The impact of different scenarios for intermittent bladder catheterization on health state utilities: results from an internet-based time trade-off survey
Bibliographic record
Abstract
AIMS: Intermittent catheterization (IC) is the gold standard for bladder management in patients with chronic urinary retention. Despite its medical benefits, IC users experience a negative impact on their quality of life (QoL). For health economics based decision making, this impact is normally measured using generic QoL measures (such as EQ-5D) that estimate a single utility score which can be used to calculate quality-adjusted life years (QALYs). But these generic measures may not be sensitive to all relevant aspects of QoL affected by intermittent catheters. This study used alternative methods to estimate the health state utilities associated with different scenarios: using a multiple-use catheter, one-time-use catheter, pre-lubricated one-time-use catheter and pre-lubricated one-time-use catheter with one less urinary tract infection (UTI) per year. METHODS: Health state utilities were elicited through an internet-based time trade-off (TTO) survey in adult volunteers representing the general population in Canada and the UK. Health states were developed to represent the catheters based on the following four attributes: steps and time needed for IC process, pain and the frequency of UTIs. RESULTS: The survey was completed by 956 respondents. One-time-use catheters, pre-lubricated one-time-use catheters and ready-to-use catheters were preferred to multiple-use catheters. The utility gains were associated with the following features: one time use (Canada: +0.013, UK: +0.021), ready to use (all: +0.017) and one less UTI/year (all: +0.011). LIMITATIONS: Internet-based survey responders may have valued health states differently from the rest of the population: this might be a source of bias. CONCLUSION: Steps and time needed for the IC process, pain related to IC and the frequency of UTIs have a significant impact on IC related utilities. These values could be incorporated into a cost utility analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".