Is There a Link Between Non-Alcoholic Fatty Liver Disease and Benign Prostate Hyperplasia/Lower Urinary Tract Symptoms: A Systematic Review and a Meta-Analysis
Bibliographic record
Abstract
Background:Prostatic growth has been thought to be the systemic manifestation of some metabolic derangements in recent studies. Nonalcoholic fatty liver disease (NAFLD), a hepatic manifestation of the metabolic syndrome, might be closely linked with benign prostate hyperplasia and lower urinary tract symptoms (BPH/LUTS). Several studies have been conducted regarding NAFLD and BPH/LUTS association. However, the results are yet to reach a clear conclusion. We aimed to gather these studies' results to make a more robust analysis through a systematic review and meta-analysis. Methods:We systematically searched Pubmed-Medline, Cochrane Library, and Science Direct databases. We excluded all experimental studies, case reports, and reviews. Our search was restricted to the English language. We used standard mean difference for BPH/LUTS-related parameters. We identified the study qualities by the Newcastle–Ottawa Scale. We conducted a publication bias analysis. Results:A total of six studies involving 7089 participants fulfilled the inclusion criteria. Our meta-analysis revealed that patients with NAFLD have larger prostate volume [0.553 (0.303–0.802), P ˂ 0.001; Q = 97.41; P-value for heterogeneity = P < 0.0001; I 2 = 94.86%]. However, the summary effect size of the other parameters of BPH/LUTS (prostate-specific antigen and international prostate symptom score) computed in our meta-analysis did not yield significant results. Conclusions:The prostate size was larger in patients with NAFLD, but the meta-analysis did not reach a significant result for LUTS among the studies. These results should be tested with well-designed studies, in particular, to clarify the association of LUTS with NAFLD.
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.044 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".