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Prediction of anemia and estimation of hemoglobin concentration using a smartphone camera
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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279386/ https://www.ncbi.nlm.nih.gov/pubmed/34260592 http://dx.doi.org/10.1371/journal.pone.0253495 |
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author | Suner, Selim Rayner, James Ozturan, Ibrahim U. Hogan, Geoffrey Meehan, Caroline P. Chambers, Alison B. Baird, Janette Jay, Gregory D. |
author_facet | Suner, Selim Rayner, James Ozturan, Ibrahim U. Hogan, Geoffrey Meehan, Caroline P. Chambers, Alison B. Baird, Janette Jay, Gregory D. |
author_sort | Suner, Selim |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8279386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-82793862021-07-31 Prediction of anemia and estimation of hemoglobin concentration using a smartphone camera Suner, Selim Rayner, James Ozturan, Ibrahim U. Hogan, Geoffrey Meehan, Caroline P. Chambers, Alison B. Baird, Janette Jay, Gregory D. PLoS One Research Article 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. Public Library of Science 2021-07-14 /pmc/articles/PMC8279386/ /pubmed/34260592 http://dx.doi.org/10.1371/journal.pone.0253495 Text en © 2021 Suner et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Suner, Selim Rayner, James Ozturan, Ibrahim U. Hogan, Geoffrey Meehan, Caroline P. Chambers, Alison B. Baird, Janette Jay, Gregory D. Prediction of anemia and estimation of hemoglobin concentration using a smartphone camera |
title | Prediction of anemia and estimation of hemoglobin concentration using a smartphone camera |
title_full | Prediction of anemia and estimation of hemoglobin concentration using a smartphone camera |
title_fullStr | Prediction of anemia and estimation of hemoglobin concentration using a smartphone camera |
title_full_unstemmed | Prediction of anemia and estimation of hemoglobin concentration using a smartphone camera |
title_short | Prediction of anemia and estimation of hemoglobin concentration using a smartphone camera |
title_sort | prediction of anemia and estimation of hemoglobin concentration using a smartphone camera |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279386/ https://www.ncbi.nlm.nih.gov/pubmed/34260592 http://dx.doi.org/10.1371/journal.pone.0253495 |
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