Lessons from meta-analyses of randomized clinical trials for analysis of distributed networks of observational databases

Perspective review: Will generative AI make common data models obsolete in future analyses of distributed data networks?

Integrating real-world healthcare data is challenging due to diverse formats and terminologies, making standardization resource-intensive. While Common Data Models (CDMs) facilitate interoperability, they often cause information loss, exhibit semantic inconsistencies, and are labor-intensive to implement and update. We explore how generative artificial intelligence (GenAI), especially large language models (LLMs), could make CDMs obsolete in quantitative healthcare data analysis by interpreting natural language queries and generating code, enabling direct interaction with raw data. Knowledge graphs (KGs) standardize relationships and semantics across heterogeneous data, preserving integrity. This perspective review proposes a fourth generation of distributed data network analysis, building on previous generations categorized by their approach to data standardization and utilization. It emphasizes the potential of GenAI to overcome the limitations CDMs with GenAI-enabled access, KGs, and automatic code generation. A data commons may further enhance this capability, and KGs may well be needed to enable effective GenAI. Addressing privacy, security, and governance is critical; any new method must ensure protections comparable to CDM-based models. Our approach would aim to enable efficient, real-time analyses across diverse datasets and enhance patient safety. We recommend prioritizing research to assess how GenAI can transform quantitative healthcare data analysis by overcoming current limitations.

Self-perception evolution among university student TikTok users: evidence from China

The effects of short movies on social media platforms are gaining worldwide popularity and are now attracting global academic attention. Employing self-perception theory and qualitative research methodology, the study examines the influence of short video applications (TikTok) on app-user engagement and evaluates the self-perceived cognitive psychological understanding of Chinese university students. The findings show that identity, attitude change, emotional perception, and civic engagement are the most influential aspects of Chinese youths' self-perceptions. Furthermore, the positive and negative correlated components influence the distribution of short video values. Such tactical use of personality construction contributes to the present psychological research of Chinese university students.

Comparative estimation of the effects of antihypertensive medications on schizophrenia occurrence: a multinational observational cohort study

BACKGROUND

The association between antihypertensive medication and schizophrenia has received increasing attention; however, evidence of the impact of antihypertensive medication on subsequent schizophrenia based on large-scale observational studies is limited. We aimed to compare the schizophrenia risk in large claims-based US and Korea cohort of patients with hypertension using angiotensin-converting enzyme (ACE) inhibitors versus those using angiotensin receptor blockers (ARBs) or thiazide diuretics.

METHODS

Adults aged 18 years who were newly diagnosed with hypertension and received ACE inhibitors, ARBs, or thiazide diuretics as first-line antihypertensive medications were included. The study population was sub-grouped based on age (> 45 years). The comparison groups were matched using a large-scale propensity score (PS)-matching algorithm. The primary endpoint was incidence of schizophrenia.

RESULTS

5,907,522; 2,923,423; and 1,971,549 patients used ACE inhibitors, ARBs, and thiazide diuretics, respectively. After PS matching, the risk of schizophrenia was not significantly different among the groups (ACE inhibitor vs. ARB: summary hazard ratio [HR] 1.15 [95% confidence interval, CI, 0.99-1.33]; ACE inhibitor vs. thiazide diuretics: summary HR 0.91 [95% CI, 0.78-1.07]). In the older subgroup, there was no significant difference between ACE inhibitors and thiazide diuretics (summary HR, 0.91 [95% CI, 0.71-1.16]). The risk for schizophrenia was significantly higher in the ACE inhibitor group than in the ARB group (summary HR, 1.23 [95% CI, 1.05-1.43]).

CONCLUSIONS

The risk of schizophrenia was not significantly different between the ACE inhibitor vs. ARB and ACE inhibitor vs. thiazide diuretic groups. Further investigations are needed to determine the risk of schizophrenia associated with antihypertensive drugs, especially in people aged > 45 years.

Impact of symptomatic menopausal transition on the occurrence of depression, anxiety, and sleep disorders: A real-world multi-site study

BACKGROUND

The menopause transition is a vulnerable period that can be associated with changes in mood and cognition. The present study aimed to investigate whether a symptomatic menopausal transition increases the risks of depression, anxiety, and sleep disorders.

METHODS

This population-based, retrospective cohort study analysed data from five electronic health record databases in South Korea. Women aged 45-64 years with and without symptomatic menopausal transition were matched 1:1 using propensity-score matching. Subgroup analyses were conducted according to age and use of hormone replacement therapy (HRT). A primary analysis of 5-year follow-up data was conducted, and an intention-to-treat analysis was performed to identify different risk windows over 5 or 10 years. The primary outcome was first-time diagnosis of depression, anxiety, and sleep disorder. We used Cox proportional hazard models and a meta-analysis to calculate the summary hazard ratio (HR) estimates across the databases.

RESULTS

Propensity-score matching resulted in a sample of 17,098 women. Summary HRs for depression (2.10; 95% confidence interval [CI] 1.63-2.71), anxiety (1.64; 95% CI 1.01-2.66), and sleep disorders (1.47; 95% CI 1.16-1.88) were higher in the symptomatic menopausal transition group. In the subgroup analysis, the use of HRT was associated with an increased risk of depression (2.21; 95% CI 1.07-4.55) and sleep disorders (2.51; 95% CI 1.25-5.04) when compared with non-use of HRT.

