Is there a link between back pain and urinary symptoms?
Bibliographic record
Abstract
AIMS: To identify epidemiological studies of mechanical low back pain and urinary dysfunction, and to identify potential evidence supporting a mechanism for this relationship. METHODS: A systematic online search was conducted of EmBASE, Medline, CINAHL, and PEDro databases. We excluded studies where an obvious link between low back pain and urinary dysfunction exists (such as cauda equina syndrome). Two reviewers used inclusion/exclusion criteria to screen the articles. Data were extracted and summarised with a narrative review, and study quality was assessed. RESULTS: We included 22/930 studies. Twelve studies addressed the epidemiological link between low back pain and urinary symptoms. The studies all found a statistically significant association between the diagnosis of urinary incontinence or urinary symptoms and low back pain, (aOR's 1.1 to 3.1). Results were consistent when stratified by sex, age, and when adjusted for confounders. The study quality was good in 4/12. Eight studies reported on an assessment/intervention related to pelvic floor function, urinary symptoms and low back pain. Pelvic floor dysfunction was common in women with low back pain, however randomized studies and pre-post studies reported mixed results for pelvic floor physiotherapy improving low back pain. The study quality was good in 3/8. CONCLUSIONS: Low back pain and urinary incontinence are associated in large epidemiological studies, and the presence of one condition seems to predispose the development of the other. There is limited evidence to suggest pelvic floor interventions are useful for low back pain in this patient population, therefore the mechanism for this relationship is still unclear.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".