Co-design of a voice-based app to monitor long COVID symptoms with its end-users: A mixed-method study.

Background: People living with Long COVID (PWLC), which is still a poorly understood disease, often face major issues accessing proper care and frequently feel abandoned by the healthcare system. PWLC frequently report impaired quality of life because of the medical burden, the variability and intensity of symptoms, and insecurity toward the future. These particular needs justify the development of innovative, minimally disruptive solutions to facilitate the monitoring of this complex and fluctuating disease. Voice-based interactions and vocal biomarkers are promising digital approaches for such health monitoring. Methods: Based on a mixed-method approach, this study describes the entire co-design process of Long COVID Companion, a voice-based digital health app to monitor Long COVID symptoms. Potential end-users of the app, both PWLC and healthcare professionals (HCP) were involved to (1) understand the unmet needs and expectations related to Long COVID care and management, (2) to assess the barriers and facilitators regarding a health monitoring app, (3) to define the app characteristics, including future potential use of vocal biomarkers and (4) to develop a first version of the app. Results: This study revealed high needs and expectations regarding a digital health app to monitor Long COVID symptoms and the readiness to use vocal biomarkers from end-users. The main expectations included improved care and daily life, and major concerns were linked to accessibility and data privacy. Long COVID Companion was developed as a web application and is composed of a health monitoring component that allows auto-evaluation of symptoms, global health, and scoring relevant symptoms and quality of life using standardized questionnaires. Conclusions: The Long COVID Companion app will address a major gap and provide day-to-day support for PWLC. However, further studies will be needed following its release, to evaluate its acceptability, usability and effectiveness.

Sex inequalities in cardiovascular risk factors and their management in primary prevention in adults living with type 1 diabetes in Germany and France: findings from DPV and SFDT1.

INTRODUCTION & OBJECTIVES: To evaluate whether cardiovascular risk factors and their management differ in primary prevention between adult males and females with type 1 diabetes (T1D) in two European countries in 2020-2022 and sex inequalities in achievement of standards of care in diabetes. METHODS: We used 2020-2022 data of patients without a cardiovascular history in the Prospective Diabetes Follow-up registry (DPV) centres, in Germany, and the Société Francophone du Diabète- Cohorte Diabète de Type 1 cohort (SFDT1), in France. RESULTS: We included 2,657 participants from the DPV registry and 1,172 from the SFDT1 study. Body mass indexes were similar in females and males with similar proportions of HbA1c < 7% (DPV: 36.6 vs 33.0%, p = 0.06, respectively; SFDT1: 23.4 vs 25.7%, p = 0.41). Females were less overweight compared to men in DPV (55.4 vs 61.0%, p < 0.01) but not in SFDT1 (48.0 vs 44.9%, p = 0.33) and were less prone to smoke (DPV: 19.7 vs 25.8%, p < 0.01; SFDT1: 21.0 vs 26.0%, p = 0.07). Systolic blood pressure was lower in females than males with a higher rate of antihypertensive therapy in case of hypertension in females in DPV (70.5 vs 63.7%, p = 0.02) but not in SFDT1 (73.3 vs 68.6%, p = 0.64). In the case of microalbuminuria, ACEi-ARB were less often prescribed in women than men in DPV (21.4 vs 37.6%, p < 0.01) but not SFDT1 (73.3 vs 67.5.0%, p = 0.43). In females compared to males, HDL-cholesterol levels were higher; triglycerides were lower in both countries. In those with LDL-cholesterol > 3.4 mmol/L (DPV: 19.9 (females) vs 23.9% (males), p = 0.01; SFDT1 17.0 vs 19.2%, p = 0.43), statin therapy was less often prescribed in females than males in DPV (7.9 vs 17.0%, p < 0.01), SFDT1 (18.2 vs 21.0%, p = 0.42). CONCLUSION: In both studies, females in primary prevention have a better cardiovascular risk profile than males. We observed a high rate of therapeutic inertia, which might be higher in females for statin treatment and nephroprotection with ACEi-ARB, especially in Germany. Diabetologists should be aware of sex-specific differences in the management of cardiorenal risk factors to develop more personalized prevention strategies.

