Cited by 368Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsCerebrospinal fluid and hydrocephalus

The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.

Accuracy of Brain Amyloid Detection in Clinical Practice Using Cerebrospinal Fluid β-Amyloid 42: A Cross-Validation Study Against Amyloid Positron Emission Tomography

Palmqvist, Sebastian, Zetterberg, Henrik, Blennow, Kaj, Vestberg, Susanna, Andreasson, Ulf, Brooks, David J., Owenius, Rikard, Hägerström, Douglas, Wollmer, Per, Minthon, Lennart, Hansson, Oskar·2014·JAMA Neurology

DOI 10.1001/jamaneurol.2014.1358

Open this paper in CoChat — free account

Abstract

IMPORTANCE: Before adding cerebrospinal fluid (CSF) biomarkers to the diagnostic workup of Alzheimer disease, it needs to be determined whether CSF biomarkers analyzed in routine clinical practice can reliably predict cortical β-amyloid (Aβ) deposition. OBJECTIVES: To study whether CSF biomarkers, analyzed consecutively in routine clinical practice during 2 years, can predict cortical Aβ deposition and to establish a threshold for Aβ42 abnormality. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study (The Swedish BioFINDER [Biomarkers For Identifying Neurodegenerative Disorders Early and Reliably] Study) was conducted at 3 memory clinics. It involved consecutively referred, nondemented patients with mild cognitive symptoms (original cohort, n = 118; validation cohort, n = 38). EXPOSURES: Amyloid positron emission tomography imaging with 18F-flutemetamol. MAIN OUTCOMES AND MEASURES: Analyses of CSF Aβ42, total tau, and phosphorylated tau using an enzyme-linked immunosorbent assay (INNOTEST) in clinical samples. RESULTS: The agreement between Aβ classification with CSF Aβ42 and 18F-flutemetamol positron emission tomography was very high (κ = 0.85). Of all the cases, 92% were classified identically using an Aβ42 cutoff of 647 pg/mL or less. Cerebrospinal fluid Aβ42 predicted abnormal cortical Aβ deposition accurately (odds ratio, 165; 95% CI, 39-693; area under the receiver operating characteristic curve, 0.94; 95% CI, 0.88-0.97). The association was independent of age, sex, APOE (apolipoprotein E) genotype, hippocampal volume, memory, and global cognition (adjusted odds ratio, 169; 95% CI, 25-1143). Using ratios of CSF Aβ42:tau or Aβ42:phosphorylated tau did not improve the prediction of Aβ deposition. Cerebrospinal fluid Aβ42 correlated significantly with Aβ deposition in all cortical regions. The highest correlations were in regions with high 18F-flutemetamol retention (eg, posterior cingulum and precuneus, r = -0.72). 18F-flutemetamol retention, but not CSF Aβ42, correlated significantly with global cognition (r = -0.32), memory function (r = -0.28), and hippocampal volume (r = -0.36) among those with abnormal Aβ deposition. Finally, the CSF Aβ42 cutoff derived from the original cohort (≤647 pg/mL) had an equally high agreement (95%; κ = 0.89) with 18F-flutemetamol positron emission tomography in the validation cohort. CONCLUSIONS AND RELEVANCE: Cerebrospinal fluid Aβ42 analyzed consecutively in routine clinical practice at an accredited laboratory can be used with high accuracy to determine whether a patient has normal or increased cortical Aβ deposition and so can be valuable for the early diagnosis of Alzheimer disease. Abnormal 18F-flutemetamol retention levels correlate with disease stage in patients with mild cognitive symptoms, but this is not the case for CSF Aβ42 measurements.

Integrity signals

Registry

Crossref · 10.1001/jamaneurol.2014.1358

Cites

48 of 48 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

“Mini-mental state”
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
Practical Statistics for Medical Research.
Walter, S., & Altman, D. G. (1992) · Biometrics · doi:10.2307/2532320 · Cited by 11,666
Practical Statistics for Medical Research
Altman, D. G. (1990) · doi:10.1201/9780429258589 · Cited by 10,668
Measuring agreement in method comparison studies
Bland, J. M., & Altman, D. G. (1999) · Statistical Methods in Medical Research · doi:10.1177/096228029900800204 · Cited by 9,619
Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade
Jack, C. R., Knopman, D. S., Jagust, W. J., Shaw, L. M., Aisen, P. S., Weiner, M. W., Petersen, R. C., & Trojanowski, J. Q. (2010) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70299-6 · Cited by 4,806
Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound‐B
Klunk, W. E., Engler, H., Nordberg, A., Wang, Y., Blomqvist, G., Holt, D. P., Bergström, M., Savitcheva, I., Huang, G., Estrada, S., et al. (2004) · Annals of Neurology · doi:10.1002/ana.20009 · Cited by 4,496
Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer's disease: a prospective cohort study
Villemagne, V. L., Burnham, S., Bourgeat, P., Brown, B., Ellis, K. A., Salvado, O., Szoeke, C., Macaulay, S. L., Martins, R., Maruff, P., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70044-9 · Cited by 2,279
Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects
Shaw, L. M., Vanderstichele, H., Knapik‐Czajka, M., Clark, C. M., Aisen, P. S., Petersen, R. C., Blennow, K., Soares, H., Simon, A., Lewczuk, P., et al. (2009) · Annals of Neurology · doi:10.1002/ana.21610 · Cited by 2,065
Self-citation
Cerebrospinal fluid and plasma biomarkers in Alzheimer disease
Blennow, K., Hampel, H., Weiner, M., & Zetterberg, H. (2010) · Nature Reviews Neurology · doi:10.1038/nrneurol.2010.4 · Cited by 1,863
Self-citation
A New Biometrical Procedure for Testing the Equality of Measurements from Two Different Analytical Methods. Application of linear regression procedures for method comparison studies in Clinical Chemistry, Part I
Passing, H., & Bablok, W. (1983) · cclm · doi:10.1515/cclm.1983.21.11.709 · Cited by 1,513

