The impact of lower urinary tract symptomatology on urine volumes in stone formers
Bibliographic record
Abstract
INTRODUCTION: We aimed to determine if there is a correlation between International Prostate Symptom scores (IPSS) and 24-hour urine collection volumes, as patients experiencing lower urinary tract symptoms (LUTS) may have impaired ability to increase fluid intake for stone prevention. METHODS: We conducted a single-centre, retrospective review was performed of stone-formers presenting from 2014-2016. Inclusion criteria were completion of an IPSS questionnaire and a 24-hour urine collection. Exclusion criteria included symptomatic stone or urinary tract infection at time of IPSS completion, inadequate 24-hour collection, or incomplete IPSS questionnaire. RESULTS: A total of 131 patients met inclusion criteria. Stratification by IPSS severity into mild (0-7), moderate (8-19), and severe (20-35) yielded groups of n=96, 28, and 7, respectively. Linear regression modelling did not reveal a correlation between IPSS score and volume (p=0.10). When compared to those with adequate urine volumes (>2 L/day, n=65), low-volume patients (<1 L/day, n=10) had a significantly higher total IPSS (11.7 vs. 6.1; p=0.036). These groups showed significant differences in their responses to questions about incomplete emptying (p=0.031), intermittency (p=0.011), and stranguria (p=0.0020), with higher scores noted in the low urine output group. CONCLUSIONS: This study is the first to examine the correlation between IPSS and 24-hour urine volume. Though our data does not show a linear relationship between urine output and IPSS, those with lower urine volumes appear to have worse self-reported voiding symptoms when compared to those with adequate volumes (>2 L/day) for stone prevention. The overall number of patients in our study is relatively small, which may account for the lack of a relationship between IPSS and 24-hour urine volumes.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".