Disposable platform provides visual and color-based point-of-care anemia self-testing

A Low-Cost Test for Anemia Using an Artificial Neural Network

BACKGROUND

Anemia during pregnancy can complicate maternal and neonatal health and even lead to fatal consequences if not diagnosed early on. Around 99% of women who face maternal mortality are from middle or low-income countries. Early screening of anemia could facilitate improved health outcomes in pregnant women. Point of care techniques are preferred due to their ability to provide results rapidly and because they can be used by personnel with minimal or no training. Such techniques are especially useful in resource-constrained settings like rural parts of developing countries.

OBJECTIVES

The aim of the study was to develop a tool using an Artificial Neural Network (ANN) to estimate hemoglobin values using color information recorded from blood sample images. Our method utilizes inexpensive consumables and a simple image acquisition setup that can be assembled easily.

METHODS

This study explores a neural network model to estimate the hemoglobin content in an individual's blood sample. Blood samples were collected from 86 volunteers and the images of blood drops were obtained using an image acquisition setup designed by the team. The color intensity values calculated from the blood drop images were used as feature descriptors for the samples. The features obtained from our samples were consequently fed to the Artificial Neural Network.

RESULTS

Our neural network that gives the best result has the architecture of 11 neurons in each of the 5 layers. The best model gave estimated hemoglobin levels by analyzing color of blood samples with an accuracy of ±1.8 g/dl Limits of agreement (LOA) and bias 0.03 g/dl (with mean error of 0.75 g/dl). The model was subsequently tested with a validation set prepared from an additional 65 samples. The estimated hemoglobin levels gave an accuracy of +2 g/dl to -1.9 g/dl Limits of agreement (LOA) and bias 0.06 g/dl (with mean error of 0.78 g/dl).

CONCLUSION

Optimization of sensitivity and specificity has been able to achieve the sensitivity and specificity values as 95.5% and 52% respectively. These results are at par with the contemporary measurement techniques indicating that our method can be used as a workable screening technique itself.

A portable smartphone-based hemoglobin point-of-care testing platform for accurate anemia diagnostics

Anemia affects over 2 billion people worldwide, with the heaviest burden borne by women and children. At present, anemia is diagnosed by measuring hemoglobin (Hb) levels, which must be done in hospitals or commercial laboratories by skilled operators. In this work, we report a portable, affordable ($3), easy-to-operate (1 min) and accurate smartphone-based Hb analyzer (SHbA) that uses a drop of finger-pricked blood for anemia point-of-care test (POCT) applications. POCT of Hb was achieved using a smartphone ambient light sensor (ALS) to accurately measure the absorbance of colorimetric Hb biochemical analysis reagents in a microcuvette, as well as an Android-based application for results analysis. SHbA validation results agreed well with those reported by a hematology analyzer, and the SHbA has an anemia diagnosis sensitivity of 95.4% and specificity of 96.3% for venous blood (n = 360) and a sensitivity of 96.39% and specificity of 95.58% for fingertip blood (n = 475). In addition, SHbA exhibits excellent performance in the diagnosis and treatment guidance of anemia high-risk populations, including tumor chemotherapy patients (n = 424), pregnant women (n = 214) and thalassemia patients (n = 208). Importantly, volunteer self-testing results (n = 20) indicate that SHbA can be used for home-based anemia diagnosis and monitoring. SHbA has the advantages of high sensitivity and specificity while being cheap and easy to operate, making it widely applicable for the diagnosis and treatment of anemia, especially for high-risk patients in areas with poor medical resources.

Measuring haemolysis in cattle serum by direct UV-VIS and RGB digital image-based methods

A simple, rapid procedure is required for the routine detection and quantification of haemolysis, one of the main sources of unreliable results in serum analysis. In this study, we compared two different approaches for the rapid determination of haemolysis in cattle serum. The first consisted of estimating haemolysis via a simple direct ultraviolet–visible (UV–VIS) spectrophotometric measurement of serum samples. The second involved analysis of red, green, blue (RGB) colour data extracted from digital images of serum samples and relating the haemoglobin (Hb) content by means of both univariate (R, G, B and intensity separately) and multivariate calibrations (R, G, B and intensity jointly) using partial least squares regression and artificial neural networks. The direct UV–VIS analysis and RGB-multivariate analysis using neural network methods were both appropriate for evaluating haemolysis in serum cattle samples. The procedures displayed good accuracy (mean recoveries of 100.7 and 102.1%, respectively), adequate precision (with coefficients of variation from 0.21 to 2.68%), limit of detection (0.14 and 0.21 g L^–1, respectively), and linearity of up to 10 g L^–1.

Smartphone-Integrated Label-Free Rapid Screening of Anemia from the Pattern Formed by One Drop of Blood on a Wet Paper Strip

Screening of anemic patients poses demanding challenges in extreme point-of-care settings where the gold standard diagnostic technologies are not pragmatic and the alternative point-of-care technologies suffer from compromised accuracy, prohibitive cost, process complexity, or reagent stability issues. As a disruption to this paradigm, here, we report the development of a smartphone-based sensor for rapid screening of anemic patients by exploiting the patterns formed by a spreading drop of blood on a wet paper strip wherein blood attempts to displace a more viscous fluid, on the porous matrix of a paper, leading to "finger-like" projections at the interface. We analyze the topological features of the pattern via smartphone-enabled image analytics and map the same with the relative occupancy of the red blood cells in the blood sample, allowing for label-free screening and classification of blood samples corresponding to moderate to severe anemic conditions. The accuracy of detection is verified by comparing with gold standard reports of hematology analyzer, showing a strong correlation coefficient (R²) of 0.975. This technique is likely to provide a crucial decision-making tool that obviates delicate reagents and skilled technicians for supreme functionality in resource-limited settings.