The impact of patient registration on utilisation and quality of care: a propensity score matching and staggered difference-in-differences analysis of a cohort of 16,775 people with type 2 diabetes.

BACKGROUND: In 2012, Luxembourg introduced a Referring Doctor (RD) policy, whereby patients voluntarily register with a primary care practitioner, who coordinates patients' health care and ensures optimal follow-up. We contribute to the limited evidence base on patient registration by evaluating the effects of the RD policy. METHODS: We used data on 16,775 people with type 2 diabetes on oral medication (PWT2D), enrolled with the Luxembourg National Fund from 2010 to 2018. We examined the utilisation of primary and specialist outpatient care, quality of care process indicators, and reimbursed prescribed medicines over the short- (until 2015) and medium-term (until 2018). We used propensity score matching to identify comparable groups of patients with and without an RD. We applied difference-in-differences methods that accounted for patients' registration with an RD in different years. RESULTS: There was low enrolment of PWT2D in the RD programme. The differences-in-differences parallel trends assumption was not met for: general practitioner (GP) consultations, GP home visits (medium-term), HbA1c test (short-term), complete cholesterol test (short-term), kidney function (urine) test (short-term), and the number of repeat prescribed cardiovascular system medicines (short-term). There was a statistically significant increase in the number of: HbA1c tests (medium-term: 0.09 (95% CI: 0.01 to 0.18)); kidney function (blood) tests in the short- (0.10 (95% CI: 0.01 to 0.19)) and medium-term (0.11 (95% CI: 0.03 to 0.20)); kidney function (urine) tests (medium-term: 0.06 (95% CI: 0.02 to 0.10)); repeat prescribed medicines in the short- (0.19 (95% CI: 0.03 to 0.36)) and medium-term (0.18 (95% CI: 0.02 to 0.34)); and repeat prescribed cardiovascular system medicines (medium-term: 0.08 (95% CI: 0.01 to 0.15)). Sensitivity analyses also revealed increases in kidney function (urine) tests (short-term: 0.07 (95% CI: 0.03 to 0.11)) and dental consultations (short-term: 0.06, 95% CI: 0.00 to 0.11), and decreases in specialist consultations (short-term: -0.28, 95% CI: -0.51 to -0.04; medium-term: -0.26, 95% CI: -0.49 to -0.03). CONCLUSIONS: The RD programme had a limited effect on care quality indicators and reimbursed prescribed medicines for PWT2D. Future research should extend the analysis beyond this cohort and explore data linkage to include clinical outcomes and socio-economic characteristics.

Smartphone use and cerebro-cardio-vascular health: opportunity or public health threat?

Graphical AbstractImpact of smartphone (over)use on cerebro-cardio-vascular health.

Heterogeneity of glycaemic phenotypes in type 1 diabetes.

AIMS/HYPOTHESIS: Our study aims to uncover glycaemic phenotype heterogeneity in type 1 diabetes. METHODS: In the Study of the French-speaking Society of Type 1 Diabetes (SFDT1), we characterised glycaemic heterogeneity thanks to a set of complementary metrics: HbA1c, time in range (TIR), time below range (TBR), CV, Gold score and glycaemia risk index (GRI). Applying the Discriminative Dimensionality Reduction with Trees (DDRTree) algorithm, we created a phenotypic tree, i.e. a 2D visual mapping. We also carried out a clustering analysis for comparison. RESULTS: We included 618 participants with type 1 diabetes (52.9% men, mean age 40.6 years [SD 14.1]). Our phenotypic tree identified seven glycaemic phenotypes. The 2D phenotypic tree comprised a main branch in the proximal region and glycaemic phenotypes in the distal areas. Dimension 1, the horizontal dimension, was positively associated with GRI (coefficient [95% CI]) (0.54 [0.52, 0.57]), HbA1c (0.39 [0.35, 0.42]), CV (0.24 [0.19, 0.28]) and TBR (0.11 [0.06, 0.15]), and negatively with TIR (-0.52 [-0.54, -0.49]). The vertical dimension was positively associated with TBR (0.41 [0.38, 0.44]), CV (0.40 [0.37, 0.43]), TIR (0.16 [0.12, 0.20]), Gold score (0.10 [0.06, 0.15]) and GRI (0.06 [0.02, 0.11]), and negatively with HbA1c (-0.21 [-0.25, -0.17]). Notably, socioeconomic factors, cardiovascular risk indicators, retinopathy and treatment strategy were significant determinants of glycaemic phenotype diversity. The phenotypic tree enabled more granularity than traditional clustering in revealing clinically relevant subgroups of people with type 1 diabetes. CONCLUSIONS/INTERPRETATION: Our study advances the current understanding of the complex glycaemic profile in people with type 1 diabetes and suggests that strategies based on isolated glycaemic metrics might not capture the complexity of the glycaemic phenotypes in real life. Relying on these phenotypes could improve patient stratification in type 1 diabetes care and personalise disease management.

Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality.

Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital mortality post-SARS-CoV-2 infection. Blood samples and clinical data from 1286 COVID-19 patients collected from 2020 to 2023 across four cohorts in Europe and Canada were analyzed, with 2906 long non-coding RNAs profiled using targeted sequencing. From a discovery cohort combining three European cohorts and 804 patients, age and the long non-coding RNA LEF1-AS1 were identified as predictive features, yielding an AUC of 0.83 (95% CI 0.82-0.84) and a balanced accuracy of 0.78 (95% CI 0.77-0.79) with a feedforward neural network classifier. Validation in an independent Canadian cohort of 482 patients showed consistent performance. Cox regression analysis indicated that higher levels of LEF1-AS1 correlated with reduced mortality risk (age-adjusted hazard ratio 0.54, 95% CI 0.40-0.74). Quantitative PCR validated LEF1-AS1's adaptability to be measured in hospital settings. Here, we demonstrate a promising predictive model for enhancing COVID-19 patient management.

Assessment of the Impact of Subcutaneous Catheter Change on Glucose Control in Patients with Type 1 Diabetes Treated by Insulin Pump in Open- and Closed-Loop Modes.

Introduction: Most continuous subcutaneous insulin infusion (CSII) catheters (KT) are changed every 3 days. This study aims at evaluating whether KT changes impact glucose control while under open-loop (OL) or automated insulin delivery (AID) modes. Methods: We included patients with type 1 diabetes who used Tandem t:slim x2 insulin pump and Dexcom G6 glucose sensor for 20 days in OL, then as AID. CSII and sensor glucose data in OL and for the past 20 days of 3-month AID were retrospectively analyzed. The percentage of time spent with sensor glucose above 180 mg/dL (%TAR180) was compared between the calendar day of KT change (D0), the next day (D1), and 2 days later (D2). Values were adjusted for age, gender, body mass index (BMI), hemoglobin A1c (HbA1c) at inclusion, and %TAR180 for the 2 h before KT change. Results: A total of 1636 KT changes were analyzed in 134 patients: 72 women (54%), age: 35.6 ± 15.7 years, BMI: 25.2 ± 4.7 kg/m2, and HbA1c: 7.5 ± 0.8%. %TAR180 in the 2 h before the KT change was 51.3 ± 37.0% in OL and 33.2 ± 30.0% in AID mode. In OL, significant absolute increases of %TAR180 at D0 versus D1 (+6.9%; P < 0.0001) or versus D2 (+6.8%; P < 0.0001) were observed. In AID, significant absolute increases of %TA180R at D0 versus D1 (+4.8%; P < 0.0001) or versus D2 (+4.2%; P < 0.0001) were also observed. Conclusion: This study shows an increase in time spent in hyperglycemia on the day of the KT change both in OL and AID modes. This additional information should be taken into account to improve current AID algorithms. ClinicalTrials.gov: NCT04939766.

