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Enregistrement W1569943631 · doi:10.1111/j.1532-5415.2007.01384.x

DEPRESSIVE SYMPTOMS AND COGNITIVE STATUS AFFECT HEALTH‐RELATED QUALITY OF LIFE IN OLDER PATIENTS WITH PARKINSON'S DISEASE

2007· letter· en· W1569943631 sur OpenAlexaffabout
Tracy Greene, Richard Camicioli

Notice bibliographique

RevueJournal of the American Geriatrics Society · 2007
Typeletter
Langueen
DomaineMedicine
ThématiqueParkinson's Disease Mechanisms and Treatments
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésMedicineGeriatric Depression ScaleMoodQuality of life (healthcare)Affect (linguistics)DementiaRating scaleDepression (economics)Parkinson's diseaseClinical Dementia RatingMontreal Cognitive AssessmentDiseaseCognitionGerontologyStroke (engine)Physical therapyPsychiatryInternal medicineDepressive symptomsPsychology

Résumé

récupéré en direct d'OpenAlex

To the Editor: Parkinson's disease (PD) is a multidimensional disorder affecting motor function, mood, and cognitive function, all of which might affect health-related quality of life (HR-QoL). The EuroQoL is an instrument that has been validated in Parkinson's disease and has been shown to accurately reflect patients' perceptions of their health.1,2 Previous studies have shown that patients with PD with on/off fluctuations, falls, insomnia, depression, and cognitive impairment have lower HR-QoL than their counterparts without these problems.3 No study we know of has focused solely on older North American patients. We set out to examine the correlates of HR-QoL in patients with PD aged 65 and older. Participants aged 65 and older were recruited from the Movement Disorders Clinic at the University of Alberta or from the Parkinson's Society of Alberta from advertisement for a longitudinal study. Patients were from Edmonton, Alberta, or its surrounding rural areas. Patients with a history of unstable heart disease, ischemic changes (e.g., stroke or transient ischemic attack), active cancer, and dementia were excluded. Control participants matched for age, sex, and education were recruited by advertisement in local senior centers, and by word of mouth. The study design was cross-sectional. As described,4 subjects and their informants were interviewed, and standardized assessments were used. A neurologist (RC) administered the Unified Parkinson's Disease Rating Scale (UPDRS) and the Cumulative Illness Rating Scale (CIRS); a trained research assistant (TG) administered the Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS), and EuroQoL 5-item questionnaire (EQ-5D), which measures participant problems in mobility, self-care, social activities, pain, anxiety, and depression. The participants were also asked to complete the EuroQoL visual analog rating, which asks participants to rate their health on a scale of 0 to 100. EQ-5D responses were categorized as no problems versus some or extreme problems for chi-square analysis. Multivariate linear regression was used to determine which factors most strongly contributed to HR-QoL on the EuroQoL visual analog. Fifty-one patients with PD and 50 age- and sex-matched controls participated in the study. Patients with PD had significantly higher (worse) GDS scores than matched controls and were more likely to take antidepressant medication. Controlling for age, sex, education, and CIRS score, GDS score was the strongest contributor to health rating based on the EuroQoL visual analog scale (beta=−0.425, P<.005). MMSE also significantly predicted HR-QoL (beta=0.296, P<.05) on the EuroQoL visual analog. Neither UPDRS III (beta=−0.075, P=.610) nor CIRS score (beta=−0.159, P=.219) were significant predictors of HR-QoL in patients with PD. Patients were more likely than control volunteers to report problems associated with mobility, self-care, social activities, anxiety, and depression, but not pain, on the EQ-5D. Depressive symptoms were the strongest predictor of HR-QoL in older people with PD, despite the fact that many people were treated for depression. The findings are similar to European studies,3,5–8 which have shown that patients with PD with depressive symptoms report lower HR-QoL but which did not focus on older patients. This suggests that HR-QoL of patients with PD might potentially be improved with proper management of depression. Depression may be underreported and often untreated in patients with PD. Effort should be made to detect, diagnose, and properly treat depression in patients with PD, although appropriate decision-making regarding treatment is difficult, given the paucity of clinical trials of depression in PD.9 The data suggest that minor deficits in cognitive functioning appear to affect HR-QoL. All participants were considered cognitively healthy, although three presented with mild cognitive impairment. Despite the overall high scores on the MMSE, it still significantly predicted HR-QoL visual analog ratings. The fact that the current study was not population-based limited it. Because of selection criteria, younger patients with PD are not represented in the results, although the sample may be representative of patients seeking subspecialty care. The results of our study are consistent with population-based studies and studies examining a broader age range of patients.3,10 The study was cross-sectional and therefore examined prevalence, not incidence of depressive symptoms and HR-QoL. Future studies should be longitudinal to address the question of whether depression is a precursor to or consequence of poor HR-QoL. The results reinforce the need for proper management of depressive symptoms in patients with PD. Healthcare providers for older people should be aware of the high prevalence and underreporting of depression in patients with PD. Understanding the link between depressive symptoms and HR-QoL might lead to improved quality of life for patients. We thank the staff at the Movement Disorders Clinic for help with recruitment of participants and Thomas Bouchard for help with data collection and follow-up of participants in the study. Financial Disclosure: Funded by the Canadian Institute of Health Research. The Editor has reviewed the submitted financial and personal conflicts list and determined that there are no conflicts with either of the authors in this letter. Author Contributions: Dr. Camicioli devised the study concept, designed the study, and obtained funding for its execution. Subjects were recruited from routine clinic visits with help from staff at the Movement Disorders Clinic. Dr. Camicioli neurologically assessed all participants, and Tracy Greene administered standardized cognitive tests. Tracy Greene performed data analysis and manuscript presentation with guidance from Dr. Camicioli. Thomas Bouchard has given written consent to be included in the acknowledgment section. Sponsor's Role: The sponsor had no role beyond funding the study.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,011
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,013

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,011
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,000
Intégrité de la recherche0,0030,003
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,012
Tête enseignante GPT0,283
Écart entre enseignants0,271 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations20
Publié2007
Routes d'admission2
Résumé présentoui

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Même revueJournal of the American Geriatrics Society→Même sujetParkinson's Disease Mechanisms and Treatments→Travaux en français237 207→