ArticleDiabetes therapy : research, treatment and education of diabetes and related disorders2019
Laboratory Computer-Based Interventions for Better Adherence to Guidelines in the Diagnosis and Monitoring of Type 2 Diabetes.
Article in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 13 citations in OpenAlex.
- Managing laboratory test ordering: a challenge in the new laboratory medicine model.Advances in laboratory medicine · 2024Article
- Article
- Albuminuria Screening in People With Type 2 Diabetes in a Managed Care Organization.AJPM focus · 2023Article
- Review
- Alopecia and Iron Deficiency: An Interventional Pilot Study in Primary Care to Improve the Request of Ferritin.Advances in hematology · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe aim was to present two automated laboratory strategies designed to detect new cases of type 2 diabetes and prediabetes and improve their monitoring.
methodsTo improve diabetes diagnosis, we automatically registered the glycated hemoglobin (HbA1c) levels of every primary care patient between 25 and 46 years old in case of abnormal lipid testing when an HbA1c test had not been requested in the current order or during the previous year and when fasting glucose was > 100 mg/dl. We counted the number of detected cases of diabetes and prediabetes and calculated the cost per identified patient. To improve diabetes monitoring, the levels of HbA1c, total cholesterol, high- and low-density lipoprotein cholesterol and triglycerides and the spot urinary albumin-to-creatinine ratios (ACRs) were automatically registered in patients with diabetes when not ordered according to guidelines. We calculated the total economic costs according to the total number of additional registered tests and reagent cost.
resultsOf 103,425 requests, 224 (0.22%) met the inclusion criteria. Seventeen (7.6%) patients were identified as having new cases of diabetes and 149 (66.5%) of prediabetes, at a cost of €15.2 and €2.3, respectively, per case detected. From 13,874 requests in patients with diabetes, 91 HbA1c and 708 lipid tests and 862 ACRs were automatically registered to comply with guidelines, resulting in expenses of €1948.90.
conclusionsMaking use of laboratory technology, it is possible to detect new cases of type 2 diabetes and prediabetes and to improve disease monitoring.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.