Urinary incontinence and quality of life: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Urinary incontinence (UI) and low quality of life (QoL) are two common conditions. Some recent literature proposed that these two entities can be associated. However, no attempt was made to collate this literature. Therefore, the aim of this study was to conduct a systematic review and meta-analysis of existing data to estimate the strength of the association between UI and QoL. Methods An electronic search of major databases up to 18th April 2020 was carried out. Meta-analysis of cross-sectional and case–control studies comparing mean values in QoL between patients with UI and controls was performed, reporting random-effects standardized mean differences (SMDs) ± 95% confidence intervals (CIs) as the effect size. Heterogeneity was assessed with the I 2 . Results Out of 8279 articles initially screened, 23 were finally included for a total of 24,983 participants, mainly women. The mean age was ≥ 50 years in 12/23 studies. UI was significantly associated with poor QoL as assessed by the short-form 36 (SF-36) total score ( n = 6 studies; UI: 473 vs. 2971 controls; SMD = − 0.89; 95% CI − 1.3 to − 0.42; I 2 = 93.5) and by the sub-scales of SF-36 and 5/8 of the domains included in the SF-36. Similar results were found using other QoL tools. The risk of bias of the studies included was generally high. Conclusions UI is associated with a poor QoL, with a strong level of certainty. This work, however, mainly based on cross-sectional and case–control studies, highlights the necessity of future longitudinal studies for better understanding the importance of UI on QoL.
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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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.040 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 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".