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Record W3093308502 · doi:10.1089/cap.2020.0096

Impact of Antipsychotic Guidelines on Laboratory Monitoring in Children with Neurodevelopmental Disorders

2020· article· en· W3093308502 on OpenAlexaffabout
Imaan Kara, Melanie Penner

Bibliographic record

VenueJournal of Child and Adolescent Psychopharmacology · 2020
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineGuidelinePediatricsAntipsychoticRetrospective cohort studyTherapeutic drug monitoringEmergency medicinePsychiatrySchizophrenia (object-oriented programming)Internal medicineDrug

Abstract

fetched live from OpenAlex

Objectives: The Canadian Alliance for Monitoring Effectiveness and Safety of Antipsychotics in Children (CAMESA) guidelines provide monitoring recommendations for children who are treated with second-generation antipsychotics (SGAs). The objective of this study was to determine the impact of the CAMESA guidelines on SGA monitoring in children with neurodevelopmental disorders. Methods: A retrospective chart review compared laboratory monitoring in children treated with SGAs who were referred to a tertiary psychopharmacology clinic before (2008–2011) and after (2013–2016) CAMESA publication. Chi-squared tests were used to detect changes in SGA use and monitoring between the two time periods. Results: A total of 345 charts were reviewed ( n = 136 pre-CAMESA, n = 209 post-CAMESA). The proportion of children taking an SGA increased significantly (35% vs. 49%; p = 0.02) as did the duration of SGA treatment before tertiary assessment (18.6 months vs. 27.2 months; p = 0.03). SGA monitoring data were missing in 40% of charts pre-CAMESA and in 31% of charts post-CAMESA. The proportion of patients with any available laboratory monitoring did not change between the time periods (35% pre-CAMESA vs. 39% post-CAMESA; p = 0.56). Similarly, the proportion of patients with full laboratory monitoring was not significantly different between time periods (15% pre-CAMESA vs. 25% post-CAMESA; p = 0.23). Conclusions: SGA monitoring rates did not significantly improve after CAMESA guideline publication. To maximize benefit and mitigate risks of these medications, there is a need to identify barriers to SGA monitoring.

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 score0.014
Threshold uncertainty score0.394

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 integrity0.0000.001
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 head0.037
GPT teacher head0.390
Teacher spread0.353 · 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

Citations7
Published2020
Admission routes2
Has abstractyes

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