clinical markers. We trained machine learning models on 86% of the samples, the remaining 14% constituted the independent test set. We combined speech features with demographics variables (age, sex, CAG repeats, and burden score) to predict cognitive, motor, and functional scores of the Unified Huntington's disease rating scale. We provided correlation between speech variables and striatal volumes. Results: Speech features combined with demographics allowed the prediction of the individual cognitive, motor, and functional scores with a relative error from 12.7 to 20.0% which is better than predictions using demographics and genetic information. Both mean and standard deviation of pause durations during backward recitation and clinical scores correlated with striatal atrophy (Spearman 0.6 and 0.5-0.6, respectively). Interpretation: Brief and examiner-free speech recording and analysis may become in the future an efficient method for remote evaluation of the individual condition in HD and likely in other NDD.
MeSH term(s)	Corpus Striatum ; Humans ; Huntington Disease/diagnosis ; Huntington Disease/genetics ; Middle Aged ; Neurodegenerative Diseases ; Prospective Studies ; Speech
Language	English
Publishing date	2022-05-14
Publishing country	Germany
Document type	Journal Article ; Multicenter Study
ZDB-ID	187050-6
ISSN	1432-1459 ; 0340-5354 ; 0012-1037 ; 0939-1517 ; 1619-800X
ISSN (online)	1432-1459
ISSN	0340-5354 ; 0012-1037 ; 0939-1517 ; 1619-800X
DOI	10.1007/s00415-022-11148-1
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Article ; Online: More than a third of middle-aged adults (50-65) have understated executive dysfunction.

Segaux, Lauriane / Oubaya, Nadia / Leissing-Desprez, Claire / Cleret De Langavant, Laurent / Broussier, Amaury / Naga, Henri / Fromentin, Isabelle / David, Jean-Philippe / Bastuji-Garin, Sylvie

Aging & mental health

2022 Volume 27, Issue 4, Page(s) 708–713

Abstract: Objectives: Understated executive dysfunction (UED) is predictive of cognitive decline and death. We aimed to assess the prevalence of UED, assessed with the clock-drawing test (CDT) and the Frontal Assessment Battery (FAB) in middle-aged adults and to ... ...

Abstract	Objectives: Understated executive dysfunction (UED) is predictive of cognitive decline and death. We aimed to assess the prevalence of UED, assessed with the clock-drawing test (CDT) and the Frontal Assessment Battery (FAB) in middle-aged adults and to investigate associated characteristics. Methods: Cross-sectional analysis of data on 516 community-dwellers aged 50-65, lacking cognitive complaints, who were included prospectively (2010-2017) after a multidimensional geriatric assessment at a "healthy ageing" outpatient clinic. Age- and educational-level-adjusted logistic models were used to assess factors associated with UED. Results: The CDT and FAB were impaired in 27.7% and 14.7% of the participants (median age: 59.7 years). The prevalence [95% confidence interval (CI)] of UED was 36.2% [32.2-40.5%]. After adjustment for age and education, participants with UED were more likely to be obese (odds ratio [95%CI] = 1.89 [1.12-3.19], Conclusion: More than one third of middle-aged adults without cognitive complaints have UED, which was linked to obesity and metabolic syndrome. Cognitive screening tests targeting executive functions might be useful for early detection of UED and the initiation of multidomain interventions improving cognitive performance.
MeSH term(s)	Humans ; Middle Aged ; Aged ; Metabolic Syndrome ; Cross-Sectional Studies ; Cognitive Dysfunction/epidemiology ; Cognitive Dysfunction/diagnosis ; Cognition ; Executive Function ; Neuropsychological Tests
Language	English
Publishing date	2022-03-04
Publishing country	England
Document type	Journal Article
ZDB-ID	1474804-6
ISSN	1364-6915 ; 1360-7863
ISSN (online)	1364-6915
ISSN	1360-7863
DOI	10.1080/13607863.2022.2046696
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