Risk Calculators in Bipolar Disorder: A Systematic Review

Ribeiro, Joana; Pereira, Daniela; Salagre, Estela; Coroa, Manuel; Oliveira, Pedro Santos Mello de; Santos, Vítor; Madeira, Nuno; Grande, Iría; Vieta, Eduard

doi:10.3390/brainsci10080525

Cited by 21 publications

(16 citation statements)

References 39 publications

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“…Bipolar disorder (BD) is a chronic psychiatric disorder characterized by the alternation of different phases, specifically hypomanic/manic and major depressive episodes. BD affects 2–3% of the general population worldwide and its onset typically occurs during adolescence or early adulthood [ 1 ]. The Fifth Edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) includes three main types of BD in the category of “Bipolar and related disorders”: BD type I, BD type II, and cyclothymic disorder [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Neutrophil-to-Lymphocyte, Platelet-to-Lymphocyte and Monocyte-to-Lymphocyte Ratio in Bipolar Disorder

et al. 2021

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Background: Several inflammatory hypotheses have been suggested to explain the etiopathogenesis of bipolar disorder (BD) and its different phases. Neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), and monocyte-to-lymphocyte (MLR) ratios have been proposed as potential peripheral biomarkers of mood episodes. Methods: We recruited 294 patients affected by BD, of which 143 were experiencing a (hypo)manic episode and 151 were in a depressive phase. A blood sample was drawn to perform a complete blood count. NLR, PLR, and MLR were subsequently calculated. A t-test was performed to evaluate differences in blood cell counts between depressed and (hypo)manic patients and a regression model was then computed. Results: Mean values of neutrophils, platelets, mean platelet volume, NLR, PLR, and MLR were significantly higher in (hypo)manic than depressed individuals. Logistic regression showed that PLR may represent an independent predictor of (hypo)mania. Conclusions: Altered inflammatory indexes, particularly PLR, may explain the onset and recurrence of (hypo)manic episodes in patients with BD. As inflammatory ratios represent economical and accessible markers of inflammation, further studies should be implemented to better elucidate their role as peripheral biomarkers of BD mood episodes.

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Section: Introductionmentioning

confidence: 99%

Neutrophil-to-Lymphocyte, Platelet-to-Lymphocyte and Monocyte-to-Lymphocyte Ratio in Bipolar Disorder

et al. 2021

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“…Some patients will experience an early functional recovery, others might exhibit severe functional difficulties from illness onset and some subgroups might experience (persistent or transitory) mild to moderate functional impairment, which still have a negative impact on their daily life. Hence, the real challenge is to predict early in the course of the disease which individual will fall into each of these trajectories in order to be able to design earlier and more tailored treatments for social and personal recovery [ 2 , 9 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Exploring Risk and Resilient Profiles for Functional Impairment and Baseline Predictors in a 2-Year Follow-Up First-Episode Psychosis Cohort Using Latent Class Growth Analysis

Salagre

Grande

Solé

et al. 2020

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Being able to predict functional outcomes after First-Episode Psychosis (FEP) is a major goal in psychiatry. Thus, we aimed to identify trajectories of psychosocial functioning in a FEP cohort followed-up for 2 years in order to find premorbid/baseline predictors for each trajectory. Additionally, we explored diagnosis distribution within the different trajectories. A total of 261 adults with FEP were included. Latent class growth analysis identified four distinct trajectories: Mild impairment-Improving trajectory (Mi-I) (38.31% of the sample), Moderate impairment-Stable trajectory (Mo-S) (18.39%), Severe impairment-Improving trajectory (Se-I) (12.26%), and Severe impairment-Stable trajectory (Se-S) (31.03%). Participants in the Mi-I trajectory were more likely to have higher parental socioeconomic status, less severe baseline depressive and negative symptoms, and better premorbid adjustment than individuals in the Se-S trajectory. Participants in the Se-I trajectory were more likely to have better baseline verbal learning and memory and better premorbid adjustment than those in the Se-S trajectory. Lower baseline positive symptoms predicted a Mo-S trajectory vs. Se-S trajectory. Diagnoses of Bipolar disorder and Other psychoses were more prevalent among individuals falling into Mi-I trajectory. Our findings suggest four distinct trajectories of psychosocial functioning after FEP. We also identified social, clinical, and cognitive factors associated with more resilient trajectories, thus providing insights for early interventions targeting psychosocial functioning.

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“…Although not exhaustive, Table 1 provides an overview of key studies presenting risk algorithms predicting a range of psychopathologies including psychosis, bipolar disorder (for a review, see Silva Ribeiro et al, 2020), depression, attention-deficit/hyperactivity disorder (ADHD), and to a lesser extent, internalizing/externalizing problems.…”

Section: Risk Calculator Parameters and Exemplars In Vulnerable Phases Of The Clinical Sequencementioning

confidence: 99%

Translating RDoC to real-world impact in developmental psychopathology: A neurodevelopmental framework for application of mental health risk calculators

et al. 2021

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The National Institute of Mental Health's Research Domain Criteria (RDoC) framework has prompted a paradigm shift from categorical psychiatric disorders to considering multiple levels of vulnerability for probabilistic risk of disorder. However, the lack of neurodevelopmentally based tools for clinical decision making has limited the real-world impact of the RDoC. Integration with developmental psychopathology principles and statistical methods actualize the clinical implementation of RDoC to inform neurodevelopmental risk. In this conceptual paper, we introduce the probabilistic mental health risk calculator as an innovation for such translation and lay out a research agenda for generating an RDoC- and developmentally informed paradigm that could be applied to predict a range of developmental psychopathologies from early childhood to young adulthood. We discuss methods that weigh the incremental utility for prediction based on intensity and burden of assessment, the addition of developmental change patterns, considerations for assessing outcomes, and integrative data approaches. Throughout, we illustrate the risk calculator approach with different neurodevelopmental pathways and phenotypes. Finally, we discuss real-world implementation of these methods for improving early identification and prevention of developmental psychopathology. We propose that mental health risk calculators can build a needed bridge between the RDoC multiple units of analysis and developmental science.

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Risk Calculators in Bipolar Disorder: A Systematic Review

Cited by 21 publications

References 39 publications

Neutrophil-to-Lymphocyte, Platelet-to-Lymphocyte and Monocyte-to-Lymphocyte Ratio in Bipolar Disorder

Neutrophil-to-Lymphocyte, Platelet-to-Lymphocyte and Monocyte-to-Lymphocyte Ratio in Bipolar Disorder

Exploring Risk and Resilient Profiles for Functional Impairment and Baseline Predictors in a 2-Year Follow-Up First-Episode Psychosis Cohort Using Latent Class Growth Analysis

Translating RDoC to real-world impact in developmental psychopathology: A neurodevelopmental framework for application of mental health risk calculators

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