New medical big data for P4 medicine on allergic conjunctivitis

Effect of antihistamine-releasing contact lenses on ocular symptoms and treatment behavior in patients with seasonal allergic conjunctivitis: A retrospective study

Purpose

This study aimed to compare subjective allergic conjunctivitis symptoms and anti-allergic eye drop use patterns between antihistamine-releasing contact lens users and daily disposable soft contact lens users during Japan's hay fever season.

Methods

This web-based retrospective cohort study included daily disposable soft contact lens or antihistamine-releasing contact lens users with a history of seasonal allergic conjunctivitis who regularly used daily disposable soft contact lenses since the previous year. The total ocular symptom score (range 0-20) based on 5-item questionnaire scores and time from the start of the hay fever season to the initiation of anti-allergic eye drop treatment were compared between antihistamine-releasing contact lens users and daily disposable soft contact lens users.

Results

The study included 24 participants: 17 using daily disposable soft contact lenses and 7 using antihistamine-releasing contact lenses. Antihistamine-releasing contact lens users experienced a greater reduction in total ocular symptom score from 2021 to 2022 compared with daily disposable soft contact lens users (mean total ocular symptom score [standard deviation]: daily disposable soft contact lens: -0.65 [1.4], antihistamine-releasing contact lens: -4.7 [3.6]; n = 24; Mann-Whitney U test, P = 0.010). Fourteen daily disposable soft contact lens users and five antihistamine-releasing contact lens users eventually required anti-allergic eye drops. Kaplan-Meier analysis revealed a significant delay in the initiation of anti-allergic eye drop treatment among those using antihistamine-releasing contact lenses compared with those using daily disposable soft contact lenses (median days, daily disposable soft contact lenses: 19 days, antihistamine-releasing contact lens: 57 days; n = 24; log-rank test, P = 0.045).

Conclusions

Antihistamine-releasing contact lenses can potentially mitigate worsening ocular allergic responses during the hay fever season when used appropriately as a preventive measure.

JACQLQ subjective symptom questionnaire score and clinical test results for patients with allergic conjunctival disease

We investigated the relationship between subjective symptoms and objective findings in patients with allergic conjunctival diseases (ACD) and test results for tear total IgE (t-tIgE), conjunctival eosinophils (c-Eo), serum total IgE (s-tIgE), serum-antigen specific IgE (s-sIgE), and serum eosinophils (s-Eo). Subjective symptoms and objective findings of patients with ACD were evaluated using Japanese Allergic Conjunctival Disease Quality of Life Questionnaire (JACQLQ), which described disability score and emotional score written by patient and clinical findings score written by ophthalmologist. We investigated the relationship between questionnaire scores and laboratory data for t-tIgE, c-Eo, s-tIgE, s-sIgE, and s-Eo. Scores of impediments to life and of moods were highest in vernal keratoconjunctivitis among ACD. Cases with positive pollen-sIgE showed significantly more nasal symptom score than those with negative pollen-sIgE (P < 0.05). Cases with positive t-tIgE or c-Eo showed significantly more objective symptoms' JACQLQ score than those with negative t-tIgE or c-Eo (P < 0.05), respectively. Cases positive for house dust/mite-sIgE, showed significantly more objective symptoms' JACQLQ score than those without for house dust/mite-sIgE (P < 0.05). These results indicate that ACD could be analyzed more accurately by the combination of JACQLQ and laboratory data.

Symptom-based stratification algorithm for heterogeneous symptoms of dry eye disease: a feasibility study

BACKGROUND/OBJECTIVE

To test the feasibility of a dry eye disease (DED) symptom stratification algorithm previously established for the general population among patients visiting ophthalmologists.

SUBJECT/METHODS

This retrospective cross-sectional study was conducted between December 2015 and October 2021 at a university hospital in Japan; participants who underwent a comprehensive DED examination and completed the Japanese version of the Ocular Surface Disease Index (J-OSDI) were included. Patients diagnosed with DED were stratified into seven clusters using a previously established symptom-based stratification algorithm for DED. Characteristics of the patients in stratified clusters were compared.

RESULTS

In total, 426 participants were included (median age [interquartile range]; 63 [48-72] years; 357 (83.8%) women). Among them, 291 (68.3%) participants were diagnosed with DED and successfully stratified into seven clusters. The J-OSDI total score was highest in cluster 1 (61.4 [52.2-75.0]), followed by cluster 5 (44.1 [38.8-47.9]). The tear film breakup time was the shortest in cluster 1 (1.5 [1.1-2.1]), followed by cluster 3 (1.6 [1.0-2.5]). The J-OSDI total scores from the stratified clusters in this study and those from the clusters identified in the previous study showed a significant correlation (r = 0.991, P < 0.001).