Relationship between multimorbidity, functional limitation, and quality of life among middle-aged and older adults: findings from the longitudinal analysis of the 2013-2020 Survey of Health, Ageing, and Retirement in Europe (SHARE).

PURPOSE: The increased burden of multimorbidity is restricting individuals' ability to live autonomously, leading to a poorer quality of life. This study estimated trajectories of functional limitation and quality of life among middle-aged (ages 50 to 64 years) and older (aged 65 years and older) individuals with and without multimorbidity. We also assessed differences in the relationship between these two trajectories by multimorbidity status and separately for each age cohort. METHODS: Data originated from the Survey of Health, Ageing, and Retirement in Europe (SHARE). In Luxembourg, data were obtained between 2013 and 2020, involving 1,585 respondents ≥ 50 years of age. Multimorbidity was defined as a self-reported diagnosis of two or more out of 16 chronic conditions; functional limitation was assessed by a combined (Instrumental) Activities of Daily Living (ADL/IADLI) scale; and to measure quality of life, we used the Control, Autonomy, Self-Realization, and Pleasure (CASP-12) scale. Latent growth curve modelling techniques were used to conduct the analysis where repeated measures of quality of life and functional limitation were treated as continuous and zero-inflated count variables, respectively. The model was assessed separately in each age cohort, controlling for the baseline covariates, and the estimates from the two cohorts were presented as components of a synthetic cohort covering the life course from the age of 50. RESULTS: Middle-aged and older adults living with multimorbidity experienced poorer quality of life throughout the life course and were at a higher risk of functional limitation than those without multimorbidity. At baseline, functional limitation had a negative impact on quality of life. Furthermore, among middle-aged adults without multimorbidity and older adults with multimorbidity, an increase in the number of functional limitations led to a decline in quality of life. These results imply that the impact of multimorbidity on functional limitation and quality of life may vary across the life course. CONCLUSION: Using novel methodological techniques, this study contributes to a better understanding of the longitudinal relationship between functional limitation and quality of life among individuals with and without multimorbidity and how this relationship changes across the life course. Our findings suggest that lowering the risk of having multimorbidity can decrease functional limitation and increase quality of life.

The role of multimorbidity and socio-economic characteristics as potential risk factors for Long Covid: evidence from the multilevel analysis of the Survey of Health, Ageing and Retirement in Europe's corona surveys (2020-2021).

BACKGROUND: A substantial proportion of individuals continue experiencing persistent symptoms following the acute stage of their Covid-19 illness. However, there is a shortage of population-based studies on Long Covid risk factors. OBJECTIVE: To estimate the prevalence of Long Covid in the population of middle-aged and older Europeans having contracted Covid-19 and to assess the role of multimorbidity and socio-economic characteristics as potential risk factors of Long Covid. METHODS: A population-based longitudinal prospective study involving a sample of respondents 50 years and older (n = 4,004) from 27 countries who participated in the 2020 and 2021 Survey of Health, Ageing and Retirement in Europe (SHARE), in particular the Corona Surveys. Analyses were conducted by a multilevel (random intercept) hurdle negative binomial model. RESULTS: Overall, 71.6% (95% confidence interval = 70.2-73.0%) of the individuals who contracted Covid-19 had at least one symptom of Long Covid up to 12 months after the infection, with an average of 3.06 (standard deviation = 1.88) symptoms. There were significant cross-country differences in the prevalence of Long Covid and number of symptoms. Higher education and being a man were associated with a lower risk of Long Covid, whilst being employed was associated with a higher risk of having Long Covid. Multimorbidity was associated with a higher number of symptoms and older age was associated with a lower number of symptoms. CONCLUSION: Our results provide evidence on the substantial burden of Long Covid in Europe. Individuals who contracted Covid-19 may require long-term support or further medical intervention, putting additional pressure on national health care systems.

Validation of a SARS-CoV-2 Surrogate Neutralization Test Detecting Neutralizing Antibodies against the Major Variants of Concern.

