Prediction of Lithium Response using Clinical Data,Acta Psychiatrica Scandinavica

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Prediction of Lithium Response using Clinical Data
Acta Psychiatrica Scandinavica ( IF 6.7 ) Pub Date : 2019-11-22 , DOI: 10.1111/acps.13122
A Nunes _{1,

2} , R Ardau ₃ , A Berghöfer ₄ , A Bocchetta ₃ , C Chillotti ₃ , V Deiana ₅ , J Garnham ₁ , E Grof _{6,

7} , T Hajek ₁ , M Manchia _{8,

9} , B Müller-Oerlinghausen ₁₀ , M Pinna ₁₁ , C Pisanu ₅ , C O'Donovan ₁ , G Severino ₅ , C Slaney ₁ , A Suwalska _{12,

13} , P Zvolsky ₁₄ , P Cervantes ₁₅ , M Del Zompo ₅ , P Grof _{6,

7} , J Rybakowski _{12,

16} , L Tondo _{11,

17} , T Trappenberg ₂ , M Alda ₁

Affiliation

Department of Psychiatry, Dalhousie University, Halifax, NS, Canada.
Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada.
Unit of Clinical Pharmacology, San Giovanni di Dio Hospital, University Hospital of Cagliari, Cagliari, Italy.
Charité University Medical Center, Institute for Social Medicine, Epidemiology and Health Economics, Berlin, Germany.
Section of Neuroscience and Clinical Pharmacology, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.
Mood Disorders Center of Ottawa, Ottawa, ON, Canada.
Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
Section of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.
Department of Pharmacology, Dalhousie University, Halifax, NS, Canada.
Charité Universitätsmedizin-Berlin, Berlin, Germany.
Centro Lucio Bini, Cagliari e Roma, Italy.
Department of Adult Psychiatry, Poznan University of Medical Sciences, Poznan, Poland.
Department of Mental Health, Poznan University of Medical Sciences, Poznan, Poland.
Department of Psychiatry, Charles University, Prague, Czech Republic.
Department of Psychiatry, McGill University Health Centre, Montreal, QC, Canada.
Department of Psychiatric Nursing, Poznan University of Medical Sciences, Poznan, Poland.
Harvard Medical School and McLean Hospital, Boston, MA, USA.

Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical markers.

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