Evidence mapPaperPMID 41935211Full record

ReviewNPJ digital medicine2026

An operational target trial emulation framework for causal inference using electronic health record data.

Yanfei Wang, Yongqiu Li, Tuo Lin, Yi Guo

Abstract readReview
In one paragraph

Review in NPJ digital 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

4 authors.

Yanfei WangDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA.
Yongqiu LiDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA.
Tuo LinDepartment of Biostatistics, University of Florida, Colleges of Public Health and Health Professions & Medicine, University of Florida, Gainesville, FL, USA.
Yi GuoDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, USA. yiguo@ufl.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Target trial emulation (TTE) enables causal inference from electronic health record (EHR) data when randomized clinical trials are infeasible, but its validity depends on whether EHR data can support the required trial design components. This review presents an operational framework that distinguishes trial specification from its realization in EHR data and clarifies how healthcare-driven data generation constrains identifiability and when EHR-based TTE can or cannot yield interpretable causal estimates.

Identifiers

PMID41935211
PMCPMC13230876

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.