Relationship Between Simple Renal Cysts and Hypertension: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Simple renal cysts (SRCs) are the most common incidentally found cystic lesions in the kidney. While their association with hypertension (HT) has been explored in various studies, the findings remain inconclusive. Thus, our meta-analysis aimed to systematically evaluate the relationship between SRCs and HT (PROSPERO ID: CRD42025580609). Methods: We conducted searches in PubMed, Web of Science Core Collection, and Scopus to identify observational studies that examined the association between SRCs and HT. All articles containing animal or pediatric (<18 years old) study populations or having <10 patients in total and/or lacking a control group that did not develop HT were excluded. Two reviewers independently screened the studies and extracted the data, and the quality of each included study was assessed using the Newcastle–Ottawa Scale. Statistical analyses were performed using Review Manager 5.4. Results: In total, 12 studies with 147,310 participants were included in this meta-analysis. Presence of SRCs was associated with a 2.04-fold higher likelihood of having HT (OR 2.04, 95%CI 1.70–2.45, p < 0.0001). Multivariate analysis further revealed that SRCs were independently associated with HT (aOR 1.36, 95%CI 1.24–1.49, p < 0.0001), with multiple SRCs (aOR 1.36, 95%CI 1.26–2.42, p = 0.0008) and bilateral SRCs (aOR 2.26, 95%CI 1.12–4.59, p = 0.02) showing a stronger association. Conclusions: This study provides the first in-depth review on the topic, showing an established link between SRCs and HT even after adjustment for major confounding factors such as age, sex, renal function, and other metabolic factors.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.038 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".