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Record W4223449912 · doi:10.1136/bmjopen-2021-055454

Assessing cardiometabolic parameter monitoring in inpatients taking a second-generation antipsychotic: The CAMI-SGA study – a cross-sectional study

2022· article· en· W4223449912 on OpenAlexafffundabout
Jennifer Fontaine, E. Chin, Jean-François Provencher, A Rainone, Dana Wazzan, Carmella Roy, Soham Rej, Marie Lordkipanidzé, Vincent Dagenais‐Beaulé

Bibliographic record

VenueBMJ Open · 2022
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsMontreal Heart InstituteMcGill UniversityMcGill University Health CentreUniversité de MontréalJewish General Hospital
FundersFonds de Recherche du Québec - SantéUniversité de MontréalJewish General Hospital
KeywordsMedicineQuetiapineRisperidoneCross-sectional studyBody mass indexAntipsychoticOlanzapineClozapineBlood pressureWaistInternal medicineBipolar disorderSchizophrenia (object-oriented programming)Psychiatry

Abstract

fetched live from OpenAlex

OBJECTIVES: This study aims to determine the proportion of initial cardiometabolic assessment and its predicting factors in adults with schizophrenia, bipolar disorder or other related diagnoses for whom a second-generation antipsychotic was prescribed in the hospital setting. DESIGN: Cross-sectional study. SETTING: The psychiatry unit of a Canadian tertiary care teaching hospital in Montreal, Canada. PARTICIPANTS: 402 patients with aforementioned disorders who initiated, restarted or switched to one of the following antipsychotics: clozapine, olanzapine, risperidone, paliperidone or quetiapine, between 2013 and 2016. PRIMARY OUTCOME MEASURES: We assessed the proportion of cardiometabolic parameters monitored. SECONDARY OUTCOME MEASURES: We identified predictors that influence the monitoring of cardiometabolic parameters and we assessed the proportion of adequate interventions following the screening of uncontrolled blood pressure and fasting glucose or glycated haemoglobin (HbA1c) results. RESULTS: Only 37.3% of patients received monitoring for at least three cardiometabolic parameters. Blood pressure was assessed in 99.8% of patients; lipid profile in 24.4%; fasting glucose or HbA1c in 33.3% and weight or body mass index in 97.8% of patients while waist circumference was assessed in 4.5% of patients. For patients with abnormal blood pressure and glycaemic values, 42.3% and 41.2% subsequent interventions were done, respectively. The study highlighted the psychiatric diagnosis (substance induced disorder OR 0.06 95% CI 0.00 to 0.44), the presence of a court-ordered treatment (OR 0.79 95% CI 0.35 to 1.79) and the treating psychiatrist (up to OR 34.0 95% CI 16.2 to 140.7) as predictors of cardiometabolic monitoring. CONCLUSIONS: This study reports suboptimal baseline cardiometabolic monitoring of patients taking an antipsychotic in a Canadian hospital. Optimising collaboration within a multidisciplinary team may increase cardiometabolic 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 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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.265
GPT teacher head0.508
Teacher spread0.243 · 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 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

Citations4
Published2022
Admission routes3
Has abstractyes

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