CONCLUSIONS

The patients with DED who visited ophthalmologists were successfully stratified by the previously established algorithm for the general population, uncovering patterns for their seemingly heterogeneous and variable clinical characteristics of DED. The results have important implications for promoting treatment interventions tailored to individual patients and implementing smartphone-based clinical data collection in the future.

Using the AllerSearch Smartphone App to Assess the Association Between Dry Eye and Hay Fever: mHealth-Based Cross-Sectional Study

BACKGROUND

Dry eye (DE) and hay fever (HF) show synergistic exacerbation of each other's pathology through inflammatory pathways.

OBJECTIVE

This study aimed to investigate the association between DE and HF comorbidity and the related risk factors.

METHODS

A cross-sectional observational study was conducted using crowdsourced multidimensional data from individuals who downloaded the AllerSearch smartphone app in Japan between February 2018 and May 2020. AllerSearch collected the demographics, medical history, lifestyle and residential information, HF status, DE symptoms, and HF-related quality of life. HF symptoms were evaluated using the nasal symptom score (0-15 points) and nonnasal symptom score (0-12 points). HF was defined by the participants' responses to the questionnaire as HF, non-HF, or unknown. Symptomatic DE was defined as an Ocular Surface Disease Index total score (0-100 points), with a threshold score of 13 points. HF-related quality of life was assessed using the Japanese Allergic Conjunctival Disease Standard Quality of Life Questionnaire (0-68 points). We conducted a multivariable linear regression analysis to examine the association between the severity of DE and HF symptoms. We subsequently conducted a multivariable logistic regression analysis to identify the factors associated with symptomatic DE (vs nonsymptomatic DE) among individuals with HF. Dimension reduction via Uniform Manifold Approximation and Projection stratified the comorbid DE and HF symptoms. The symptom profiles in each cluster were identified using hierarchical heat maps.

RESULTS

This study included 11,284 participants, classified into experiencing HF (9041 participants), non-HF (720 participants), and unknown (1523 participants) groups. The prevalence of symptomatic DE among individuals with HF was 49.99% (4429/9041). Severe DE symptoms were significantly associated with severe HF symptoms: coefficient 1.33 (95% CI 1.10-1.57; P<.001) for mild DE, coefficient 2.16 (95% CI 1.84-2.48; P<.001) for moderate DE, and coefficient 3.80 (95% CI 3.50-4.11; P<.001) for severe DE. The risk factors for comorbid symptomatic DE among individuals with HF were identified as female sex; lower BMI; medicated hypertension; history of hematologic, collagen, heart, liver, respiratory, or atopic disease; tomato allergy; current and previous mental illness; pet ownership; living room and bedrooms furnished with materials other than hardwood, carpet, tatami, and vinyl; discontinuation of contact lens use during the HF season; current contact lens use; smoking habits; and sleep duration of <6 hours per day. Uniform Manifold Approximation and Projection stratified the heterogeneous comorbid DE and HF symptoms into 14 clusters. In the hierarchical heat map, cluster 9 was comorbid with the most severe HF and DE symptoms, and cluster 1 showed severe HF symptoms with minimal DE-related symptoms.

CONCLUSIONS

This crowdsourced study suggested a significant association between severe DE and HF symptoms. Detecting DE among individuals with HF could allow effective prevention and interventions through concurrent treatment for ocular surface management along with HF treatment.

Perioperative Nursing Informatics Relevant Data Standard Research in the Context of Medical Big Data: Improving Patients? Health Behavior

Objectives: Our objective was to determine the progress of perioperative nursing informatics relevant data standard research in the context of medical big data. We also determine the moderating impact of big data in healthcare between standard data and perioperative nursing informatics. Methods: We used Smart PLS for structual equation modeling and reviewed some recent literature and briefly discussed the progress on perioperative nursing standardized data in five aspects. Results: Our findings demonstrate that the direct impact of standard data and big data in healthcare is positively confirmed on perioperative nursing informatics. The moderating impact of big data in healthcare between standard data and perioperative nursing informatics is also confirmed. Conclusions: Our model is novel in the literature. Big data can be used by the healthcare system to the advanced level for patient record-keeping according to their health behavior and improving the methods of treatment.