CONCLUSIONS

Our findings suggest that women with symptomatic menopausal transition exhibit an increased risk of developing depression, anxiety, and sleep disorders. Therefore, women experiencing a symptomatic menopausal transition should be monitored closely so that interventions can be applied early.

Roboethics of tourism and hospitality industry: A systematic review

This study aims to give a comprehensive analysis of customers' acceptance and use of AI gadgets and its relevant ethical issues in the tourism and hospitality business in the era of the Internet of Things. Adopting a PRISMA methodology for Systematic Reviews and Meta-Analyses, the present research reviews how tourism and hospitality scholars have conducted research on AI technology in the field of tourism and the hospitality industry. Most of the journal articles related to AI issues published in Web of Science, ScienceDirect.com and the journal websites were considered in this review. The results of this research offer a better understanding of AI implementation with roboethics to investigate AI-related issues in the tourism and hospitality industry. In addition, it provides decision-makers in the hotel industry with practical references on service innovation, participation in the design of AI devices and AI device applications, meeting customer needs, and optimising customer experience. The theoretical implications and practical interpretations are further identified.

The Nordic perioperative and intensive care registries-Collaboration and research possibilities

BACKGROUND

The Nordic perioperative and intensive care registries have been built up during the last 25 years to improve quality in intensive and perioperative care. We aimed to describe the Nordic perioperative and intensive care registries and to highlight possibilities and challenges in future research collaboration between these registries.

MATERIAL AND METHOD

We present an overview of the following Nordic registries: Swedish Perioperative Registry (SPOR), the Danish Anesthesia Database (DAD), the Finnish Perioperative Database (FIN-AN), the Icelandic Anesthesia Database (IS-AN), the Danish Intensive Care Database (DID), the Swedish Intensive Care Registry (SIR), the Finnish Intensive Care Consortium, the Norwegian Intensive Care and Pandemic Registry (NIPaR), and the Icelandic Intensive Care Registry (IS-ICU).

RESULTS

Health care systems and patient populations are similar in the Nordic countries. Despite certain differences in data structure and clinical variables, the perioperative and intensive care registries have enough in common to enable research collaboration. In the future, even a common Nordic registry could be possible.

CONCLUSION

Collaboration between the Nordic perioperative and intensive care registries is both possible and likely to produce research of high quality. Research collaboration between registries may have several add-on effects and stimulate international standardization regarding definitions, scoring systems, and benchmarks, thereby improving overall quality of care.

Methodological frontiers in vaccine safety: qualifying available evidence for rare events, use of distributed data networks to monitor vaccine safety issues, and monitoring the safety of pregnancy interventions

While vaccines are rigorously tested for safety and efficacy in clinical trials, these trials do not include enough subjects to detect rare adverse events, and they generally exclude special populations such as pregnant women. It is therefore necessary to conduct postmarketing vaccine safety assessments using observational data sources. The study of rare events has been enabled in through large linked databases and distributed data networks, in combination with development of case-centred methods. Distributed data networks necessitate common protocols, definitions, data models and analytics and the processes of developing and employing these tools are rapidly evolving. Assessment of vaccine safety in pregnancy is complicated by physiological changes, the challenges of mother-child linkage and the need for long-term infant follow-up. Potential sources of bias including differential access to and utilisation of antenatal care, immortal time bias, seasonal timing of pregnancy and unmeasured determinants of pregnancy outcomes have yet to be fully explored. Available tools for assessment of evidence generated in postmarketing studies may downgrade evidence from observational data and prioritise evidence from randomised controlled trials. However, real-world evidence based on real-world data is increasingly being used for safety assessments, and new tools for evaluating real-world evidence have been developed. The future of vaccine safety surveillance, particularly for rare events and in special populations, comprises the use of big data in single countries as well as in collaborative networks. This move towards the use of real-world data requires continued development of methodologies to generate and assess real world evidence.

Comprehensive Comparative Effectiveness and Safety of First-Line β-Blocker Monotherapy in Hypertensive Patients: A Large-Scale Multicenter Observational Study

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Analytic and Data Sharing Options in Real-World Multidatabase Studies of Comparative Effectiveness and Safety of Medical Products

A wide range of analytic and data sharing options are available in nonexperimental multidatabase studies designed to assess the real-world benefits and risks of medical products. Researchers often consider six scientific domains when choosing among these options-study design, exposure type, outcome type, covariate summarization technique, covariate adjustment method, and data sharing approach. This article reviews available analytic and data sharing options and discusses key scientific and practical considerations when choosing among these options in multidatabase studies of comparative effectiveness and safety of medical products. The scientific considerations must be balanced against what the data-contributing sites are able or willing to share. While pooling of person-level data sets remains the most familiar and analytically flexible approach, newer analytic and data sharing approaches that share less granular summary-level information may be equally valid and preferred in some multidatabase studies, especially when sharing of person-level data is challenging or infeasible.