Evidence map›Paper›PMID 37061690›Full record

Trial reportBMC primary care2023

Randomized prospective trial to detect and distinguish between medication nonadherence, drug-drug interactions, and disease progression in chronic cardiometabolic disease.

John W Peabody, Divya Ganesan, Czarlota Valdenor, David Paculdo, Joshua Schrecker, Christopher Westerfield, Rebecca Heltsley

Registry-linked trialOpen access · goldAbstract readRandomized Controlled Trial
In one paragraph

Trial report in BMC primary care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05192590 (Establishing Clinical Utility Evidence for Chronic Disease Management Testing), which is not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 35% of its field
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.

NCT05192590 nacompletednot on this map

Establishing Clinical Utility Evidence for Chronic Disease Management Testing (CDMT): A CPV® RandomizedControlled Trial

TypeinterventionalSponsorQure Healthcare, LLCRan2021 to 2023Enrolled247ConditionsCardiometabolic SyndromeArmsEducational Materials and Chronic Disease Management Test (CDMT)
3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 2 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Review
  4. Article
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

7 authors at 2 institutions in 2 countries.

John W PeabodyQURE Healthcare, San Francisco, CA, USA. jpeabody@qurehealthcare.com.
Divya GanesanQURE Healthcare, San Francisco, CA, USA.
Czarlota ValdenorQURE Healthcare, San Francisco, CA, USA.
David PaculdoQURE Healthcare, San Francisco, CA, USA.
Joshua SchreckerAegis Sciences Corporation, Nashville, TN, USA.
Christopher WesterfieldAegis Sciences Corporation, Nashville, TN, USA.
Rebecca HeltsleyAegis Sciences Corporation, Nashville, TN, USA.
AEgis Technologies (United States) · USPacific Environment · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDisentangling nonadherence (NA), drug-drug interactions (DDIs), and disease progression from each other is an important clinical challenge for providers caring for patients with cardiometabolic diseases. NAs and DDIs are both ubiquitous and often overlooked. We studied a novel chronic disease management (CDM) test to detect medication adherence and the presence and severity of DDIs. MATERIALS AND

methodsWe conducted a prospective, randomized controlled trial of 236 primary care physicians using computer-based, simulated patients, measuring clinical care with and without access to the CDM test. The primary outcomes were whether use of the CDM test increased the accuracy of diagnoses and ordering better treatments and how effective the intervention materials were in getting participants to order the CDM test.

resultsPhysicians given the CDM test results showed a + 13.2% improvement in their diagnosis and treatment quality-of-care scores (p < 0.001) in the NA patient cases and a + 13.6% improvement in the DDI cases (p < 0.001). The difference-in-difference calculations between the intervention and control groups were + 10.4% for NA and + 10.8% for DDI (p < 0.01 for both). After controlling for physician and practice co-factors, intervention, compared to control, was 50.4x more likely to recognize medication NA and 3.3x more likely to correctly treat it. Intervention was 26.9x more likely to identify the DDI and 15.7x more likely to stop/switch the interacting medication compared to control. We found no significant improvements for the disease progression patient cases.

conclusionDistinguishing between nonadherence, drug-drug interactions, and disease progression is greatly improved using a reliable test, like the CDM test; improved diagnostic accuracy and treatment has the potential to improve patient quality of life, medication safety, clinical outcomes, and efficiency of health delivery.

trial registrationclinicaltrials.gov (NCT05192590).

Indexed as

Cardiovascular DiseasesQuality of LifeDisease ProgressionDrug InteractionsHumansMedication AdherenceProspective StudiesAdverse drug reactionsCardiometabolic diseasesDisease progressionDrug-drug interactionsMedication nonadherencePolypharmacy

Identifiers

PMID37061690
PMCPMC10105436
OpenAlexW4365814316

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.