Flagged first, then by citations

Show all 48 references

Sorted by citations

Items 201–300 of 368

Cerebrospinal Fluid Progranulin, but Not Serum Progranulin, Is Reduced in GRN-Negative Frontotemporal Dementia
Wilke, C., Gillardon, F., Deuschle, C., Hobert, M. A., Jansen, I. E., Metzger, F. G., Heutink, P., Gasser, T., Maetzler, W., Blauwendraat, C., et al. (2016) · Neurodegenerative Diseases · doi:10.1159/000448896 · Cited by 29
APOE4 impact on soluble and insoluble tau pathology is mostly influenced by amyloid-β
Cicognola, C., Salvadó, G., Smith, R. A., Palmqvist, S., Stomrud, E., Betthauser, T. J., Johnson, S. C., Janelidze, S., Mattsson, N., Hansson, O., et al. (2025) · Brain · doi:10.1093/brain/awaf016 · Cited by 31
Self-citation
Age-Related Tau Burden and Cognitive Deficits Are Attenuated in KLOTHO KL-VS Heterozygotes
Driscoll, I. F., Ma, Y., Gallagher, C. L., Johnson, S. C., Asthana, S., Hermann, B. P., Sager, M. A., Blennow, K., Zetterberg, H., Carlsson, C. M., et al. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-200944 · Cited by 28
Self-citation
Multianalyte Nanopore Detection of Alzheimer's Disease Biomarkers: A Label‐Free Platform with Improved Sensitivity and Range
Liu, Q., Ouyang, Y., Wang, Y., Zhou, S., Zhan, Y., & Wang, L. (2025) · Advanced Healthcare Materials · doi:10.1002/adhm.202405058 · Cited by 29
Neuroimmune nexus of depression and dementia: Shared mechanisms and therapeutic targets
Herman, F. J., Simkovic, S. J., & Pasinetti, G. M. (2019) · British Journal of Pharmacology · doi:10.1111/bph.14569 · Cited by 29
The age-related effect on cognitive performance in cognitively healthy elderly is mainly caused by underlying AD pathology or cerebrovascular lesions: implications for cutoffs regarding cognitive impairment
Borland, E., Stomrud, E., van Westen, D., Hansson, O., & Palmqvist, S. (2020) · Alzheimer s Research & Therapy · doi:10.1186/s13195-020-00592-8 · Cited by 27
Self-citation
Cerebral hypoperfusion is not associated with an increase in amyloid β pathology in middle‐aged or elderly people
Hansson, O., Palmqvist, S., Ljung, H., Cronberg, T., van Westen, D., & Smith, R. A. (2017) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2017.06.2265 · Cited by 28
Self-citation
Reduced binding of apoE4 to complement factor H promotes amyloid‐β oligomerization and neuroinflammation
Chernyaeva, L., Ratti, G., Teirilä, L., Fudo, S., Rankka, U., Pelkonen, A., Korhonen, P., Leskinen, K., Keskitalo, S., Salokas, K., et al. (2023) · EMBO Reports · doi:10.15252/embr.202256467 · Cited by 29
Cerebrospinal Fluid Levels of Amyloid Beta 1-43 Mirror 1-42 in Relation to Imaging Biomarkers of Alzheimer’s Disease
Almdahl, I. S., Lauridsen, C., Selnes, P., Kalheim, L. F., Coello, C. S., Gajdzik, B., Møller, I., Wettergreen, M., Grambaitė, R., Bjørnerud, A., et al. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00009 · Cited by 27
Association of Hippocampal Subfields, CSF Biomarkers, and Cognition in Patients With Parkinson Disease Without Dementia
Becker, S., Granert, O., Timmers, M., Pilotto, A., Nueten, L. V., Röeben, B., Salvadore, G., Galpern, W. R., Streffer, J. R., Scheffler, K., et al. (2020) · Neurology · doi:10.1212/wnl.0000000000011224 · Cited by 26
The relationship between white matter microstructure and self-perceived cognitive decline
Archer, D. B., Moore, E. E., Pamidimukkala, U., Shashikumar, N., Pechman, K. R., Blennow, K., Zetterberg, H., Landman, B. A., Hohman, T. J., Jefferson, A. L., et al. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102794 · Cited by 26
Self-citation
Parkinson’s disease: evolution of cognitive impairment and CSF Aβ1–42 profiles in a prospective longitudinal study
Lerche, S., Wurster, I., Röeben, B., Machetanz, G., Zimmermann, M., Bernhard, F. P., Stransky, E., Deuschle, C., Schulte, C., Hansson, O., et al. (2018) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2018-318956 · Cited by 26
Self-citation
The effect of diagnostic criteria on outcome measures in preclinical and prodromal Alzheimer's disease: Implications for trial design
Bertens, D., Tijms, B. M., Vermunt, L., Prins, N. D., Scheltens, P., Visser, P. J., & Initiative, A. D. N. (2017) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1016/j.trci.2017.08.005 · Cited by 26
Analytical and Clinical Performance of Amyloid-Beta Peptides Measurements in CSF of ADNIGO/2 Participants by an LC–MS/MS Reference Method
Korecka, M., Figurski, M., Landau, S. M., Brylska, M., Alexander, J., Blennow, K., Zetterberg, H., Jagust, W., Trojanowski, J. Q., Shaw, L. M. J., et al. (2020) · Clinical Chemistry · doi:10.1093/clinchem/hvaa012 · Cited by 25
Self-citation
Β-Amyloid Burden is Not Associated with Cognitive Impairment in Schizophrenia: A Systematic Review
Chung, J. K., Nakajima, S., Plitman, E., Iwata, Y., Uy, D., Gerretsen, P., Caravaggio, F., Chakravarty, M. M., & Graff‐Guerrero, A. (2016) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2016.03.013 · Cited by 24
The Effects of Tau, Amyloid, and White Matter Lesions on Mobility, Dual Tasking, and Balance in Older People
