Evidence map›Paper›PMID 34077973›Full record

ArticleApplied clinical informatics2021

Developing the Minimum Dataset for the New Mexico Decedent Image Database.

Shamsi Daneshvari Berry, Philip J Kroth, Heather J H Edgar, Teddy D Warner

Abstract read
In one paragraph

Article in Applied clinical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. The current state of forensic imaging - perspectives.International journal of legal medicine · 2025
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Efficient cascaded V-net optimization for lower extremity CT segmentation validated using bone morphology assessment.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2022
    Article
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.

Shamsi Daneshvari BerryWestern Michigan University, Homer Stryker M.D. School of Medicine, Kalamazoo, Michigan, United States.
Philip J KrothWestern Michigan University, Homer Stryker M.D. School of Medicine, Kalamazoo, Michigan, United States.
Heather J H EdgarUniversity of New Mexico, Albuquerque, New Mexico, United States.
Teddy D WarnerUniversity of New Mexico, Albuquerque, New Mexico, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA minimum dataset (MDS) can be determined ad hoc by an investigator or small team; by a metadata expert; or by using a consensus method to take advantage of the global knowledge and expertise of a large group of experts. The first method is the most commonly applied.

objectiveHere, we describe a use of the third approach using a modified Delphi method to determine the optimal MDS for a dataset of full body computed tomography scans. The scans are of decedents whose deaths were investigated at the New Mexico Office of the Medical Investigator and constitute the New Mexico Decedent Image Database (NMDID).

methodsThe authors initiated the consensus process by suggesting 50 original variables to elicit expert reactions. Experts were recruited from a variety of scientific disciplines and from around the world. Three rounds of variable selection showed high rates of consensus.

resultsIn total, 59 variables were selected, only 52% of which the original resource authors selected. Using a snowball method, a second set of experts was recruited to validate the variables chosen in the design phase. During the validation phase, no variables were selected for deletion.

conclusionNMDID is likely to remain more "future proof" than if a single metadata expert or only the original team of investigators designed the metadata.

Indexed as

Research DesignConsensusDatabases, FactualDelphi TechniqueNew Mexico

Identifiers

PMID34077973
PMCPMC8172257

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.