Dataset Information

Clinical Care Among Individuals with Prediabetes in Primary Care: a Retrospective Cohort Study.

ABSTRACT:

Background

The incidence of diabetes in the general US population (6.7 per 1000 adults in 2018) has not changed significantly since 2000, suggesting that individuals with prediabetes are not connecting to evidence-based interventions.

Objective

We sought to describe the clinical care of individuals with prediabetes, determine patient factors associated with this care, and evaluate risk for diabetes development.

Design

Retrospective cohort study using linked claims and electronic health record data.

Participants

We created a cohort of adults with prediabetes based on laboratory measures. We excluded patients with a prior history of diabetes, pregnancy in prior 6 months, or recent steroid use.

Main measures

We measured ordering and completion of clinical services targeting prediabetes management and diabetes incidence within 12 months following cohort entry. We tested the strength of the association between individuals' characteristics and outcomes of interest using bivariate and multiple logistic regression.

Results

Our cohort included 3888 patients with a laboratory diagnosis of prediabetes (incident or prevalent prediabetes). Within 12 months, 63.4% had repeat glycemic testing, yet only 10.4% had coded diagnoses of prediabetes, 1.0% were referred for nutrition services, and 5.4% were prescribed metformin. Most patients completed labs and nutrition visits when referred and filled metformin when prescribed. Individuals with a higher glycemic level or BMI were more likely to receive prediabetes clinical care. Six percent of individuals developed diabetes within 12 months of cohort entry and had higher glycemic levels and BMI ≥ 30 kg/m². In the adjusted model, Black individuals had 1.4 times higher odds of developing diabetes than White individuals.

Conclusions

Rates of prediabetes clinical care activities are low and have not improved. Strategies are urgently needed to improve prediabetes care delivery thereby preventing or delaying incident diabetes.

SUBMITTER: Tseng E

PROVIDER: S-EPMC8890680 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Clinical Care Among Individuals with Prediabetes in Primary Care: a Retrospective Cohort Study.

Tseng Eva E Durkin Nowella N Clark Jeanne M JM Maruthur Nisa M NM Marsteller Jill A JA Segal Jodi B JB

Journal of general internal medicine 20220302 16

<h4>Background</h4>The incidence of diabetes in the general US population (6.7 per 1000 adults in 2018) has not changed significantly since 2000, suggesting that individuals with prediabetes are not connecting to evidence-based interventions.<h4>Objective</h4>We sought to describe the clinical care of individuals with prediabetes, determine patient factors associated with this care, and evaluate risk for diabetes development.<h4>Design</h4>Retrospective cohort study using linked claims and elect ...[more]

