Evidence map›Paper›PMID 26270134›Full record

Trial reportDiabetes technology & therapeutics2015

Bolus Estimation--Rethinking the Effect of Meal Fat Content.

Srinivas Laxminarayan, Jaques Reifman, Stephanie S Edwards, Howard Wolpert, Garry M Steil

Abstract readComparative StudyRandomized Controlled Trial
In one paragraph

Trial report in Diabetes technology & therapeutics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Dietary treatment of type 1 diabetes - once upon a time versus today.Pediatric endocrinology, diabetes, and metabolism · 2023
    Review
  4. Nutrition education to type 1 diabetes patients: few changes over the time.Frontiers in clinical diabetes and healthcare · 2023
    Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Review
  10. Insulin:Carbohydrate Ratio--Part of the Story.Diabetes technology & therapeutics · 2015
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Srinivas Laxminarayan1 Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center , U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland.
Jaques Reifman1 Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center , U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland.
Stephanie S Edwards2 Joslin Diabetes Center , Boston, Massachusetts.
Howard Wolpert2 Joslin Diabetes Center , Boston, Massachusetts.
Garry M Steil3 Harvard Medical School , Boston, Massachusetts.

Funding

Harvard Clinical and Translational Science CenterUL1TR001102 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2013 to 2017
$106.2M
NCATS NIH HHS UL1 TR001102
6 · The paper itself

Abstract

backgroundTraditionally, insulin bolus calculations for managing postprandial glucose levels in individuals with type 1 diabetes rely solely on the carbohydrate content of a meal. However, recent studies have reported that other macronutrients in a meal can alter the insulin required for good postprandial control. Specifically, studies have shown that high-fat (HF) meals require more insulin than low-fat (LF) meals with identical carbohydrate content. Our objective was to assess the mechanisms underlying the higher insulin requirement observed in one of these studies. MATERIALS AND

methodsWe used a combination of previously validated metabolic models to fit data from a study comparing HF and LF dinners with identical carbohydrate content in seven subjects with type 1 diabetes. For each subject and dinner type, we estimated the model parameters representing the time of peak meal-glucose appearance (τ(m)), insulin sensitivity (S(I)), the net hepatic glucose balance, and the glucose effect at zero insulin in four time windows (dinner, early night, late night, and breakfast) and assessed the differences in model parameters via paired Wilcoxon signed-rank tests.

resultsDuring the HF meal, the τ(m) was significantly delayed (mean and standard error [SE]: 102 [14] min vs. 71 [4] min; P = 0.02), and S(I) was significantly lower (7.25 × 10(-4) [1.29 × 10(-4)] mL/μU/min vs. 8.72 × 10(-4) [1.08 × 10(-4)] mL/μU/min; P = 0.02).

conclusionsIn addition to considering the putative delay in gastric emptying associated with HF meals, we suggest that clinicians reviewing patient records consider that the fat content of these meals may alter S(I).

Indexed as

Diet, DiabeticDiet, Fat-RestrictedDiet, High-FatAdultAgedCombined Modality TherapyDiabetes Mellitus, Type 1Dietary FatsDigestionDrug Dosage CalculationsFemaleGastric EmptyingHumansHyperglycemiaHypoglycemiaHypoglycemic AgentsDietary FatsHypoglycemic AgentsInsulin

Identifiers

PMID26270134
PMCPMC4677112

What OpenQuestion holds

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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 OpenQuestion graph.