Evidence map›Paper›PMID 38999770›Full record

Trial reportNutrients2024

Efficacy of AI-Guided (GenAIS

Evgeny Pokushalov, Andrey Ponomarenko, John Smith, Michael Johnson, Claire Garcia, Inessa Pak, Evgenya Shrainer, Dmitry Kudlay, Sevda Bayramova, Richard Miller

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
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

10 authors.

Evgeny PokushalovCenter for New Medical Technologies, 630090 Novosibirsk, Russia.ORCID 0000-0002-9494-4234
Andrey PonomarenkoCenter for New Medical Technologies, 630090 Novosibirsk, Russia.ORCID 0000-0002-5468-9961
John SmithScientific Research Laboratory, Triangel Scientific, San Francisco, CA 94101, USA.
Michael JohnsonScientific Research Laboratory, Triangel Scientific, San Francisco, CA 94101, USA.
Claire GarciaScientific Research Laboratory, Triangel Scientific, San Francisco, CA 94101, USA.
Inessa PakCenter for New Medical Technologies, 630090 Novosibirsk, Russia.
Evgenya ShrainerCenter for New Medical Technologies, 630090 Novosibirsk, Russia.ORCID 0000-0002-9675-3044
Dmitry KudlayInstitute of Pharmacy, I.M. Sechenov First Moscow State Medical University (Sechenov University), 119991 Moscow, Russia.ORCID 0000-0003-1878-4467
Sevda BayramovaCenter for New Medical Technologies, 630090 Novosibirsk, Russia.
Richard MillerScientific Research Laboratory, Triangel Scientific, San Francisco, CA 94101, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emerging evidence suggests that personalized dietary supplement regimens can significantly influence lipid metabolism and cardiovascular risk. The efficacy of AI-guided dietary supplement prescriptions, compared with standard physician-guided prescriptions, remains underexplored. In a randomized, parallel-group pilot study, 70 patients aged 40-75 years with LDL-C levels between 70 and 190 mg/dL were enrolled. Participants were randomized to receive either AI-guided dietary supplement prescriptions or standard physician-guided prescriptions for 90 days. The primary endpoint was the percent change in LDL-C levels. Secondary endpoints included changes in total cholesterol, HDL-C, triglycerides, and hsCRP. Supplement adherence and side effects were monitored. Sixty-seven participants completed the study. The AI-guided group experienced a 25.3% reduction in LDL-C levels (95% CI: -28.7% to -21.9%), significantly greater than the 15.2% reduction in the physician-guided group (95% CI: -18.5% to -11.9%;

Indexed as

Cholesterol, LDLDietary SupplementsAdultAgedCholesterol, HDLFemaleHumansHypercholesterolemiaMaleMiddle AgedPilot ProjectsTreatment OutcomeTriglyceridesCholesterol, HDLCholesterol, LDLTriglyceridesAI-guided prescriptionscardiovascular healthdietary supplementsLDL-Cpersonalized medicinetriglycerides

Identifiers

PMID38999770
PMCPMC11243060

What OpenQuestion holds

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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.