PMID: 35237886

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Project description:BackgroundMicro- and macrovascular complications are a major burden for individuals with diabetes and can already arise in a prediabetic state. To allocate effective treatments and to possibly prevent these complications, identification of those at risk is essential.ObjectiveThis study aimed to build machine learning (ML) models that predict the risk of developing a micro- or macrovascular complication in individuals with prediabetes or diabetes.MethodsIn this study, we used electronic health records from Israel that contain information about demographics, biomarkers, medications, and disease codes; span from 2003 to 2013; and were queried to identify individuals with prediabetes or diabetes in 2008. Subsequently, we aimed to predict which of these individuals developed a micro- or macrovascular complication within the next 5 years. We included 3 microvascular complications: retinopathy, nephropathy, and neuropathy. In addition, we considered 3 macrovascular complications: peripheral vascular disease (PVD), cerebrovascular disease (CeVD), and cardiovascular disease (CVD). Complications were identified via disease codes, and, for nephropathy, the estimated glomerular filtration rate and albuminuria were considered additionally. Inclusion criteria were complete information on age and sex and on disease codes (or measurements of estimated glomerular filtration rate and albuminuria for nephropathy) until 2013 to account for patient dropout. Exclusion criteria for predicting a complication were diagnosis of this specific complication before or in 2008. In total, 105 predictors from demographics, biomarkers, medications, and disease codes were used to build the ML models. We compared 2 ML models: logistic regression and gradient-boosted decision trees (GBDTs). To explain the predictions of the GBDTs, we calculated Shapley additive explanations values.ResultsOverall, 13,904 and 4259 individuals with prediabetes and diabetes, respectively, were identified in our underlying data set. For individuals with prediabetes, the areas under the receiver operating characteristic curve for logistic regression and GBDTs were, respectively, 0.657 and 0.681 (retinopathy), 0.807 and 0.815 (nephropathy), 0.727 and 0.706 (neuropathy), 0.730 and 0.727 (PVD), 0.687 and 0.693 (CeVD), and 0.707 and 0.705 (CVD); for individuals with diabetes, the areas under the receiver operating characteristic curve were, respectively, 0.673 and 0.726 (retinopathy), 0.763 and 0.775 (nephropathy), 0.745 and 0.771 (neuropathy), 0.698 and 0.715 (PVD), 0.651 and 0.646 (CeVD), and 0.686 and 0.680 (CVD). Overall, the prediction performance is comparable for logistic regression and GBDTs. The Shapley additive explanations values showed that increased levels of blood glucose, glycated hemoglobin, and serum creatinine are risk factors for microvascular complications. Age and hypertension were associated with an elevated risk for macrovascular complications.ConclusionsOur ML models allow for an identification of individuals with prediabetes or diabetes who are at increased risk of developing micro- or macrovascular complications. The prediction performance varied across complications and target populations but was in an acceptable range for most prediction tasks.

Project description:ObjectiveLifestyle interventions can be efficacious in reducing cardiovascular disease risk factors and are recommended as first-line interventions in England. However, recent information on the use of these interventions in primary care is lacking. We investigated for how many patients with newly diagnosed hypertension, hyperlipidaemia or obesity, lifestyle interventions were recorded in their primary care electronic health record.DesignA retrospective cohort study.SettingEnglish primary care, using UK Clinical Practice Research Datalink.ParticipantsA total of 770,711 patients who were aged 18 years or older and received a new diagnosis of hypertension, hyperlipidaemia or obesity between 2010 and 2019.Main outcome measuresRecord of lifestyle intervention and/or medication in 12 months before to 12 months after initial diagnosis (2-year timeframe).ResultsAnalyses show varying results across conditions: While 55.6% (95% CI 54.9-56.4) of individuals with an initial diagnosis of hypertension were recorded as having lifestyle support (lifestyle intervention or signposting) within the 2-year timeframe, this number was reduced to 45.2% (95% CI 43.8-46.6) for hyperlipidaemia and 52.6% (95% CI 51.1-54.1) for obesity. For substantial proportions of individuals neither lifestyle support nor medication (hypertension: 12.2%, 95% CI 11.9-12.5; hyperlipidaemia: 32.2%, 95% CI 31.2-33.3; obesity: 43.9%, 95% CI 42.3-45.4) were recorded. Sensitivity analyses confirm that limited proportions of patients had lifestyle support recorded in their electronic health record before they were first prescribed medication (diagnosed and undiagnosed), ranging from 12.1% for hypertension to 19.7% for hyperlipidaemia, and 19.5% for obesity (23.4% if restricted to Orlistat).ConclusionsLimited evidence of lifestyle support for individuals with cardiovascular risk factors (hypertension, hyperlipidaemia, obesity) recommended by national guidelines in England may stem from poor recording in electronic health records but may also represent missed opportunities. Given the link between progression to cardiovascular disease and modifiable lifestyle factors, early support for patients to manage their conditions through non-pharmaceutical interventions by establishing lifestyle modification as first-line treatment is crucial.

Dataset Information

Clinical Care Among Individuals with Prediabetes in Primary Care: a Retrospective Cohort Study.

Background

Objective

Design

Participants

Main measures

Results

Conclusions

Publications

Clinical Care Among Individuals with Prediabetes in Primary Care: a Retrospective Cohort Study.

Similar Datasets

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