ArticlePloS one2024
Prognostic nomogram for uncontrolled type 2 diabetes using Thailand nation-wide cross-sectional studies.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUncontrolled type 2 diabetes (T2DM) and limited hemoglobin A1c (HbA1c) levels examination are a burden in community hospitals in Thailand. The nomogram from the patients' information might be a practical solution to identify a high-risk group of diabetic complications. Thus, this study aimed to establish an effective prognostic nomogram for patients with uncontrolled T2DM.
methodsSequential nationwide cross-sectional studies of T2DM patients in 2018 and 2015 were utilized for development and validation groups, respectively, with this chronological order aiming to capture recent trends during development and assess the nomogram's robustness across diverse timeframes. The predictive outcome was uncontrolled T2DM, defined as HbA1c ≥9%. The model was determined by multivariable regression analysis and established an effective prognostic nomogram. The receiver operating characteristic curve, Hosmer-Lemeshow goodness of fit test, and decision curve analysis (DCA) was applied to evaluate the performance of the nomogram.
resultsIn 2018, 24% of the 38,568 participants in the development group had uncontrolled T2DM (defined as Hba1c ≥9%). The predictive nomogram of uncontrolled diabetes consisted of demographic characteristics, prescription medications, history of diabetic complications, and laboratory results (C-statistic of 0.77). The goodness of fit test and DCA showed good agreement between the result and clinical application for T2DM.
conclusionThe predictive nomogram demonstrates simplicity, accuracy, and valuable prediction to enhance diabetic care in resource-limited countries, including Thailand.
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.