Artificial Intelligence-Supported Development of Health Guideline Questions.

BACKGROUND: Guideline questions are typically proposed by experts. OBJECTIVE: To assess how large language models (LLMs) can support the development of guideline questions, providing insights on approaches and lessons learned. DESIGN: Two approaches for guideline question generation were assessed: 1) identification of questions conveyed by online search queries and 2) direct generation of guideline questions by LLMs. For the former, the researchers retrieved popular queries on allergic rhinitis using Google Trends (GT) and identified those conveying questions using both manual and LLM-based methods. They then manually structured as guideline questions the queries that conveyed relevant questions. For the second approach, they tasked an LLM with proposing guideline questions, assuming the role of either a patient or a clinician. SETTING: Allergic Rhinitis and its Impact on Asthma (ARIA) 2024 guidelines. PARTICIPANTS: None. MEASUREMENTS: Frequency of relevant questions generated. RESULTS: The authors retrieved 3975 unique queries using GT. From these, they identified 37 questions, of which 22 had not been previously posed by guideline panel members and 2 were eventually prioritized by the panel. Direct interactions with LLMs resulted in the generation of 22 unique relevant questions (11 not previously suggested by panel members), and 4 were eventually prioritized by the panel. In total, 6 of 39 final questions prioritized for the 2024 ARIA guidelines were not initially thought of by the panel. The researchers provide a set of practical insights on the implementation of their approaches based on the lessons learned. LIMITATION: Single case study (ARIA guidelines). CONCLUSION: Approaches using LLMs can support the development of guideline questions, complementing traditional methods and potentially augmenting questions prioritized by guideline panels. PRIMARY FUNDING SOURCE: Fraunhofer Cluster of Excellence for Immune-Mediated Diseases.

English tweets on allergy: Content analysis and association with surveillance data.

BACKGROUND: Analysis of X (formerly Twitter) posts can inform on the interest/perceptions that social media users have on health subjects. In this study, we aimed to analyse tweets on allergic conditions, comparing them with surveillance data. METHODS: We retrieved tweets from England on "allergy," "asthma," and "allergic rhinitis," published between 2016 and 2021. We estimated the correlation between the frequency of tweets on "asthma" and "allergic rhinitis" and English surveillance data on the incidence of asthma and allergic rhinitis medical visits. We performed sentiment analysis, computing a score informing on the emotional tone of assessed tweets. We applied a topic modelling approach to identify topics (clusters of words frequently occurring together) for tweets on each assessed condition. RESULTS: We analysed a total of 13,605 tweets on "allergy," 7767 tweets on "asthma," and 11,974 tweets on "allergic rhinitis." Food-related words were preponderant on tweets on "allergy," while "eyes" was the most frequent meaningful word on "allergy rhinitis" tweets. We observed seasonal patterns for tweets on "allergic rhinitis," both in their frequency and sentiment - the incidence of allergic rhinitis medical visits was moderately to strongly correlated with the frequency (ρ = 0.866) and sentiment (ρ = -0.474) of tweets on "allergic rhinitis." For tweets on "asthma," no such patterns/correlations were observed. The average sentiment score was negative for all assessed conditions, ranging from -0.004 ("asthma") to -0.083 ("allergic rhinitis"). CONCLUSIONS: Tweets on "allergic rhinitis" displayed a seasonal pattern regarding their frequency and sentiment, which correlated with surveillance data. No such patterns were observed for "asthma."

Adenoma detection rate by colonoscopy in real-world population-based studies: a systematic review and meta-analysis.

BACKGROUND: Adenoma detection rate (ADR) is a quality indicator set at a minimum of 25% in unselected populations by the European Society of Gastrointestinal Endoscopy (ESGE). Nevertheless, a lack of pooled observational data resembling real-world practice limits support for this threshold. We aimed to perform a systematic review with meta-analysis to evaluate the pooled rates for conventional adenoma detection, polyp detection (PDR), cecal intubation, bowel preparation, and complications in population-based studies. METHODS: The PubMed, Scopus, and Web of Science databases were searched until May 2023 for populational-based studies reporting overall ADR in unselected individuals. A random-effects model was used for meta-analysis. RESULTS: 31 studies were included, comprising 3 644 561 subjects. A high quality of procedures was noticeable, with a high cecal intubation rate and low complication rate. The overall pooled ADR, PDR, and rate of cancer detection were 26.5% (95%CI 23.3% to 29.7%), 38.3% (95%CI 32.5% to 44.1%), and 2.7% (95%CI 1.5% to 3.9%), respectively. ADR varied according to indication: screening 33.3% (95%CI 24.5% to 42.2%), surveillance 42.9% (95%CI 36.9% to 49.0%), and diagnostic 24.7% (95%CI 19.5% to 29.9%), with subgroup analysis revealing rates of 34.4% (95%CI 22.0% to 40.5%) for post-fecal occult blood test and 26.6% (95%CI 22.6% to 30.5%) for primary colonoscopy screening. Diminutive conventional adenomas yielded a pooled rate of 59.9% (95%CI 43.4% to 76.3%). The pooled rate for overall serrated lesion detection was 12.4% (95%CI 8.8% to 16.0%). Male sex and higher age were significantly associated with an ADR above the benchmark. CONCLUSION: This first meta-analysis relying on real-world observational studies supports the ESGE benchmark for ADR, while suggesting that different benchmarks might be used according to indication, sex, and age.

Individuals' attitudes toward digital mental health apps and implications for adoption in Portugal: web-based survey.

BACKGROUND: The literature is consensual regarding the academic community exhibiting higher levels of mental disorder prevalence than the general population. The potential of digital mental health apps for improving access to resources to cope with these issues is ample. However, studies have yet to be performed in Portugal on individuals' attitudes and perceptions toward digital mental health applications or their preferences and decision drivers on obtaining mental health care, self-assessment, or treatment. OBJECTIVE: This study aims to understand the determinants of digital mental health applications use in the Portuguese academic community of Porto, along with potential adoption barriers and enablers. METHODS: A cross-sectional, web-based survey was delivered via dynamic email to the University of Porto's academic community. Data collection occurred between September 20 and October 20, 2022. We used structural equation modeling to build three models, replicating a peer-reviewed and published study and producing a newly full mediation model shaped by the collected data. We tested the relationships between use of digital mental health apps and perceived stress, perceived need to seek help for mental health, perceived stigma, past use of mental health services, privacy concerns, and social influence. RESULTS: Of the 539 participants, 169 (31.4%) reported having used digital mental health apps. Perceived stress and a latent variable, comprising perceptions of mental health problems and coping strategies, were positively associated with mental health app use, while privacy concerns regarding one's information being accessible to others were negatively associated. Perceived stigma, need to seek help, and close relationships did not have a statistically significant direct effect. CONCLUSIONS: These findings can inform product and policy development of new, better-targeted digital mental health app interventions, with implications for researchers and academia, industry, and policymakers. Our study concludes that, to maximize adherence to these apps, they should have low to no financial charges, demonstrate evidence of their helpfulness and focus on the timely delivery of care. We also conclude that to foster digital mental health app use, there is a need to improve mental health literacy, namely regarding self-awareness of one's conditions, acceptable stress levels, and overall behavior towards mental health. TRIAL REGISTRATION: RR2-10.2196/41040.

Regional, sex, and age inequities in asthma hospital admissions in Spain and Portugal.

BACKGROUND: Asthma presents a significant health challenge, imposing a considerable burden on healthcare services. Discrepancies in asthma-related hospitalisations may reflect underlying health disparities. We aimed to analyse inequities in asthma hospital admissions in mainland Portugal and Spain, from a regional perspective and considering sex and age. METHODS: We conducted a retrospective study using data from the Spanish and Portuguese national hospitalisations databases. We calculated crude national and regional yearly hospitalisation rates according per Nomenclature of Territorial Units for Statistics region. Additionally, we calculated hospitalisation rates adjusted for asthma prevalence and the female-to-male ratio in asthma hospital admissions per age group, considering the female-to-male ratio in the overall population. RESULTS: Between 2012 and 2016, there were 92,084 asthma hospital admissions in mainland Spain and 7717 in mainland Portugal. There was a trend for a higher-than-average rate of asthma-related hospitalisations in the Northern regions of both countries. Women had a hospitalisation rate that was 3.2 times higher than men. Age was associated with higher risk for asthma hospitalisation, with individuals aged 65 and older displaying a hospitalisation rate 4.5 times higher than those under 65. Additionally, while hospitalisations in women aged <65 years were 2.3 times more likely than in men of the same age, hospitalisations in women aged ≥65 years were 3.5 times higher than in men aged ≥65 years. CONCLUSION: This study suggests that marked regional inequities in asthma hospital admissions exist in Spain and Portugal. Additionally, women are particularly at risk of hospitalisation due to asthma, and such risk increases with age.

COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study.

BACKGROUND: Contact tracing is a fundamental intervention in public health. When systematically applied, it enables the breaking of chains of transmission, which is important for controlling COVID-19 transmission. In theoretically perfect contact tracing, all new cases should occur among quarantined individuals, and an epidemic should vanish. However, the availability of resources influences the capacity to perform contact tracing. Therefore, it is necessary to estimate its effectiveness threshold. We propose that this effectiveness threshold may be indirectly estimated using the ratio of COVID-19 cases arising from quarantined high-risk contacts, where higher ratios indicate better control and, under a threshold, contact tracing may fail and other restrictions become necessary. OBJECTIVE: This study assessed the ratio of COVID-19 cases in high-risk contacts quarantined through contact tracing and its potential use as an ancillary pandemic control indicator. METHODS: We built a 6-compartment epidemiological model to emulate COVID-19 infection flow according to publicly available data from Portuguese authorities. Our model extended the usual susceptible-exposed-infected-recovered model by adding a compartment Q with individuals in mandated quarantine who could develop infection or return to the susceptible pool and a compartment P with individuals protected from infection because of vaccination. To model infection dynamics, data on SARS-CoV-2 infection risk (IR), time until infection, and vaccine efficacy were collected. Estimation was needed for vaccine data to reflect the timing of inoculation and booster efficacy. In total, 2 simulations were built: one adjusting for the presence and absence of variants or vaccination and another maximizing IR in quarantined individuals. Both simulations were based on a set of 100 unique parameterizations. The daily ratio of infected cases arising from high-risk contacts (q estimate) was calculated. A theoretical effectiveness threshold of contact tracing was defined for 14-day average q estimates based on the classification of COVID-19 daily cases according to the pandemic phases and was compared with the timing of population lockdowns in Portugal. A sensitivity analysis was performed to understand the relationship between different parameter values and the threshold obtained. RESULTS: An inverse relationship was found between the q estimate and daily cases in both simulations (correlations >0.70). The theoretical effectiveness thresholds for both simulations attained an alert phase positive predictive value of >70% and could have anticipated the need for additional measures in at least 4 days for the second and fourth lockdowns. Sensitivity analysis showed that only the IR and booster dose efficacy at inoculation significantly affected the q estimates. CONCLUSIONS: We demonstrated the impact of applying an effectiveness threshold for contact tracing on decision-making. Although only theoretical thresholds could be provided, their relationship with the number of confirmed cases and the prediction of pandemic phases shows the role as an indirect indicator of the efficacy of contact tracing.