Evidence map›Paper›PMID 39931425›Full record

ArticleJournal of pain research2025

The Use of Electronic Consent (eConsent) Within the Ketamine for Long-Lasting Pain Relief After Surgery (KALPAS) Multicenter Trial.

Lisa V Doan, Jeri Burr, Raven Perez, Hamleini Martinez, Randy Cuevas, Kevin Watt, Jing Wang

Abstract read
In one paragraph

Article in Journal of pain research, 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

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.

Lisa V DoanDepartment of Anesthesiology, Perioperative Care, and Pain Medicine, New York University Grossman School of Medicine, New York, NY, USA.ORCID 0000-0002-7833-1753
Jeri BurrDepartment of Pediatrics, University of Utah, Salt Lake City, UT, USA.ORCID 0000-0002-5443-6534
Raven PerezDepartment of Anesthesiology, Perioperative Care, and Pain Medicine, New York University Grossman School of Medicine, New York, NY, USA.ORCID 0009-0005-7060-0559
Hamleini MartinezDepartment of Anesthesiology, Perioperative Care, and Pain Medicine, New York University Grossman School of Medicine, New York, NY, USA.
Randy CuevasDepartment of Anesthesiology, Perioperative Care, and Pain Medicine, New York University Grossman School of Medicine, New York, NY, USA.
Kevin WattDepartment of Pediatrics, University of Utah, Salt Lake City, UT, USA.
Jing WangDepartment of Anesthesiology, Perioperative Care, and Pain Medicine, New York University Grossman School of Medicine, New York, NY, USA.

Funding

COVID-19 Supplement - Center for Innovative TRIals in ChilDrEN and AdulTs (TRIDENT)U24TR001608 · NCATS · DUKE UNIVERSITY · PI BENJAMIN, DANIEL K., HERNANDEZ, ADRIAN · 2016 to 2022
$177.0M
Utah Trial Innovation CenterU24TR001597 · NCATS · UNIVERSITY OF UTAH · PI DEAN, JONATHAN MICHAEL · 2016 to 2022
$39.6M
Johns Hopkins-Tufts Trial Innovation Center HEAL Pain ERN SupplementU24TR001609 · NCATS · JOHNS HOPKINS UNIVERSITY · PI HANLEY, DANIEL F · 2016 to 2022
$36.3M
Improving Clinical trial Education, Recruitment, and Enrollment at CTSA Hubs (I-CERCH) - HEAL SupplementU24TR001579 · NCATS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HARRIS, PAUL A., WILKINS, CONSUELO HOPKINS · 2016 to 2022
$34.1M
HEAL Sickle Cell and CDE SupplementU24TR004315 · NCATS · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI DWYER, JAMIE P., SWARD, KATHERINE ANN · 2022 to 2025
$13.8M
Optimizing the use of ketamine to reduce chronic postsurgical painUH3CA261067 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DOAN, LISA, WANG, JING · 2021 to 2024
$5.2M
NCATS NIH HHS U24 TR001579NCATS NIH HHS U24 TR001597NCATS NIH HHS U24 TR001608NCATS NIH HHS U24 TR001609NCATS NIH HHS U24 TR004315NCI NIH HHS UH3 CA261067
6 · The paper itself

Abstract

Background: The informed consent process has traditionally taken place in person. The introduction of electronic consent (eConsent) has made remote consenting processes possible. Use of eConsent has increased since the COVID-19 pandemic. It has streamlined the process of consenting patients and has been shown to benefit the research study team and participants. eConsent in the Ketamine Analgesia for Long-Lasting Pain Relief After Surgery Kalpas Study: The KALPAS study is a multicenter, double-blind, randomized controlled study investigating the effectiveness of ketamine in reducing chronic post-mastectomy pain in women undergoing mastectomy for oncologic indication. The study uses a two-part consent form consisting of a master consent with information applicable to all sites and site-specific information. All potential participants receive the full two-part consent form for review. When signing the eConsent, however, all potential participants are provided with a concise summary of the informed consent document, an approach not widely used by multicenter studies. eConsent has been noted to be beneficial to research staff when trying to gather informed consent from participants who live far away from the hospital, want to include their family and friends, and for researchers who can approach patients outside of their clinical appointments. Conclusion: The ability to consent patients remotely has allowed for a flexible workflow within sites and a more patient-centric process that focuses on including loved ones in the discussion and scheduling time to speak to a principal investigator. Demand for eConsent will likely continue in the post-COVID era, and use of a concise summary can allow for a more efficient consenting process.

Indexed as

clinical trialsconcise summaryelectronic consentinformed consent

Identifiers

PMID39931425
PMCPMC11808973

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.