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Record W4378715438 · doi:10.2196/48302

Intravenous Magnesium: Prompt Use for Asthma in Children Treated in the Emergency Department (IMPACT-ED): Protocol for a Multicenter Pilot Randomized Controlled Trial

2023· article· en· W4378715438 on OpenAlexaffvenue
Michael D. Johnson, Bradley J. Barney, Joseph E. Rower, Yaron Finkelstein, Joseph J. Zorc

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldNursing
TopicMagnesium in Health and Disease
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood Institute
KeywordsEmergency departmentMedicineAsthmaProtocol (science)Randomized controlled trialMedical emergencyEmergency medicinePhysical therapyAlternative medicineSurgeryNursingInternal medicine

Abstract

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BACKGROUND: Children managed for asthma in an emergency department (ED) may be less likely to be hospitalized if they receive intravenous magnesium sulfate (IVMg). Asthma guidelines recommend IVMg for severely sick children but note a lack of evidence to support this recommendation. All previous trials of IVMg in children with asthma have been too small to answer whether IVMg is effective and safe. A few major questions remain about IVMg. First, it has not been tested early in the course of ED treatment, when the impact on hospitalization would be greatest. Second, the clinical impact of hypotension, a known adverse effect of IVMg, has not been well characterized in previous research. Third, no trials have compared different IVMg doses or serial serum magnesium (total and ionized) concentrations to optimize dosing, so the most effective dose is unknown. A large, conclusive, randomized, placebo-controlled clinical trial of IVMg might be challenging due to the need to enroll and complete study procedures quickly, a lack of understanding of blood pressure changes after IVMg, and a lack of pharmacologic information to guide the optimal doses of IVMg to be tested. Therefore, a pilot study to inform the above gaps is warranted before conducting a definitive trial. OBJECTIVE: The objectives of this study are to (1) demonstrate the feasibility of enrolling children with severe acute asthma in the ED in a multicenter, randomized controlled trial of a placebo, low-dose IVMg, or high-dose IVMg; (2) demonstrate the feasibility of timely delivery of study medication, assessment of blood pressure, and evaluation of adverse events in a standardized protocol; and (3) externally validate a previously constructed pharmacokinetic model and develop a combined pharmacokinetic/pharmacodynamic model for IVMg using magnesium (total and ionized) serum concentrations and their correlation with measures of efficacy and safety. METHODS: This pilot trial tests procedures and gathers information to plan a definitive trial. The pilot trial will enroll as many as 90 children across 3 sites, randomize each child to 1 of 3 study arms, measure blood pressure frequently, and collect 3 blood samples from each participant with corresponding clinical asthma scores. RESULTS: The project was funded by the National Heart, Lung, and Blood Institute (1 R34HL152047-2) in March 2022. Enrollment began in September 2022, and 43 children have been enrolled as of April 2023. We will submit the results for publication in late 2023. CONCLUSIONS: The results of this study will guide the planning of a large, definitive, multicenter trial powered to evaluate if IVMg reduces hospitalization. Blood pressure measurements will inform a monitoring plan for the larger trial, and blood samples and asthma scores will be used to validate pharmacologic models to select the optimal dose of IVMg to be evaluated in the definitive trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT05166811; https://clinicaltrials.gov/ct2/show/NCT05166811. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48302.

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)0.042
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.050
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.041
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0100.006
Bibliometrics0.0020.003
Science and technology studies0.0030.004
Scholarly communication0.0050.004
Open science0.0040.002
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0500.009

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 head0.167
GPT teacher head0.534
Teacher spread0.367 · 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 designRandomized trial
Domainnot available
GenreProtocol

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
Published2023
Admission routes2
Has abstractyes

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