Evidence mapPaperPMID 39132476Full record

ArticlemedRxiv : the preprint server for health sciences2024

Medications that Regulate Gastrointestinal Transit Influence Inpatient Blood Glucose.

Amanda Momenzadeh, Caleb Cranney, So Yung Choi, Catherine Bresee, Mourad Tighiouart, Roma Gianchandani, Joshua Pevnick, Jason H Moore, Jesse G Meyer

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Amanda MomenzadehDepartment of Computational Biomedicine; Cedars-Sinai; Los Angeles, CA USA.
Caleb CranneyDepartment of Computational Biomedicine; Cedars-Sinai; Los Angeles, CA.
So Yung ChoiBiostatistics Shared Resource; Cedars-Sinai; Los Angeles, CA.
Catherine BreseeBiostatistics Shared Resource; Cedars-Sinai; Los Angeles, CA.
Mourad TighiouartBiostatistics Shared Resource; Cedars-Sinai; Los Angeles, CA.
Roma GianchandaniDivision of Endocrinology, Diabetes & Metabolism; Cedars-Sinai; Los Angeles, CA.
Joshua PevnickDivision of General Internal Medicine; Cedars-Sinai; Los Angeles, CA.
Jason H MooreDepartment of Computational Biomedicine; Cedars-Sinai; Los Angeles, CA.
Jesse G MeyerDepartment of Computational Biomedicine; Cedars-Sinai; Los Angeles, CA.ORCID 0000-0003-2753-3926

Funding

UCLA Clinical and Translational Science InstituteUL1TR001881 · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2025 to 2025
$9.9M
NCATS NIH HHS UL1 TR001881
6 · The paper itself

Abstract

Objective: A multitude of factors affect a hospitalized individual's blood glucose (BG), making BG difficult to predict and manage. Beyond medications well established to alter BG, such as beta-blockers, there are likely many medications with undiscovered effects on BG variability. Identification of these medications and the strength and timing of these relationships has potential to improve glycemic management and patient safety. Materials and Methods: EHR data from 103,871 inpatient encounters over 8 years within a large, urban health system was used to extract over 500 medications, laboratory measurements, and clinical predictors of BG. Feature selection was performed using an optimized Lasso model with repeated 5-fold cross-validation on the 80% training set, followed by a linear mixed regression model to evaluate statistical significance. Significant medication predictors were then evaluated for novelty against a comprehensive adverse drug event database. Results: We found 29 statistically significant features associated with BG; 24 were medications including 10 medications not previously documented to alter BG. The remaining five factors were Black/African American race, history of type 2 diabetes mellitus, prior BG (mean and last) and creatinine. Discussion: The unexpected medications, including several agents involved in gastrointestinal motility, found to affect BG were supported by available studies. This study may bring to light medications to use with caution in individuals with hyper- or hypoglycemia. Further investigation of these potential candidates is needed to enhance clinical utility of these findings. Conclusion: This study uniquely identifies medications involved in gastrointestinal transit to be predictors of BG that may not well established and recognized in clinical practice.

Indexed as

electronic health recordsendocrinologyhospitalmedication systemspharmacologyregression analysis

Identifiers

PMID39132476
PMCPMC11312652

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.