Looking for the Good Timing: Predictors of Length of Stay and Therapeutic Outcomes in Adolescent Inpatients with Severe or Treatment-Refractory Mood Disorders

Benarous, Xavier; Cravero, Cora; Jakubowicz, Barbara; Morales, Pierre; Cohen, Doron

doi:10.1089/cap.2020.0138

Cited by 6 publications

(9 citation statements)

References 44 publications

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“…A retrospective chart review demonstrated adolescents with mood disorders were more likely to have experienced psychosocial stressors in early life. They were also more likely to have had a severe first episode, worse functioning at admission and longer duration of hospitalization – indicating potential association between early life adversity and severity of mood disorder [16].…”

Section: Sociodemographic Determinantsmentioning

confidence: 99%

Sociodemographic and cultural determinants of mood disorders

D’cruz¹,

Chaturvedi

2021

Current Opinion in Psychiatry

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Purpose of reviewThe present review aims to examine, summarize and update information on the sociodemographic and cultural determinants of mood disorders. Recent findingsKnown sociodemographic and cultural determinants continue to be good predictors of the risk of developing a mood disorder over the lifetime. Polygenic risk scores do not appear to offer any advantages over these determinants at present. There is also new and emerging understanding of the role of lifestyle and environmental factors in mediating vulnerability to mood disorder. The influence of ethnicity and migration, on the other hand, is far more complex than initially envisaged. SummaryRecent evidence on sociodemographic determinants of mood disorders confirms associations derived from existing literature. There is also new and emerging evidence on how quality of sleep, diet and the environment influence risk of mood disorders. Culture and ethnicity, depending on context, may contribute to both vulnerability and resilience. Socioeconomic deprivation may be the final common pathway through which several sociodemographic and cultural determinants of mood disorders act.

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Section: Sociodemographic Determinantsmentioning

confidence: 99%

Sociodemographic and cultural determinants of mood disorders

D’cruz¹,

Chaturvedi

2021

Current Opinion in Psychiatry

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“…It is suggested that the length of stay is influenced by the patient's characteristics and external factors such as social characteristics. For example, lower functioning and longer duration of the current episode were predictors for the length of stay in adolescent inpatients with mood disorders (4). A retrospective study showed that functioning and pre-admission psychiatric polypharmacy predicted 30-day re-hospitalization in patients with BD-I (5).…”

Section: Introductionmentioning

confidence: 99%

“…However, only a few studies have examined predictors of length of stay and hospitalization times in patients with BD (2,4), and the key factors influencing length of stay and hospitalization times are still unclear. This was a multicenter cohort study of BD.…”

Section: Introductionmentioning

confidence: 99%

Factors associated with hospitalization times and length of stay in patients with bipolar disorder

Shi,

Zhao,

Yang

et al. 2023

Front. Psychiatry

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AimAppraise the clinical features and influencing factors of the hospitalization times and length of stay in bipolar disorder (BD) patients.MethodsThis is a multicenter, observational, cohort study of patients diagnosed of type I or type II bipolar disorder. Five hundred twenty outpatients in seven hospitals from six cities in China were recruited from February 2013 to June 2014 and followed up using a continuous sampling pattern. The research included a retrospective period of 12 months and the prospective period of 9 months. The demographic and clinical features of the patients were collected. The influencing factors that could affect the length of stay (number of days spent in the hospital in the prospective period) were analyzed by poisson's regression and the hospitalization times (times of hospitalization in the prospective and retrospective period) was analyzed by general linear model. The selected variables included gender, age, years of education, occupational status, residence status, family history of mental disease, comorbid substance abuse, comorbid anxiety disorder, times of suicide (total suicide times that occurred in the retrospective and prospective period), polarity of the first mood episode, and BD type(I/II).ResultsPoisson's regression analysis showed that suicide times [Incidence Rate Ratio (IRR) = 1.20, p < 0.001], use of antipsychotic (IRR = 0.62, p = 0.011), and use of antidepressant (IRR = 0.56, p < 0.001) were correlated to more hospitalization times. Linear regression analysis showed that BD type II (β = 0.28, p = 0.005) and unemployment (β = 0.16, p = 0.039) which might mean longer duration of depression and poor function were correlated to longer length of stay. However, patients who experienced more suicide times (β = −0.21, p = 0.007) tended to have a shorter length of stay.ConclusionOverall, better management of the depressive episode and functional rehabilitation may help to reduce the length of stay. BD patients with more hospitalization times were characterized by higher risk of suicide and complex polypharmacy. Patients at high risk of suicide tended to have inadequate therapy and poor compliance, which should be assessed and treated adequately during hospitalization.Clinical trial registrationwww.ClinicalTrials.gov, Identifier: NCT01770704.

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“…Existing research tends to address characteristics influencing admissions, such as length of stay or therapeutic outcomes following an admission (Benarous et al, 2021 ). Less is known about adolescent inpatient units, such as their key features and how and why these specialist programs address major mental health issues (in terms of how they operate and function) (Delaney, 2019 ; Hayes et al, 2018 ; Mojtabai et al, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Key features of adolescent inpatient units and development of a checklist to improve consistency in reporting of settings

Hayes

Simmons

Palmer

et al. 2022

Psychiatric Ment Health Nurs

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What is known on the subject?• Little is known about adolescent inpatient units, key features which define them, and how these essential services operate and deliver care.• Greater attention to operational models, services, and philosophies of practice will improve reporting and allow for the advancement of knowledge, comparison of study results, and a clearer direction for mental health nursing clinicians and researchers.

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Looking for the Good Timing: Predictors of Length of Stay and Therapeutic Outcomes in Adolescent Inpatients with Severe or Treatment-Refractory Mood Disorders

Cited by 6 publications

References 44 publications

Sociodemographic and cultural determinants of mood disorders

Sociodemographic and cultural determinants of mood disorders

Factors associated with hospitalization times and length of stay in patients with bipolar disorder

Key features of adolescent inpatient units and development of a checklist to improve consistency in reporting of settings

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