Nilsson, M. H., Tangen, G. G., Palmqvist, S., van Westen, D., Mattsson, N., Stomrud, E., & Hansson, O. (2020) · The Journals of Gerontology Series A · doi:10.1093/gerona/glaa143 · Cited by 25
Self-citation
A multinational study distinguishing Alzheimer's and healthy patients using cerebrospinal fluid tau/Aβ42 cutoff with concordance to amyloid positron emission tomography imaging
Yi, M., Stromswold, J., Wilson, K., Holder, D., Sur, C., Laterza, O., Savage, M. J., Struyk, A. F., Scheltens, P., Teunissen, C. E., et al. (2017) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2017.02.004 · Cited by 23
How Accurately Do Patients and Their Care Partners Report Results of Amyloid-β PET Scans for Alzheimer’s Disease Assessment?
James, H. J., Houtven, C. H. V., Lippmann, S., Burke, J. R., Shepherd‐Banigan, M. E., Bélanger, E., Wetle, T. F., & Plassman, B. L. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-190922 · Cited by 23
Network Connectivity Determines Cortical Thinning In Early Parkinson’s Disease ProgressionPreprint
Yau, Y., Zeighami, Y., Baker, T. E., Larcher, K., Vainik, U., Dadar, M., Fonov, V., Hagmann, P., Griffa, A., Mišić, B., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/147611 · Cited by 24
18F‐Florbetaben PET/CT to Assess Alzheimer's Disease: A new Analysis Method for Regional Amyloid Quantification
Alongi, P., Sardina, D. S., Coppola, R., Scalisi, S., Puglisi, V., Arnone, A., Raimondo, G. D., Munerati, E., Alaimo, V., Midiri, F., et al. (2019) · Journal of Neuroimaging · doi:10.1111/jon.12601 · Cited by 23
Higher levels of neurofilament light chain and total tau in CSF are associated with negative outcome after shunt surgery in patients with normal pressure hydrocephalus
Braun, M., Bjurnemark, C., Seo, W., Freyhult, E., Nyholm, D., Niemelä, V., Blennow, K., Zetterberg, H., Fällmar, D., Kultima, K., et al. (2022) · Fluids and Barriers of the CNS · doi:10.1186/s12987-022-00306-2 · Cited by 22
Self-citation
Central and Peripheral Inflammation in Mild Cognitive Impairment in the Context of Alzheimer’s Disease
Schmidt-Morgenroth, I., Michaud, P., Gasparini, F., & Avraméas, A. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241310523 · Cited by 26
Investigating hypotheses of neurodegeneration by learning dynamical systems of protein propagation in the brain
Garbarino, S., & Lorenzi, M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117980 · Cited by 27
Evaluation of cerebrospinal fluid glycoprotein NMB (GPNMB) as a potential biomarker for Alzheimer’s disease
Aichholzer, F., Klafki, H., Ogorek, I., Vogelgsang, J. S., Wiltfang, J., Scherbaum, N., Weggen, S., & Wirths, O. (2021) · Alzheimer s Research & Therapy · doi:10.1186/s13195-021-00828-1 · Cited by 23
Blood-based CNS regionally and neuronally enriched extracellular vesicles carrying pTau217 for Alzheimer’s disease diagnosis and differential diagnosis
Guo, Z., Tian, C., Shi, Y., Song, X., Yin, W., Tao, Q., Liu, J., Peng, G.-P., Wu, Z., Wang, Y., et al. (2024) · Acta Neuropathologica Communications · doi:10.1186/s40478-024-01727-w · Cited by 23
Comparative Analysis of Different Definitions of Amyloid-β Positivity to Detect Early Downstream Pathophysiological Alterations in Preclinical Alzheimer
Milà‐Alomà, M., Salvadó, G., Shekari, M., Grau‐Rivera, O., Sala‐Vila, A., Sánchez‐Benavides, G., Arenaza‐Urquijo, E. M., Gónzalez‐de‐Echávarri, J. M., Simon, M., Kollmorgen, G., et al. (2021) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2020.51 · Cited by 22
Self-citation
CSF placental growth factor – a novel candidate biomarker of frontotemporal dementia
Hansson, O., Santillo, A. F., Meeter, L. H. H., Nilsson, K. H., Waldö, M. L., Nilsson, C., Blennow, K., Swieten, J. C. V., & Janelidze, S. (2019) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.763 · Cited by 20
Self-citation
Clinic-Based Validation of Cerebrospinal Fluid Biomarkers with Florbetapir PET for Diagnosis of Dementia
Álvarez, I., Aguilar, M., González, J. M., Ysamat, M., Lorenzo‐Bosquet, C., Alonso, Á., Tartari, J. P., Romero, S. P. Z., Díez-Fairén, M., Cárcel, M., et al. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-170753 · Cited by 19
Derivation and utility of an Aβ-PET pathology accumulation index to estimate Aβ load
Leuzy, A., Lilja, J., Buckley, C. J., Ossenkoppele, R., Palmqvist, S., Battle, M. R., Farrar, G., Thal, D. R., Janelidze, S., Stomrud, E., et al. (2020) · Neurology · doi:10.1212/wnl.0000000000011031 · Cited by 20
Self-citation
Benchmarking biomarker‐based criteria for Alzheimer's disease: Data from the Swedish Dementia Registry, SveDem
Rosén, C., Farahmand, B. Y., Skillbäck, T. B., Nägga, K., Mattsson, N., Kilander, L., Religa, D., Wimo, A. B., Blennow, K., Winblad, B. G., et al. (2015) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2015.04.007 · Cited by 20
Self-citation
[ 18 F]-Flutemetamol Uptake in Cortex and White Matter: Comparison with Cerebrospinal Fluid Biomarkers and [ 18 F]-Fludeoxyglucose
Kalheim, L. F., Fladby, T., Coello, C. S., Bjørnerud, A., & Selnes, P. (2018) · Journal of Alzheimer s Disease · doi:10.3233/jad-170582 · Cited by 20
The pathway to secondary prevention of Alzheimer's disease