SARS-CoV-2 infection and/or vaccination elicit a broad range of neutralizing antibody responses against the different variants of concern (VOC). We established a new variant-adapted surrogate virus neutralization test (sVNT) and assessed the neutralization activity against the ancestral B.1 (WT) and VOC Delta, Omicron BA.1, BA.2, and BA.5. Analytical performances were compared against the respective VOC to the reference virus neutralization test (VNT) and two CE-IVD labeled kits using three different cohorts collected during the COVID-19 waves. Correlation analyses showed moderate to strong correlation for Omicron sub-variants (Spearman's r = 0.7081 for BA.1, r = 0.7205 for BA.2, and r = 0.6042 for BA.5), and for WT (r = 0.8458) and Delta-sVNT (r = 0.8158), respectively. Comparison of the WT-sVNT performance with two CE-IVD kits, the "Icosagen SARS-CoV-2 Neutralizing Antibody ELISA kit" and the "Genscript cPass, kit" revealed an overall good correlation ranging from 0.8673 to -0.8773 and a midway profile between both commercial kits with 87.76% sensitivity and 90.48% clinical specificity. The BA.2-sVNT performance was similar to the BA.2 Genscript test. Finally, a correlation analysis revealed a strong association (r = 0.8583) between BA.5-sVNT and VNT sVNT using a double-vaccinated cohort (n = 100) and an Omicron-breakthrough infection cohort (n = 91). In conclusion, the sVNT allows for the efficient prediction of immune protection against the various VOCs.

Novel, computational IgE-clustering in a population-based cross-sectional study: Mapping the allergy burden.

BACKGROUND: Even though the prevalence of allergies is increasing, population-based data are still scarce. As a read-out for chronic inflammatory information, new methods are needed to integrate individual biological measurements and lifestyle parameters to mitigate the consequences and costs of allergic burden for society. METHODS: More than 480.000 data points were collected from 1462 Luxembourg adults during the representative, cross-sectional European Health Examination Survey, spanning health and lifestyle reports. Deep IgE-profiles based on unsupervised clustering were correlated with data of the health survey. FINDINGS: 42.6% of the participants reported a physician-diagnosed allergy and 44% were found to be IgE-positive to at least one allergen or extract. The main sensitization sources were tree pollens followed by grass pollens and mites (52.4%, 51.8% and 40.3% of sensitized participants respectively), suggesting seasonal as well as perennial burden. The youngest group of participants (25-34 years old) showed the highest burden of sensitization, with 18.2% of them having IgE to 10 or more allergen groups. Unsupervised clustering revealed that the biggest cluster of 24.4% of participants was also the one with the highest medical need, marked by their multi-sensitization to respiratory sources. INTERPRETATION: Our novel approach to analyzing large biosample datasets together with health information allows the measurement of the chronic inflammatory disease burden in the general population and led to the identification of the most vulnerable groups in need of better medical care.

The Long COVID experience from a patient's perspective: a clustering analysis of 27,216 Reddit posts.

Objective: This work aims to study the profiles of Long COVID from the perspective of the patients spontaneously sharing their experiences and symptoms on Reddit. Methods: We collected 27,216 posts shared between July 2020 and July 2022 on Long COVID-related Reddit forums. Natural language processing, clustering techniques and a Long COVID symptoms lexicon were used to extract the different symptoms and categories of symptoms and to study the co-occurrences and correlation between them. Results: More than 78% of the posts mentioned at least one Long COVID symptom. Fatigue (29.4%), pain (22%), clouded consciousness (19.1%), anxiety (17.7%) and headaches (15.6%) were the most prevalent symptoms. They also highly co-occurred with a variety of other symptoms (e.g., fever, sinonasal congestion). Different categories of symptoms were found: general (45.5%), neurological/ocular (42.9%), mental health/psychological/behavioral (35.2%), body pain/mobility (35.1%) and cardiorespiratory (31.2%). Posts focusing on other concerns of the community such as vaccine, recovery and relapse and, symptom triggers were detected. Conclusions: We demonstrated the benefits of leveraging large volumes of data from Reddit to characterize the heterogeneity of Long COVID profiles. General symptoms, particularly fatigue, have been reported to be the most prevalent and frequently co-occurred with other symptoms. Other concerns, such as vaccination and relapse following recovery, were also addressed by the Long COVID community.

