Interventions to decrease pain and anxiety in patients undergoing urodynamic study: Is there any clear evidence? A systematic review and meta-analysis
Bibliographic record
Abstract
Urodynamic study (UDS) is a valuable diagnostic procedure for assessing lower urinary tract symptoms but often induces pain and anxiety due to its invasive nature. This systematic review and meta-analysis aimed to evaluate the effectiveness of various interventions to reduce pain and anxiety in patients undergoing UDS. A comprehensive search was conducted in PubMed, ScienceDirect, EMBASE, and EBSCO up to October 2024. Twenty-two studies, including randomized controlled trials and observational studies, were included. Risk of bias was assessed using RoB 2, ROBINS-I, and the Newcastle–Ottawa Scale. Meta-analysis using Review Manager 5.3 showed that providing detailed information to patients significantly reduced pain (SMD: 0.84; 95% CI: 0.20–1.48; p = 0.01), while music therapy and anesthetic agents did not yield significant effects. The overall pooled effect on pain was not statistically significant. For anxiety, the pooled analysis indicated a modest but significant reduction (SMD: 0.57; 95% CI: 0.11–1.02; p = 0.04), despite high heterogeneity. Interventions such as mindfulness, aromatherapy, and heating pads showed potential in individual studies but were not included in meta-analysis due to limited data. The findings highlight that while certain interventions may alleviate discomfort during UDS, evidence remains inconsistent. Well-designed, large-scale trials are needed to establish standardized approaches for enhancing patient comfort during UDS.
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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 | 0.016 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.036 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".