Deep-Learning-Based Hemoglobin Concentration Prediction and Anemia Screening Using Ultra-Wide Field Fundus Images

Background: Anemia is the most common hematological disorder. The purpose of this study was to establish and validate a deep-learning model to predict Hgb concentrations and screen anemia using ultra-wide-field (UWF) fundus images.

Methods: The study was conducted at Peking Union Medical College Hospital. Optos color images taken between January 2017 and June 2021 were screened for building the dataset. ASModel_UWF using UWF images was developed. Mean absolute error (MAE) and area under the receiver operating characteristics curve (AUC) were used to evaluate its performance. Saliency maps were generated to make the visual explanation of the model.

Results: ASModel_UWF acquired the MAE of the prediction task of 0.83 g/dl (95%CI: 0.81–0.85 g/dl) and the AUC of the screening task of 0.93 (95%CI: 0.92–0.95). Compared with other screening approaches, it achieved the best performance of AUC and sensitivity when the test dataset size was larger than 1000. The model tended to focus on the area around the optic disc, retinal vessels, and some regions located at the peripheral area of the retina, which were undetected by non-UWF imaging.

Conclusion: The deep-learning model ASModel_UWF could both predict Hgb concentration and screen anemia in a non-invasive and accurate way with high efficiency.

Point-of-care microchip electrophoresis for integrated anemia and hemoglobin variant testing

Anemia affects over 25% of the world's population with the heaviest burden borne by women and children. Genetic hemoglobin (Hb) variants, such as sickle cell disease, are among the major causes of anemia. Anemia and Hb variant are pathologically interrelated and have an overlapping geographical distribution. We present the first point-of-care (POC) platform to perform both anemia detection and Hb variant identification, using a single paper-based electrophoresis test. Feasibility of this new integrated diagnostic approach is demonstrated via testing individuals with anemia and/or sickle cell disease. Hemoglobin level determination is performed by an artificial neural network (ANN) based machine learning algorithm, which achieves a mean absolute error of 0.55 g dL^-1 and a bias of -0.10 g dL^-1 against the gold standard (95% limits of agreement: 1.5 g dL^-1) from Bland-Altman analysis on the test set. Resultant anemia detection is achieved with 100% sensitivity and 92.3% specificity. With the same tests, subjects with sickle cell disease were identified with 100% sensitivity and specificity. Overall, the presented platform enabled, for the first time, integrated anemia detection and hemoglobin variant identification using a single point-of-care test.

Non-invasive hemoglobin measurement devices require refinement to match diagnostic performance with their high level of usability and acceptability

Anemia remains an important global health problem. Inexpensive, accurate, and noninvasive solutions are needed to monitor and evaluate anemia in resource-limited settings. We evaluated the performance of multiple point-of-care hemoglobin devices, including a novel noninvasive smartphone application tested on Apple® and Android® cell phones, Masimo Pronto®, and HemoCue® Hb-301 and Hb-801, against a gold-standard hematology analyzer (reference hemoglobin) using venous blood. We examined correlations between hemoglobin devices and reference hemoglobin, device accuracy (average bias, Bland-Altman plots, clinical performance) and classification bias (sensitivity, specificity) among 299 refugees (10mo-65y) in Atlanta, GA. Semi-structured interviews (n = 19) with participants and staff assessed usability and acceptability. Mean reference hemoglobin was 13.7 g/dL (SD:1.8) with 12.5% anemia. Noninvasive hemoglobin devices were not well correlated with reference hemoglobin (Apple® R² = 0.08, Android® R² = 0.11, Masimo Pronto® R² = 0.29), but stronger correlations were reported with HemoCue® Hb-301 (R² = 0.87) and Hb-801 (R² = 0.88). Bias (SD) varied across each device: Apple®: -1.6 g/dL (2.0), Android®: -0.7 g/dL (2.0), Masimo Pronto®: -0.4 g/dL (1.6), HemoCue® Hb-301: +0.4 g/dL (0.7) and HemoCue® Hb-801: +0.2 g/dL (0.6). Clinically acceptable performance (within ± 1 g/dL of reference hemoglobin) was higher for the invasive devices (HemoCue® Hb-301: 90.3%; HemoCue® Hb-801: 93.4%) compared to noninvasive devices (Apple®: 31.5%; Android®: 34.6%; Masimo Pronto®: 49.5%). Sensitivity and specificity were 63.9% and 48.2% for Apple®, 36.1% and 67.6% for Android®, 45.7% and 85.3% for Masimo Pronto®, 54.3% and 97.6% for HemoCue® Hb-301, and 66.7% and 97.6% for HemoCue® Hb-801. Noninvasive devices were considered easy to use and were the preferred method by participants. Among the only studies to compare multiple point-of-care approaches to hemoglobin testing, the diagnostic ability of HemoCue® was comparable to reference hemoglobin, while noninvasive devices had high user acceptability but considerable biases. Improvements in noninvasive device performance and further testing in anemic populations are recommended before broader use.

Emerging point-of-care technologies for anemia detection

Anemia, characterized by low blood hemoglobin level, affects about 25% of the world's population with the heaviest burden borne by women and children. Anemia leads to impaired cognitive development in children, as well as high morbidity and early mortality among sufferers. Anemia can be caused by nutritional deficiencies, oncologic treatments and diseases, and infections such as malaria, as well as inherited hemoglobin or red cell disorders. Effective treatments are available for anemia upon early detection and the treatment method is highly dependent on the cause of anemia. There is a need for point-of-care (POC) screening, early diagnosis, and monitoring of anemia, which is currently not widely accessible due to technical challenges and cost, especially in low- and middle-income countries where anemia is most prevalent. This review first introduces the evolution of anemia detection methods followed by their implementation in current commercially available POC anemia diagnostic devices. Then, emerging POC anemia detection technologies leveraging new methods are reviewed. Finally, we highlight the future trends of integrating anemia detection with the diagnosis of relevant underlying disorders to accurately identify specific root causes and to facilitate personalized treatment and care.