McDade, E., Bednar, M. M., Brashear, H. R., Miller, D. S., Maruff, P., Randolph, C., Ismail, Z., Carrillo, M. C., Weber, C. J., Bain, L. J., et al. (2020) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1002/trc2.12069 · Cited by 20
Using florbetapir positron emission tomography to explore cerebrospinal fluid cut points and gray zones in small sample sizes
Weston, P. S. J., Paterson, R. W., Marc Modat, A., Burgos, N., Cardoso, M. J., Magdalinou, N. K., Lehmann, M., Dickson, J. C., Barnes, A., Bomanji, J. B., et al. (2015) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2015.10.001 · Cited by 19
Self-citation
Are neuropsychiatric symptoms in dementia linked to CSF biomarkers of synaptic and axonal degeneration?
Bloniecki, V., Zetterberg, H., Aarsland, D., Vannini, P., Kvartsberg, H., Winblad, B. G., Blennow, K., & Freund‐Levi, Y. (2020) · Alzheimer s Research & Therapy · doi:10.1186/s13195-020-00718-y · Cited by 21
Self-citation
Impact of cerebrospinal fluid matrix on the detection of Alzheimer's disease with Aβ42 and influence of disease on the total‐Aβ42/Aβ40 ratio
Slemmon, J. R., Shapiro, A., Mercken, M. H., Streffer, J. R., Romano, G. J., Andreasen, N., Zetterberg, H., & Blennow, K. (2015) · Journal of Neurochemistry · doi:10.1111/jnc.13297 · Cited by 20
Self-citation
The supersaturation perspective on the amyloid hypothesis
Barron, D. P., & Guo, Z. (2023) · Chemical Science · doi:10.1039/d3sc03981a · Cited by 18
Reduced Levels of Cerebrospinal Fluid/Plasma Aβ40 as an Early Biomarker for Cerebral Amyloid Angiopathy in RTg-DI Rats
Zhu, X. A., Xu, F., Hoos, M. D., Lee, H., Benveniste, H., & Nostrand, W. E. V. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21010303 · Cited by 18
Millipore xMap® Luminex (HATMAG-68K): An Accurate and Cost-Effective Method for Evaluating Alzheimer's Biomarkers in Cerebrospinal Fluid
Hansen, É. D. O., Dias, N. S., Burgos, I. C. B., Costa, M. V., Teixeira‐Carvalho, A., Teixeira, A. L., Barbosa, I. G., dos Santos, L. A. V., Rosa, D. V., Ribeiro, A. J. F., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.716686 · Cited by 19
β-Amyloid–Dependent and –Independent Genetic Pathways Regulating CSF Tau Biomarkers in Alzheimer Disease
Kumar, A., Janelidze, S., Stomrud, E., Palmqvist, S., Hansson, O., Mattsson, N., & Initiative, A. D. N. (2022) · Neurology · doi:10.1212/wnl.0000000000200605 · Cited by 17
Self-citation
Cerebrospinal Fluid Biomarkers for Alzheimer Disease Among Patients With Dementia
Skillbäck, T. B., Jönsson, L., Skoog, I. G., Blennow, K., Eriksdotter, M., Zetterberg, H., & Kern, S. (2025) · JAMA Neurology · doi:10.1001/jamaneurol.2025.0693 · Cited by 18
Self-citation
Correcting for the Absence of a Gold Standard Improves Diagnostic Accuracy of Biomarkers in Alzheimer’s Disease
Coart, E., Barrado, L. G., Duits, F. H., Scheltens, P., van der Flier, W. M., Teunissen, C. E., van der Vies, S. M., Burzykowski, T., & Initiative, A. D. N. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-142886 · Cited by 17
Low Cerebrospinal Fluid Aβ 42 and Aβ 40 are Related to White Matter Lesions in Cognitively Normal Elderly
Skoog, I. G., Kern, S., Zetterberg, H., Östling, S., Börjesson‐Hanson, A., Guo, X., & Blennow, K. (2018) · Journal of Alzheimer s Disease · doi:10.3233/jad-170950 · Cited by 18
Self-citation
Comparative evaluation of two immunoassays for cerebrospinal fluid β-Amyloid1–42 measurement
Zecca, C., Brescia, V., Piccininni, M., Capozzo, R., Barone, R., Barulli, M. R., & Logroscino, G. (2019) · Clinica Chimica Acta · doi:10.1016/j.cca.2019.02.033 · Cited by 16
Health utility in preclinical and prodromal Alzheimer's disease for establishing the value of new disease‐modifying treatments—EQ‐5D data from the Swedish BioFINDER study
Gustavsson, A., Rakêt, L. L., Lilja, M., Rutten‐Jacobs, L. C. A., Wahl, H. F., Bagijn, M., Stomrud, E., Hansson, O., & Palmqvist, S. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12355 · Cited by 15
Self-citation
Posterior atrophy predicts time to dementia in patients with amyloid-positive mild cognitive impairment
Initiative, T. A. D. N., Pyun, J.-M., Park, Y. H., Kim, H.-R., Suh, J., Kang, M. J., Kim, B. J., Youn, Y. C., Jang, J.-W., & Kim, S. (2017) · Alzheimer s Research & Therapy · doi:10.1186/s13195-017-0326-y · Cited by 14
Biomarker-related phospho-tau217 appears in synapses around Aβ plaques prior to tau tangle in cerebral cortex of preclinical Alzheimer’s disease
Hirota, Y., Sakakibara, Y., Morishima, M., Sano, T., Hara, M., Arakawa, A., Takao, M., Murayama, S., Saito, Y., Sekiya, M., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116203 · Cited by 15
Distributions of Aβ42 and Aβ42/40 in the Cerebrospinal Fluid in View of the Probability Theory
Lewczuk, P., Wiltfang, J., Kornhuber, J., & Verhasselt, A. (2021) · Diagnostics · doi:10.3390/diagnostics11122372 · Cited by 13
Recent advances in pre-clinical diagnosis of Alzheimer’s disease
Zhou, J., Benoit, M., & Sharoar, M. G. (2021) · Metabolic Brain Disease · doi:10.1007/s11011-021-00733-4 · Cited by 14
PRESS-based EFOR algorithm for the dynamic parametrical modeling of nonlinear MDOF systems
Liu, H., Zhu, Y., Luo, Z., & Han, Q. (2017) · Frontiers of Mechanical Engineering · doi:10.1007/s11465-017-0459-5 · Cited by 12
