An Improved Clinical and Genetics-Based Prediction Model for Diabetic Foot Ulcer Healing.
Adv Wound Care (New Rochelle)
; 13(6): 281-290, 2024 06.
Article
de En
| MEDLINE
| ID: mdl-38258807
ABSTRACT
Objective:
The goal of this investigation was to use comprehensive prediction modeling tools and available genetic information to try to improve upon the performance of simple clinical models in predicting whether a diabetic foot ulcer (DFU) will heal.Approach:
We utilized a cohort study (n = 206) that included clinical factors, measurements of circulating endothelial precursor cells (CEPCs), and fine sequencing of the NOS1AP gene. We derived and selected relevant predictive features from this patient-level information using statistical and machine learning techniques. We then developed prognostic models using machine learning approaches and assessed predictive performance. The presentation is consistent with TRIPOD requirements.Results:
Models using baseline clinical and CEPC data had an area under the receiver operating characteristic curve (AUC) of 0.73 (0.66-0.80). Models using only single nucleotide polymorphisms (SNPs) of the NOS1AP gene had an AUC of 0.67 (95% confidence interval, CI [0.59-0.75]). However, models incorporating baseline and SNP information resulted in improved AUC (0.80, 95% CI [0.73-0.87]). Innovation We provide a rigorous analysis demonstrating the predictive potential of genetic information in DFU healing. In this process, we present a framework for using advanced statistical and bioinformatics techniques for creating superior prognostic models and identify potentially predictive SNPs for future research.Conclusion:
We have developed a new benchmark for which future predictive models can be compared against. Such models will enable wound care experts to more accurately predict whether a patient will heal and aid clinical trialists in designing studies to evaluate therapies for subjects likely or unlikely to heal.Mots clés
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Cicatrisation de plaie
/
Pied diabétique
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Polymorphisme de nucléotide simple
/
Apprentissage machine
Type d'étude:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limites:
Aged
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Female
/
Humans
/
Male
/
Middle aged
Langue:
En
Journal:
Adv Wound Care (New Rochelle)
Année:
2024
Type de document:
Article
Pays d'affiliation:
États-Unis d'Amérique