Mixed-methods study protocol to identify expectations of people with type 1 diabetes and their caregivers about voice-based digital health solutions to support the management of diabetes distress: the PsyVoice study.

INTRODUCTION: Type 1 diabetes (T1D) requires continuous management to obtain a good metabolic control and prevent acute complications. This often affects psychological well-being. People with T1D frequently report diabetes distress (DD). Psychological issues can negatively affect metabolic control and well-being. New technologies can improve quality of life, reduce the treatment burden and improve glycaemic control. Voice technology may serve as an innovative and inexpensive remote monitoring device to evaluate psychological well-being. Tailoring digital health interventions according to the ability and interest of their intended 'end-users' increases the acceptability of the intervention itself. PsyVoice explores the perspectives and needs of people with T1D on voice-based digital health interventions to manage DD. METHODS AND ANALYSIS: PsyVoice is a mixed-methods study with qualitative and quantitative data sources. For the qualitative part, the researchers will invite 20 people with a T1D or caregivers of children with T1D to participate in in-depth semi-structured interviews. They will be invited as well to answer three questionnaires to assess socio-demographics, diabetes management, e-Health literacy and diabetes distress. Information from questionnaires will be integrated with themes developed in the qualitative analysis of the interviews. People with T1D will be invited to participate in the protocol and give feedback on interview guides, questionnaires, information sheets and informed consent. ETHICS AND DISSEMINATION: PsyVoice received ethical approval from Luxembourg's National Research Ethics Committee. Participants will receive information about the purpose, risks and strategies to ensure the confidentiality and anonymity of the study. The results of PsyVoice will guide the selection and development of voice-based technological interventions for managing DD. The outcome will be disseminated to academic and non-academic stakeholders through peer-reviewed open-access journals and a lay public report. TRIAL REGISTRATION NUMBER: This study is registered on ClinicalTrials.gov with the number NCT05517772.

Association between endometriosis and risk of type 2 diabetes: Results from the prospective E3N cohort.

OBJECTIVE: Several studies suggest an association between endometriosis and the risk of cardio-metabolic diseases. This study aimed to prospectively evaluate the association between history of endometriosis and incident type 2 diabetes. STUDY DESIGN: E3N is a prospective cohort of 98,995 French women aged 40-65 years at inclusion. Multivariable Cox regression models were used to estimate hazard ratios and 95 % confidence intervals for the association between endometriosis and incident type 2 diabetes. We evaluated effect modification by age, body mass index, infertility treatment, adherence to the Mediterranean diet, and menopausal status. RESULTS: Age at inclusion was 51 ± 6 years and there were 2672 incident cases of type 2 diabetes. A total of 4606 women reported surgically-confirmed endometriosis among 83,582 women with no history of diabetes at inclusion. Endometriosis was not associated with type 2 diabetes risk in a model adjusted for age, BMI, physical activity, smoking, education, age at menarche and oral contraceptive use (hazard ratio [HR] = 1.09; 95 % confidence interval [CI] = 0.92-1.29), neither after further adjustment for family history of diabetes, hypertension and menopausal status (HR = 0.97;95%CI = 0.80-1.16). The relationship did not differ by age at inclusion, BMI, infertility treatment, diet or menopausal status (p > 0.05). CONCLUSIONS: Surgically-confirmed endometriosis was not associated with the risk of type 2 diabetes in this large cohort, confirming that endometriosis is not a risk marker for type 2 diabetes.

Co-Design of a Voice-Based Digital Health Solution to Monitor Persisting Symptoms Related to COVID-19 (UpcomingVoice Study): Protocol for a Mixed Methods Study.

