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
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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“Mixture modeling statistics provide an unbiased threshold for abnormality (i.e., the diagnosis or status is not used in analysis) and it is a well-established method for defining Aβ PET cut-offs12, 17, 60, 61.”
From Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity (2017) · cites this paper as [60]
Citations
Cites
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
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-citationCerebrospinal 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-citationPassing, H., & Bablok, W. (1983) · cclm · doi:10.1515/cclm.1983.21.11.709 · Cited by 1,513
Cited by
Sorted by citations
Items 301–368 of 368
Alzheimer’s Disease Cerebrospinal Fluid (CSF) Biomarkers
Khan, T. K. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-804832-0.00005-5 · Cited by 5
López‐Font, I., Boix, C. P., Zetterberg, H., Blennow, K., & Sáez‐Valero, J. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-161275 · Cited by 4
Self-citationKnapskog, A., Brækhus, A., & Engedal, K. (2018) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0000000000000268 · Cited by 4
Constantinescu, R., Mahamud, U., Constantinescu, C., Eriksson, B., Novakova, L., Olsson, B., Rosengren, L., Blennow, K., & Axelsson, M. (2019) · Acta Neurologica Scandinavica · doi:10.1111/ane.13118 · Cited by 4
Self-citationMirza, A. A., Dutta, M., Mishra, S. D., & Mirza, A. U. (2020) · Lecture notes in networks and systems · doi:10.1007/978-981-15-3020-3_28 · Cited by 4
Kumar, A., Binette, A. P., Bali, D., Janelidze, S., Stomrud, E., Palmqvist, S., Vogel, J. W., Hansson, O., & Mattsson, N. (2025) · Brain Communications · doi:10.1093/braincomms/fcaf353 · Cited by 3
Self-citationBlood-brain barrier water exchange in relation to amyloid, cognition and cerebrovascular burden
Padrela, B. E., Tecelão, S. R. R., Kirsebom, B., Geier, O. M., Tranfa, M., Masserini, F., Sneve, M. H., Slivka, M., FALCH, E., Pålhaugen, L., et al. (2025) · NeuroImage Clinical · doi:10.1016/j.nicl.2025.103926 · Cited by 3
Xu, Y., Zhang, G., Yang, L., Qin, H., Zhou, Z. L., Li, Q., Liu, H., Wang, R., Cai, Z., Jing, L., et al. (2024) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2024.161 · Cited by 3
Clinical value of Alzheimer's disease biomarker testing
Patel, K. J., Yang, D., Best, J. R., Chambers, C., Lee, P. E., Henri‐Bhargava, A., Funnell, C. R., Foti, D. J., Pettersen, J. A., Feldman, H., et al. (2024) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12464 · Cited by 3
Tavares-Júnior, J. W. L., Ciurleo, G. C. V., Feitosa, E. D. A. A. F., Oriá, R. B., & Braga‐Neto, P. (2024) · Journal of Alzheimer s Disease · doi:10.3233/jad-231368 · Cited by 3
Intraperitoneal hyperthermia in the management of pseudomyxoma peritonei.
Hsu, K.-H., Chou, C.-Y., & Chang, Y.-C. (2007) · PubMed · Cited by 3
Rådestig, M. A., Skoog, J., Zetterberg, H., Skillbäck, T. B., Zettergren, A., Sterner, T. R., Fässberg, M. M., Sacuiu, S. F., Wærn, M., Wetterberg, H., et al. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-220452 · Cited by 3
Self-citationWhere Should I Draw the Line: PET-Driven, Data-Driven, or Manufacturer Cut-Off?