Point-of-care haemoglobin testing in African hospitals: a neglected essential diagnostic test

Owing to the rapid turnaround time in the assessment of haemoglobin level by point-of-care tests (POC Hb), these have grown in popularity and scope in large parts of the world. However, whilst POC testing for malaria and HIV remains has been integrated into patient management in Africa, the use of POC haemoglobin testing remains neglected by health services. The main users of transfusions (paediatric, maternity and trauma services) present largely as emergencies. Ward-based POC Hb could result in more rapid and accurate diagnosis of anaemia, contributing to saving of lives and at the same time reduce unnecessary transfusions which deplete the limited supplies of donated blood in Africa. Severe anaemia requiring transfusion is a major cause of paediatric admission in Africa. At a dissemination meeting to discuss the results of a large phase III paediatric transfusion trial and steps to implementation of the findings participants strongly recommended that one of the most pressing actions required was to prioritise the use of POC haemoglobin testing. This would facilitate implementation of the new transfusion algorithm, developed at the meeting, which refines patient management including blood transfusions. We present the rationale for the strongly recommended prioritisation of POC Hb, using paediatric transfusion as an exemplar.

Automated Cardiac Pulse Cycle Analysis From Photoplethysmogram (PPG) Signals Generated From Fingertip Videos Captured Using a Smartphone to Measure Blood Hemoglobin Levels

Two billion people are affected by hemoglobin (Hgb) related diseases. Usual clinical assessments of Hgb are conducted by analyzing venipuncture-obtained blood samples in laboratories. A non-invasive, cheap, point-of-care and accurate Hgb test is needed everywhere. Our group has developed a non-invasive Hgb measurement system using 10-second Smartphone videos of the index fingertips. Custom hardware sets were used to illuminate the fingers. We tested four lighting conditions with wavelengths in the near-infrared spectrum suggested by the absorption properties of two primary components of blood-oxygenated Hgb and plasma. We found a strong linear correlation between our measured and laboratory-measured Hgb levels in 167 patients with a mean absolute percentage error (MAPE) of 5%. In our initial analysis, critical tasks were performed manually. Now, using the same data, we have automated or modified all the steps. For all, male, and female subjects we found a MAPE of 6.43%, 5.34%, and 4.85 and mean squared error (MSE) of 0.84, 0.5, and 0.49 respectively. The new analyses however, have suggested inexplicable inconsistencies in our results, which we attribute to laboratory measurement errors reflected in a non-normative distribution of Hgb levels in our studied patients, as well as excess noise in the specific signals we measured in the videos. Based on these encouraging results, and the promise of greater accuracy with our revised hardware and software tools, we now propose a rigorous validation study to demonstrate that this approach to hemoglobin measurement is appropriate for general clinical application.

Noninvasive Hemoglobin Level Prediction in a Mobile Phone Environment: State of the Art Review and Recommendations

BACKGROUND

There is worldwide demand for an affordable hemoglobin measurement solution, which is a particularly urgent need in developing countries. The smartphone, which is the most penetrated device in both rich and resource-constrained areas, would be a suitable choice to build this solution. Consideration of a smartphone-based hemoglobin measurement tool is compelling because of the possibilities for an affordable, portable, and reliable point-of-care tool by leveraging the camera capacity, computing power, and lighting sources of the smartphone. However, several smartphone-based hemoglobin measurement techniques have encountered significant challenges with respect to data collection methods, sensor selection, signal analysis processes, and machine-learning algorithms. Therefore, a comprehensive analysis of invasive, minimally invasive, and noninvasive methods is required to recommend a hemoglobin measurement process using a smartphone device.

OBJECTIVE

In this study, we analyzed existing invasive, minimally invasive, and noninvasive approaches for blood hemoglobin level measurement with the goal of recommending data collection techniques, signal extraction processes, feature calculation strategies, theoretical foundation, and machine-learning algorithms for developing a noninvasive hemoglobin level estimation point-of-care tool using a smartphone.

METHODS

We explored research papers related to invasive, minimally invasive, and noninvasive hemoglobin level measurement processes. We investigated the challenges and opportunities of each technique. We compared the variation in data collection sites, biosignal processing techniques, theoretical foundations, photoplethysmogram (PPG) signal and features extraction process, machine-learning algorithms, and prediction models to calculate hemoglobin levels. This analysis was then used to recommend realistic approaches to build a smartphone-based point-of-care tool for hemoglobin measurement in a noninvasive manner.

RESULTS

The fingertip area is one of the best data collection sites from the body, followed by the lower eye conjunctival area. Near-infrared (NIR) light-emitting diode (LED) light with wavelengths of 850 nm, 940 nm, and 1070 nm were identified as potential light sources to receive a hemoglobin response from living tissue. PPG signals from fingertip videos, captured under various light sources, can provide critical physiological clues. The features of PPG signals captured under 1070 nm and 850 nm NIR LED are considered to be the best signal combinations following a dual-wavelength theoretical foundation. For error metrics presentation, we recommend the mean absolute percentage error, mean squared error, correlation coefficient, and Bland-Altman plot.

CONCLUSIONS

We addressed the challenges of developing an affordable, portable, and reliable point-of-care tool for hemoglobin measurement using a smartphone. Leveraging the smartphone's camera capacity, computing power, and lighting sources, we define specific recommendations for practical point-of-care solution development. We further provide recommendations to resolve several long-standing research questions, including how to capture a signal using a smartphone camera, select the best body site for signal collection, and overcome noise issues in the smartphone-captured signal. We also describe the process of extracting a signal's features after capturing the signal based on fundamental theory. The list of machine-learning algorithms provided will be useful for processing PPG features. These recommendations should be valuable for future investigators seeking to build a reliable and affordable hemoglobin prediction model using a smartphone.

