Assessing Global and Regional Interest in Home Dialysis Modalities, 2004-2024
Bibliographic record
Abstract
Background: Home dialysis, including peritoneal dialysis and home hemodialysis, represents crucial renal replacement therapy options for patients with end-stage kidney disease. With the internet becoming a primary source for healthcare information, this study aimed to analyze global and regional interests in home dialysis using Google Trends™ data from January 2004 to March 2024. Methods: A comprehensive analysis was conducted using Google Trends™ with the search terms "Peritoneal Dialysis" and "Home Hemodialysis." The study extracted worldwide trends and detailed regional interests within the United States. Interest levels were quantitatively assessed based on Google Trends™ indices, providing insights into temporal patterns and geographical distributions of public interest. Results: The study found fluctuating global interest in PD, with a peak in March 2022 and the lowest interest in December 2008. The most recent data from March 2024 showed a significant interest level of 94, indicating a recent upward trend. Notably, Mexico exhibited the highest relative interest in PD. Within the United States, Tennessee demonstrated the highest interest. For Home Hemodialysis, peak interest was recorded in July 2004, with the most recent data from March 2024 showing a modest increase in interest. The United States led in relative interest for Home Hemodialysis, followed by Australia, Canada, and the United Arab Emirates. Mississippi was the state with the highest interest within the United States. Conclusion: This study offers crucial insights into the global and regional landscape of interest in home dialysis modalities, highlighting the significance of leveraging online platforms to increase public awareness, education, and engagement in peritoneal dialysis and home hemodialysis. By understanding the temporal and geographical patterns of interest, healthcare providers, policymakers, and patient advocacy groups can develop targeted strategies to promote the benefits of home dialysis, address knowledge gaps, and improve access to these life-sustaining treatments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".