Sánchez‐Soblechero, A., López‐García, S., Lage, C., Fernández‐Matarrubia, M., Irure, J., López‐Hoyos, M., Jiménez-Bonilla, J. F., Quirce, R., de Arcocha-Torres, M., Cuenca-Vera, O., et al. (2024) · Journal of Alzheimer s Disease · doi:10.3233/jad-230678 · Cited by 2
Larsson, V., Hall, S., Blennow, K., & Hansson, O. (2025) · PLoS ONE · doi:10.1371/journal.pone.0325560 · Cited by 2
Self-citationYim, S., Park, S., Lim, K. Y., Kang, H., Shin, D., Jang, H., Weiner, M. W., Zetterberg, H., Blennow, K., González‐Ortiz, F., et al. (2025) · Alzheimer s Research & Therapy · doi:10.1186/s13195-025-01870-z · Cited by 3
Self-citationHellquist, E., Janelidze, S., Weidung, B., Franzon, K., Giedraitis, V., Ingelsson, M., Bali, D., Veličkaitė, V., Zetterberg, H., Hansson, O., et al. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251390387 · Cited by 2
Self-citationZhao, Y. S., Xi, E., Wang, Z., Gao, N., Sun, H., & Zhu, G. (2025) · JACS Au · doi:10.1021/jacsau.5c01121 · Cited by 2
Mattsson, N., Karlsson, L., Tang, W., Blennow, K., Zetterberg, H., Bateman, R. J., Schindler, S. E., Barthélemy, N. R., Palmqvist, S., Stomrud, E., et al. (2025) · EMBO Molecular Medicine · doi:10.1038/s44321-025-00348-7 · Cited by 3
Self-citationLimited Diagnostic Performance of Cerebrospinal Fluid Glial Fibrillary Acidic Protein in Dementia
Erickson, P., Skillbäck, T. B., Kern, S., Skoog, I. G., Jönsson, L., Andréasson, U., Blennow, K., Eriksdotter, M., & Zetterberg, H. (2026) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000550601 · Cited by 2
Self-citationBollack, A., Schwarz, A. J., Bourgeat, P., Doré, V., Fripp, J., Page, C., Bonke, E. M., Thurfjell, L., Hass, M., Balhorn, W., et al. (2026) · Neuroimage Reports · doi:10.1016/j.ynirp.2026.100343 · Cited by 2
Self-citationThe biological diagnosis of Alzheimer’s disease using blood-based biomarkers: A Canadian prospective
Kumar, P., Mousavi, A., & Frykman, H. (2025) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2025.110980 · Cited by 2
Alzheimer’s Disease and Other Neurodegenerative Disorders
Rosén, C., Zetterberg, H., & Blennow, K. (2015) · Springer eBooks · doi:10.1007/978-3-319-01225-4_20 · Cited by 2
Self-citationCarrera-Muñoz, I., Cueva, L. T., Romero-Fábrega, J. C., Triviño‐Ibáñez, E. M., Vílchez-Carrillo, R. M., Pardo, C. C., & Gómez-Río, M. M. (2020) · Current Alzheimer Research · doi:10.2174/1567205017666201109092637 · Cited by 2
Biomarqueurs du liquide cérébrospinal
Leroy, M., Vaudran, L., Deramecourt, V., Pasquier, F., Chen, Y., Schraen‐Maschke, S., & Lebouvier, T. (2021) · Pratique Neurologique - FMC · doi:10.1016/j.praneu.2021.03.014 · Cited by 4
APOE4 impact on soluble and insoluble tau pathology is mostly influenced by amyloid-betaPreprint
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. (2024) · medRxiv · doi:10.1101/2024.09.20.24314064 · Cited by 2
Self-citationCognitive status and demographics modify the association between subjective cognition and amyloid
Bolton, C. J., Khan, O. A., Liu, D., Wilhoite, S., Dumitrescu, L. C., Peterson, A. J., Blennow, K., Zetterberg, H., Hohman, T. J., Jefferson, A. L., et al. (2024) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.52209 · Cited by 1
Self-citationPérez-Ramírez, R., Cuchillo‐Ibáñez, I., Sánchez, R., Sanahuja, A. B., Escamilla, S., Gasset, R. M., Zetterberg, H., Blennow, K., Sáez‐Valero, J., & Todolí‐Torró, J. (2025) · Journal of Neurochemistry · doi:10.1111/jnc.70307 · Cited by 1
Self-citationAlzheimer’s Disease and the Search for Environmental Risk Factors
