336. PSYCHIATRIC RISKS OF CORTICOSTEROIDS: FINDINGS FROM A SYSTEMATIC REVIEW AND META-ANALYSIS
Bibliographic record
Abstract
Abstract Background Corticosteroids (CSs) are widely used to treat autoimmune diseases, allergic conditions, and cancers, but they are often associated with psychiatric side effects, such as insomnia, anxiety, depression, mania, and psychosis. Comprehensive evaluations of psychiatric risks, including acute and long-term effects, as well as their associations with dose and cumulative exposure, remain limited. Understanding these relationships is crucial for optimizing therapeutic strategies and minimizing psychiatric risks. Aims & Objectives This study aimed to systematically evaluate the psychiatric risks associated with corticosteroid use, focusing on both acute and long-term settings. The primary objectives included assessing the risks of depression, mania, and psychosis, and examining their associations with dose, and duration. Method A systematic literature search was conducted in MEDLINE and Embase databases up to March 22, 2024, using keywords related to corticosteroids and psychiatric symptoms. Observational studies with clearly defined psychiatric outcomes and quantifiable data were included. Data were analyzed using a random-effects model, and heterogeneity was assessed with the I² statistic. For studies reporting multiple non-independent outcomes, we conducted a three-level meta-analysis to account for the dependency between effect sizes within studies. In addition, qualitative data were synthesized to explore patterns of symptom progression and their relationship with treatment characteristics. The risk of bias was evaluated using the Newcastle-Ottawa Scale. Results A total of 69 studies were included, comprising cross-sectional, cohort, pre-post, case-control, and other observational study designs. The three-level meta-analysis of depressive symptoms, based on six studies with seven groups and 10 effect sizes, revealed a pooled standardized mean difference (SMD) of 1.01 (95%Confidence Interval (CI)=0.40–1.61, p<0.01) with significant heterogeneity (I²=84%). Six acute-phase studies on mania and depressive symptoms demonstrated that mania was more frequently reported than depressive symptoms, with a pooled odds ratio (OR) of 2.37 (95%CI=1.52–3.69, p<0.01) and low heterogeneity (I²=0%). For psychosis, a meta-analysis of six studies reported a pooled proportion of 3.0% (95%CI=1.0%–8.6%), with high heterogeneity (I²=92%) indicating variability across studies. Qualitative assessments suggested that high doses and prolonged use of CSs were consistently associated with an increased risk of psychiatric symptoms. Acute symptoms, such as mania and psychosis, were often reported within 3–14 days of treatment initiation, whereas depressive symptoms were more frequently associated with long-term exposure. Discussion & Conclusions This meta-analysis highlighted the differential risks of psychiatric symptoms associated with CS use. Mania and psychosis were more frequent during acute treatment, particularly at high doses, while depression was predominantly observed in long-term use. These findings underscore the importance of early monitoring and individualized treatment strategies, especially for patients receiving high-dose or prolonged CS treatment. The high heterogeneity observed in studies on depression and psychosis reflects the complexity of these risks and the need for further research to explore contributing factors. This study provides new insights into the dose- and time-dependent effects of CS-induced psychiatric symptoms, offering effective risk management strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.051 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".