The minimal clinically important difference of app-based electronic patient-reported outcomes for hay fever

BACKGROUND

Hay fever is a common allergic disease, with an estimated worldwide prevalence of 14.4% and a variety of symptoms. This study assessed the minimal clinically important difference (MCID) of nasal symptom score (NSS), non-nasal symptom score (NNSS), and total symptoms score (TSS) for app-based hay-fever monitoring.

METHODS

MCIDs were calculated based on the data from a previous large-scale, crowdsourced, cross-sectional study using AllerSearch, an in-house smartphone application. MCIDs were determined with anchor-based and distribution-based methods. The face scale score of the Japanese Allergic Conjunctival Disease Standard Quality of Life Questionnaire Domain III and the daily stress level due to hay fever were used as anchors for determining MCIDs. The MCID estimates were summarized as MCID ranges.

RESULTS

A total of 7590 participants were included in the analysis (mean age: 35.3 years, 57.1% women). The anchor-based method produced a range of MCID values (median, interquartile range) for NSS (2.0, 1.5-2.1), NNSS (1.0, 0.9-1.2), and TSS (2.9, 2.4-3.3). The distribution-based method produced two MCIDs (based on half a standard deviation, based on a standard error of measurement) for NSS (2.0, 1.8), NNSS (1.3, 1.2), and TSS (3.0, 2.3). The final suggested MCID ranges for NSS, NNSS, and TSS were 1.8-2.1, 1.2-1.3, and 2.4-3.3, respectively.

CONCLUSIONS

MCID ranges for app-based hay-fever symptom assessment were obtained from the data collected through a smartphone application, AllerSearch. These estimates may be useful for monitoring the subjective symptoms of Japanese patients with hay fever through mobile platforms.

Diagnostic Ability of a Smartphone App for Dry Eye Disease: Protocol for a Multicenter, Open-Label, Prospective, and Cross-sectional Study

BACKGROUND

Dry eye disease (DED) is one of the most common ocular surface diseases. Numerous patients with DED remain undiagnosed and inadequately treated, experiencing various subjective symptoms and a decrease in quality of life and work productivity. A mobile health smartphone app, namely, the DEA01, has been developed as a noninvasive, noncontact, and remote screening device, in the context of an ongoing paradigm shift in the health care system, to facilitate a diagnosis of DED.

OBJECTIVE

This study aimed to evaluate the capabilities of the DEA01 smartphone app to facilitate a DED diagnosis.

METHODS

In this multicenter, open-label, prospective, and cross-sectional study, the test method will involve using the DEA01 smartphone app to collect and evaluate DED symptoms, based on the Japanese version of the Ocular Surface Disease Index (J-OSDI), and to measure the maximum blink interval (MBI). The standard method will then involve a paper-based J-OSDI evaluation of subjective symptoms of DED and tear film breakup time (TFBUT) measurement in an in-person encounter. We will allocate 220 patients to DED and non-DED groups, based on the standard method. The primary outcome will be the sensitivity and specificity of the DED diagnosis according to the test method. Secondary outcomes will be the validity and reliability of the test method. The concordance rate, positive and negative predictive values, and the likelihood ratio between the test and standard methods will be assessed. The area under the curve of the test method will be evaluated using a receiver operating characteristic curve. The internal consistency of the app-based J-OSDI and the correlation between the app-based J-OSDI and paper-based J-OSDI will be assessed. A DED diagnosis cutoff value for the app-based MBI will be determined using a receiver operating characteristic curve. The app-based MBI will be assessed to determine a correlation between a slit lamp-based MBI and TFBUT. Adverse events and DEA01 failure data will be collected. Operability and usability will be assessed using a 5-point Likert scale questionnaire.

RESULTS

Patient enrollment will start in February 2023 and end in July 2023. The findings will be analyzed in August 2023, and the results will be reported from March 2024 onward.

CONCLUSIONS

This study may have implications in identifying a noninvasive, noncontact route to facilitate a diagnosis of DED. The DEA01 may enable a comprehensive diagnostic evaluation within a telemedicine setting and facilitate early intervention for undiagnosed patients with DED confronting health care access barriers.

TRIAL REGISTRATION

Japan Registry of Clinical Trials jRCTs032220524; https://jrct.niph.go.jp/latest-detail/jRCTs032220524.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/45218.

Individual multidisciplinary clinical phenotypes of nasal and ocular symptoms in hay fever: Crowdsourced cross-sectional study using AllerSearch

BACKGROUND

Multidisciplinary efforts to prospectively collect and analyze symptoms of hay fever are limited. We aimed to identify the characteristics of nasal and ocular symptoms of hay fever, using the AllerSearch smartphone application.

