Evidence map›Paper›PMID 39064626›Full record

ReviewNutrients2024

Assessing Carbohydrate Counting Accuracy: Current Limitations and Future Directions.

Débora Amorim, Francisco Miranda, Andreia Santos, Luís Graça, João Rodrigues, Mara Rocha, Maria Aurora Pereira, Clementina Sousa, Paula Felgueiras, Carlos Abreu

Abstract readReview
In one paragraph

Review in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. 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

10 authors.

Débora AmorimApplied Digital Transformation Laboratory (Adit-LAB), Polytechnic Institute of Viana do Castelo, Rua Escola Industrial e Comercial de Nun'Álvares, 4900-347 Viana do Castelo, Portugal.ORCID 0000-0002-1448-1779
Francisco MirandaPolytechnic Institute of Viana do Castelo, Rua Escola Industrial e Comercial de Nun'Álvares, 4900-347 Viana do Castelo, Portugal.ORCID 0000-0002-7700-1269
Andreia SantosSchool of Health of the Polytechnic Institute of Viana do Castelo, Rua Escola Industrial e Comercial de Nun'Alvares, 4900-347 Viana do Castelo, Portugal.ORCID 0009-0007-7273-7270
Luís GraçaHealth Sciences Research Unit: Nursing (UICISA: E), School of Health of the Polytechnic Institute of Viana do Castelo, Rua Escola Industrial e Comercial de Nun'Alvares, 4900-347 Viana do Castelo, Portugal.ORCID 0000-0001-7510-2202
João RodriguesCenter for Translational Health and Medical Biotechnology Research (TBIO)/Health Research Network (RISE-Health), School of Health of the Polytechnic Institute of Porto, Rua Dr. António Bernardino de Almeida 400, 4200-072 Porto, Portugal.
Mara RochaHealth Sciences Research Unit: Nursing (UICISA: E), School of Health of the Polytechnic Institute of Viana do Castelo, Rua Escola Industrial e Comercial de Nun'Alvares, 4900-347 Viana do Castelo, Portugal.
Maria Aurora PereiraHealth Sciences Research Unit: Nursing (UICISA: E), School of Health of the Polytechnic Institute of Viana do Castelo, Rua Escola Industrial e Comercial de Nun'Alvares, 4900-347 Viana do Castelo, Portugal.
Clementina SousaHealth Sciences Research Unit: Nursing (UICISA: E), School of Health of the Polytechnic Institute of Viana do Castelo, Rua Escola Industrial e Comercial de Nun'Alvares, 4900-347 Viana do Castelo, Portugal.
Paula FelgueirasSchool of Health of the Polytechnic Institute of Viana do Castelo, Rua Escola Industrial e Comercial de Nun'Alvares, 4900-347 Viana do Castelo, Portugal.
Carlos AbreuApplied Digital Transformation Laboratory (Adit-LAB), Polytechnic Institute of Viana do Castelo, Rua Escola Industrial e Comercial de Nun'Álvares, 4900-347 Viana do Castelo, Portugal.ORCID 0000-0001-9005-9599

Funding

NORTE 2020 Norte-01-0145-FEDER-000043
6 · The paper itself

Abstract

Diabetes mellitus is a prevalent chronic autoimmune disease with a high impact on global health, affecting millions of adults and resulting in significant morbidity and mortality. Achieving optimal blood glucose levels is crucial for diabetes management to prevent acute and long-term complications. Carbohydrate counting (CC) is widely used by patients with type 1 diabetes to adjust prandial insulin bolus doses based on estimated carbohydrate content, contributing to better glycemic control and improved quality of life. However, accurately estimating the carbohydrate content of meals remains challenging for patients, leading to errors in bolus insulin dosing. This review explores the current limitations and challenges in CC accuracy and emphasizes the importance of personalized educational programs to enhance patients' abilities in carbohydrate estimation. Existing tools for assessing patient learning outcomes in CC are discussed, highlighting the need for individualized approaches tailored to each patient's needs. A comprehensive review of the relevant literature was conducted to identify educational programs and assessment tools dedicated to training diabetes patients on carbohydrate counting. The research aims to provide insights into the benefits and limitations of existing tools and identifies future research directions to advance personalized CC training approaches. By adopting a personalized approach to CC education and assessment, healthcare professionals can empower patients to achieve better glycemic control and improve diabetes management. Moreover, this review identifies potential avenues for future research, paving the way for advancements in personalized CC training and assessment approaches and further enhancing diabetes management strategies.

Indexed as

Blood GlucoseDiabetes Mellitus, Type 1Dietary CarbohydratesGlycemic ControlHumansHypoglycemic AgentsInsulinMealsPatient Education as TopicQuality of LifeBlood GlucoseDietary CarbohydratesHypoglycemic AgentsInsulincarbohydrate countingdiabetes mellitusinsulin therapynutritional educationpersonalized medicine

Identifiers

PMID39064626
PMCPMC11279647

What Socratic holds

Textmetadata
LicenceCC BY
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.