Clinical and real-world evaluation of a fingernail selfie smartphone app for noninvasive, individually-personalized estimation of blood hemoglobin levels

Abstract

Patients with chronic anemia, or low blood hemoglobin levels, are frequently subjected to the cost, inconvenience, and discomfort of traditional hematology analyzer-based measurements of blood hemoglobin levels via complete blood counts. Elimination of the need for complete blood count testing for hemoglobin screening is an unmet clinical need that we previously addressed by developing a non-invasive smartphone app that estimates hemoglobin levels via image analysis of fingernail bed images. In this work, we present additional data yielding significant improvement upon our previously established technology and describe the clinical validation, and real-world translation of the technology into a commercial product. To improve accuracy and create a clinical use case, we trained the app algorithm on individuals with chronic anemia to personalize the image analysis algorithm for estimating hemoglobin levels. Individual-level differences associated with using the app (variations between individuals, how a user captures images, the specific smartphone they use, the lighting conditions in the location they take the pictures, and biological variability within a population) appear to be the greatest source of measurement variability within larger sample sets. Therefore, we hypothesized that personalization of the algorithm could correct for user-to-user variability and translate to improved accuracy at the individual level. To test this hypothesis, we trained and tested personalized algorithms for individuals in clinical and real world settings. We enrolled 35 chronically anemic subjects [a chronic kidney disease (CKD) cohort] in a clinical study wherein the app algorithm was trained using complete blood count data and paired fingernail bed images, then tested against complete blood count data at subsequent study timepoints. After personalization, testing data revealed a mean absolute error (MAE) of 0.74 g/dL with a root mean squared error (RMSE) of 0.97 g/dL across all testing visits across all subjects, a significant improvement when compared to performance without personalization in the same user group (1.36 g/dL MAE and 1.70 g/dL RMSE, p = 3.13E-11). The app was also used in the real world by real app users who self-reported lab/complete blood count blood draw results. App performance findings were consistent with analysis of self-reported data from 17 individuals using our app. After training of the individual app algorithm in the real world, testing data revealed a mean absolute error (MAE) of 0.62 g/dL with a root mean squared error (RMSE) of 0.85 g/dL when 4 training data points were used, an improvement when compared to performance of the app without personalization in the same user group (0.71 g/dL MAE and 1.27 g/dL RMSE). The personalized app accuracy is similar to that of other noninvasive Hgb measurement technologies currently on the market as medical devices with US Food & Drug Administration (US FDA) clearance. Thus, our technology represents a significant step forward towards true personalized medicine in a digital healthcare setting.

Competing Interest Statement

R.G.M, P.L, J.S, E.A.T, and W.A.L are all employed by Sanguina, Inc and have an interest in the technology described in this study. Furthermore, R.G.M, P.L, E.A.T, and W.A.L are equity holders in Sanguina, Inc.

Funding Statement

Funding for this study was provided in part by the National Heart Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) via award 2R44HL139250-02A1 as well as by AstraZeneca.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The Advarra institutional review board gave ethical approval for the clinical work (Pro00049129).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.

Yes

Data Availability

All data produced in the present study are available upon reasonable request to the authors.

留言 (0)

沒有登入
gif