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Record W4403434484 · doi:10.47363/jpsrr/2024(6)173

Neuroplasticity Alterations Induced by Isotretinoin Use in RARAGene Polymorphism is Associated with Increased Risk of Depressionand Suicidal Ideation in Patients with Vitamin D Deficiency: ASystematic Review and Meta-Analysis

2024· review· en· W4403434484 on OpenAlexaboutno aff
Borges Julian YV

Bibliographic record

VenueJournal of Psychiatry Research Reviews & Reports · 2024
Typereview
Languageen
FieldMedicine
TopicAcne and Rosacea Treatments and Effects
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisSuicidal ideationDepression (economics)vitamin D deficiencyMedicineVitamin D and neurologyBioinformaticsOncologyInternal medicineBiologyPoison controlSuicide preventionEnvironmental health

Abstract

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Rationale: Isotretinoin is widely used for severe acne treatment, but concerns have emerged regarding its potential association with depression and suicidal ideation. Previous studies have produced mixed findings, necessitating a comprehensive evaluation of the evidence. This systematic review and meta-analysis aim to clarify the association between isotretinoin use and the onset of depression or suicidal ideation, focusing on genetic predispositions, particularly in patients with vitamin D deficiency.Objectives: This review assesses the risk of depression and suicidal ideation in patients treated with isotretinoin for severe acne compared to those not using isotretinoin. A secondary focus is placed on identifying specific genetic factors, such as polymorphisms in the RARA and LEP genes, that may predispose patients to these psychiatric side effects.Eligibility Criteria: Randomized controlled trials (RCTs), cohort studies, and case-control studies comparing isotretinoin users to non-users were included. Exclusion criteria included studies that lacked a comparator group or did not report psychiatric outcomes (depression or suicidal ideation).Outcomes: The primary outcome was the incidence of depression or suicidal ideation among isotretinoin users compared to non-users. Secondary outcomes examined the influence of genetic polymorphisms, specifically in the RARA and LEP genes, on the risk of developing psychiatric side effects.Risk of Bias: Risk of bias was assessed using the Cochrane Risk of Bias tool for randomized trials and the Newcastle-Ottawa Scale for observational studies. The overall quality of the included studies was moderate to high.Synthesis Methods: A random-effects meta-analysis was performed to pool odds ratios (ORs) with 95% confidence intervals (CIs). Heterogeneity was assessed using the I² statistic, and sensitivity analyses were conducted to ensure the robustness of the findings.Included Studies: Fifteen studies were included, comprising 3 randomized controlled trials, 7 cohort studies, and 5 case-control studies, with a total of 8,000 isotretinoin users and 10,000 non-users. The studies were conducted in diverse clinical settings with a follow-up range of 6 months to 5 years.Synthesis of Results: The pooled analysis demonstrated a significant association between isotretinoin use and an increased risk of depression (OR: 1.3, 95% CI: 1.1–1.5, p < 0.05). Specific genetic polymorphisms, particularly in the RARA and LEP genes, were identified as potential risk factors for developing depression among isotretinoin users, particularly in patients with concurrent vitamin D deficiency.Conclusions: Isotretinoin use is associated with an increased risk of depression, particularly in individuals with specific genetic polymorphisms such as RARA and LEP. Clinicians should consider conduct precision medicine genetic testing testing for these polymorphisms before initiating isotretinoin treatment and closely monitor patients for psychiatric alterations, mood changes, especially those with with vitamin D deficiency or genetic predisposition to depression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.018
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.089
GPT teacher head0.385
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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