Smartphone-Enabled Paper-Based Hemoglobin Sensor for Extreme Point-of-Care Diagnostics

We report a simple, affordable (∼0.02 US $/test), rapid (within 5 min), and quantitative paper-based sensor integrated with smartphone application for on-spot detection of hemoglobin (Hgb) concentration using approximately 10 μL of finger-pricked blood. Quantitative analytical colorimetry is achieved via an Android-based application (Sens-Hb), integrating key operational steps of image acquisition, real-time analysis, and result dissemination. Further, feedback from the machine learning algorithm for adaptation of calibration data offers consistent dynamic improvement for precise predictions of the test results. Our study reveals a successful deployment of the extreme point-of-care test in rural settings where no infrastructural facilities for diagnostics are available. The Hgb test device is validated both in the controlled laboratory environment (n = 200) and on the field experiments (n = 142) executed in four different Indian villages. Validation results are well correlated with the pathological gold standard results (r = 0.9583) with high sensitivity and specificity for the healthy (n = 136) (>11 g/dL) (specificity: 97.2%), mildly anemic (n = 55) (<11 g/dL) (sensitivity: 87.5%, specificity: 100%), and severely anemic (n = 9) (<7 g/dL) (sensitivity: 100%, specificity: 100%) samples. Results from field trials reveal that only below 5% cases of the results are interpreted erroneously by classifying mildly anemic patients as healthy ones. On-field deployment has unveiled the test kit to be extremely user friendly that can be handled by minimally trained frontline workers for catering the needs of the underserved communities.

Point-of-care testing of plasma free hemoglobin and hematocrit for mechanical circulatory support

Hematological analysis is essential for patients who are supported by a mechanical circulatory support (MCS). The laboratory methods used to analyze blood components are conventional and accurate, but they require a mandatory turn-around-time for laboratory results, and because of toxic substances, can also be hazardous to analysis workers. Here, a simple and rapid point-of-care device is developed for the measurement of plasma free hemoglobin (PFHb) and hematocrit (Hct), based on colorimetry. The device consists of camera module, minimized centrifuge system, and the custom software that includes the motor control algorithm for the centrifuge system, and the image processing algorithm for measuring the color components of blood from the images. We show that our device measured PFHb with a detection limit of 0.75 mg/dL in the range of (0–100) mg/dL, and Hct with a detection limit of 2.14% in the range of (20–50)%. Our device had a high correlation with the measurement method generally used in clinical laboratories (PFHb R = 0.999, Hct R = 0.739), and the quantitative analysis resulted in precision of 1.44 mg/dL for PFHb value of 14.5 mg/dL, 1.36 mg/dL for PFHb value of 53 mg/dL, and 1.24% for Hct 30%. Also, the device can be measured without any pre-processing when compared to the clinical laboratory method, so results can be obtained within 5 min (about an 1 h for the clinical laboratory method). Therefore, we conclude that the device can be used for point-of-care measurement of PFHb and Hct for MCS.

AnemoCheck-LRS: an optimized, color-based point-of-care test to identify severe anemia in limited-resource settings

BACKGROUND

Severe anemia is common and frequently fatal for hospitalized patients in limited-resource settings. Lack of access to low-cost, accurate, and rapid diagnosis of anemia impedes the delivery of life-saving care and appropriate use of the limited blood supply. The WHO Haemoglobin Colour Scale (HCS) is a simple low-cost test but frequently inaccurate. AnemoCheck-LRS (limited-resource settings) is a rapid, inexpensive, color-based point-of-care (POC) test optimized to diagnose severe anemia.

METHODS

Deidentified whole blood samples were diluted with plasma to create variable hemoglobin (Hb) concentrations, with most in the severe (≤ 7 g/dL) or profound (≤ 5 g/dL) anemia range. Each sample was tested with AnemoCheck-LRS and WHO HCS independently by three readers and compared to Hb measured by an electronic POC test (HemoCue 201+) and commercial hematology analyzer.

RESULTS

For 570 evaluations within the limits of detection of AnemoCheck-LRS (Hb ≤ 8 g/dL), the average difference between AnemoCheck-LRS and measured Hb was 0.5 ± 0.4 g/dL. In contrast, the WHO HCS overestimated Hb with an absolute difference of 4.9 ± 1.3 g/dL for samples within its detection range (Hb 4-14 g/dL, n = 405). AnemoCheck-LRS was much more sensitive (92%) for the diagnosis of profound anemia than WHO HCS (22%).

CONCLUSIONS

AnemoCheck-LRS is a rapid, inexpensive, and accurate POC test for anemia. AnemoCheck-LRS is more accurate than WHO HCS for detection of low Hb levels, severe anemia that may require blood transfusion. AnemoCheck-LRS should be tested prospectively in limited-resource settings where severe anemia is common, to determine its utility as a screening tool to identify patients who may require transfusion.

Guidance for gynecologists utilizing telemedicine during COVID‐19 pandemic based on expert consensus and rapid literature reviews

Background

COVID‐19 has impacted delivery of outpatient gynecology and shifted care toward use of telemedicine.

Objective

To rapidly review literature and society guidelines and create expert consensus to provide guidance regarding management of outpatient gynecology scenarios via telemedicine.

Search strategy

Searches were conducted in Medline and Cochrane databases from inception through April 15, 2020.

Selection criteria

Literature searches were conducted for articles on telemedicine and abnormal uterine bleeding, chronic pelvic pain, endometriosis, vaginitis, and postoperative care. Searches were restricted to available English language publications.

Data collection and analysis

Expedited literature review methodology was followed and 10 943 citations were single‐screened. Full‐text articles and relevant guidelines were reviewed and narrative summaries developed.

Main results

Fifty‐one studies on the use of telemedicine in gynecology were found. Findings were reported for these studies and combined with society guidelines and expert consensus on four topics (abnormal uterine bleeding, chronic pelvic pain and endometriosis, vaginal discharge, and postoperative care).

