Non-Laboratory-Based Risk Prediction Tools for Undiagnosed Pre-Diabetes: A Systematic Review.
Diagnostics (Basel)
; 13(7)2023 Mar 29.
Article
en En
| MEDLINE
| ID: mdl-37046512
ABSTRACT
Early detection of pre-diabetes (pre-DM) can prevent DM and related complications. This review examined studies on non-laboratory-based pre-DM risk prediction tools to identify important predictors and evaluate their performance. PubMed, Embase, MEDLINE, CINAHL were searched in February 2023. Studies that developed tools with (1) pre-DM as a prediction outcome, (2) fasting/post-prandial blood glucose/HbA1c as outcome measures, and (3) non-laboratory predictors only were included. The studies' quality was assessed using the CASP Clinical Prediction Rule Checklist. Data on pre-DM definitions, predictors, validation methods, performances of the tools were extracted for narrative synthesis. A total of 6398 titles were identified and screened. Twenty-four studies were included with satisfactory quality. Eight studies (33.3%) developed pre-DM risk tools and sixteen studies (66.7%) focused on pre-DM and DM risks. Age, family history of DM, diagnosed hypertension and obesity measured by BMI and/or WC were the most common non-laboratory predictors. Existing tools showed satisfactory internal discrimination (AUROC 0.68-0.82), sensitivity (0.60-0.89), and specificity (0.50-0.74). Only twelve studies (50.0%) had validated their tools externally, with a variance in the external discrimination (AUROC 0.31-0.79) and sensitivity (0.31-0.92). Most non-laboratory-based risk tools for pre-DM detection showed satisfactory performance in their study populations. The generalisability of these tools was unclear since most lacked external validation.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
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Risk_factors_studies
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Screening_studies
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Systematic_reviews
Idioma:
En
Revista:
Diagnostics (Basel)
Año:
2023
Tipo del documento:
Article
País de afiliación:
China