Infodemiology of antiphospholipid syndrome: Merging informatics and epidemiology
Bibliographic record
Abstract
OBJECTIVE: To investigate trends in Internet search volumes linked to Antiphospholipid Syndrome (APS), using Big Data monitoring and data mining. METHODS: Based on the large amount of data generated by Google Trends and scientific search tools (SCOPUS, Medline/Pubmed, and ClinicalTrails.gov), we performed a longitudinal analysis based on the term "antiphospholipid" in a 5-year web-based research. RESULTS: Google Trends captured that APS-related digital interest was generally steady in the study period (Relative Search Volume [RSV] mean value 71.1±9.3% [95%CI 55.6-89.4], median 72.0), with no significant peak based on different seasons (e.g. winter vs. summer time). When comparing the APS-related digital interest with search volumes generated in the same time period for Inherited Thrombophilias (IT) and Systemic Lupus Erythematosus (SLE), we found a digital interest 35-times higher for APS than for IT (RSV mean value 71.1±9.3% [95%CI 55.6-89.4] vs. 2±3.2% [95%CI 0.7-7.4]). When compared to SLE, APS reached a similar RSV, showing a comparable digital interest (RSV mean value 71.1±9.3% [95%CI 55.6-89.4] vs. 87±11.8% [95%CI 60.7-107.9]). When adjusting for relative search volumes of Google Trends, we found a relative prevalence of search volumes of 35.5% in Europe, 12.3% in the United States, 11.5% in South America, 11.2% in Australia, 9.2% in Canada, 9.2% in Japan, and 5.1% in India. We observed an overall similar distribution of search volumes from Google Trends compared to results from Medline/Pubmed, SCOPUS, and ClinicalTrials.gov. In brief, the United States and Europe (mainly Italy, the United Kingdom, Spain, France, and Germany) presented the higher RSV. Similarly, these countries showed a higher number of research publications and on-going trials in the field of APS. CONCLUSION: In this study, we demonstrated that the interest in APS is not equally distributed globally. Thus, geopolitical differences might represent a challenge when attempting to estimate the prevalence of APS or designing worldwide investigations in APS. Combining the expanding framework of infodemiology with scientific networking collaborative efforts, such as AntiPhospholipid Syndrome Alliance For Clinical Trials and InternatiOnal Networking (APS ACTION), will help better define the syndrome in terms of prevalence, event occurrence ratios, and thrombosis risk assessment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".