Cerebrospinal fluid in the dementias
Zetterberg, H., Rohrer, J. D., & Schott, J. M. (2017) · Handbook of clinical neurology · doi:10.1016/b978-0-12-804279-3.00006-x · Cited by 13
Self-citation
Effects of long-term sleep disruption on cognitive function and brain amyloid-β burden: a case-control study
Thomas, J., Ooms, S. J., Mentink, L. J., Booij, J., Rikkert, M. G. M. O., Overeem, S., Kessels, R. P. C., & Claassen, J. A. H. R. (2020) · Alzheimer s Research & Therapy · doi:10.1186/s13195-020-00668-5 · Cited by 13
Cytokines as Potential Biomarkers of Parkinson Disease
Alcalay, R. N. (2016) · JAMA Neurology · doi:10.1001/jamaneurol.2016.3335 · Cited by 12
Mild Cognitive Impairment Staging Yields Genetic Susceptibility, Biomarker, and Neuroimaging Differences
Moore, E. E., Liu, D., Pechman, K. R., Acosta, L. M. Y., Bell, S. P., Davis, L. T., Blennow, K., Zetterberg, H., Landman, B. A., Schrag, M., et al. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.00139 · Cited by 11
Self-citation
Cerebrospinal fluid biomarkers of axonal and synaptic degeneration in a population-based sample
Rådestig, M. A., Skoog, I. G., Skillbäck, T. B., Zetterberg, H., Kern, J., Zettergren, A., Andréasson, U., Wetterberg, H., Kern, S., & Blennow, K. (2023) · Alzheimer s Research & Therapy · doi:10.1186/s13195-023-01193-x · Cited by 11
Self-citation
Amyloid hypothesis through the lens of Aβ supersaturation
Guo, Z. (2021) · Neural Regeneration Research · doi:10.4103/1673-5374.303021 · Cited by 11
Decreased plasma nicotinamide and altered NAD+ metabolism in glial cells surrounding Aβ plaques in a mouse model of Alzheimer's disease
Sekiya, M., Sakakibara, Y., Hirota, Y., Ito, N., Chikamatsu, S., Takei, K., Nishijima, R., & Iijima, K. (2024) · Neurobiology of Disease · doi:10.1016/j.nbd.2024.106694 · Cited by 10
Biomarkers for Alzheimer’s disease across diverse biological domains: an umbrella review and evidence map
Kang, J., Son, Y., Yim, Y., Cho, H., Kim, J., Lark, A. R. S., Mir, F. A., Kim, H. J., Park, J., Lee, H., et al. (2025) · Journal of Advanced Research · doi:10.1016/j.jare.2025.07.022 · Cited by 10
Coexistence of Amyotrophic Lateral Sclerosis and Alzheimer’s Disease: Case Report and Review of the Literature
Verde, F., Aiello, E. N., Adobbati, L., Poletti, B., Solca, F., Tiloca, C., Sangalli, D., Maranzano, A., Muscio, C., Ratti, A., et al. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-230562 · Cited by 10
Characterization of Cerebrospinal Fluid BACE1 Species
López‐Font, I., Boix, C. P., Zetterberg, H., Blennow, K., & Sáez‐Valero, J. (2019) · Molecular Neurobiology · doi:10.1007/s12035-019-01677-8 · Cited by 10
Self-citation
Altered Balance of Reelin Proteolytic Fragments in the Cerebrospinal Fluid of Alzheimer’s Disease Patients
López‐Font, I., Lennol, M. P., Iborra‐Lázaro, G., Zetterberg, H., Blennow, K., & Sáez‐Valero, J. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23147522 · Cited by 11
Self-citation
Association of IL1RAP-related genetic variation with cerebrospinal fluid concentration of Alzheimer-associated tau protein
Zettergren, A., Höglund, K., Kern, S., Thorvaldsson, V., Skoog, J., Hansson, O., Andreasen, N., Bogdanović, N., Blennow, K., Skoog, I. G., et al. (2019) · Scientific Reports · doi:10.1038/s41598-018-36650-3 · Cited by 11
Self-citation
Aβ status assessment in a hypothetical scenario prior to treatment with disease‐modifying therapies: Evidence from 10‐year real‐world experience at university memory clinics
Brendel, M., Parvizi, T., Gnörich, J. S., Topfstedt, C. E., Büerger, K., Janowitz, D., Rauchmann, B., Perneczky, R., Kurz, C., Mehrens, D., et al. (2024) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.70031 · Cited by 13
Decreased serum PF4 levels correlate with cognitive decline and CSF biomarkers in Alzheimer's disease in a Chinese cohort
Sun, H., Chen, D., Ma, Y.-Y., Liu, B., Wang, J., Lai, Y., Zeng, G., Shen, Y., Tan, C., Bu, X., et al. (2025) · Experimental Gerontology · doi:10.1016/j.exger.2025.112689 · Cited by 9
The Role of Cerebrospinal Fluid Biomarkers in the Evolution of Diagnostic Criteria in Alzheimer’s Disease: Shortcomings in Prodromal Diagnosis
Szalárdy, L., Zádori, D., Klivènyi, P., & Vécsei, L. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160037 · Cited by 10
The 12-Word Philadelphia Verbal Learning Test Performances in Older Adults: Brain MRI and Cerebrospinal Fluid Correlates and Regression-Based Normative Data
Gifford, K. A., Liu, D., Neal, J. E., Babicz, M. A., Thompson, J. L., Walljasper, L., Wiggins, M. E., Turchan, M., Pechman, K. R., Osborn, K. E., et al. (2018) · Dementia and Geriatric Cognitive Disorders Extra · doi:10.1159/000494209 · Cited by 9
Self-citation
Dissecting the Structural Organization of Multiprotein Amyloid Aggregates Using a Bottom-Up Approach
Chaudhary, H., Meister, S. W., Zetterberg, H., Löfblom, J., & Lendel, C. (2020) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.0c00110 · Cited by 9
Self-citation
CCCDTD5: Clinical role of neuroimaging and liquid biomarkers in patients with cognitive impairment