Conclusions

Guidance for treating gynecological conditions via telemedicine based on expedited literature review, review of society recommendations, and expert consensus is presented. Due to minimal evidence surrounding telemedicine and gynecology, a final consensus document is presented here that can be efficiently used in a clinical setting.

Guidance for gynecologists using telemedicine during COVID‐19 based on rapid literature review, review of society recommendations, and expert consensus in accessible format.

A Portable Smartphone-linked Device for Direct, Rapid and Chemical-Free Hemoglobin Assay

We describe the development and clinical evaluation of an automated smartphone-linked sensor capable of chemical-free, quantitative measurement of hemoglobin concentration ([Hb]) in whole blood samples. We have demonstrated that our sensor could analyze an unprocessed blood specimen with a mean processing time of <8 s and provided the [Hb] results with ~99% accuracy against a reference hematology analyzer with coefficient of variation (CV) of 1.21% measured at [Hb] = 11.2 g/dL. Its diagnostic capability for anemia was evaluated by measuring [Hb] of 142 clinical blood specimens and comparing the results with those from an automated hematology analyzer (ADVIA 2120i, Siemens AG, Germany) and a portable hemoglobinomteter (Hb201+, Hemocue, Sweden). The sensor yielded comparable sensitivities and specificities of 87.50% and 100.00% for males, and 94.44% and 100.00% for females, respectively, for anemic detection. The results suggested that our optical sensor based on the intrinsic photothermal response of Hb molecules and advances in consumer electronics, particularly smartphone capabilities, enables a direct, chemical-free [Hb] assay accessible to people in both developed and developing countries.

Label-Free Analysis of Multivalent Protein Binding Using Bioresponsive Nanogels and Surface Plasmon Resonance (SPR)

Precise identification of protein-protein interactions is required to improve our understanding of biochemical pathways for biology and medicine. In physiology, how proteins interact with other proteins or small molecules is crucial for maintaining biological functions. For instance, multivalent protein binding (MPB), in which a ligand concurrently interacts with two or more receptors, plays a key role in regulating complex but accurate biological functions, and its interference is related to many diseases. Therefore, determining MPB and its kinetics has long been sought, which currently requires complicated procedures and instruments to distinguish multivalent binding from monovalent binding. Here, we show a method for quickly evaluating the MPB over monovalent binding and its kinetic parameters in a label-free manner. Engaging pNIPAm-co-AAc nanogels with MPB-capable moieties (e.g., PD-1 antigen and biocytin) permits a surface plasmon resonance (SPR) instrument to evaluate the MPB events by amplifying signals from the specific target molecules. Using our MPB-based method, PD-1 antibody that forms a type of MPB by complexing with two PD-1 proteins, which are currently used for cancer immunotherapy, is detectable down to a level of 10 nM. In addition, small multivalent cations (e.g., Ca²⁺, Fe²⁺, and Fe³⁺) are distinguishably measurable over monovalent cations (e.g., Na⁺ and K⁺) with the pNIPAm-co-AAc nanogels.

Methods and analyzers for hemoglobin measurement in clinical laboratories and field settings

This paper describes and compares methods and analyzers used to measure hemoglobin (Hb) in clinical laboratories and field settings. We conducted a literature review for methods used to measure Hb in clinical laboratories and field settings. We described methods to measure Hb and factors influencing results. Automated hematology analyzer (AHA) was reference for all Hb comparisons using evaluation criteria of ±7% set by College of American Pathologists (CAP) and Clinical Laboratory Improvement Amendments (CLIA). Capillary fingerprick blood usually produces higher Hb concentrations compared with venous blood. Individual drops produced lower concentrations than pooled capillary blood. Compared with the AHA: (1) overall cyanmethemoglobin (1.0-8.0  g/L), WHO Colour Scale (0.5-10.0  g/L), paper-based devices (5.0-7.0  g/L), HemoCue® Hb-201 (1.0-16.0  g/L) and Hb-301 (0.5-6.0  g/L), and Masimo Pronto® (0.3-14.0  g/L) overestimated concentrations; (2) Masimo Radical®-7 both under- and overestimated concentrations (0.3-104.0  g/L); and (3) other methods underestimated concentrations (2.0-16.0  g/L). Most mean concentration comparisons varied less than ±7% of the reference. Hb measurements are influenced by several analytical factors. With few exceptions, mean concentration bias was within ±7%, suggesting acceptable performance. Appropriate, high-quality methods in all settings are necessary to ensure the accuracy of Hb measurements.This paper describes and compares methods and analyzers used to measure hemoglobin (Hb) in clinical laboratories and field settings. With few exceptions, mean concentration bias was within ±7%, suggesting acceptable performance. Appropriate, high-quality methods in all settings are necessary to ensure the accuracy of Hb measurements.

Smartphone app for non-invasive detection of anemia using only patient-sourced photos

We introduce a paradigm of completely non-invasive, on-demand diagnostics that may replace common blood-based laboratory tests using only a smartphone app and photos. We initially targeted anemia, a blood condition characterized by low blood hemoglobin levels that afflicts >2 billion people. Our app estimates hemoglobin levels by analyzing color and metadata of fingernail bed smartphone photos and detects anemia (hemoglobin levels <12.5 g dL⁻¹) with an accuracy of ±2.4 g dL⁻¹ and a sensitivity of 97% (95% CI, 89–100%) when compared with CBC hemoglobin levels (n = 100 subjects), indicating its viability to serve as a non-invasive anemia screening tool. Moreover, with personalized calibration, this system achieves an accuracy of ±0.92 g dL⁻¹ of CBC hemoglobin levels (n = 16), empowering chronic anemia patients to serially monitor their hemoglobin levels instantaneously and remotely. Our on-demand system enables anyone with a smartphone to download an app and immediately detect anemia anywhere and anytime.