BACKGROUND: Between 10% and 20% of people with a COVID-19 infection will develop the so-called long COVID syndrome, which is characterized by fluctuating symptoms. Long COVID has a high impact on the quality of life of affected people, who often feel abandoned by the health care system and are demanding new tools to help them manage their symptoms. New digital monitoring solutions could allow them to visualize the evolution of their symptoms and could be tools to communicate with health care professionals (HCPs). The use of voice and vocal biomarkers could facilitate the accurate and objective monitoring of persisting and fluctuating symptoms. However, to assess the needs and ensure acceptance of this innovative approach by its potential users-people with persisting COVID-19-related symptoms, with or without a long COVID diagnosis, and HCPs involved in long COVID care-it is crucial to include them in the entire development process. OBJECTIVE: In the UpcomingVoice study, we aimed to define the most relevant aspects of daily life that people with long COVID would like to be improved, assess how the use of voice and vocal biomarkers could be a potential solution to help them, and determine the general specifications and specific items of a digital health solution to monitor long COVID symptoms using vocal biomarkers with its end users. METHODS: UpcomingVoice is a cross-sectional mixed methods study and consists of a quantitative web-based survey followed by a qualitative phase based on semistructured individual interviews and focus groups. People with long COVID and HCPs in charge of patients with long COVID will be invited to participate in this fully web-based study. The quantitative data collected from the survey will be analyzed using descriptive statistics. Qualitative data from the individual interviews and the focus groups will be transcribed and analyzed using a thematic analysis approach. RESULTS: The study was approved by the National Research Ethics Committee of Luxembourg (number 202208/04) in August 2022 and started in October 2022 with the launch of the web-based survey. Data collection will be completed in September 2023, and the results will be published in 2024. CONCLUSIONS: This mixed methods study will identify the needs of people affected by long COVID in their daily lives and describe the main symptoms or problems that would need to be monitored and improved. We will determine how using voice and vocal biomarkers could meet these needs and codevelop a tailored voice-based digital health solution with its future end users. This project will contribute to improving the quality of life and care of people with long COVID. The potential transferability to other diseases will be explored, which will contribute to the deployment of vocal biomarkers in general. TRIAL REGISTRATION: ClinicalTrials.gov NCT05546918; https://clinicaltrials.gov/ct2/show/NCT05546918. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46103.

Interaction between plasma phospholipid odd-chain fatty acids and GAD65 autoantibodies on the incidence of adult-onset diabetes: the EPIC-InterAct case-cohort study.

AIMS/HYPOTHESIS: Islet autoimmunity may progress to adult-onset diabetes. We investigated whether circulating odd-chain fatty acids (OCFA) 15:0 and 17:0, which are inversely associated with type 2 diabetes, interact with autoantibodies against GAD65 (GAD65Ab) on the incidence of adult-onset diabetes. METHODS: We used the European EPIC-InterAct case-cohort study including 11,124 incident adult-onset diabetes cases and a subcohort of 14,866 randomly selected individuals. Adjusted Prentice-weighted Cox regression estimated HRs and 95% CIs of diabetes in relation to 1 SD lower plasma phospholipid 15:0 and/or 17:0 concentrations or their main contributor, dairy intake, among GAD65Ab-negative and -positive individuals. Interactions between tertiles of OCFA and GAD65Ab status were estimated by proportion attributable to interaction (AP). RESULTS: Low concentrations of OCFA, particularly 17:0, were associated with a higher incidence of adult-onset diabetes in both GAD65Ab-negative (HR 1.55 [95% CI 1.48, 1.64]) and GAD65Ab-positive (HR 1.69 [95% CI 1.34, 2.13]) individuals. The combination of low 17:0 and high GAD65Ab positivity vs high 17:0 and GAD65Ab negativity conferred an HR of 7.51 (95% CI 4.83, 11.69), with evidence of additive interaction (AP 0.25 [95% CI 0.05, 0.45]). Low dairy intake was not associated with diabetes incidence in either GAD65Ab-negative (HR 0.98 [95% CI 0.94, 1.02]) or GAD65Ab-positive individuals (HR 0.97 [95% CI 0.79, 1.18]). CONCLUSIONS/INTERPRETATION: Low plasma phospholipid 17:0 concentrations may promote the progression from GAD65Ab positivity to adult-onset diabetes.