Next Article in Journal
GSTM1 and Liver Iron Content in Children with Sickle Cell Anemia and Iron Overload
Previous Article in Journal
CMR Tissue Characterization in Patients with HFmrEF
Previous Article in Special Issue
Artificial Intelligence for Automatic Measurement of Sagittal Vertical Axis Using ResUNet Framework
Open AccessCommunication

Computed and Subjective Blue Scleral Color Analysis as a Diagnostic Tool for Iron Deficiency: A Pilot Study

1
Internal Medicine Department, University Hospital Clermont-Ferrand, 1 place Lucie et Raymond Aubrac, 63003 Clermont-Ferrand, France
2
Clermont Auvergne University, CNRS, SIGMA Clermont, Institute Pascal, Campus universitaire des Cézeaux, 4 Avenue Blaise Pascal, 63178 Aubière, France
3
LISIC Laboratory, Côte d’Opale University, 50 Rue Ferdinand Buisson, 62228 Calais, France
4
University Hospital Clermont-Ferrand, Biostatistics Unit, 58 Rue Montalembert, 63003 Clermont-Ferrand, France
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2019, 8(11), 1876; https://doi.org/10.3390/jcm8111876
Received: 11 October 2019 / Revised: 30 October 2019 / Accepted: 1 November 2019 / Published: 5 November 2019
(This article belongs to the Special Issue The Future of Artificial Intelligence in Clinical Medicine)
Iron deficiency (ID) is the most common nutritional deficiency. ID diagnosis requires ferritin measurement because clinical findings are poor and nonspecific. We studied the diagnostic value of blue sclera, which was scarcely reported as a specific and sensitive sign of ID. We enrolled 74 patients suspected of having ID. Pictures of their eyes were taken using a smartphone under similar daylight conditions. Three independent physicians graded the scleral color, and a computer analysis yielded the blue percentile of the sclera image. Final analysis included 67 patients (mean age 59.9 ± 20.1 years). Fifty-one had ID. Subjective blue scleral color was associated with ID for physician 1 (64.5% vs. 86.1%, p = 0.03). Sensitivity was 60.8% (CI95: 46.1%; 74.2%), specificity 68.8% (CI95: 41.3%; 89%), and positive predictive value 86.1% (CI95: 70.5%; 95.3%). A marginal difference was observed for other physicians (p = 0.05). Computer analysis showed higher blue in the ID group (p = 0.04). The area under the receiver operating characteristic (ROC) curve was 0.7 (0.54; 0.85). Sensitivity was 78.4% (CI95: 63.7%; 88.7%), specificity was 50% (CI95: 24.7%; 75.3%). Assessment of blue sclera was not influenced by iris color, sex, or anemia. We showed that blue sclera has good positive predictive value for ID diagnosis, and computer analysis was correlated to clinical assessment. Improvement of this innovative, non-invasive method could provide an easy handling and inexpensive diagnosis tool for ID. View Full-Text
Keywords: sclera; iron metabolism disorders; anemia; ROC curve; smartphone; diagnostic imaging sclera; iron metabolism disorders; anemia; ROC curve; smartphone; diagnostic imaging
Show Figures

Figure 1

MDPI and ACS Style

Lobbes, H.; Dehos, J.; Pereira, B.; Le Guenno, G.; Sarry, L.; Ruivard, M. Computed and Subjective Blue Scleral Color Analysis as a Diagnostic Tool for Iron Deficiency: A Pilot Study. J. Clin. Med. 2019, 8, 1876.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop