Think you're anaemic? Take a selfie of your eye

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US researchers say they have developed an algorithm that can detect whether you are anaemic by examining a picture of your inner eyelid. Anaemia - a low haemoglobin concentration in your blood - affects more than 25 per cent of the global population, and can be a significant risk factor for issues that could lead to death, especially for children, the elderly, and the chronically ill. The team say a standard smartphone image would suffice, and would remove the need for invasive and infrastructure-needing blood tests. 

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From: PLOS

Smartphone photos can be used to detect anemia

Algorithm could allow screening without the need for invasive, infrastructure-requiring blood tests

A picture of a person’s inner eyelid taken with a standard smartphone camera can be used to screen for anemia, according to a new study published this week in the open-access journal PLOS ONE by Selim Suner of Brown University and Rhode Island Hospital, USA, and colleagues.

Anemia, a low blood hemoglobin concentration, affects an estimated 5.6% of Americans and more than 25% of the global population. Severe anemia is a significant risk factor for morbidity and mortality, especially in children, the elderly and the chronically ill. There is an unmet need for inexpensive, accessible and non-invasive point-of-care tools to screen for and diagnose anemia.

Previous studies have shown that the inside of a person’s lower eyelid—called the palpebral conjunctiva—appears paler with anemia.  In the new study, researchers obtained smartphone images of the palpebral conjunctiva from 142 patients with a wide range of hemoglobin levels. They zoomed into a small region of the conjunctiva in each photo and developed a new algorithm optimizing color resolution as well as a prediction model linking conjunctiva color, compared to the surrounding skin and whites of the eyes, to hemoglobin levels. Then, the team tested the new algorithms on photos collected from 202 new patients.

When analyzing the new set of photographs, the model was 72.6% accurate (CI 71.4-73.8), 72.8% sensitive (71-74.6), and 72.5% specific (70.8-74.1) at predicting anemia. Accuracy for transfusion thresholds was higher, at 94.4% accurate (93.7-95.0) for a low transfusion threshold and 86% accurate (85.0-86.9) for a higher threshold. Skin tone did not change results, but image quality had some effect. The results suggest that a smartphone app could be used to screen for anemia in a telehealth or remote setting where the infrastructure for blood tests is not available.

The authors add: “Images of the lower eyelid’s vascular surface obtained by a smartphone camera can be utilized to estimate blood hemoglobin concentration and predict anemia which is a serious health condition afflicting billions of people world-wide with a disproportionate effect in developing countries.  Utilization of non-invasive techniques to detect anemia opens the door to widespread screening, early diagnosis and treatment, particularly in low resource settings where access to healthcare is sparce.”

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conference:
PLOS ONE
Research:Paper
Organisation/s: Brown University, USA
Funder: J.R. Funded by Brown Emergency Medicine Foundation who played no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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