Kukull, W. A. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-800228-5.00015-7 · Cited by 1
The Mediterranean Diet in Preventing Alzheimer’s Disease
Tourk, F. (2020) · The George Washington University Undergraduate Review · doi:10.4079/2578-9201.3(2020).09 · Cited by 1
Bensaïdane, M. R., Bouchard, R. W., Fortin, M., Houde, M., Rosa‐Neto, P., Poulin, S. P., Verret, L., Soucy, J., Beauregard, J., & Laforce, R. J. (2015) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2015.06.027 · Cited by 1
A + T ± status across MCI and dementia due to AD: a clinic-based, retrospective study
Verde, F., Aiello, E. N., Milone, I., Grigoli, E. G., Dubini, A., Ratti, A., Poletti, B., Ticozzi, N., & Silani, V. (2022) · Neurological Sciences · doi:10.1007/s10072-022-06346-8 · Cited by 1
Cerebrospinal Fluid Total Prion Protein
Zetterberg, H. (2015) · JAMA Neurology · doi:10.1001/jamaneurol.2014.4078 · Cited by 1
Self-citationDepression in Alzheimer's disease : biomarkers and treatment
Enache, D. (2015) · Figshare · Cited by 1
Molecular Imaging in Alzheimer Clinical Trials
Schmidt, M. E., Matthews, D. C., & Staelens, S. G. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-802173-6.00020-4
Troubles progressifs de la mémoire et du langage, lésion focale, chez un homme de 78ans
Sarazin, M., Lambert, I., & de Paula, A. M. (2016) · Pratique Neurologique - FMC · doi:10.1016/j.praneu.2016.07.012
Lawford‐Smith, H. (2015)
Bäckström, D. C. (2019) · KTH Publication Database DiVA (KTH Royal Institute of Technology)
Risk factors for development of neurocognitive disorders
Gustavsson, A. (2019) · Lund University Publications (Lund University)
Ruolo dei biomarcatori nella diagnostica liquorale della malattia di Alzheimer
Cinquanta, L., & Brusca, I. (2019) · La Rivista Italiana della Medicina di Laboratorio - Italian Journal of Laboratory Medicine · doi:10.23736/s1825-859x.19.00028-8
Cerebrospinal fluid biomarkers and cognition in older adults
Rådestig, M. A. (2021)
Яхьяевич, Я. Н., & Vagabov, N. M. (2009) · VESTNIK OF ASTRAKHAN STATE TECHNICAL UNIVERSITY SERIES MARINE ENGINEERING AND TECHNOLOGIES
Bao, Y., Wang, Z., Shea, Y. F., Chiu, P. K., Kwan, J. S. K., Chan, F. H.-W., & Mak, H. K. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4148575
Chernyaeva, L., Ratti, G., Teirilä, L., Rankka, U., Fudo, S., Pelkonen, A., Korhonen, P., Leskinen, K., Keskitalo, S., Salokas, K., et al. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4163140
Sex and Education Modify the Association Between Subjective Cognitive Decline and Amyloid PathologyPreprint
Bolton, C. J., Khan, O. A., Liu, D., Wilhoite, S., Dumitrescu, L. C., Peterson, A. J., Blennow, K., Zetterberg, H., Hohman, T. J., Jefferson, A. L., et al. (2023) · medRxiv · doi:10.1101/2023.11.03.23297795
Self-citationDuits, F. H., Wesenhagen, K. E. J., Ekblad, L. L., Wolters, E. E., Willemse, E. A. J., Scheltens, P., van der Flier, W. M., Teunissen, C. E., Visser, P. J., & Tijms, B. M. (2021) · Figshare · doi:10.6084/m9.figshare.13521232
Towards in vivo MRI-based diagnostics and tracking of dementia
Ortega‐Cruz, D. (2024) · UPM Digital Archive (Technical University of Madrid) · doi:10.20868/upm.thesis.81334
Bao, Y., Wang, Z., Guo, L., Bai, G., Feng, Y., & Zhao, G.-D. (2024) · Neuroradiology · doi:10.1007/s00234-024-03364-5
Cardiovascular rate pressure product is associated with NfL in older adults at risk for AD
Odo, C. C., Strong, J., Lose, S. R., Ma, Y., Gallagher, C. L., Bendlin, B. B., Zetterberg, H., Blennow, K., Carlsson, C. M., Kollmorgen, G., et al. (2025) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.70086