Brisson, M., Brodeur, C., Guillon, L. L., Masellis, M., Stoessl, A. J., Tamm, A., Zukotynski, K., Ismail, Z., Gauthier, S. G., Rosa‐Neto, P., et al. (2020) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12098 · Cited by 9
How far is the goal of applying β-amyloid in cerebrospinal fluid for clinical diagnosis of Alzheimer’s disease with standardization of measurements?
Zou, Y., Yu, S., Ma, X., Ma, C., Mao, C., Mu, D., Li, L., Gao, J., & Qiu, L. (2022) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2022.11.013 · Cited by 9
Contribution of clinical information to the predictive performance of plasma β-amyloid levels for amyloid positron emission tomography positivity
Chun, M. Y., Jang, H., Kim, H. J., Kim, J. P., Gallacher, J., Allué, J. A., Sarasa, L., Castillo, S., Pascual‐Lucas, M., Na, D. L., et al. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2023.1126799 · Cited by 9
Protofibrillar and Fibrillar Amyloid-β Binding Proteins in Cerebrospinal Fluid
Rahman, M. M., Westermark, G. T., Zetterberg, H., Härd, T., & Sandgren, M. (2018) · Journal of Alzheimer’s Disease · doi:10.3233/jad-180596 · Cited by 9
Self-citation
Standardized Procedures for Blood and Cerebrospinal Fluid Collection and Storage in Neurodegenerative Biomarker Research: A Comprehensive Review
Kwon, H. S., Kim, G. H., Park, S. A., Moon, S. Y., Jang, J., Park, K. H., Park, Y. H., Lim, J., Yang, D. W., Choi, S. H., et al. (2025) · Dementia and Neurocognitive Disorders · doi:10.12779/dnd.2025.24.3.162 · Cited by 9
Zooming into Disease at the Nanoscale: High-Speed Atomic Force Microscopy in Biomedical Discovery
Lim, K., & Wong, R. W.-C. (2026) · ACS Nano · doi:10.1021/acsnano.5c20737 · Cited by 8
The Frontal Assessment Battery (FAB) effectively discriminates between MCI and dementia within the clinical spectrum of neurochemically confirmed Alzheimer’s disease
Aiello, E. N., Verde, F., Milone, I., Grigoli, E. G., Dubini, A., Carelli, L., Ferrucci, R., Priori, A., Ratti, A., Torresani, E., et al. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.1054321 · Cited by 8
AD‐associated CSF biomolecular changes are attenuated in KL‐VS heterozygotes
Driscoll, I. F., Ma, Y., Lose, S. R., Gallagher, C. L., Johnson, S. C., Asthana, S., Hermann, B. P., Sager, M. A., Blennow, K., Zetterberg, H., et al. (2022) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12383 · Cited by 8
Self-citation
Through the eyes into the brain, using artificial intelligence
Sathianvichitr, K., Lamoureux, O., Nakada, S., Tang, Z., Schmetterer, L. F., Chen, C., Cheung, C. Y.-L., Najjar, R. P., & Miléa, D. (2023) · Annals of the Academy of Medicine Singapore · doi:10.47102/annals-acadmedsg.2022369 · Cited by 8
Connecting Cohorts to Diminish Alzheimer’s Disease (CONCORD-AD): A Report of an International Research Collaboration Network
Pavlik, V. N., for the CONCORD-AD investigators, Burnham, S. C., Kass, J. S., Helmer, C., Palmqvist, S., Vassilaki, M., Dartigues, J., Hansson, O., Masters, C. L., et al. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-210525 · Cited by 8
Self-citation
Transferring Cut-off Values between Assays for Cerebrospinal Fluid Alzheimer’s Disease Biomarkers
Barrado, L. G., Coart, E., Vanderstichele, H., & Burzykowski, T. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150511 · Cited by 8
Assessment of 18F-Florbetaben Amyloid PET Imaging in Patients with Suspected Alzheimer’s Disease and Isolated Increase in Cerebrospinal Fluid Tau Proteins
Manca, C., Hopes, L., Kearney‐Schwartz, A., Roch, V., Karcher, G., Baumann, C., Marie, P., Malaplate, C., Jonveaux, T., & Verger, A. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-181146 · Cited by 8
Lower semantic fluency scores and a phonemic-over-semantic advantage predict abnormal CSF P-tau181 levels in Aβ + patients within the Alzheimer’s disease clinical spectrum
Aiello, E. N., Verde, F., Solca, F., Milone, I., Grigoli, E. G., Dubini, A., Ratti, A., Ferrucci, R., Torresani, E., Priori, A., et al. (2023) · Neurological Sciences · doi:10.1007/s10072-023-06643-w · Cited by 7
Alzheimer’s Disease Diagnosis and Management in the Age of Amyloid Monoclonal Antibodies
Hales, C. M. (2024) · Medical Clinics of North America · doi:10.1016/j.mcna.2024.10.003 · Cited by 7
Cardiorespiratory Fitness Modifies Influence of Sleep Problems on Cerebrospinal Fluid Biomarkers in an At-Risk Cohort
Law, L. L., Sprecher, K. E., Dougherty, R. J., Edwards, D. F., Koscik, R. L., Gallagher, C. L., Carlsson, C. M., Zetterberg, H., Blennow, K., Asthana, S., et al. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-180291 · Cited by 7
Self-citation
Chronic hypoperfusion due to intracranial large artery stenosis is not associated with cerebral β-amyloid deposition and brain atrophy
Fan, D., Li, H., Chen, D., Chen, Y., Yi, X., Yang, H., Shi, Q., Jiao, F., Tang, Y., Li, Q., et al. (2022) · Chinese Medical Journal · doi:10.1097/cm9.0000000000001918 · Cited by 7
Comparative analysis of Elecsys and ELISA for differentiating amyloid-PET status in a Korean memory clinic based on cerebrospinal fluid biomarkers
Park, S. A., An, Y., Park, Y.-J., Lee, J.-Y., Jeon, H., Kim, Y. S., Lee, K., Sun, K., Lee, S. M., & Moon, S. Y. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251314886 · Cited by 6
