Focus on Depression in Parkinson's Disease: A Delphi Consensus of Experts in Psychiatry, Neurology, and Geriatrics.

Major and minor forms of depression are significant contributors to Parkinson's disease morbidity and caregiver burden, affecting up to 50% of these patients. Nonetheless, symptoms of depression are still underrecognized and undertreated in this context due to scarcity of evidence and, consequently, consistent clinical guideline recommendations. Here, we carried out a prospective, multicentre, 2-round modified Delphi survey with 49 questions about the aetiopathological mechanisms of depression in Parkinson's disease (10), clinical features and connections with motor and nonmotor symptoms (10), diagnostic criteria (5), and therapeutic options (24). Items were assessed by a panel of 37 experts (neurologists, psychiatrists, and a geriatrist), and consensus was achieved in 81.6% of them. Depressive symptoms, enhanced by multiple patient circumstances, were considered Parkinson's disease risk factors but not clinical indicators of motor symptom and disease progression. These patients should be systematically screened for depression while ruling out both anhedonia and apathy symptoms as they are not necessarily linked to it. Clinical scales (mainly the Geriatric Depression Scale GDS-15) can help establishing the diagnosis of depression, the symptoms of which will require treatment regardless of severity. Efficacious and well-tolerated pharmacological options for Parkinson's comorbid depression were selective serotonin reuptake inhibitors (especially sertraline), dual-action serotonin and norepinephrine reuptake inhibitors (venlafaxine, desvenlafaxine, and duloxetine), multimodal (vortioxetine, bupropion, mirtazapine, and tianeptine), and anti-Parkinsonian dopamine agonists (pramipexole, ropinirole, and rotigotine). Tricyclic antidepressants and combining type B monoamine oxidase inhibitors with serotonergic drugs have serious side effects in these patients and therefore should not be prescribed. Electroconvulsive therapy was indicated for severe and drug-refractory cases. Cognitive behavioural therapy was recommended in cases of mild depression. Results presented here are useful diagnostic and patient management guidance for other physicians and important considerations to improve future drug trial design.

Depression in Alzheimer's Disease: A Delphi Consensus on Etiology, Risk Factors, and Clinical Management.

Background: Alzheimer's disease (AD) and other forms of dementia are among the most common causes of disability in the elderly. Dementia is often accompanied by depression, but specific diagnostic criteria and treatment approaches are still lacking. This study aimed to gather expert opinions on dementia and depressed patient management to reduce heterogeneity in everyday practice. Methods: Prospective, multicenter, 2-round Modified Delphi survey with 53 questions regarding risk factors (11), signs and symptoms (7), diagnosis (8), and treatment (27) of depression in dementia, with a particular focus on AD. The questionnaire was completed by a panel of 37 expert physicians in neurodegenerative diseases (19 neurologists, 17 psychiatrists, and 1 geriatrician). Results: Consensus was achieved in 40 (75.5%) of the items: agreement in 33 (62.3%) and disagreement in 7 (13.2%) of them. Among the most relevant findings, depression in the elderly was considered an early sign (prodromal) and/or a dementia risk factor, so routine cognitive check-ups in depressed patients should be adopted, aided by clinical scales and information from relatives. Careful interpretation of neuropsychological assessment must be carried out in patients with depression as it can undermine cognitive outcomes. As agreed, depression in early AD is characterized by somatic symptoms and can be differentiated from apathy by the presence of sadness, depressive thoughts and early-morning awakening. In later-phases, symptoms of depression would include sleep-wake cycle reversal, aggressive behavior, and agitation. Regardless of the stage of dementia, depression would accelerate its course, whereas antidepressants would have the opposite effect. Those that improve cognitive function and/or have a dual or multimodal mode of action were preferred: Duloxetine, venlafaxine/desvenlafaxine, vortioxetine, tianeptine, and mirtazapine. Although antidepressants may be less effective than in cognitively healthy patients, neither dosage nor treatment duration should differ. Anti-dementia cholinesterase inhibitors may have a synergistic effect with antidepressants. Exercise and psychological interventions should not be applied alone before any pharmacological treatment, yet they do play a part in improving depressive symptoms in demented patients. Conclusions: This study sheds light on several unresolved clinical challenges regarding depression in dementia patients. Further studies and specific recommendations for this comorbid patient population are still needed.

Phonetic relevance and phonemic grouping of speech in the automatic detection of Parkinson's Disease.

Literature documents the impact of Parkinson's Disease (PD) on speech but no study has analyzed in detail the importance of the distinct phonemic groups for the automatic identification of the disease. This study presents new approaches that are evaluated in three different corpora containing speakers suffering from PD with two main objectives: to investigate the influence of the different phonemic groups in the detection of PD and to propose more accurate detection schemes employing speech. The proposed methodology uses GMM-UBM classifiers combined with a technique introduced in this paper called phonemic grouping, that permits observation of the differences in accuracy depending on the manner of articulation. Cross-validation results reach accuracies between 85% and 94% with AUC ranging from 0.91 to 0.98, while cross-corpora trials yield accuracies between 75% and 82% with AUC between 0.84 and 0.95, depending on the corpus. This is the first work analyzing the generalization properties of the proposed approaches employing cross-corpora trials and reaching high accuracies. Among the different phonemic groups, results suggest that plosives, vowels and fricatives are the most relevant acoustic segments for the detection of PD with the proposed schemes. In addition, the use of text-dependent utterances leads to more consistent and accurate models.