METHODS

This mobile health-based prospective observational study using the AllerSearch smartphone application was conducted between February 1, 2018, and May 1, 2020. Individuals who downloaded AllerSearch from Japan and provided comprehensive self-assessments (including 17 items related to quality of life [QoL]-related items) were included. The characteristics and risk factors for allergic rhinitis (AR) and allergic conjunctivitis (AC) were identified using hierarchical heat maps and multivariate logistic regression.

RESULTS

Of the 9041 participants with hay fever, 58.8% had AR and AC, 22.2% had AR, and 5.7% had AC. The AR-AC comorbid cohort showed worse symptoms of hay fever and QoL scores than the other cohorts. Factors (odds ratio, 95% confidence interval) associated with AR-AC included a lower age (0.98, 0.97-0.98), female sex (1.31, 1.19-1.45), liver disease (1.58, 1.26-2.35), dry eye disease (1.45, 1.30-1.63), unknown dry eye disease status (1.46, 1.31-1.62), contact lens use discontinuation during the hay fever season (1.69, 1.28-2.23), and bedroom flooring material other than hardwood, carpet, tatami, or vinyl (1.91, 1.16-3.14).

CONCLUSIONS

Analysis of medical big data for hay fever performed using a mobile health app helped identify risk factors and characteristics of AC, AR, and AR-AC. Phenotyping of highly variable symptoms of hay fever, such as nasal and ocular symptoms, can facilitate better-quality clinical care.

P4 Medicine for Heterogeneity of Dry Eye: A Mobile Health-based Digital Cohort Study

During the 5th Science, Technology, and Innovation Basic Plan, the Japanese government proposed a novel societal concept -Society 5.0- that promoted a healthcare system characterized by its capability to provide unintrusive, predictive, longitudinal care through the integration of cyber and physical space. The role of Society 5.0 in managing our quality of vision will become more important in the modern digitalized and aging society, both of which are known risk factors for developing dry eye. Dry eye is the most common ocular surface disease encountered in Japan with symptoms including increased dryness, eye discomfort, and decreased visual acuity. Owing to its complexity, implementation of P4 (predictive, preventive, personalized, participatory) medicine in managing dry eye requires a comprehensive understanding of its pathology, as well as a strategy to visualize and stratify its risk factors. Using DryEyeRhythm®, a mobile health (mHealth) smartphone software (app), we established a route to collect holistic medical big data on dry eye, such as the subjective symptoms and lifestyle data for each individual. The studies to date aided in determining the risk factors for severe dry eye, the association between major depressive disorder and dry eye exacerbation, eye drop treatment adherence, app-based stratification algorithms based on symptomology, blink detection biosensoring as a dry eye-related digital phenotype, and effectiveness of app-based dry eye diagnosis support compared to traditional methods. These results contribute to elucidating disease pathophysiology and promoting preventive and effective measures to counteract dry eye through mHealth.

Surfing the COVID-19 Tsunami with Teleophthalmology: the Advent of New Models of Eye Care

Purpose of Review

In this article, we reviewed the impact resulting from the COVID-19 pandemic on the traditional model of care in ophthalmology.

Recent Findings

Though virtual eye care has been present for more than 20 years, the COVID-19 pandemic has established a precedent to seriously consider its role in the evolving paradigm of vision and eye care. New hybrid models of care have enhanced or replaced traditional synchronous and asynchronous visits. The increased use of smart phoneography and mobile applications enhanced the remote examination of patients. Use of e-learning became a mainstream tool to continue accessing education and training.

Summary

Teleophthalmology has demonstrated its value for screening, examining, diagnosing, monitoring treatment, and increasing access to education. However, much of the progress made following the COVID-19 pandemic is at risk of being lost as society pushes to reestablish normalcy. Further studies during the new norm are required to prove a more permanent role for virtual eye care.

