Readmission and associated clinical factors among individuals admitted with bipolar affective disorder at a psychiatry facility in Uganda
Notice bibliographique
Résumé
BACKGROUND: Bipolar affective disorder (BAD) is a common severe mental health condition with a relapsing course that may include periods of hospital re-admissions. With recurrent relapses and admissions, the course, prognosis, and patient's overall quality of life can be affected negatively. This study aims to explore the rates and clinical factors associated with re-admission among individuals with BAD. METHOD: This study used data from a retrospective chart review of all records of patients with BAD admitted in 2018 and followed up their hospital records for four years till 2021 at a large psychiatric unit in Uganda. Cox regression analysis was used to determine the clinical characteristics associated with readmission among patients diagnosed with BAD. RESULTS: A total of 206 patients living with BAD were admitted in 2018 and followed up for four years. The average number of months to readmission was 9.4 (standard deviation = 8.6). The incidence of readmission was 23.8% (n = 49/206). Of those readmitted during the study period, 46.9% (n = 23/49) and 28.6% (n = 14/49) individuals were readmitted twice and three times or more, respectively. The readmission rate in the first 12 months following discharge was 69.4% (n = 34/49) at first readmission, 78.3% (n = 18/23) at second readmission, and 87.5% (n = 12/14) at third or more times. For the next 12 months, the readmission rate was 22.5% (n = 11/49) for the first, 21.7% (n = 5/23) for the second, and 7.1% (n = 1/14) for more than two readmissions. Between 25 and 36 months, the readmission rate was 4.1% (n = 2/49) for the first readmission and 7.1% (n = 1/14) for the third or more times. Between 37 and 48 months, the readmission rate was 4.1% (n = 2/49) for those readmitted the first time. Patients who presented with poor appetite and undressed in public before admission were at increased risk of being readmitted with time. However, the following symptoms/clinical presentations, were protective against having a readmission with time, increased number of days with symptoms before admission, mood lability, and high energy levels. CONCLUSION: The incidence of readmission among individuals living with BAD is high, and readmission was associated with patients' symptoms presentation on previous admission. Future studies looking at BAD using a prospective design, standardized scales, and robust explanatory model are warranted to understand causal factors for hospital re-admission and inform management strategies.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».