Anemia has a global prevalence of over 2 billion people and is diagnosed via blood-based laboratory test. Here the authors describe a smartphone app that can estimate hemoglobin levels and detect anemia by analyzing pictures of fingernail beds taken with a smartphone and without the need of any external equipment.

Mucous Membrane Color Assessment Variability of Veterinary Students Using Either Colorimetric or Word-Based Scales

A colorimetric scale has the potential to be very useful as a training tool for students in veterinary training programs. The authors of this report hypothesized that clinically active, graduate level veterinary students would assess mucous membrane color with greater consistency using an image-based system than with traditional word-based techniques. Third- and fourth-year veterinary students were asked to evaluate 10 canine gingival mucosa images and rate them with either an image-based scale designed by the authors or a word-based system. Although the mean absolute deviations from the median values were greater for the word scale (0.22) than for the image scale (0.20) indicating increased variation, mixed model analysis did not demonstrate these differences were significant ( p = .120). Based on this data it is possible that prior image and word-based instruction made it easier for the students to differentiate mucous membrane colors, or that the majority of the students were multimodal learners rather than single-type learners, making previous instruction techniques effective regardless of whether they were visual or read/write based. The authors recommend that future investigators both evaluate previous student instruction and consider administering visual, auditory, read/write, kinesthetic (VARK) tests when investigating potential learning aids in veterinary medicine.

Mobile diagnostics: next-generation technologies forin vitrodiagnostics

The emergence of a wide range of applications of smartphones along with advances in ‘liquid biopsy’ has significantly propelled medical research particularly in the field ofin vitrodiagnostics (IVD).

Simultaneous point-of-care detection of anemia and sickle cell disease in Tanzania: the RAPID study

Both anemia and sickle cell disease (SCD) are highly prevalent across sub-Saharan Africa, and limited resources exist to diagnose these conditions quickly and accurately. The development of simple, inexpensive, and accurate point-of-care (POC) assays represents an important advance for global hematology, one that could facilitate timely and life-saving medical interventions. In this prospective study, Robust Assays for Point-of-care Identification of Disease (RAPID), we simultaneously evaluated a POC immunoassay (Sickle SCAN™) to diagnose SCD and a first-generation POC color-based assay to detect anemia. Performed at Bugando Medical Center in Mwanza, Tanzania, RAPID tested 752 participants (age 1 day to 20 years) in four busy clinical locations. With minimally trained medical staff, the SCD POC assay diagnosed SCD with 98.1% sensitivity and 91.1% specificity. The hemoglobin POC assay had 83.2% sensitivity and 74.5% specificity for detection of severe anemia (Hb ≤ 7 g/dL). Interobserver agreement was excellent for both POC assays (r = 0.95-0.96). Results for the hemoglobin POC assay have informed the second-generation assay design to be more suitable for low-resource settings. RAPID provides practical feasibility data regarding two novel POC assays for the diagnosis of anemia and SCD in real-world field evaluations and documents the utility and potential impact of these POC assays for sub-Saharan Africa.

Point-of-care diagnostics to improve maternal and neonatal health in low-resource settings

Each day, approximately 830 women and 7400 newborns die from complications during pregnancy and childbirth. Improving maternal and neonatal health will require bringing rapid diagnosis and treatment to the point of care in low-resource settings. However, to date there are few diagnostic tools available that can be used at the point of care to detect the leading causes of maternal and neonatal mortality in low-resource settings. Here we review both commercially available diagnostics and technologies that are currently in development to detect the leading causes of maternal and neonatal mortality, highlighting key gaps in development where innovative design could increase access to technology and enable rapid diagnosis at the bedside.

3D printed microfluidic mixer for point-of-care diagnosis of anemia

3D printing has been an emerging fabrication tool in prototyping and manufacturing. We demonstrated a 3D microfluidic simulation guided computer design and 3D printer prototyping for quick turnaround development of microfluidic 3D mixers, which allows fast self-mixing of reagents with blood through capillary force. Combined with smartphone, the point-of-care diagnosis of anemia from finger-prick blood has been successfully implemented and showed consistent results with clinical measurements. Capable of 3D fabrication flexibility and smartphone compatibility, this work presents a novel diagnostic strategy for advancing personalized medicine and mobile healthcare.

Development and validation of a noncontact spectroscopic device for hemoglobin estimation at point-of-care

Anemia severely and adversely affects human health and socioeconomic development. Measuring hemoglobin with the minimal involvement of human and financial resources has always been challenging. We describe a translational spectroscopic technique for noncontact hemoglobin measurement at low-resource point-of-care settings in human subjects, independent of their skin color, age, and sex, by measuring the optical spectrum of the blood flowing in the vascular bed of the bulbar conjunctiva. We developed software on the LabVIEW platform for automatic data acquisition and interpretation by nonexperts. The device is calibrated by comparing the differential absorbance of light of wavelength 576 and 600 nm with the clinical hemoglobin level of the subject. Our proposed method is consistent with the results obtained using the current gold standard, the automated hematology analyzer. The proposed noncontact optical device for hemoglobin estimation is highly efficient, inexpensive, feasible, and extremely useful in low-resource point-of-care settings. The device output correlates with the different degrees of anemia with absolute and trending accuracy similar to those of widely used invasive methods. Moreover, the device can instantaneously transmit the generated report to a medical expert through e-mail, text messaging, or mobile apps.

