Investigating interactive methods in remote chestfeeding support for lactation consulting professionals in Brazil.

Objective: Lactation consultants (LCs) positively impact chestfeeding rates by providing in-person support to struggling parents. In Brazil, LCs are a scarce resource and in high demand, risking chestfeeding rates across many communities nationwide. The transition to remote consultations during the COVID-19 pandemic made LCs face several challenges to solve chestfeeding problems due to limited technical resources for management, communication, and diagnosis. This study investigates the main technological issues LCs have in remote consultations and what technology features are helpful for chestfeeding problem-solving in remote settings. Methods: This paper implements qualitative investigation through a contextual study ( n = 10 ) and a participatory session ( n = 5 ) to determine stakeholders' preferences for technology features in solving chestfeeding problems. Findings: The contextual study with LCs in Brazil characterized (1) the current appropriation of technologies that help during consultations, (2) technology limitations that affect LCs' decision-making, (3) challenges and benefits of remote consultations, and (4) cases that are easy and difficult to solve remotely. The participatory session brings LCs' perceptions on (1) components for an effective remote evaluation, (2) preferred elements by professionals when providing remote feedback to parents, and (3) feelings about using technology resources for remote consultations. Conclusion: Findings suggest that LCs adapted their methodologies for remote consultations, and the perceived benefits of this modality show interest in continuing to provide remote care as long as more integrative and nurturing applications are offered to their clients. We learned that fully remote lactation care might not be the main objective for overall populations in Brazil, but as a hybrid mode of care that benefits parents by having both modalities of consultations available to them. Finally, remote support helps reduce financial, geographic, and cultural barriers in lactation care. However, future research must identify how generalized solutions for remote lactation care can be, especially for different cultures and regions.

Smartphone camera oximetry in an induced hypoxemia study.

Hypoxemia, a medical condition that occurs when the blood is not carrying enough oxygen to adequately supply the tissues, is a leading indicator for dangerous complications of respiratory diseases like asthma, COPD, and COVID-19. While purpose-built pulse oximeters can provide accurate blood-oxygen saturation (SpO2) readings that allow for diagnosis of hypoxemia, enabling this capability in unmodified smartphone cameras via a software update could give more people access to important information about their health. Towards this goal, we performed the first clinical development validation on a smartphone camera-based SpO2 sensing system using a varied fraction of inspired oxygen (FiO2) protocol, creating a clinically relevant validation dataset for solely smartphone-based contact PPG methods on a wider range of SpO2 values (70-100%) than prior studies (85-100%). We built a deep learning model using this data to demonstrate an overall MAE = 5.00% SpO2 while identifying positive cases of low SpO2 < 90% with 81% sensitivity and 79% specificity. We also provide the data in open-source format, so that others may build on this work.

High Sensitivity, Rapid Detection of Virus in High Traffic Environments.

The global pandemic caused by the SARS-CoV-2 virus has underscored the need for rapid, simple, scalable, and high-throughput multiplex diagnostics in non-laboratory settings. Here we demonstrate a multiplex reverse-transcription loop-mediated isothermal amplification (RT-LAMP) coupled with a gold nanoparticle-based lateral flow immunoassay (LFIA) capable of detecting up to three unique viral gene targets in 15 min. RT-LAMP primers associated with three separate gene targets from the SARS-CoV-2 virus (Orf1ab, Envelope, and Nucleocapsid) were added to a one-pot mix. A colorimetric change from red to yellow occurs in the presence of a positive sample. Positive samples are run through a LFIA to achieve specificity on a multiplex three-test line paper assay. Positive results are indicated by a characteristic crimson line. The device is almost fully automated and is deployable in any community setting with a power source.

Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study.

Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease. We selected 73 of these 704 participants with reliable confirmation of COVID-19 by PCR testing and high-quality physiological data for algorithm training to identify onset of COVID-19 using machine learning classification. The algorithm identified COVID-19 an average of 2.75 days before participants sought diagnostic testing with a sensitivity of 82% and specificity of 63%. The receiving operating characteristic (ROC) area under the curve (AUC) was 0.819 (95% CI [0.809, 0.830]). Including continuous temperature yielded an AUC 4.9% higher than without this feature. For further validation, we obtained SARS CoV-2 antibody in a subset of participants and identified 10 additional participants who self-reported COVID-19 disease with antibody confirmation. The algorithm had an overall ROC AUC of 0.819 (95% CI [0.809, 0.830]), with a sensitivity of 90% and specificity of 80% in these additional participants. Finally, we observed substantial variation in accuracy based on age and biological sex. Findings highlight the importance of including temperature assessment, using continuous physiological features for alignment, and including diverse populations in algorithm development to optimize accuracy in COVID-19 detection from wearables.

Using airflow-driven, evaporative gradients to improve sensitivity and fluid control in colorimetric paper-based assays.

Microfluidic paper-based analytical devices (µPADs) are foundational devices for point-of-care testing, yet suffer from limitations in regards to their sensitivity and capability in handling complex assays. Here, we demonstrate an airflow-based, evaporative method that is capable of manipulating fluid flows within paper membranes to offer new functionalities for multistep delivery of reagents and improve the sensitivity of µPADs by 100-1000 times. This method applies an air-jet to a pre-wetted membrane, generating an evaporative gradient such that any solutes become enriched underneath the air-jet spot. By controlling the lateral position of this spot, the solutes in the paper strip are enriched and follow the air jet trajectory, driving the reactions and enhancing visualization for colorimetric readout in multistep assays. The technique has been successfully applied to drive the sequential delivery in multistep immunoassays as well as improve sensitivity for colorimetric detection assays for nucleic acids and proteins via loop-mediated isothermal amplification (LAMP) and ELISA. For colorimetric LAMP detection of the COVID-19 genome, enrichment of the solution on paper could enhance the contrast of the dye in order to more clearly distinguish between the positive and negative results to achieve a sensitivity of 3 copies of SARS-Cov-2 RNAs. For ELISA, enrichment of the oxidized TMB substrate yielded a sensitivity increase of two-to-three orders of magnitude when compared to non-enriched samples - having a limit of detection of around 200 fM for IgG. Therefore, this enrichment method represents a simple process that can be easily integrated into existing detection assays for controlling fluid flows and improving detection of biomarkers on paper.