University of Oulu

Antti J. Luikku, Anette Hall, Ossi Nerg, Anne M. Koivisto, Mikko Hiltunen, Seppo Helisalmi, … Ville Leinonen. (2019). Predicting Development of Alzheimer’s Disease in Patients with Shunted Idiopathic Normal Pressure Hydrocephalus. Journal of Alzheimer's Disease, vol. 71, no. 4, pp. 1233-1243, https://doi.org/10.3233/JAD-190334

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
Publish Date: 2019-10-03
Description:

Abstract

Background: 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.

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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.