Smartphone-Based Rapid Screening of Urinary Biomarkers

An ambulatory pre-screening Point-of-Care (POC) device compatible with commercially available diapers has been developed to rapidly screen urine samples for incontinent or functionally impaired elderly. This POC device consists of a set of colorimetric reaction pads with accompanying reference colors. A smartphone with camera is a convenient tool for analysis of colorimetric assays; and a software application has been developed for smartphones to photograph the colorimetric assay and classify colorimetric reactions according to the reference colors. To facilitate detection of multiple biomarkers, e.g., 12 biomarkers with 2-7 references per biomarker, automatic localization of test/reference pads has been implemented through recognition of corner alignment marks and projective coordinate transformation for perspective removal. Each test run trains a set of classifiers from extracted reference data, which is used to classify the extracted test data. The smartphone application gives semi-quantitative results and functions independently of illumination intensity, illumination color, device type (smartphone brand/model), device settings (ISO, shutter speed, aperture) and automatic camera preprocessing. The smartphone application has been tested successfully on Samsung Galaxy S3, S6 Edge, S7 Edge, ZTE Nubia V7 mini and Iphone 6 in various illumination conditions.

Utilization Management in a Large Community Hospital

The utilization management of laboratory tests in a large community hospital is similar to academic and smaller community hospitals. There are numerous factors that influence laboratory utilization. Outside influences like hospitals buying physician practices, increasing numbers of hospitalists, and hospital consolidation will influence the number and complexity of the test menu that will need to be monitored for over and/or under utilization in the central laboratory and reference laboratory. CLIA’88 outlines the four test categories including point-of-care testing (waived) and provider-performed microscopy that need laboratory test utilization management. Incremental cost analysis is the most efficient method for evaluating utilization reduction cost savings. Economies of scale define reduced unit cost per test as test volume increases. Outreach programs in large community hospitals provide additional laboratory tests from non-patients in physician offices, nursing homes, and other hospitals. Disruptive innovations are changing the present paradigms in clinical diagnostics, like wearable sensors, MALDI-TOF, multiplex infectious disease panels, cell-free DNA, and others. Obsolete tests need to be universally defined and accepted by manufacturers, physicians, laboratories, and hospitals, to eliminate access to their reagents and testing platforms.

Encapsulating chromogenic reaction substrates with porous hydrogel scaffolds onto arrayed capillary tubes toward a visual and high-throughput colorimetric strategy for rapid occult blood tests

A porous hydrogel composite was used to encapsulate the chromogenic reaction substrates onto capillary tubes arrayed for visual and high-throughput occult blood test.

DNA biosensor combining single-wavelength colorimetry and a digital lock-in amplifier within a smartphone

Smartphone camera based gold nanoparticle colorimetry (SCB-AuNP colorimetry) has shown good potential for point-of-care applications. However, due to the use of a camera as a photo-detector, there are major limitations to this technique such as a low bit resolution (∼8 bits mainstream) and a low data acquisition rate. These issues have limited the ultimate sensitivity of smartphone based colorimetry as well as the possibility to integrate efficiently a more sensitive approach such as detection based on a lock-in amplifier (LIA). In this paper, we improve the metrological performance of the smartphone to overcome existing issues by adding the LIA capability to AuNP sensing. In this work, instead of using the camera as a photo-detector, the audio jack is used as a photo-detector reader and function generator for driving a laser diode in order to achieve a smartphone based digital lock-in amplifier AuNP colorimetric (SBLIA-AuNP colorimetry) system. A full investigation on the SBLIA design, parameters and performance is comprehensively provided. It is found that the SBLIA can reduce most of the noise and provides a detection noise-to-signal ratio down to -63 dB, which is much better than the -49 dB of the state-of-the-art SCB based method. A DNA detection experiment is demonstrated to reveal the efficacy of the proposed metrological method. The results are compared to UV-visible spectrometry, which is the gold standard for colorimetric measurement. Based on our results, the SBLIA-AuNP colorimetric system has a detection limit of 0.77 nM on short strand DNA detection, which is 5.7 times better than the 4.36 nM limit of a commercial UV-visible spectrometer. Judging from the results, we believe that the sensitive SBLIA would be further extended to other optical diagnostic tools in the near future.

Diagnosis of iron deficiency anemia using density-based fractionation of red blood cells

Iron deficiency anemia (IDA) is a nutritional disorder that impacts over one billion people worldwide; it may cause permanent cognitive impairment in children, fatigue in adults, and suboptimal outcomes in pregnancy. IDA can be diagnosed by detection of red blood cells (RBCs) that are characteristically small (microcytic) and deficient in hemoglobin (hypochromic), typically by examining the results of a complete blood count performed by a hematology analyzer. These instruments are expensive, not portable, and require trained personnel; they are, therefore, unavailable in many low-resource settings. This paper describes a low-cost and rapid method to diagnose IDA using aqueous multiphase systems (AMPS)-thermodynamically stable mixtures of biocompatible polymers and salt that spontaneously form discrete layers having sharp steps in density. AMPS are preloaded into a microhematocrit tube and used with a drop of blood from a fingerstick. After only two minutes in a low-cost centrifuge, the tests (n = 152) were read by eye with a sensitivity of 84% (72-93%) and a specificity of 78% (68-86%), corresponding to an area under the curve (AUC) of 0.89. The AMPS test outperforms diagnosis by hemoglobin alone (AUC = 0.73) and is comparable to methods used in clinics like reticulocyte hemoglobin concentration (AUC = 0.91). Standard machine learning tools were used to analyze images of the resulting tests captured by a standard desktop scanner to 1) slightly improve diagnosis of IDA-sensitivity of 90% (83-96%) and a specificity of 77% (64-87%), and 2) predict several important red blood cell parameters, such as mean corpuscular hemoglobin concentration. These results suggest that the use of AMPS combined with machine learning provides an approach to developing point-of-care hematology.