Clinical significance of plasma candidate biomarkers of Alzheimer’s Disease
Lewczuk, P., Łukaszewicz‐Zając, M., Kornhuber, J., & Mroczko, B. (2024) · Neurologia i Neurochirurgia Polska · doi:10.5603/pjnns.100675 · Cited by 7
Elevated cerebrospinal fluid biomarkers of neuroinflammation and neuronal damage in essential hypertension with secondary insomnia: Implications for Alzheimer’s disease risk
Zhang, F., Han, X., Mu, Q., Zailani, H., Liu, W., Do, Q. L., Wu, Y., Wu, N., Kang, Y., Su, K., et al. (2024) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2024.12.157 · Cited by 6
Integrating MRI Volume and Plasma p-Tau217 for Amyloid Risk Stratification in Early-Stage Alzheimer Disease
Yim, S., Park, S., Lim, K., Kang, H., Shin, D., Jo, H., Jang, H., Weiner, M. W., Zetterberg, H., Blennow, K., et al. (2025) · Neurology · doi:10.1212/wnl.0000000000213954 · Cited by 6
Self-citation
Brain network dynamics determine tau presence while regional vulnerability governs tau load in Alzheimer’s diseasePreprint
Xiao, Y., Spotorno, N., An, L., Bazinet, V., Hansen, J. Y., Strandberg, O. T., Shafiei, G., Behjat, H., Funck, T., Salvadó, G., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.17.648358 · Cited by 6
Self-citation
Ultrasensitive Assays Detect Different Conformations of Plasma β Amyloids
Li, C.-Y., Fan, L., Lin, C., Hu, C., & Chiu, M. (2025) · ACS Omega · doi:10.1021/acsomega.4c10879 · Cited by 5
Third Ventricle Width Assessed by Transcranial Sonography as Predictor of Long-Term Cognitive Impairment
Crespo-Cuevas, A. M., Elena López-Cancio, M., Cáceres, C. M., González, A., Ispierto, L., Hernández‐Pérez, M., Mataró, M., Planas, A. M., Canento, T., Martín-Aguilar, L., et al. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-190949 · Cited by 5
Inter-modality assessment of medial temporal lobe atrophy in a non-demented population: application of a visual rating scale template across radiologists with varying clinical experience
Håkansson, C., Tamaddon, A., Andersson, H., Torisson, G., Mårtensson, G., Truong, M., Annertz, M., Londos, E., Björkman‐Burtscher, I. M., Hansson, O., et al. (2021) · European Radiology · doi:10.1007/s00330-021-08177-1 · Cited by 5
Self-citation
Real‐world performance of plasma p‐tau181 in a heterogeneous memory clinic cohort
Parvizi, T., Wurm, R., König, T., Silvaieh, S., Altmann, P., Klotz, S., Regelsberger, G., Traub‐Weidinger, T., Gelpí, E., & Stögmann, E. (2024) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.52116 · Cited by 5
Diagnostic de la maladie d’Alzheimer : apport de l’imagerie au florbétapir et autres radiopharmaceutiques de la plaque amyloïde
Semah, F., Deberdt, W. G., & Ceccaldi, M. P. (2016) · Médecine Nucléaire · doi:10.1016/j.mednuc.2016.08.001 · Cited by 5
Validity and Normative Data for the Biber Figure Learning Test: A Visual Supraspan Memory Measure
Gifford, K. A., Liu, D., Neal, J. E., Acosta, L. M. Y., Bell, S. P., Wiggins, M. E., Wisniewski, K. M., Godfrey, M., Logan, L. A., Hohman, T. J., et al. (2018) · Assessment · doi:10.1177/1073191118773870 · Cited by 5
Self-citation
Reply: Do we still need positron emission tomography for early Alzheimer’s disease diagnosis?
Palmqvist, S., Mattsson, N., & Hansson, O. (2016) · Brain · doi:10.1093/brain/aww169 · Cited by 5
Self-citation
Higher levels of myelin are associated with higher resistance against tau pathology in Alzheimer’s diseasePreprint
Rubinski, A., Franzmeier, N., Dewenter, A., Luan, Y., Smith, R. A., Strandberg, O. T., Ossenkoppele, R., Dichgans, M., Hansson, O., Ewers, M., et al. (2022) · medRxiv · doi:10.1101/2022.03.02.22271746 · Cited by 5
Self-citation
A Surface-Engineered Microfluidic Platform with Algorithmic Optimization for Plasma Biomarker Detection in Alzheimer’s Disease
Cheng, Y., Tang, L., Yi, T., Xu, H., Yang, D., Zhou, Z., Gao, W., Ke, Z., Mao, C., Hu, Z., et al. (2025) · ACS Sensors · doi:10.1021/acssensors.5c03653 · Cited by 4
Advances in Aβ Plaque Detection and the Value of Knowing: Overcoming Challenges to Improving Patient Outcomes in Alzheimer’s Disease
Jovalekic, A., Bullich, S., Catafau, A. M., & Santi, S. D. (2016) · Neurodegenerative Disease Management · doi:10.2217/nmt-2016-0026 · Cited by 4
Statistical estimation and comparison of group-specific bivariate correlation coefficients in family-type clustered studies
Luo, J. R., Gao, F., Liu, J., Wang, G., Chen, L., Fagan, A. M., Day, G. S., Vöglein, J., Chhatwal, J. P., Xiong, C., et al. (2021) · Journal of Applied Statistics · doi:10.1080/02664763.2021.1899141 · Cited by 5
A β-Amyloid(1-42) Biosensor Based on Molecularly Imprinted Poly-Pyrrole for Early Diagnosis of Alzheimer’s Disease
Vais, R. D., Yadegari, H., Heli, H., & Sattarahmady, N. (2021) · Journal of Biomedical Physics and Engineering · doi:10.31661/jbpe.v0i0.1070 · Cited by 4
A Case of Early-Onset Alzheimer’s Disease Mimicking Schizophrenia in a Patient with Presenilin 1 Mutation (S170P)
Kim, H., Jang, J. H., Ham, H.-G., Choo, S. H., Park, J.-H., Kang, S. H., Hwangbo, S., Jang, H., Na, D. L., Seo, S. W., et al. (2021) · Journal of Alzheimer s Disease · doi:10.3233/jad-210650 · Cited by 4

