Evidence map›Paper›PMID 40714034›Full record

ArticleAmerican heart journal2026

Relationship between industry payments to physicians and prescription patterns for PCSK9is, ARNis and DOACs: A report from the NCDR PINNACLE registry.

Amarnath R Annapureddy, Karthik Murugiah, Luke Zheng, Karl E Minges, Gowtham R Grandhi, Joseph S Ross, Tariq Ahmad, Benjamin A Rodwin, Sanket S Dhruva, Saket Girotra and 3 more

Abstract read
In one paragraph

Article in American heart journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Amarnath R AnnapureddySection of Cardiovascular Medicine, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, NE.
Karthik MurugiahSection of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT.
Luke ZhengCardiovascular Medicine, Baim Institute for Clinical Research, Boston, MA.
Karl E MingesCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT; College of Health Professions, Sacred Heart University, Fairfield, Connecticut.
Gowtham R GrandhiDivision of Cardiology, VCU School of Medicine, Richmond, VA.
Joseph S RossCenter for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT; Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT; Department of Health Policy and Management, Yale School of Public Health, New Haven, CT.
Tariq AhmadSection of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT.
Benjamin A RodwinSection of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT; VA Connecticut Healthcare System, West Haven, CT.
Sanket S DhruvaUniversity of California, San Francisco School of Medicine, San Francisco, CA; Section of Cardiology, Department of Medicine, San Francisco Veterans Affairs Medical Center, San Francisco, CA.
Saket GirotraSection of Cardiology, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX.
Elias J DayoubDivision of Cardiology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI.
Jeptha P CurtisSection of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT.
Nihar R DesaiSection of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT. Electronic address: nihar.desai@yale.edu.

Funding

Leveraging Physician Networks to Improve Care and Outcomes for Low-Income PopulationsR01HL144644 · NHLBI · YALE UNIVERSITY · PI NDUMELE, CHIMA · 2019 to 2021
$1.6M
Automated ascertainment of bleeding and target lesion revascularization after percutaneous coronary intervention (PCI) using electronic health record (EHR) dataK08HL157727 · NHLBI · YALE UNIVERSITY · PI Karthik Murugiah · 2022 to 2026
$831k
Peripheral Artery Disease: Long-term Survival & Outcomes Study (PEARLS)R56HL158803 · NHLBI · UT SOUTHWESTERN MEDICAL CENTER · PI GIROTRA, SAKET · 2021 to 2021
$633k
AHRQ HHS R01 HS022882AHRQ HHS R01 HS025164FDA HHS U01 FD005938HSRD VA IK2 HX003357NHLBI NIH HHS K08 HL157727NHLBI NIH HHS R01 HL144644NHLBI NIH HHS R56 HL158803
6 · The paper itself

Abstract

backgroundWe examined the association of industry payments to physicians and prescriptions for proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, angiotensin receptor-neprilysin inhibitor (ARNi), and direct oral anticoagulants (DOAC).

methodsUsing 2017 data from the NCDR PINNACLE Registry, we idenitifed 3 patient cohorts: those with atherosclerotic cardiovascular disease (ASCVD) and/or dyslipidemia, heart failure with reduced ejection fraction (HFrEF), and nonvalvular atrial fibrillation (NVAF). We linked physicians to the 2017 Open Payments data using National Provider Identifiers to determine whether they had received industry payments related to PCSK9 inhibitors, ARNi, or DOACs. The primary outcome of the study was the proportion of patients within each cohort who were prescribed the corresponding medication. Within each cohort, we evaluated the association between the receipt of industry payments by the treating physician (<$100, $100-$1,000, >$1,000) and likelihood of prescribing the corresponding medication using regression analyses.

resultsOverall, 0.2% of ASCVD patients were prescribed PCSK9 inhibitors, 9.0% of HFrEF patients were prescribed ARNi, and 38.7% of NVAF patients were prescribed DOACs. Patients whose physicians receiveds payments related to PCSK inhibitors were more likely to be prescribed them (ASCVD cohort: odds ratio [OR] 1.35; 95% confidence interval [CI],1.15-1.57), as were patients in the HFrEF cohort prescribed ARNi (OR 1.43; 95% CI, 1.19-1.71). No significant association was observed for DOAC prescribing (OR 0.99; 95% CI, 0.95-1.03). Across all 3 cohorts, physicians who received higher-value payments were more likely to prescribe the corresponding medications than those who received lower-value payments.

conclusionsPatients with ASCVD or HFrEF whose physicians received industry payments were more likely to be prescribed PCSK9 inhibitors or ARNi, regardless of the payment amount. For DOACs, an association with prescribing was observed only among physicians who received higher-value payments.

Indexed as

Angiotensin Receptor AntagonistsAnticoagulantsConflict of InterestDrug IndustryDrug PrescriptionsPCSK9 InhibitorsPractice Patterns, Physicians'AgedAtherosclerosisAtrial FibrillationDyslipidemiasFemaleHeart FailureHumansMaleMiddle AgedAngiotensin Receptor AntagonistsAnticoagulantsNeprilysinPCSK9 InhibitorsPCSK9 protein, humanProprotein Convertase 9

Identifiers

PMID40714034
PMCPMC12621269

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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.