Tissue remodeling in adult vernal keratoconjunctivitis

Our aim is to describe local tissue remodeling in a cohort of adult VKC patients. Male patients diagnosed with active VKC were enrolled in an open pilot study into two groups according disease onset: childhood classic VKC and adult VKC. Visual acuity and ocular surface clinical examination focusing on chronic inflammatory sequelae and impression cytology were performed in all enrolled subjects. Conjunctival imprints were processed for molecular, biochemical and immunofluorescent analysis for tissue remodeling (TGFβ1,2,3 and αSMA) and epigenetic (DNMT3a, Keap1; Nrf2) markers as well as androgen receptors were investigated and compared between groups. Clinical assessment showed increased conjunctival scarring in adult VKC compared to classic VKC. Immunoreactivity for αSMA and expression of TGFβ were higher in adult VKC group. Significantly higher levels of TGFβ3 (3.44 ± 1.66; p < 0.05) were detected in adult VKC compared to childhood VKC, associated with an increasing trend of TGFβ1 (1.58 ± 0.25) and TGFβ2 (1.65 ± 0.20) isoforms levels. Molecular analysis showed a relative increase in tissue remodeling/fibrogenic transcripts (TGFβ isoforms and αSMA) associated to a significant increase of selective epigenetic targets (DNMT3, Nrf2 and keap1) in adult VKC phenotype. Increased local conjunctival androgen receptors was detected in patients with adult variants compared to classic childhood VKC and healthy subjects. Finally, a direct correlation between TGFβ and androgen receptor expression was also detected. A pro-fibrotic clinical and biomolecular trait was unveiled in adult variant of VKC, which causes ocular surface disease and visual impairment.

Patient and public involvement in mobile health-based research for hay fever: a qualitative study of patient and public involvement implementation process

BACKGROUND

Smartphones are being increasingly used for research owing to their multifunctionality and flexibility, and crowdsourced research using smartphone applications (apps) is effective in the early detection and management of chronic diseases. We developed the AllerSearch app to gather real-world data on individual subjective symptoms and lifestyle factors related to hay fever. This study established a foundation for interactive research by adopting novel, diverse perspectives accrued through implementing the principles of patient and public involvement (PPI) in the development of our app.

METHODS

Patients and members of the public with a history or family history of hay fever were recruited from November 2019 to December 2021 through a dedicated website, social networking services, and web briefing according to the PPI Guidebook 2019 by the Japan Agency for Medical Research and Development. Nine opinion exchange meetings were held from February 2020 to December 2021 to collect opinions and suggestions for updating the app. After each meeting, interactive evaluations from PPI contributors and researchers were collected. The compiled suggestions were then incorporated into the app, establishing an active feedback loop fed by the consistently interactive infrastructure.

RESULTS

Four PPI contributors (one man and three women) were recruited, and 93 items were added/changed in the in-app survey questionnaire in accordance with discussions from the exchange meetings. The exchange meetings emphasized an atmosphere and opportunity for participants to speak up, ensuring frequent opportunities for them to contribute to the research. In March 2020, a public website was created to display real-time outcomes of the number of participants and users' hay-fever-preventative behaviors. In August 2020, a new PPI-implemented AllerSearch app was released.

CONCLUSIONS

This study marks the first research on clinical smartphone apps for hay fever in Japan that implements PPI throughout its timeline from research and development to the publication of research results. Taking advantage of the distinct perspectives offered by PPI contributors, a step was taken toward actualizing a foundation for an interactive research environment. These results should promote future PPI research and foster the establishment of a social construct that enables PPI efforts in various fields.

Prevalence of Comorbidity between Dry Eye and Allergic Conjunctivitis: A Systematic Review and Meta-Analysis

This systematic review aimed to determine the comorbid dry eye (DE) and allergic conjunctivitis (AC) prevalence. We searched PubMed and EMBASE for articles published until 22 March 2022, combining the terms “(dry eye OR keratoconjunctivitis sicca) AND allergic conjunctivitis.” Study-specific estimates (DE and AC incidence rates among patients with AC and DE, respectively) were combined using the one-group meta-analysis in a random-effects model. The initial search yielded 700 studies. Five articles reporting AC incidence among individuals with DE and six articles reporting DE incidence among individuals with AC were included in the qualitative synthesis. In these nine articles, the total sample size was 7254 patients. The DE incidence among individuals with AC was 0.9–97.5%; the AC incidence among individuals with DE was 6.2–38.0%. One-group meta-analysis using a random-effects model showed that 47.2% (95% confidence interval: 0.165–0.779; 320/1932 cases) of patients with AC had comorbid DE and 17.8% (95% confidence interval: 0.120–0.236; 793/4855 cases) of patients with DE had comorbid AC, as defined by each article. Complimentary screening and treatment for patients with DE and AC may improve long-term outcomes and prevent chronic ocular damage in highly susceptible populations.

Individual characteristics and associated factors of hay fever: A large-scale mHealth study using AllerSearch

BACKGROUND

The prevalence of hay fever, a multifactorial allergic disease, is increasing. Identifying individual characteristics and associated factors of hay fever is essential for predictive, preventive, personalized, and participatory (P4) medicine. This study aimed to identify individual characteristics and associated factors of hay fever using an iPhone application AllerSearch.

