Evidence map›Paper›PMID 37350915›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2023

High Resolution and Spatiotemporal Place-Based Computable Exposures at Scale.

Erika Rasnick, Patrick Ryan, Jeff Blossom, Heike Luttmann-Gibson, Nathan Lothrop, Rima Habre, Diane R Gold, Andrew Vancil, Joel Schwartz, James E Gern and 1 more

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

Erika RasnickCincinnati Children's Hospital Medical Center.
Patrick RyanCincinnati Children's Hospital Medical Center.
Jeff BlossomCenter for Geographic Analysis, Harvard University.
Heike Luttmann-GibsonDepartment of Environmental Health, Harvard T.H. Chan School of Public Health.
Nathan LothropAsthma and Airway Disease Research Center, University of Arizona.
Rima HabreDepartment of Population and Public Health Sciences, University of Southern California.
Diane R GoldDepartment of Environmental Health, Harvard T.H. Chan School of Public Health.
Andrew VancilCincinnati Children's Hospital Medical Center.
Joel SchwartzDepartment of Epidemiology, Harvard T. H. Chan School of Public Health.
James E GernDepartment of Pediatrics, School of Medicine and Public Health, University of Wisconsin-Madison.
Cole BrokampCincinnati Children's Hospital Medical Center.

Funding

Wisconsin Infant Study Cohort (WISC) ECHO Pediatric Follow-UpUH3OD023282 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI James E. Gern · 2018 to 2026
$64.8M
Wisconsin Infant Study Cohort (WISC) ECHO Pediatric Follow-UpUG3OD023282 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI GERN, JAMES E. · 2016 to 2024
$19.3M
NIH HHS UG3 OD023282NIH HHS UH3 OD023282
6 · The paper itself

Abstract

Place-based exposures, termed "geomarkers", are powerful determinants of health but are often understudied because of a lack of open data and integration tools. Existing DeGAUSS (Decentralized Geomarker Assessment for Multisite Studies) software has been successfully implemented in multi-site studies, ensuring reproducibility and protection of health information. However, DeGAUSS relies on transporting geomarker data, which is not feasible for high-resolution spatiotemporal data too large to store locally or download over the internet. We expanded the DeGAUSS framework for high-resolution spatiotemporal geomarkers. Our approach stores data subsets based on coarsened location and year in an online repository, and appropriate subsets are downloaded to complete exposure assessment locally using exact date and location. We created and validated two free and open-source DeGAUSS containers for estimation of high-resolution, daily ambient air pollutant exposures, transforming published exposure assessment models into computable exposures for geomarker assessment at scale.

Identifiers

PMID37350915
PMCPMC10283107

What OpenQuestion holds

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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 OpenQuestion graph.