Self-citationNiwa, M., Noda, K., Kobayashi, Y., Kageyama, I., & Kodama, K. (2025) · Bioanalysis · doi:10.1080/17576180.2025.2515011
The biological diagnosis of Alzheimer’s disease using blood-based biomarkers: a Canadian prospective
Kumar, P., Mousavi, A., & Frykman, H. (2025) · Clinical Biochemistry · doi:10.1016/j.clinbiochem.2025.111015
Duits, F. H., Wesenhagen, K. E. J., Ekblad, L. L., Wolters, E. E., Willemse, E. A. J., Scheltens, P., van der Flier, W. M., Teunissen, C. E., Visser, P. J., & Tijms, B. M. (2021) · Figshare · doi:10.6084/m9.figshare.13521229
Aichholzer, F., Klafki, H., Ogorek, I., Vogelgsang, J. S., Wiltfang, J., Scherbaum, N., Weggen, S., & Wirths, O. (2021) · Figshare · doi:10.6084/m9.figshare.14538839
Aichholzer, F., Klafki, H., Ogorek, I., Vogelgsang, J. S., Wiltfang, J., Scherbaum, N., Weggen, S., & Wirths, O. (2021) · Figshare · doi:10.6084/m9.figshare.14538842
Novak, G., Streffer, J. R., Timmers, M., Henley, D. B., Brashear, H. R., Bogert, J., Russu, A., Janssens, L., Tesseur, I. C., Tritsmans, L., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12308243
Guo, Z., Tian, C., Shi, Y., Song, X.-R., Yin, W., Tao, Q.-Q., Liu, J., Peng, G.-P., Wu, Z.-Y., Wang, Y.-J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26689169
Aichholzer, F., Klafki, H., Ogorek, I., Vogelgsang, J. S., Wiltfang, J., Scherbaum, N., Weggen, S., & Wirths, O. (2021) · Figshare · doi:10.6084/m9.figshare.14538845
Guo, Z., Tian, C., Shi, Y., Song, X.-R., Yin, W., Tao, Q.-Q., Liu, J., Peng, G.-P., Wu, Z.-Y., Wang, Y.-J., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26689172
Aichholzer, F., Klafki, H., Ogorek, I., Vogelgsang, J. S., Wiltfang, J., Scherbaum, N., Weggen, S., & Wirths, O. (2021) · Figshare · doi:10.6084/m9.figshare.14538848
Hagberg, G., Ihle-Hansen, H., Fure, B., Thommessen, B., Ihle‐Hansen, H., Øksengård, A. R., Beyer, M. K., Wyller, T. B., Müller, E. G., Pendlebury, S. T., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12276821
Aichholzer, F., Klafki, H., Ogorek, I., Vogelgsang, J. S., Wiltfang, J., Scherbaum, N., Weggen, S., & Wirths, O. (2021) · Figshare · doi:10.6084/m9.figshare.14538851
Braun, M., Bjurnemark, C., Seo, W., Freyhult, E., Nyholm, D., Niemelä, V., Blennow, K., Zetterberg, H., Fällmar, D., Kultima, K., et al. (2022) · Figshare · doi:10.6084/m9.figshare.19174132
Self-citationNovak, G., Streffer, J. R., Timmers, M., Henley, D. B., Brashear, H. R., Bogert, J., Russu, A., Janssens, L., Tesseur, I. C., Tritsmans, L., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12308252
Novak, G., Streffer, J. R., Timmers, M., Henley, D. B., Brashear, H. R., Bogert, J., Russu, A., Janssens, L., Tesseur, I. C., Tritsmans, L., et al. (2020) · Figshare · doi:10.6084/m9.figshare.12308258
Thorvaldsson, V., Svensson, J., Basic, E., Jonsson, M. A. G., Kettunen, P., & Wallin, A. (2026) · Journal of the International Neuropsychological Society · doi:10.1017/s135561772510177x
Zimmermann, M., Fandrich, M., Schulte, C., Jakobi, M., Wurster, I., Lerche, S., Zimmermann, S., Deuschle, C., Schneiderhan‐Marra, N., Joos, T. O., et al. (2026) · GeroScience · doi:10.1007/s11357-026-02495-2
Metadata
- 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
- Venue
- JAMA Neurology
- Publisher
- American Medical Association (AMA)
- Published
- 2014-10-01
- Volume
- 71
- Issue
- 10
- Pages
- 1282
- ISSN
- 2168-6149 (ISSN-L)
- 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