METHODS

This large-scale mobile health-based cross-sectional study was conducted between February 2018 and May 2020. Individuals who downloaded AllerSearch in Japan and provided a comprehensive self-assessment (general characteristics, medical history, lifestyle habits, and hay fever symptoms [score range 0-36]) were included. Associated factors of hay fever (vs. non-hay fever) and severe hay fever symptoms were identified using multivariate logistic and linear regression analyses, respectively.

RESULTS

Of the included 11,284 individuals, 9041 had hay fever. Factors associated with hay fever (odds ratio) included age (0.98), female sex (1.33), atopic dermatitis (1.40), history of dry eye diagnosis (1.36), discontinuation of contact lens use during hay fever season (3.34), frequent bowel movements (1.03), and less sleep duration (0.91). The factors associated with severe hay fever symptoms among individuals with hay fever (coefficient) included age (-0.104), female sex (1.329), history of respiratory disease (1.539), history of dry eye diagnosis (0.824), tomato allergy (1.346), discontinuation of contact lens use during hay fever season (1.479), smoking habit (0.614), and having a pet (0.303).

CONCLUSIONS

Our large-scale mobile health-based study using AllerSearch elucidated distinct hay fever presentation patterns, characteristics, and factors associated with hay fever. Our study establishes the groundwork for effective individualized interventions for P4 medicine.

Rehabilitation of Sepsis Patients with Acute Kidney Injury Based on Intelligent Medical Big Data

The objective of this study was to explore rehabilitation of patients with acute kidney injury (AKI) treated with Xuebijing injection by using intelligent medical big data analysis system. Based on Hadoop distributed processing technology, this study designed a medical big data analysis system and tested its performance. Then, this analysis system was used to systematically analyze rehabilitation of sepsis patients with AKI treated with Xuebijing injection. It is found that the computing time of this system does not increase obviously with the increase of cases. The results of systematic analysis showed that the glomerular filtration rate (59.31 ± 3.87% vs 44.53 ± 3.53%) in the experimental group was obviously superior than that in the controls after one week of treatment. The levels of urea nitrogen (9.32 ± 2.21 mmol/L vs. 14.32 ± 0.98 mmol/L), cystatin C (1.65 ± 0.22 mg/L vs. 2.02 ± 0.13 mg/L), renal function recovery time (6.12 ± 1.66 days vs. 8.66 ± 1.17 days), acute physiology and chronic health evaluation system score (8.98 ± 2.12 points vs. 12.45 ± 2.56 points), sequential organ failure score (7.22 ± 0.86 points vs. 8.61 ± 0.97 points), traditional Chinese medicine (TCM) syndrome score (6.89 ± 1.11 points vs. 11.33 ± 1.23 points), and ICU time (16.43 ± 2.37 days vs. 12.15 ± 2.56 days) in the experimental group were obviously lower than those in the controls, and the distinctions had statistical significance (P < 0.05). The significant efficiency (37.19% vs. 25.31%) and total effective rate (89.06% vs. 79.06%) in the experimental group were obviously superior than those in the controls, and distinction had statistical significance (P < 0.05). In summary, the medical big data analysis system constructed in this study has high efficiency. Xuebijing injection can improve the renal function of sepsis patients with kidney injury, and its therapeutic effect is obviously better than that of Western medicine, and it has clinical application and promotion value.

Smartphone-based digital phenotyping for dry eye toward P4 medicine: a crowdsourced cross-sectional study

Multidimensional integrative data analysis of digital phenotyping is crucial for elucidating the pathologies of multifactorial and heterogeneous diseases, such as the dry eye (DE). This crowdsourced cross-sectional study explored a novel smartphone-based digital phenotyping strategy to stratify and visualize the heterogenous DE symptoms into distinct subgroups. Multidimensional integrative data were collected from 3,593 participants between November 2016 and September 2019. Dimension reduction via Uniform Manifold Approximation and Projection stratified the collected data into seven clusters of symptomatic DE. Symptom profiles and risk factors in each cluster were identified by hierarchical heatmaps and multivariate logistic regressions. Stratified DE subgroups were visualized by chord diagrams, co-occurrence networks, and Circos plot analyses to improve interpretability. Maximum blink interval was reduced in clusters 1, 2, and 5 compared to non-symptomatic DE. Clusters 1 and 5 had severe DE symptoms. A data-driven multidimensional analysis with digital phenotyping may establish predictive, preventive, personalized, and participatory medicine.

