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Enregistrement W2919839293 · doi:10.1176/appi.pn.2019.2a11

Study Sheds Light on Trajectory of Developing Bipolar Disorder

2019· article· en· W2919839293 sur OpenAlexaboutno aff
Linda M. Richmond

Notice bibliographique

RevuePsychiatric News · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueBipolar Disorder and Treatment
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBipolar disorderPsychiatryAnxietyPsychologyDepression (economics)PsychopathologyBipolar illnessFamily historyPrevalence of mental disordersClinical psychologyMedicineLithium (medication)Mania

Résumé

récupéré en direct d'OpenAlex

Back to table of contents Previous article Next article Clinical and Research NewsFull AccessStudy Sheds Light on Trajectory of Developing Bipolar DisorderLinda M. RichmondLinda M. RichmondSearch for more papers by this authorPublished Online:28 Feb 2019https://doi.org/10.1176/appi.pn.2019.2a11AbstractAnxiety, sleep disorders, and/or major depression in young people whose parents have bipolar disorder may complicate early recognition and treatment. As many as 1 in 4 children who has a parent with bipolar disorder may go on to develop the disorder. A large prospective study published in AJP in Advance suggests that childhood sleep and anxiety disorders may be important predictors of the illness.Anne Duffy, M.D., and colleagues found that bipolar spectrum disorders developed in 25 percent of children who had one parent with bipolar disorder and that childhood sleep or anxiety disorders were more likely among those who developed it.“For clinicians, in order to accurately diagnose emerging psychiatric disorders, we need to take into account the developmental trajectory of emerging psychopathology as well as the family history of psychiatric illness,” lead study author Anne Duffy, M.D., a professor in the Department of Psychiatry at Queen’s University in Canada, told Psychiatric News. “Symptoms alone are not sufficient information to make a stable and accurate diagnosis.”The study included 279 “high-risk” participants (aged 5 to 25 years) who had one parent diagnosed with bipolar I or bipolar II disorder. The researchers categorized the high-risk participants into two groups, according to how their parents responded to lithium. Parents of the participants were considered to be “responsive to lithium” if they had no new recurrences over at least three years while on the medication; all others were considered nonresponsive to the medication. Also included in the study were 87 “comparison” participants—those with similar socioeconomic backgrounds from Ottawa schools whose parents had had no history of major psychiatric disorder.Participants were followed for up to 21 years, about 8 years on average for the high-risk group. All participants completed research assessments administered by a psychiatrist at baseline and about every year thereafter.The researchers observed bipolar spectrum disorders in 25 percent of the “high-risk” offspring, with an average age of onset of 21 years old, while about 11 percent of the group were diagnosed with psychotic spectrum disorders. Neither disorder was observed in the comparison group. The researchers found evidence that earlier age of onset of parental bipolar disorder was associated with an increased risk of mood disorder, including bipolar disorder and depression, in the offspring.The researchers found no difference in the prevalence of bipolar disorder among participants based on whether their parent responded to lithium; however, psychotic disorders manifested almost exclusively among the offspring of lithium-nonresponsive parents (20 percent compared with 1 percent).Individuals with childhood anxiety disorder or a sleep disorder were nearly twice as likely to develop a mood disorder, Duffy and colleagues found. Subthreshold depressive or manic symptoms were even more telling, and participants with such symptoms were 2.7 times more likely and 2.3 times more likely, respectively, to develop a mood disorder.“The implication is that clinically significant anxiety, mood, and sleep symptoms in children at confirmed familial risk for bipolar disorder identify an ultra-high-risk group that likely warrants closer surveillance and support,” the researchers wrote.The researchers diagnosed major depressive disorder almost exclusively among the high-risk offspring (33 percent of the high-risk group versus 5 percent of the comparison group). A similar pattern emerged for sleep disorders (23 percent of high-risk group versus none of the comparison group). Bipolar disorder typically unfolded in a progressive clinical sequence in individuals with familial risk, Duffy said. Depressive episodes were predominant early in the illness, especially among the offspring of individuals who responded to lithium.This study did not, however, find evidence to support a proposed pediatric bipolar subtype of illness in childhood characterized by chronic rapid fluctuating moodiness, irritability, neurodevelopmental disorder, and explosive temper. “This suggests this phenotype has nothing to do with bipolar disorder that persists into adulthood,” Duffy said.Overall the findings indicate the role that anxiety, sleep disorders, and major depression—especially with psychotic symptoms—may play in the development of bipolar disorder in young people with a familial risk. “Early clinical intervention and prevention efforts,” the researchers wrote, “should emphasize low-risk interventions addressing mood symptoms, anxiety and sleep disorders, and prevention of substance misuse.”The study was supported by a grant from the Canadian Institutes of Health Research. ■“The Emergent Course of Bipolar Disorder: Observations Over Two Decades From the Canadian High-Risk Offspring Cohort” can be accessed here. ISSUES NewArchived

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,074
Score d'incertitude au seuil0,599

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,013
Tête enseignante GPT0,275
Écart entre enseignants0,262 · 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 tête enseignante, pas un consensus.

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

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

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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