Evidence map›Paper›PMID 42130176›Full record

Trial reportJournal of clinical hypertension (Greenwich, Conn.)2026

Antihypertensive Combinations Modify Cardiovascular Risk Factor Importance: A Machine Learning Analysis of the ACCOMPLISH Trial.

Niko Kaciroti, Phillip D Levy, Kenneth A Jamerson, Robert D Brook

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of clinical hypertension (Greenwich, Conn.), 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
–field-weighted citation impact
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

4 authors.

Niko KacirotiDepartments of Pediatrics and Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.
Phillip D LevyIntegrative Biosciences Center, Wayne State University, Detroit, Michigan, USA.
Kenneth A JamersonDivision of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Robert D BrookIntegrative Biosciences Center, Wayne State University, Detroit, Michigan, USA.ORCID 0000-0002-8521-7262

Funding

American Heart Association AHA 878605NIMHD NIH HHS P50 MD017351-01
6 · The paper itself

Abstract

Results from the ACCOMPLISH (Avoiding Cardiovascular Events through COMbination Therapy in Patients LIving with Systolic Hypertension) trial suggest that combining benazepril with amlodipine, rather than hydrochlorothiazide, provides superior cardiovascular protection potentially in a BP-independent manner. We employed random survival forest, a powerful machine learning approach, to compare the relative importance of risk factors (i.e., variable importance factor (VIF)), focusing on in-trial BP control for predicting the primary composite cardiovascular outcome in the 2 treatment limbs. Among the 6 risk factors with significantly different VIFs between treatments, all were lower under benazepril/amlodipine combination. The VIF for achieved systolic BP at 6-months was 35% lower in the benazepril/amlodipine (0.082) versus the benazepril/hydrochlorothiazide (0.126) limb. The fact that in-trial BP control was less important for preventing cardiovascular events during benazepril/amlodipine treatment provides novel support for our contention that this combination regimen provides a degree of clinically-relevant cardio-protective actions in a BP-independent manner.

Indexed as

AmlodipineAntihypertensive AgentsBenzazepinesCardiovascular DiseasesHypertensionMachine LearningBlood PressureDrug Therapy, CombinationFemaleHeart Disease Risk FactorsHumansHydrochlorothiazideMaleRisk FactorsAmlodipineAntihypertensive AgentsbenazeprilBenzazepinesHydrochlorothiazideclinical trialscombination antihypertensive therapymachine learning

Identifiers

PMID42130176
PMCPMC13172597

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.