Evidence map›Paper›PMID 32783464›Full record

ArticleJournal of diabetes science and technology2021

Automated Self-Adjusting Subcutaneous Insulin Algorithm for Patients NPO or on TPN or Enteral Feedings.

Sophie Patzek, Heidemarie W MacMaster, Esther Rov-Ikpah, Craig San Luis, Craig Johnson, Venkateswarlu Juttukonda, Robert J Rushakoff

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Article in Journal of diabetes science and technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

3 citing papers in PubMed.

  1. Observational
  2. Inpatient Insulin Dosing Calculators.Diabetes spectrum : a publication of the American Diabetes Association · 2025
    Article
  3. Article
4 · The record

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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

7 authors.

Sophie PatzekDivision of Endocrinology and Metabolism, University of California, San Francisco, CA, USA.ORCID 0000-0001-7002-5340
Heidemarie W MacMasterDepartment of Pharmacy, Lahey Hospital and Medical Center, Burlington, MA, USA.
Esther Rov-IkpahInstitute for 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.
Venkateswarlu JuttukondaDepartment of Clinical Applications & Analytics, University of California, San Francisco, CA, USA.
Robert J RushakoffDivision of Endocrinology and Metabolism, University of California, San Francisco, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPerioperative diabetes patients are often treated with sliding-scale insulin, despite a lack of evidence to support therapeutic effectiveness. We introduced an automated subcutaneous insulin algorithm (SQIA) to improve glycemic control in these patients while maintaining the simplicity of a q4 hour adjustable sliding-scale insulin order set.

methodsIn this pilot study, we implemented a fully programmed, self-adjusting SQIA as part of a structured order set in the electronic medical record for adult patients who are nil per os, or on continuous enteral tube feedings or total parenteral nutrition. The nurse only enters the current glucose in the Medication Administration Record, and then the calculated dose is shown. The new dose is based on previous dose, and current and previous glucoses. The SQIA titrates the glucose to 120-180 mg/dL. For this pilot, this order set was utilized for complex perioperative oncologic patients.

resultsThe median duration on the SQIA was 58 hours. Glucoses at titration initiation were highest at 206 ± 63 mg/dL, and came down to 156 ± 29 mg/dL by 72 hours. The majority of measured glucoses (66.8%, n = 647) were maintained between 80 and 180 mg/dL. There were no glucoses lower than 60 mg/dL, and only 0.3% (n = 3) were below 70 mg/dL. There was a low rate of errors (1%).

conclusionsA simple automated SQIA can be used to titrate insulin to meet the changing metabolic requirements of individuals perioperatively and maintain glucose within the target range for these hospitalized patients.

Indexed as

HyperglycemiaInsulinAdultAlgorithmsBlood GlucoseEnteral NutritionHumansHypoglycemic AgentsPilot ProjectsBlood GlucoseHypoglycemic AgentsInsulinhospital diabeteshyperalimentation diabetesinpatient diabetesnil per os diabetes

Identifiers

PMID32783464
PMCPMC8655274

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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.