Evidence map›Paper›PMID 38454631›Full record

ArticleJournal of diabetes science and technology2024

Novel Automated Self-adjusting Subcutaneous Insulin Algorithm Improves Glycemic Control and Physician Efficiency in Hospitalized Patients.

Paras B Mehta, Michael A Kohn, Esther Rov-Ikpah, Craig San Luis, Craig Johnson, Gwendolyn Lee, Suneil Koliwad, Robert J Rushakoff

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of diabetes science and technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Observational
  2. Review
  3. Article
  4. Association Between Daily Insulin Dose Adjustments and Glycemic Control in Noncritically Ill Hospitalized Hyperglycemic Patients: A Retrospective Cohort Study.Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2025
    Article
  5. Article
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

8 authors.

Paras B MehtaDivision of Endocrinology and Metabolism, University of California, San Francisco, CA, USA.
Michael A KohnDepartment of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.ORCID 0000-0001-5459-5044
Esther Rov-IkpahInstitute of Nursing Excellence, University of California, San Francisco, CA, USA.
Craig San LuisDepartment of Clinical Systems, University of California, San Francisco, CA, USA.
Craig JohnsonDepartment of Health Informatics, University of California, San Francisco, CA, USA.
Gwendolyn LeeDepartment of Medicine, University of California, San Francisco, CA, USA.
Suneil KoliwadDivision of Endocrinology and Metabolism, University of California, San Francisco, CA, USA.ORCID 0000-0002-7367-1054
Robert J RushakoffDivision of Endocrinology and Metabolism, University of California, San Francisco, CA, USA.ORCID 0000-0001-7502-9092

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHyperglycemia occurs in 22% to 46% of hospitalized patients, negatively affecting patient outcomes, including mortality, inpatient complications, length of stay, and hospital costs. Achieving inpatient glycemic control is challenging due to inconsistent caloric intake, changes from home medications, a catabolic state in the setting of acute illness, consequences of acute inflammation, intercurrent infection, and limitations in labor-intensive glucose monitoring and insulin administration.

methodWe conducted a retrospective cross-sectional analysis at the University of California San Francisco hospitals between September 3, 2020 and September 2, 2021, comparing point-of-care glucose measurements in patients on nil per os (NPO), continuous total parenteral nutrition, or continuous tube feeding assigned to our novel automated self-adjusting subcutaneous insulin algorithm (SQIA) or conventional, physician-driven insulin dosing. We also evaluated physician efficiency by tracking the number of insulin orders placed or modified.

resultsThe proportion of glucose in range (70-180 mg/dL) was higher in the SQIA group than in the conventional group (71.0% vs 69.0%,

conclusionsThe SQIA reduced severe hyperglycemia, hypoglycemia, and severe hypoglycemia compared with conventional insulin dosing. It also improved physician efficiency by reducing the number of order modifications a physician had to place.

Indexed as

AlgorithmsBlood GlucoseGlycemic ControlHypoglycemic AgentsInsulinAgedCross-Sectional StudiesFemaleHospitalizationHumansHyperglycemiaHypoglycemiaInjections, SubcutaneousMaleMiddle AgedRetrospective StudiesBlood GlucoseHypoglycemic AgentsInsulinblood glucoseinpatient diabetes managementnil per osphysician efficiencyself-adjusting insulin administrationtotal parenteral nutritiontube feeding

Identifiers

PMID38454631
PMCPMC11089873

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Registered trials

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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 OpenQuestion graph.