Evidence map›Paper›PMID 41271284›Full record

ReviewClinics in geriatric medicine2026

Artificial Intelligence, Informatics, and Pain in Aging.

Urszula A Snigurska, Ragnhildur I Bjarnadottir

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Clinics in geriatric medicine, 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

2 authors.

Urszula A SnigurskaPain Research and Intervention Center of Excellence, Clinical and Translational Science Institute, University of Florida, 2004 Mowry Road, PO Box 100242, Gainesville, FL 32610, USA. Electronic address: usnigurska@ufl.edu.
Ragnhildur I BjarnadottirDepartment of Family, Community and Health Systems Science, College of Nursing, University of Florida, 1225 Center Drive, PO Box 100197, Gainesville, FL 32610, USA.

Funding

Social Determinants of Health, Race/Ethnicity, and White Matter HyperintensitiesP30AG066506 · NIA · UNIVERSITY OF FLORIDA · PI Ranjan Duara, DAVID LOEWENSTEIN · 2020 to 2026
$25.6M
the Integrative and Multidisciplinary Pain and Aging Research Training (IMPART) ProgramT32AG049673 · NIA · UNIVERSITY OF FLORIDA · PI FILLINGIM, ROGER B · 2015 to 2024
$3.2M
Harmonizing and Integrating Nursing Data into Multidisciplinary Datasets to Evaluate Hospital Care and Readmissions of Older Adults with Alzheimer's Disease-Related DementiasR33AG072265 · NIA · UNIVERSITY OF FLORIDA · PI KEENAN, GAIL M, MACIEIRA, TAMARA G.R. · 2023 to 2025
$2.1M
Advancing Interdisciplinary Science of Aging through Identification of Iatrogenic Complications: The UF EHR Clinical Data Infrastructure for Enhanced Patient Safety among the Elderly (UF-ECLIPSE)R33AG062884 · NIA · UNIVERSITY OF FLORIDA · PI INGIBJARGARDOTTIR BJARNADOTTIR, RAGNHILDUR, LUCERO, ROBERT J · 2021 to 2023
$2.1M
NIA NIH HHS P30 AG066506NIA NIH HHS R33 AG062884NIA NIH HHS R33 AG072265NIA NIH HHS T32 AG049673
6 · The paper itself

Abstract

The aging population is disproportionately affected by pain in the acute care setting. Due to the complexity of the pain experience, pain management presents with significant challenges. Recent advancements in advanced analytics and computational tools offer a promise for addressing these challenges and improving pain management outcomes among older patients. This review summarizes the recent advancements in artificial intelligence and its potential for better pain management practices across acute-care settings.

Indexed as

AgingArtificial IntelligencePainPain ManagementAgedHumansAgedAlgorithmsArtificial intelligenceClinical decision-makingEvidence-based practiceLarge language modelsPain managementPrecision medicine

Identifiers

PMID41271284
PMCPMC13524524

What Socratic holds

Textmetadata
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 Socratic graph.