The Prevalence of LUTS in Men Aged ≥40 years based on the IPSS-Ina Questionnaire
Bibliographic record
Abstract
Objectives. LUTS (Lower Urinary Tract Symptoms) are several symptoms experienced by a person due to various pathologies that occur in the lower urinary tract. The prevalence of LUTS in ≥ 40-year-old men is high and many methods including IPSS have been made to measure LUTS. Unfortunately, the high prevalence is not followed by the number of patients who are seeking treatment for their LUTS.Methods. This observational cross-sectional study used 45 men aged ≥40 years who came to Tongauna Health Center. Each respondent was asked to fill out the IPSS questionnaire. Moreover, when the respondent has LUTS, he is also asked if he is ever looking for health care providers, where he consultations, and what the reason is if he is never looking for it.Result. Of 45 men, there are 37 men who have LUTS and only 8 asymptomatic men. Mild LUTS is the most common symptom with 22 respondents, followed by moderate with 11 respondents, and only 4 respondents who suffered from severe LUTS. Pleased (1) is the most respondent’s feel for their Quality of Life score. Only 7 respondents are ever looking for treatment, and the common reasons for them not getting treatment are their misperception about LUTS, economic factors, and attitude toward their illness.Conclusion. The number of LUTS patients≥40 years old male at Tongauna District is high, but their initiative to treat this symptom is still low due to many factors like knowledge, economic, and patient attitude.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".