Evidence map›Paper›PMID 40782724›Full record

ArticleSurgery2025

Early peripheral vascular intervention for treating patients with claudication: A decision analysis using national administrative claims data.

Chen Dun, Jesse A Columbo, Caitlin W Hicks, Harold P Lehmann

Abstract read
In one paragraph

Article in Surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Chen DunBiomedical Informatics and Data Science, Johns Hopkins University School of Medicine, Baltimore, MD; Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, MD. Electronic address: cdun1@jhmi.edu.
Jesse A ColumboSection of Vascular Surgery, Heart and Vascular Center, Dartmouth Hitchcock Medical Center, Lebanon, NH. Electronic address: https://twitter.com/ColumboJesse.
Caitlin W HicksDivision of Vascular Surgery and Endovascular Therapy, Department of Surgery, The Johns Hopkins School of Medicine, Baltimore, MD. Electronic address: https://twitter.com/CaitlinWHicks.
Harold P LehmannBiomedical Informatics and Data Science, Johns Hopkins University School of Medicine, Baltimore, MD.

Funding

Risk Factors and Outcomes Associated with Late-Life Diabetic Peripheral NeuropathyK23DK124515 · NIDDK · JOHNS HOPKINS UNIVERSITY · PI HICKS, CAITLIN WHITNEY · 2020 to 2024
$898k
Comparative-Effectiveness of Procedures for Carotid RevascularizationK08HL165087 · NHLBI · DARTMOUTH-HITCHCOCK CLINIC · PI Jesse A Columbo · 2023 to 2026
$587k
NHLBI NIH HHS K08 HL165087NIDDK NIH HHS K23 DK124515
6 · The paper itself

Abstract

objectivesClaudication, a symptom commonly associated with peripheral artery disease, affects approximately 30-40% of adults in the United States. A decision analysis is needed to integrate data, information, and knowledge from multiple sources about the stages of a patient's journey in this condition to assess the optimal treatment approach.

methodsWe designed a decision model including patient perspective and outcomes of claudication, peripheral vascular intervention, open surgical bypass, chronic limb-threatening ischemia, and amputation. Time horizon was 2 years and tradeoffs were expressed as "cost-effectiveness," with "cost" taken as number of procedures, and "effectiveness," the amount of time in claudication and/or recovery. The treatment alternatives were peripheral vascular intervention within 6 months of initial diagnosis of claudication (early peripheral vascular intervention) or peripheral vascular intervention >6 months after claudication diagnosis (to allow for guideline-directed conservative therapy first). Probabilities were derived from 100% Medicare fee-for-service claims data between January 2017 and December 2021. A Markov model was designed and populated for the 2 scenarios. The main outcomes included the estimated number of peripheral vascular interventions, estimated number of open bypass procedures, and total time in claudication. Using Monte Carlo Simulation, 1,000,000 patients were run through the model for the 2-year time horizon. Sensitivity analysis using propensity score matching was conducted to control for baseline differences between groups, matching patients on age, sex, race, and comorbidities.

resultsA cohort comprising 445,305 patients newly diagnosed with claudication was identified, exhibiting a mean age of 76.2 years. Among these patients, 12,102 (2.7%) underwent early peripheral vascular intervention, whereas 433,203 (97.3%) had no early peripheral vascular intervention. The simulation demonstrated that patients who underwent an early peripheral vascular intervention experienced an estimated average of 3.6 peripheral vascular interventions over the 2 years, whereas those who did not undergo early peripheral vascular intervention averaged 0.3 PVIs over 2 years. Moreover, patients who underwent early peripheral vascular intervention were projected to undergo an average of 1.7 open bypass procedures subsequent to the initial diagnosis of claudication, whereas those who did not receive early peripheral vascular intervention were expected to undergo 0.8 open bypass procedures. The duration of time spent in a state of claudication was observed to be 190 days for patients who underwent early peripheral vascular intervention, in contrast to 360 days for those who did not receive early peripheral vascular intervention. After controlling for baseline characteristics such as age, sex, race, and comorbidities, the results remained consistent in the propensity score matched groups.

conclusionOur novel methodology used claims data to arrive at day-to-day transitions to assess the impact of early peripheral vascular intervention in the management of claudication among patients. Our findings reinforce professional guidelines that early peripheral vascular intervention may not confer beneficial outcomes to patients, potentially leading to adverse effects and necessitating further interventions. This study underscores the significance of health care informatics in harnessing data, technology, and analytical methodologies to enhance decision-making processes, optimize resource allocation, improve the quality-of-care delivery, and promote evidence-based practices within the health care domain.

Indexed as

Decision Support TechniquesIntermittent ClaudicationPeripheral Arterial DiseaseVascular Surgical ProceduresAgedAged, 80 and overAmputation, SurgicalCost-Benefit AnalysisFemaleHumansMaleMarkov ChainsMedicareMiddle AgedTreatment OutcomeUnited States

Identifiers

PMID40782724
PMCPMC12338061

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.