Authors: Palmqvist, S., Zetterberg, H., Blennow, K., Vestberg, S., Andreasson, U., Brooks, D. J., Owenius, R., Hägerström, D., Wollmer, P., Minthon, L., & Hansson, O.
Affiliations: Lund University (SE)
University of Gothenburg (SE)
Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Gothenburg and Mölndal, Sweden
Aarhus University (DK)
GE Healthcare, Life Sciences, Uppsala, Sweden
Skåne University Hospital (SE)
Corresponding author: Hansson, Oskar
ORCID: Palmqvist, Sebastian
Zetterberg, Henrik
Blennow, Kaj
Vestberg, Susanna
Brooks, David J.
Wollmer, Per
Hansson, Oskar
Venue: JAMA Neurology
Publisher: American Medical Association (AMA)
Published: 2014-10-01
Volume: 71
Issue: 10
Pages: 1282
ISSN: 2168-6149 (ISSN-L)
DOI: 10.1001/jamaneurol.2014.1358
OpenAlex: W1992165389
Cited by: 368
References: 48
Citations by year: 2026: 5 · 2025: 25 · 2024: 21 · 2023: 16 · 2022: 27 · 2021: 38 · 2020: 48 · 2019: 46 · 2018: 31 · 2017: 34 · 2016: 33 · 2015: 39 · 2014: 3
FWCI: 27.74
Type: journal article
Language: en
Open access: closed
Locations: JAMA Neurology (publishedVersion)
PubMed (publishedVersion)
Lund University Publications (Lund University) (submittedVersion)
Topics: Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
Health Sciences › Medicine › Clinical Neurology › Cerebrospinal fluid and hydrocephalus
Keywords: Alzheimer's disease, cerebrospinal fluid biomarkers, amyloid-beta 42, cortical amyloid deposition, 18F-flutemetamol PET, total tau, phosphorylated tau, diagnostic accuracy, mild cognitive impairment, APOE genotype, hippocampal volume, memory clinics, early detection of neurodegeneration
MeSH terms: Aged, Aged, 80 and over, Alzheimer Disease, Aniline Compounds, Brain, Cerebral Cortex, Cross-Sectional Studies, Female, Gyrus Cinguli, Humans, Male, Middle Aged, Peptide Fragments, Reproducibility of Results, Cohort Studies, Amyloid beta-Peptides, Radiopharmaceuticals, Early Diagnosis, Positron-Emission Tomography, Benzothiazoles, Cognitive Dysfunction

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Accuracy of Brain Amyloid Detection in Clinical Practice Using Cerebrospinal Fluid β-Amyloid 42: A Cross-Validation Study Against Amyloid Positron Emission Tomography

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks