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Record W2403664471 · doi:10.5498/wjp.v5.i4.412

Risk for emerging bipolar disorder, variants, and symptoms in children with attention deficit hyperactivity disorder, now grown up

2015· article· en· W2403664471 on OpenAlexfundno aff
Ahmed Z. Elmaadawi

Bibliographic record

VenueWorld Journal of Psychiatry · 2015
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsnot available
FundersJanssen PharmaceuticalsNational Institute of Nursing ResearchUniversity of Illinois at Urbana-ChampaignPurdue PharmaUniversity of California, IrvineMcGill UniversityCincinnati Children's Hospital Medical CenterNational Institutes of HealthOhio State UniversityPurdue UniversityNational Institute on Drug AbuseShireYork UniversityU.S. Department of JusticeEli Lilly and CompanyUniversity of PittsburghMayo ClinicNational Institute of Mental HealthPfizerFlorida International UniversityAutism Speaks
KeywordsIrritabilityAttention deficit hyperactivity disorderBipolar disorderPsychiatryPathognomonicAttention deficitMedicineMethylphenidatePediatricsPsychologyClinical psychologyMoodInternal medicineCognitionDisease

Abstract

fetched live from OpenAlex

AIM: To determine the prevalence of bipolar disorder (BD) and sub-threshold symptoms in children with attention deficit hyperactivity disorder (ADHD) through 14 years' follow-up, when participants were between 21-24 years old. METHODS: First, we examined rates of BD type I and II diagnoses in youth participating in the NIMH-funded Multimodal Treatment Study of ADHD (MTA). We used the diagnostic interview schedule for children (DISC), administered to both parents (DISC-P) and youth (DISCY). We compared the MTA study subjects with ADHD (n = 579) to a local normative comparison group (LNCG, n = 289) at 4 different assessment points: 6, 8, 12, and 14 years of follow-ups. To evaluate the bipolar variants, we compared total symptom counts (TSC) of DSM manic and hypomanic symptoms that were generated by DISC in ADHD and LNCG subjects. Then we sub-divided the TSC into pathognomonic manic (PM) and non-specific manic (NSM) symptoms. We compared the PM and NSM in ADHD and LNCG at each assessment point and over time. We also evaluated the irritability as category A2 manic symptom in both groups and over time. Finally, we studied the irritability symptom in correlation with PM and NSM in ADHD and LNCG subjects. RESULTS: DISC-generated BD diagnosis did not differ significantly in rates between ADHD (1.89%) and LNCG 1.38%). Interestingly, no participant met BD diagnosis more than once in the 4 assessment points in 14 years. However, on the symptom level, ADHD subjects reported significantly higher mean TSC scores: ADHD 3.0; LNCG 1.7; P < 0.001. ADHD status was associated with higher mean NSM: ADHD 2.0 vs LNCG 1.1; P < 0.0001. Also, ADHD subjects had higher PM symptoms than LNCG, with PM means over all time points of 1.3 ADHD; 0.9 LNCG; P = 0.0001. Examining both NSM and PM, ADHD status associated with greater NSM than PM. However, Over 14 years, the NSM symptoms declined and changed to PM over time (df 3, 2523; F = 20.1; P < 0.0001). Finally, Irritability (BD DSM criterion-A2) rates were significantly higher in ADHD than LNCG (χ(2) = 122.2, P < 0.0001), but irritability was associated more strongly with NSM than PM (df 3, 2538; F = 43.2; P < 0.0001). CONCLUSION: Individuals with ADHD do not appear to be at significantly greater risk for developing BD, but do show higher rates of BD symptoms, especially NSM. The greater linkage of irritability to NSM than to PM suggests caution when making BD diagnoses based on irritability alone as one of 2 (A-level) symptoms for BD diagnosis, particularly in view of its frequent presentation with other psychopathologies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.688

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.252
Teacher spread0.244 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2015
Admission routes1
Has abstractyes

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