Changes in hyperglycaemia-related testing for prediabetes and type 2 diabetes mellitus management: a prospective, cross-sectional survey of 16 years of general practice data from Australia
Notice bibliographique
Résumé
Abstract Background The rising prevalence of prediabetes increases the population risk of type 2 diabetes mellitus (T2DM), metabolic syndrome and cardiovascular disease. Early identification by General Practitioners (GPs) provides opportunities for lifestyle modifications that can lower these risks. Methods This study examined 16 years of hyperglycaemia-related testing for patients in Australia aged 13 years or older with, or at risk of a diagnosis of T2DM. The Bettering the Evaluation and Care of Health (BEACH) study is a national cross-sectional survey, with a single-stage, cluster sampling design. Approximately 1,000 GPs were randomly selected annually (2000/01–20,015/16) from across Australia, who each recorded details of 100 consecutive clinical encounters with consenting patients. Point estimates were adjusted for intracluster correlation and GP characteristics. Results Fifteen thousand six hundred seventy nine GPs recorded details of 1,387,190 clinical encounters with patients aged 13 + years. Prediabetes and T2DM were managed at 0.25% (95% CI: 0.24–0.27%) and 3.68% (95% CI: 3.62–3.73%) of encounters respectively. By the end of the study, the proportion of encounters where prediabetes was managed was 2.3 times higher and for T2DM, 1.5 times higher. The proportion of prediabetes (55.9%, 95% CI: 53.9–57.8%) and T2DM (27.3%, 95% CI: 26.7–27.9%) management occasions where one or more hyperglycaemia-related tests were requested were relatively stable. However, differences in the types of tests were observed. For prediabetes, glucose tolerance tests were most common but from 2014/15, requests for HbA1c tests began to increase. For T2DM, HbA1c tests were most common, and requests for one or more glucose tests gradually declined. Conclusion The observed 16-year annual trends align with the rising incidence of prediabetes and T2DM. GPs appeared to be strongly influenced by changes to the national insurance scheme and clinical guidelines for hyperglycaemia-related pathology testing. However, some GPs may have been pre-empting policy changes as there was also evidence of ‘unendorsed’ testing, notably for prediabetes, that warrants further investigation. The increasing proportion of encounters for prediabetes, coupled with a high proportion of management occasions where pathology was requested have substantial resource implications. Calls to lower the risk threshold for prediabetes screening therefore warrant an economic analysis. Ongoing, reliable, up-to-date data is needed to inform clinical practice guidelines and policy in Australia.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».