DYSGLYCEMIA ASSOCIATED WITH ANTIPSYCHOTIC USE: A SYSTEMATIC REVIEW
Notice bibliographique
Résumé
Abstract Background Antipsychotics (APs) are the cornerstone of treatment for schizophrenia spectrum disorders (SSDs) and are approved for treatment of affective disorders including bipolar disorder (BD). However, AP use is associated with severe metabolic consequences including weight gain, dyslipidemia, and dysglycemia. Although studies indicate that glucose dysfunction can occur independently of weight gain, AP-induced glycemic changes are most often considered to be a consequence of AP-induced weight gain. Aim & Objectives The aims of this review are to 1) specifically clarify the effect of APs on glucose homeostasis independently of weight gain and 2) determine whether APs similarly impact glycemic control independently of drug class and treatment duration. Method: We searched MEDLINE, EMBASE, PsychINFO, CENTRAL, CINAHL, and Web of Science to identify all randomized controlled trials (RCTs) that compared the effect of APs on glucose metabolism to placebo (PBO), with no restriction on psychiatric diagnosis. Random effects meta-analyses examined glucose dysfunction as both continuous and dichotomous outcomes, with subgroup analyses conducted for study length, AP type, and age (child/adolescent vs. adult). Results Of 20954 references identified in our search, 70 RCTs in patients with SSDs (N=40 studies) and BD (N=30 studies) met our inclusion criteria. In both populations, AP use was associated with a significantly greater increase in fasting glucose compared to placebo (mean difference (MD) SSD = 0.05 mmol/L [0.01, 0.09], p=0.02, I2=0%, n=8542 AP vs. n=3333 PBO; MD BD = 0.10 mmol/L [0.05, 0.15], p<0.0001, I2=46%, n=6018 AP vs. n=4137 PBO). Sub-group analyses revealed that neither study length nor AP type altered this finding. Nevertheless, in patients with BD, significantly impacted AP-induced alterations in blood glucose, with adults showing a greater increase (p=0.03, I2=79%). Plasma insulin was also significantly increased by AP exposure (MD SSD = 13.97 pmol/L [6.42, 21.51], p=0.0003, I2=0%, n=3678 AP vs. n=1169 PBO; MD BD = 12.85 pmol/L [1.14, 24.56], p=0.03, I2=55%, n=2111 AP vs. n=1676 PBO), with a significant subgroup difference according to AP type in both groups. There was an additional effect of study length on plasma insulin in individuals with SSDs (p=0.03, I2=79.8%). Importantly, the strength of the effect of different APs on glucose did not appear to follow the established hierarchy of weight gain liabilities outlined in the literature. Specifically, so-called weight neutral APs such as ziprasidone and lurasidone produced comparable dysglycemia to APs traditionally associated with significant weight gain like olanzapine (SSD: p=0.45, I2 =0%; BD: p=0.46, I2=0%). Furthermore, AP exposure did not appear to have a significant effect on or hyperglycemia. Discussion & Conclusion Our review demonstrates that both short- and long-term exposure to APs is associated with a significant increase in dysglycemia risk as indicated by drug-induced elevations in fasting blood glucose and insulin. Furthermore, all APs cause some degree of regardless of exposure time and established propensities for AP-induced weight gain. Further studies are required to better understand how AP use contributes to dysglycemia, including temporal changes throughout the treatment course, and how these effects could potentially be mitigated using metabolic interventions.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,021 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,008 | 0,007 |
| Bibliométrie | 0,007 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».