3D printed auto-mixing chip enables rapid smartphone diagnosis of anemia

Clinical diagnosis requiring central facilities and site visits can be burdensome for patients in resource-limited or rural areas. Therefore, development of a low-cost test that utilizes smartphone data collection and transmission would beneficially enable disease self-management and point-of-care (POC) diagnosis. In this paper, we introduce a low-cost iPOC^3D diagnostic strategy which integrates 3D design and printing of microfluidic POC device with smartphone-based disease diagnosis in one process as a stand-alone system, offering strong adaptability for establishing diagnostic capacity in resource-limited areas and low-income countries. We employ smartphone output (AutoCAD 360 app) and readout (color-scale analytical app written in-house) functionalities for rapid 3D printing of microfluidic auto-mixers and colorimetric detection of blood hemoglobin levels. The auto-mixing of reagents with blood via capillary force has been demonstrated in 1 second without the requirement of external pumps. We employed this iPOC^3D system for point-of-care diagnosis of anemia using a training set of patients (n_anemia = 16 and n_healthy = 6), which showed consistent measurements of blood hemoglobin levels (a.u.c. = 0.97) and comparable diagnostic sensitivity and specificity, compared with standard clinical hematology analyzer. Capable of 3D fabrication flexibility and smartphone compatibility, this work presents a novel diagnostic strategy for advancing personalized medicine and mobile healthcare.

Illumination and device independence for colorimetric detection of urinary biomarkers with smartphone

Diaper wearing elderly with functional impairments and/or incontinence is at high risk of contracting urinary tract infections. Nurses struggle with collection of urine samples for analysis. Therefore, a smartphone application is under development as a rapid screening device to work in conjunction with a colorimetric diaper assay that collects and tests urine within a diaper. The focus of this work is to make a practical and useful tool that medical personnel (the user) can use for rapid screening on patients in the field, only with a smartphone and assay available. The main challenge is to achieve illumination and device independency for a wide range of colorimetric biomarkers without using any standardization, such as attachments, special lamps, or boxes. We achieved illumination and device independent semi-quantitative detection by using discriminant analysis and classification of simultaneously photographed colorimetric test results and reference colors to ensure that any variation in image conditions applies approximately equal for reference and test. This requires retraining of classifiers on each analysis, but appears to be the most viable solution to solving the challenges while maintaining the user-friendliness.

Reading Out Single-Molecule Digital RNA and DNA Isothermal Amplification in Nanoliter Volumes with Unmodified Camera Phones

Digital single-molecule technologies are expanding diagnostic capabilities, enabling the ultrasensitive quantification of targets, such as viral load in HIV and hepatitis C infections, by directly counting single molecules. Replacing fluorescent readout with a robust visual readout that can be captured by any unmodified cell phone camera will facilitate the global distribution of diagnostic tests, including in limited-resource settings where the need is greatest. This paper describes a methodology for developing a visual readout system for digital single-molecule amplification of RNA and DNA by (i) selecting colorimetric amplification-indicator dyes that are compatible with the spectral sensitivity of standard mobile phones, and (ii) identifying an optimal ratiometric image-process for a selected dye to achieve a readout that is robust to lighting conditions and camera hardware and provides unambiguous quantitative results, even for colorblind users. We also include an analysis of the limitations of this methodology, and provide a microfluidic approach that can be applied to expand dynamic range and improve reaction performance, allowing ultrasensitive, quantitative measurements at volumes as low as 5 nL. We validate this methodology using SlipChip-based digital single-molecule isothermal amplification with λDNA as a model and hepatitis C viral RNA as a clinically relevant target. The innovative combination of isothermal amplification chemistry in the presence of a judiciously chosen indicator dye and ratiometric image processing with SlipChip technology allowed the sequence-specific visual readout of single nucleic acid molecules in nanoliter volumes with an unmodified cell phone camera. When paired with devices that integrate sample preparation and nucleic acid amplification, this hardware-agnostic approach will increase the affordability and the distribution of quantitative diagnostic and environmental tests.

An accurate and inexpensive color-based assay for detecting severe anemia in a limited-resource setting

Severe anemia is an important cause of morbidity and mortality among children in resource-poor settings, but laboratory diagnostics are often limited in these locations. To address this need, we developed a simple, inexpensive, and color-based point-of-care (POC) assay to detect severe anemia. The purpose of this study was to evaluate the accuracy of this novel POC assay to detect moderate and severe anemia in a limited-resource setting. The study was a cross-sectional study conducted on children with sickle cell anemia in Luanda, Angola. The hemoglobin concentrations obtained by the POC assay were compared to reference values measured by a calibrated automated hematology analyzer. A total of 86 samples were analyzed (mean hemoglobin concentration 6.6 g/dL). There was a strong correlation between the hemoglobin concentrations obtained by the POC assay and reference values obtained from an automated hematology analyzer (r=0.88, P<0.0001). The POC assay demonstrated excellent reproducibility (r=0.93, P<0.0001) and the reagents appeared to be durable in a tropical setting (r=0.93, P<0.0001). For the detection of severe anemia that may require blood transfusion (hemoglobin <5 g/dL), the POC assay had sensitivity of 88.9% and specificity of 98.7%. These data demonstrate that an inexpensive (<$0.25 USD) POC assay accurately estimates low hemoglobin concentrations and has the potential to become a transformational diagnostic tool for severe anemia in limited-resource settings.

An instantaneous low-cost point-of-care anemia detection device

We present a small, compact and portable device for point-of-care instantaneous early detection of anemia. The method used is based on direct hematocrit measurement from whole blood samples by means of impedance analysis. This device consists of a custom electronic instrumentation and a plug-and-play disposable sensor. The designed electronics rely on straightforward standards for low power consumption, resulting in a robust and low consumption device making it completely mobile with a long battery life. Another approach could be powering the system based on other solutions like indoor solar cells, or applying energy-harvesting solutions in order to remove the batteries. The sensing system is based on a disposable low-cost label-free three gold electrode commercial sensor for 50 μL blood samples. The device capability for anemia detection has been validated through 24 blood samples, obtained from four hospitalized patients at Hospital Clínic. As a result, the response, effectiveness and robustness of the portable point-of-care device to detect anemia has been proved with an accuracy error of 2.83% and a mean coefficient of variation of 2.57% without any particular case above 5%.