Evidence map›Paper›PMID 34260592›Full record

Observational studyPloS one2021

Prediction of anemia and estimation of hemoglobin concentration using a smartphone camera.

Selim Suner, James Rayner, Ibrahim U Ozturan, Geoffrey Hogan, Caroline P Meehan, Alison B Chambers, Janette Baird, Gregory D Jay

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.1field-weighted citation impact, top 4% of its field
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

21 citing papers in PubMed, 60 citations in OpenAlex.

  1. Article
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  4. Smartphone-Based Anemia ScreeningCurrent medical imaging · 2025
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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

8 authors at 1 institution in 1 country.

Selim SunerDepartment of Emergency Medicine, Brown University, Providence, Rhode Island, United States of America.
James RaynerDepartment of Emergency Medicine, Brown University, Providence, Rhode Island, United States of America.
Ibrahim U OzturanAlpert School of Medicine, Brown University, Providence, Rhode Island, United States of America.ORCID 0000-0002-1364-5292
Geoffrey HoganAlpert School of Medicine, Brown University, Providence, Rhode Island, United States of America.
Caroline P MeehanDepartment of Emergency Medicine, Brown University, Providence, Rhode Island, United States of America.
Alison B ChambersDepartment of Medicine, Brown University, Providence, Rhode Island, United States of America.ORCID 0000-0003-0567-746X
Janette BairdDepartment of Emergency Medicine, Brown University, Providence, Rhode Island, United States of America.
Gregory D JayDepartment of Emergency Medicine, Brown University, Providence, Rhode Island, United States of America.ORCID 0000-0003-1517-8488
Brown University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Anemia, defined as a low hemoglobin concentration, has a large impact on the health of the world's population. We describe the use of a ubiquitous device, the smartphone, to predict hemoglobin concentration and screen for anemia. This was a prospective convenience sample study conducted in Emergency Department (ED) patients of an academic teaching hospital. In an algorithm derivation phase, images of both conjunctiva were obtained from 142 patients in Phase 1 using a smartphone. A region of interest targeting the palpebral conjunctiva was selected from each image. Image-based parameters were extracted and used in stepwise regression analyses to develop a prediction model of estimated hemoglobin (HBc). In Phase 2, a validation model was constructed using data from 202 new ED patients. The final model based on all 344 patients was tested for accuracy in anemia and transfusion thresholds. Hemoglobin concentration ranged from 4.7 to 19.6 g/dL (mean 12.5). In Phase 1, there was a significant association between HBc and laboratory-predicted hemoglobin (HBl) slope = 1.07 (CI = 0.98-1.15), p<0.001. Accuracy, sensitivity, and specificity of HBc for predicting anemia was 82.9 [79.3, 86.4], 90.7 [87.0, 94.4], and 73.3 [67.1, 79.5], respectively. In Phase 2, accuracy, sensitivity and specificity decreased to 72.6 [71.4, 73.8], 72.8 [71, 74.6], and 72.5 [70.8, 74.1]. Accuracy for low (<7 g/dL) and high (<9 g/dL) transfusion thresholds was 94.4 [93.7, 95] and 86 [85, 86.9] respectively. Error trended with increasing HBl values (slope 0.27 [0.19, 0.36] and intercept -3.14 [-4.21, -2.07] (p<0.001) such that HBc tended to underestimate hemoglobin in higher ranges and overestimate in lower ranges. Higher quality images had a smaller bias trend than lower quality images. When separated by skin tone results were unaffected. A smartphone can be used in screening for anemia and transfusion thresholds. Improvements in image quality and computational corrections can further enhance estimates of hemoglobin.

Indexed as

SmartphoneAdultAgedAged, 80 and overAlgorithmsAnemiaConjunctivaFemaleHemoglobinsHumansImage Processing, Computer-AssistedMaleMiddle AgedPhotographyProspective StudiesReproducibility of ResultsHemoglobins

Identifiers

PMID34260592
PMCPMC8279386
OpenAlexW3180713012

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.