A novel personalised treatment approach for psoriasis: anti-VEGF-A therapy

Chronic plaque psoriasis is an inflammatory skin disease in which genetic predisposition along with environmental factors lead to the development of the disease, which affects 2% of the UK’s population and is associated with extracutaneous morbidities and a reduced quality of life. A complex crosstalk between innate and adaptive immunity, the epithelia and the vasculature maintain the inflammatory milieu in psoriasis. Despite the development of promising treatment strategies, mostly targeting the immune system, treatments fail to fulfil every patient’s goals. Vascular endothelial growth factor‐A (VEGF‐A) mediates angiogenesis and is upregulated in the plaques and plasma of patients with psoriasis. Transgenic expression of VEGF‐A in experimental models led to the development of skin lesions that share many psoriasis features. Targeting VEGF‐A in in vivo models of psoriasis‐like inflammation resulted in disease clearance. Anti‐angiogenesis treatments are widely used for cancer and eye disease and there are clinical reports of patients treated with VEGF‐A inhibitors who have experienced Psoriasis Area and Severity Index improvement. Existing psoriasis treatments downregulate VEGF‐A and angiogenesis as part of their therapeutic effect. Pharmacogenetics studies suggest the existence of different genetic signatures within patients with psoriasis that correspond with different treatment responsiveness and disease severity. There is a subset of patients with psoriasis with an increased predisposition to produce high levels of VEGF‐A, who may be most likely to benefit from anti‐VEGF‐A therapy, offering an opportunity to personalize treatment in psoriasis. Anti‐VEGF‐A therapies may offer an alternative to existing anticytokine strategies or be complementary to standard treatments for the management of psoriasis.

Influential Usage of Big Data and Artificial Intelligence in Healthcare

Artificial intelligence (AI) is making computer systems capable of executing human brain tasks in many fields in all aspects of daily life. The enhancement in information and communications technology (ICT) has indisputably improved the quality of people's lives around the globe. Especially, ICT has led to a very needy and tremendous improvement in the health sector which is commonly known as electronic health (eHealth) and medical health (mHealth). Deep machine learning and AI approaches are commonly presented in many applications using big data, which consists of all relevant data about the medical health and diseases which a model can access at the time of execution or diagnosis of diseases. For example, cardiovascular imaging has now accurate imaging combined with big data from the eHealth record and pathology to better characterize the disease and personalized therapy. In clinical work and imaging, cancer care is getting improved by knowing the tumor biology and helping in the implementation of precision medicine. The Markov model is used to extract new approaches for leveraging cancer. In this paper, we have reviewed existing research relevant to eHealth and mHealth where various models are discussed which uses big data for the diagnosis and healthcare system. This paper summarizes the recent promising applications of AI and big data in medical health and electronic health, which have potentially added value to diagnosis and patient care.

Data Dentistry: How Data Are Changing Clinical Care and Research

Data are a key resource for modern societies and expected to improve quality, accessibility, affordability, safety, and equity of health care. Dental care and research are currently transforming into what we term data dentistry, with 3 main applications: 1) medical data analysis uses deep learning, allowing one to master unprecedented amounts of data (language, speech, imagery) and put them to productive use. 2) Data-enriched clinical care integrates data from individual (e.g., demographic, social, clinical and omics data, consumer data), setting (e.g., geospatial, environmental, provider-related data), and systems level (payer or regulatory data to characterize input, throughput, output, and outcomes of health care) to provide a comprehensive and continuous real-time assessment of biologic perturbations, individual behaviors, and context. Such care may contribute to a deeper understanding of health and disease and a more precise, personalized, predictive, and preventive care. 3) Data for research include open research data and data sharing, allowing one to appraise, benchmark, pool, replicate, and reuse data. Concerns and confidence into data-driven applications, stakeholders’ and system’s capabilities, and lack of data standardization and harmonization currently limit the development and implementation of data dentistry. Aspects of bias and data-user interaction require attention. Action items for the dental community circle around increasing data availability, refinement, and usage; demonstrating safety, value, and usefulness of applications; educating the dental workforce and consumers; providing performant and standardized infrastructure and processes; and incentivizing and adopting open data and data sharing.

