Evidence map›Paper›PMID 39991614›Full record

ArticleJournal of hand surgery global online2025

Inexperienced Evaluator Identification of Hand Ischemia Via Video Processed with Pigment-Enhancing Technology.

Max Horowitz, Aygul Iskandarova, Gabriel Yohe, Shihab Rahman, Nicholas Durr, Aviram M Giladi

Abstract read
In one paragraph

Article in Journal of hand surgery global online, 2025. 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. 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

6 authors.

Max HorowitzThe Curtis National Hand Center, MedStar Union Memorial Hospital, Baltimore, MD.
Aygul IskandarovaThe Curtis National Hand Center, MedStar Union Memorial Hospital, Baltimore, MD.
Gabriel YoheThe Curtis National Hand Center, MedStar Union Memorial Hospital, Baltimore, MD.
Shihab RahmanDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD.
Nicholas DurrDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD.
Aviram M GiladiThe Curtis National Hand Center, MedStar Union Memorial Hospital, Baltimore, MD.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Eulerian video magnification (EVM)+waveform is a novel video processing software that enhances visualization of tissue perfusion and has been shown to improve hand surgeon identification of ischemia via video alone. The purpose of this study is to determine whether EVM+waveform technology will support improved accuracy in identifying hand ischemia for less experienced persons, regardless of the evaluator's health care experience or the melanin content of the hand in the video. Methods: Healthy volunteers were recruited for us to record videos of their hands both perfused and under tourniquet-induced ischemia. Videos were processed with EVM+waveform and inserted into a 26-question survey. There were two types of questions presented in each survey. One format showed a video processed with EVM+waveform, and the respondent was asked if the hand was ischemic, perfused, or if they were unsure. The second format presented two side-by-side videos, one ischemic and one perfused. Both were processed with EVM+waveform, and the respondent had to choose which was ischemic. Respondents included both medical and non-medical professionals none of whom had experience with hand surgery. Results: A total of 64 survey responses were recorded. The EVM+waveform technology significantly improved accuracy in determining ischemia regardless of the respondent's health care experience. Respondents were divided into medical doctorate (MD; n = 15) and non-MD (n = 49) groups. Both groups demonstrated significant improvement in determining ischemia when using EVM+waveform. Within the non-MD cohort, accuracy percentages significantly improved across Fitzpatrick types IV, V, and VI. Within the MD cohort, accuracy percentages significantly improved across Fitzpatrick types III, V, and VI. Conclusions: These findings further establish EVM+waveform as an effective modality for identifying ischemia via video alone, as it enhanced performance for inexperienced evaluators. EVM+waveform is effective for assessing various skin types, especially those with higher skin melanin content. Type of study/level of evidence: Diagnostic, IV.

Indexed as

Eulerian video magnificationInexperienced evaluator identificationIschemia evaluationTele-triageUpper extremity

Identifiers

PMID39991614
PMCPMC11846574

What OpenQuestion 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 OpenQuestion graph.