Health-related quality of life and economic impact of urinary incontinence due to detrusor overactivity associated with a neurologic condition: a systematic review
Bibliographic record
Abstract
BACKGROUND: Patients with neurologic diseases often have neurogenic detrusor overactivity (NDO), which can result in a loss of voluntary bladder control and uncontrollable urinary incontinence (UI).The impact of UI due to NDO on patients' lives has not been well studied. The objective of this review was to assess the health-related quality of life (HRQoL) and economic burden in patients with urgency UI due to NDO in select countries in North America, the European Union, Asia, and Australia. METHODS: Systematic literature searches and reviews of articles published in English (January 2000 to February 2011) were conducted using MEDLINE®, EMBASE®, and the Cochrane Library. Studies assessing the impact of UI on HRQoL of patients with an underlying neurologic condition of interest (i.e., multiple sclerosis, spinal cord injury, Parkinson's disease, stroke, or spina bifida) were included. Economic studies in urgency UI also were included. RESULTS: Of 876 citations generated in the initial search, a total of 27 articles were deemed relevant: 16 articles presented HRQoL data and 11 articles presented information on the economic burden of UI. Humanistic studies used a range of HRQoL instruments to measure HRQoL burden, and the economic studies included different cost components to quantify the economic burden, making meaningful comparisons challenging. Despite this heterogeneity, the literature suggests that HRQoL in patients with UI due to NDO is worse than patients with UI in general or those with the same underlying neurologic condition without UI. In addition, urgency UI also results in substantial economic costs. CONCLUSIONS: Incontinent patients with underlying neurologic conditions have impaired HRQoL as well as substantial economic burden attributable to UI due to NDO. There is a need for urgency UI treatments that improve HRQoL of these patients and alleviate the economic burden of this condition.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".