Wearable Devices in Health Monitoring from the Environmental towards Multiple Domains: A Survey

The World Health Organization (WHO) recognizes the environmental, behavioral, physiological, and psychological domains that impact adversely human health, well-being, and quality of life (QoL) in general. The environmental domain has significant interaction with the others. With respect to proactive and personalized medicine and the Internet of medical things (IoMT), wearables are most important for continuous health monitoring. In this work, we analyze wearables in healthcare from a perspective of innovation by categorizing them according to the four domains. Furthermore, we consider the mode of wearability, costs, and prolonged monitoring. We identify features and investigate the wearable devices in the terms of sampling rate, resolution, data usage (propagation), and data transmission. We also investigate applications of wearable devices. Web of Science, Scopus, PubMed, IEEE Xplore, and ACM Library delivered wearables that we require to monitor at least one environmental parameter, e.g., a pollutant. According to the number of domains, from which the wearables record data, we identify groups: G1, environmental parameters only; G2, environmental and behavioral parameters; G3, environmental, behavioral, and physiological parameters; and G4 parameters from all domains. In total, we included 53 devices of which 35, 9, 9, and 0 belong to G1, G2, G3, and G4, respectively. Furthermore, 32, 11, 7, and 5 wearables are applied in general health and well-being monitoring, specific diagnostics, disease management, and non-medical. We further propose customized and quantified output for future wearables from both, the perspectives of users, as well as physicians. Our study shows a shift of wearable devices towards disease management and particular applications. It also indicates the significant role of wearables in proactive healthcare, having capability of creating big data and linking to external healthcare systems for real-time monitoring and care delivery at the point of perception.

Heterogeneity of eye drop use among symptomatic dry eye individuals in Japan: large-scale crowdsourced research using DryEyeRhythm application

PURPOSE

To determine eye drop type and usage frequency and investigate risk factors for no eye drop use in individuals with symptomatic dry eye (DE) in Japan.

STUDY DESIGN

Crowdsourced observational study.

METHODS

This study was conducted using the DryEyeRhythm smartphone application between November 2016 and September 2019. Data collected included the type and frequency of eye drop use, demographics, medical history, lifestyle, and self-reported symptoms. Symptomatic DE was defined as an Ocular Surface Disease Index total score of ≥ 13. Risk factors for no eye drop use were identified using multivariate logistic regression analyses.

RESULTS

Among 2619 individuals with symptomatic DE, 1876 did not use eye drops. The most common eye drop type was artificial tears (53.4%), followed by hyaluronic acid 0.1% (33.1%) and diquafosol sodium 3% (18.7%). Risk factors (odds ratio [95% confidence interval]) for no eye drop use were age (0.97 [0.97-0.98]), body mass index (1.04 [1.01-1.07]), brain disease (0.38 [0.15-0.98]), collagen disease (0.30 [0.13-0.68]), mental illness other than depression and schizophrenia (0.65 [0.45-0.93]), cataract surgery (0.12 [0.02-0.59]), ophthalmic surgery other than cataract and laser-assisted in situ keratomileusis (0.55 [0.34-0.88]), current (0.47 [0.38-0.57]) or past (0.58 [0.43-0.77]) contact lens use, >8 h screen exposure time (1.38 [1.05-1.81]), <6 h (1.24 [1.01-1.52]) and >9 h (1.34 [1.04-1.72]) sleep time, and water intake (0.97 [0.94-0.98]).

CONCLUSION

Many participants with symptomatic DE did not use optimized eye drop treatment and identified risk factors for no eye drop use. The DryEyeRhythm application may help improve DE treatment.

Diagnostic ability of maximum blink interval together with Japanese version of Ocular Surface Disease Index score for dry eye disease

Various symptoms of the dry eye disease (DED) interfere with the quality of life and reduce work productivity. Therefore, screening, prevention, and treatment of DED are important. We aimed to investigate the potential diagnostic ability of the maximum blink interval (MBI) (the length of time participants could keep their eyes open) with disease-specific questionnaire for DED. This cross-sectional study included 365 patients (252 with DED and 113 without DED) recruited between September 2017 and December 2019. Discriminant validity was assessed by comparing the non-DED and DED groups based on the MBI with a Japanese version of the Ocular Surface Disease Index (J-OSDI) and tear film breakup time (TFBUT) with J-OSDI classifications. The MBI with J-OSDI showed good discriminant validity by known-group comparisons. The positive and predictive values of MBI with J-OSDI were 96.0% (190/198 individuals) and 37.1% (62/167 individuals), respectively. The area under the receiver operating characteristic curve (AUC) of MBI with J-OSDI was 0.938 (95% confidence interval 0.904–0.971), the sensitivity was 75.4% (190/252 individuals), and the specificity was 92.9% (105/113 individuals), which are similar to the diagnostic ability of TFBUT with J-OSDI (AUC 0.954). In conclusion, MBI with J-OSDI may be a simple, non-invasive screening test for DED.