Dataset Information

Unmet medical needs in intermittent Claudication with diabetes and coronary artery disease-A "real-world" analysis on 21?197 PAD patients.

ABSTRACT:

Background

Peripheral artery disease (PAD) is frequently co-prevalent with coronary artery disease (CAD) and diabetes (DM). The study aims to define the burden of CAD and/ or DM in PAD patients at moderate stages and further to evaluate its impact on therapy and outcome.

Methods

Study is based on health insurance claims data of the BARMER reflecting an unselected "real-world" scenario. Retrospective analyses were based on 21?197 patients hospitalized for PAD Rutherford 1-3 between 1 January 2009 to 31 December 2011, including a 4-year follow-up (median 775?days).

Results

In PAD patients, CAD is prevalent in 25.3% (n = 5355), DM in 23.5% (n = 4976), and both CAD and DM in 8.2% (n = 1741). Overall, in-hospital mortality was 0.4%, being increased if CAD was present (CAD alone: OR 1.849; 95%-CI 1.066-3.208; DM alone: OR 1.028; 95%-CI 0.520-2.033; CAD and DM: OR 3.115; 95%-CI 1.720-5.641). Both, CAD and DM increased long-term mortality (CAD alone: HR 1.234; 95%-CI 1.106-1.376; DM alone: HR 1.260; 95%-CI 1.125-1.412; CAD and DM: HR 1.76; 95%-CI 1.552-1.995). DM further increased long-term amputation risk (DM alone: HR 2.238; 95%-CI 1.849-2.710; DM and CAD: HR 2.199; 95%-CI 1.732-2.792), whereas CAD (alone) did not.

Conclusions

In a greater perspective, the data identify also mild to modest stage PAD patients at particular risk for adverse outcomes in presence of CAD and/or DM. CAD and DM both are related with a highly increased risk of long-term mortality even in intermittent claudication, and DM independently increased amputation risk.

SUBMITTER: Stalling P

PROVIDER: S-EPMC6553564 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

Unmet medical needs in intermittent Claudication with diabetes and coronary artery disease-A "real-world" analysis on 21 197 PAD patients.

Stalling Philipp P Engelbertz Christiane C Lüders Florian F Meyborg Matthias M Gebauer Katrin K Waltenberger Johannes J Reinecke Holger H Freisinger Eva E

Clinical cardiology 20190506 6

<h4>Background</h4>Peripheral artery disease (PAD) is frequently co-prevalent with coronary artery disease (CAD) and diabetes (DM). The study aims to define the burden of CAD and/ or DM in PAD patients at moderate stages and further to evaluate its impact on therapy and outcome.<h4>Methods</h4>Study is based on health insurance claims data of the BARMER reflecting an unselected "real-world" scenario. Retrospective analyses were based on 21 197 patients hospitalized for PAD Rutherford 1-3 between ...[more]

PMID: 31017298

Similar Datasets

Project description:BackgroundGuidelines recommend cardiovascular risk reduction and supervised exercise therapy as the first line of treatment in intermittent claudication, but implementation challenges and poor patient compliance lead to significant variation in management and therefore outcomes. The development of a precise risk stratification tool is proposed through a machine-learning algorithm that aims to provide personalized outcome predictions for different management strategies.MethodsFeature selection was performed using the least absolute shrinkage and selection operator method. The model was developed using a bootstrapped sample based on patients with intermittent claudication from a vascular centre to predict chronic limb-threatening ischaemia, two or more revascularization procedures, major adverse cardiovascular events, and major adverse limb events. Algorithm performance was evaluated using the area under the receiver operating characteristic curve. Calibration curves were generated to assess the consistency between predicted and actual outcomes. Decision curve analysis was employed to evaluate the clinical utility. Validation was performed using a similar dataset.ResultsThe bootstrapped sample of 10 000 patients was based on 255 patients. The model was validated using a similar sample of 254 patients. The area under the receiver operating characteristic curves for risk of progression to chronic limb-threatening ischaemia at 2 years (0.892), risk of progression to chronic limb-threatening ischaemia at 5 years (0.866), likelihood of major adverse cardiovascular events within 5 years (0.836), likelihood of major adverse limb events within 5 years (0.891), and likelihood of two or more revascularization procedures within 5 years (0.896) demonstrated excellent discrimination. Calibration curves demonstrated good consistency between predicted and actual outcomes and decision curve analysis confirmed clinical utility. Logistic regression yielded slightly lower area under the receiver operating characteristic curves for these outcomes compared with the least absolute shrinkage and selection operator algorithm (0.728, 0.717, 0.746, 0.756, and 0.733 respectively). External calibration curve and decision curve analysis confirmed the reliability and clinical utility of the model, surpassing traditional logistic regression.ConclusionThe machine-learning algorithm successfully predicts outcomes for patients with intermittent claudication across various initial treatment strategies, offering potential for improved risk stratification and patient outcomes.