Impact of a clinical decision support tool on dementia diagnostics in memory clinics: The predictnd validation study
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Impact of a clinical decision support tool on dementia diagnostics in memory clinics : The predictnd validation study. / Bruun, Marie; Frederiksen, Kristian S.; Rhodius-Meester, Hanneke F.M.; Baroni, Marta; Gjerum, Le; Koikkalainen, Juha; Urhemaa, Timo; Tolonen, Antti; Gils, Mark Van; Tong, Tong; Guerrero, Ricardo; Rueckert, Daniel; Dyremose, Nadia; Andersen, Birgitte Bo; Simonsen, Anja H.; Lemstra, Afina; Hallikainen, Merja; Kurl, Sudhir; Herukka, Sanna Kaisa; Remes, Anne M.; Waldemar, Gunhild; Soininen, Hilkka; Mecocci, Patrizia; Van Der Flier, Wiesje M.; Lötjönen, Jyrki; Hasselbalch, Steen G.
I: Current Alzheimer Research, Bind 16, Nr. 2, 2019, s. 91-101.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Impact of a clinical decision support tool on dementia diagnostics in memory clinics
T2 - The predictnd validation study
AU - Bruun, Marie
AU - Frederiksen, Kristian S.
AU - Rhodius-Meester, Hanneke F.M.
AU - Baroni, Marta
AU - Gjerum, Le
AU - Koikkalainen, Juha
AU - Urhemaa, Timo
AU - Tolonen, Antti
AU - Gils, Mark Van
AU - Tong, Tong
AU - Guerrero, Ricardo
AU - Rueckert, Daniel
AU - Dyremose, Nadia
AU - Andersen, Birgitte Bo
AU - Simonsen, Anja H.
AU - Lemstra, Afina
AU - Hallikainen, Merja
AU - Kurl, Sudhir
AU - Herukka, Sanna Kaisa
AU - Remes, Anne M.
AU - Waldemar, Gunhild
AU - Soininen, Hilkka
AU - Mecocci, Patrizia
AU - Van Der Flier, Wiesje M.
AU - Lötjönen, Jyrki
AU - Hasselbalch, Steen G.
PY - 2019
Y1 - 2019
N2 - Background: Determining the underlying etiology of dementia can be challenging. Computer- based Clinical Decision Support Systems (CDSS) have the potential to provide an objective comparison of data and assist clinicians. Objectives: To assess the diagnostic impact of a CDSS, the PredictND tool, for differential diagnosis of dementia in memory clinics. Methods: In this prospective multicenter study, we recruited 779 patients with either subjective cognitive decline (n=252), mild cognitive impairment (n=219) or any type of dementia (n=274) and followed them for minimum 12 months. Based on all available patient baseline data (demographics, neuropsychological tests, cerebrospinal fluid biomarkers, and MRI visual and computed ratings), the PredictND tool provides a comprehensive overview and analysis of the data with a likelihood index for five diagnostic groups; Alzheimer´s disease, vascular dementia, dementia with Lewy bodies, frontotemporal dementia and subjective cognitive decline. At baseline, a clinician defined an etiological diagnosis and confidence in the diagnosis, first without and subsequently with the PredictND tool. The follow-up diagnosis was used as the reference diagnosis. Results: In total, 747 patients completed the follow-up visits (53% female, 69±10 years). The etiological diagnosis changed in 13% of all cases when using the PredictND tool, but the diagnostic accuracy did not change significantly. Confidence in the diagnosis, measured by a visual analogue scale (VAS, 0-100%) increased (ΔVAS=3.0%, p<0.0001), especially in correctly changed diagnoses (ΔVAS=7.2%, p=0.0011). Conclusion: Adding the PredictND tool to the diagnostic evaluation affected the diagnosis and increased clinicians’ confidence in the diagnosis indicating that CDSSs could aid clinicians in the differential diagnosis of dementia.
AB - Background: Determining the underlying etiology of dementia can be challenging. Computer- based Clinical Decision Support Systems (CDSS) have the potential to provide an objective comparison of data and assist clinicians. Objectives: To assess the diagnostic impact of a CDSS, the PredictND tool, for differential diagnosis of dementia in memory clinics. Methods: In this prospective multicenter study, we recruited 779 patients with either subjective cognitive decline (n=252), mild cognitive impairment (n=219) or any type of dementia (n=274) and followed them for minimum 12 months. Based on all available patient baseline data (demographics, neuropsychological tests, cerebrospinal fluid biomarkers, and MRI visual and computed ratings), the PredictND tool provides a comprehensive overview and analysis of the data with a likelihood index for five diagnostic groups; Alzheimer´s disease, vascular dementia, dementia with Lewy bodies, frontotemporal dementia and subjective cognitive decline. At baseline, a clinician defined an etiological diagnosis and confidence in the diagnosis, first without and subsequently with the PredictND tool. The follow-up diagnosis was used as the reference diagnosis. Results: In total, 747 patients completed the follow-up visits (53% female, 69±10 years). The etiological diagnosis changed in 13% of all cases when using the PredictND tool, but the diagnostic accuracy did not change significantly. Confidence in the diagnosis, measured by a visual analogue scale (VAS, 0-100%) increased (ΔVAS=3.0%, p<0.0001), especially in correctly changed diagnoses (ΔVAS=7.2%, p=0.0011). Conclusion: Adding the PredictND tool to the diagnostic evaluation affected the diagnosis and increased clinicians’ confidence in the diagnosis indicating that CDSSs could aid clinicians in the differential diagnosis of dementia.
KW - Alzheimer´s disease
KW - CDSS
KW - Computer-assisted diagnosis
KW - Dementia with lewy body
KW - Differential diagnosis
KW - Frontotemporal disease
KW - Neurodegenerative disease
KW - Vascular dementia
U2 - 10.2174/1567205016666190103152425
DO - 10.2174/1567205016666190103152425
M3 - Journal article
C2 - 30605060
AN - SCOPUS:85061191635
VL - 16
SP - 91
EP - 101
JO - Current Alzheimer Research
JF - Current Alzheimer Research
SN - 1567-2050
IS - 2
ER -
ID: 235968945