Predicting development of Alzheimer's disease in patients with shunted idiopathic normal pressure hydrocephalus |
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Author: | Luikku, Antti J.1,2; Hall, Anette1; Nerg, Ossi1,3; |
Organizations: |
1Institute of Clinical Medicine - Neurology, University of Eastern Finland, Kuopio, Finland 2Neurosurgery of NeuroCenter, Kuopio University Hospital, Kuopio, Finland 3Neurology of NeuroCenter, Kuopio University Hospital, Kuopio, Finland
4Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
5Department of Radiology, Kuopio University Hospital, Kuopio, Finland 6Combinostics Ltd, Tampere, Finland 7Department of Pathology, Kuopio University Hospital, Kuopio, Finland; and Department of Pathology, University of Eastern Finland, Kuopio, Finland 8Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University and Department of Pathology and Cytology, Uppsala University Hospital, Uppsala, Sweden 9Research Unit of Clinical Neuroscience, Neurology, University of Oulu, Oulu, Finland 10jMedical Research Center, Oulu University Hospital, Oulu, Finland 11Division of Clinical Geriatrics, NVS, Karolinska Institutet, Stockholm, Sweden 12Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland 13Medical Research Center, Oulu University Hospital, Oulu, Finland |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 0.3 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2019100330987 |
Language: | English |
Published: |
IOS Press,
2019
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Publish Date: | 2019-10-03 |
Description: |
AbstractBackground: Idiopathic normal pressure hydrocephalus (iNPH) patients often develop Alzheimer’s disease (AD) related brain pathology. Disease State Index (DSI) is a method to combine data from various sources for differential diagnosis and progression of neurodegenerative disorders. Objective: To apply DSI to predict clinical AD in shunted iNPH-patients in a defined population. Methods: 335 shunted iNPH-patients (median 74 years) were followed until death (n = 185) or 6/2015 (n = 150). DSI model (including symptom profile, onset age of NPH symptoms, atrophy of medial temporal lobe in CT/MRI, cortical brain biopsy finding, and APOE genotype) was applied. Performance of DSI model was evaluated with receiver operating characteristic (ROC) curve analysis. Results:A total of 70 (21%) patients developed clinical AD during median follow-up of 5.3 years. DSI-model predicted clinical AD with moderate effectiveness (AUC = 0.75). Significant factors were cortical biopsy (0.69), clinical symptoms (0.66), and medial temporal lobe atrophy (0.66). Conclusion: We found increased occurrence of clinical AD in previously shunted iNPH patients as compared with general population. DSI supported the prediction of AD. Cortical biopsy during shunt insertion seems indicated for earlier diagnosis of comorbid AD. see all
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Series: |
Journal of Alzheimer's disease |
ISSN: | 1387-2877 |
ISSN-E: | 1875-8908 |
ISSN-L: | 1387-2877 |
Volume: | 71 |
Issue: | 4 |
Pages: | 1233 - 1243 |
DOI: | 10.3233/JAD-190334 |
OADOI: | https://oadoi.org/10.3233/JAD-190334 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
3124 Neurology and psychiatry |
Subjects: | |
Funding: |
This study was funded by Academy of Finland (decision no 263193), VTR grant V16001 of Kuopio University Hospital, The Finnish Medical Foundation, Sigrid Juselius Foundation, Maire Taponen Foundation, the Strategic Funding of the University of Eastern Finland (UEF-Brain), VPH-DARE@IT project funded by European Union's Seventh Framework Programme (FP7/2007-2013) grant agreement no. 601055, From Patient Data to Clinical Diagnosis in Neurodegenerative Diseases PredictND project funded by the European Union's Seventh Framework Programme (FP7/2007-2013) grant agreement no. 611005, and is part of the BIOMARKAPD project in the frame of JPND. Sponsors had no role in the design or conduct of this research. |
Copyright information: |
© IOS Publishing. This is the pre-copyedited, author-produced version of an article accepted for publication in Journal of Alzheimer's Disease following peer review. The definitive Version of Record can be found online at https://doi.org/10.3233/JAD-190334. |