Evidence map›Paper›PMID 39973985›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Predicting symptomatic response to prokinetic treatment using Gastric Alimetry.

Chris Varghese, Sibylle Van Hove, Gabriel Schamberg, Billy Wu, Nooriyah Poonawala, Mikaela Law, Nicky Dachs, Gen Johnston, India Fitt, Daphne Foong and 7 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. 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

5 · Who and what money

Authors and funding

17 authors.

Chris Varghese
Sibylle Van Hove
Gabriel Schamberg
Billy Wu
Nooriyah Poonawala
Mikaela Law
Nicky Dachs
Gen Johnston
India Fitt
Daphne Foong
Henry P Parkman
Thomas Abell
Vincent Ho
Stefan Calder
Armen A Gharibans
Christopher N Andrews
Gregory O'Grady

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic neurogastroduodenal disorders are challenging to manage, with therapy often initiated on a trial and error basis. Prokinetics play a significant role in management, but responses are variable and have been associated with adverse events, impacting widespread use. We investigated whether body surface gastric mapping (BSGM) biomarkers (using Gastric Alimetry Methods: Patients with chronic gastroduodenal symptoms taking oral prokinetic, regardless of gastric emptying status, were prospectively recruited and underwent BSGM (30 m baseline, 482 kcal standardised meal, 4 h postprandial recording) whilst off prokinetic. Patients were followed up with daily symptom diaries. A subset was compared to matched patients not taking prokinetics. Prokinetic responders were defined based on symptom improvement greater than a minimum clinically important difference methodology. Key Results: 42 patients (88% female; median age 36; median BMI 26) taking prokinetics were analysed. Prokinetic prescribing, compared to matched patients, was independent of BSGM metrics (p>0.15). In patients on existing prokinetics (withheld for BSGM), lower amplitudes predicted reduced symptom burden, whereas low rhythm stability predicted a worse symptom burden (p<0.05). In prokinetic-naive patients (i.e. started on a prokinetic during the study), a lower postprandial amplitude predicted responders (mean 37.5±10.6 uV in responders [n=5] vs mean 54.8±6.6 uV among non-responders [n=3], p=0.047). Conclusions: Gastric Alimetry biomarkers may help in the prediction of prokinetic response in patients with chronic gastroduodenal symptoms. Lower post-prandial amplitudes, indicating a reduced meal response, appear to predict benefit, whilst impaired rhythm stability predicted poorer therapeutic response.

Identifiers

PMID39973985
PMCPMC11838638

What Socratic holds

Textmetadata
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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 Socratic graph.