Relationship Between Serum Testosterone and Severity of Lower Urinary Tract Symptoms Among Malaysian Men
Bibliographic record
Abstract
Background Lower urinary tract symptoms (LUTS) are commonly experienced among ageing males. The increasing prevalence of late-onset hypogonadism suggests a possible relationship between serum testosterone and severity of LUTS. This study examines the association between serum testosterone and severity of lower urinary tract symptoms among Malaysian men, as reflected by the International Prostate Symptom Score (IPSS). Method A total of 163 men with LUTS were enrolled in a cross-sectional study in Hospital Canselor Tuanku Mukhriz, Malaysia. Full examination, IPSS, and serum total testosterone (TT) levels were evaluated. Categorical and continuous correlations were analyzed using chi-square test and age-adjusted Pearson’s partial correlation, respectively. Result Mean age was 66.25 (SD = 7.05), with mean serum TT of 16.74 nmol/L (SD = 6.32). Twenty eight percent (n = 46) had low testosterone levels. Severity of LUTS (mild, moderate, severe) was not found to be dependent on TT status (normal, low, severely low), (χ2 [4, N = 163] = 4.24, P = 0.37). Weak negative correlations between total IPSS and IPSS storage sub-score with serum TT levels were exhibited respectively (r = −0.17, P < 0.05; r = −0.17, P < 0.05). Conclusion Among elderly Malaysian men, severity of LUTS and TT status were not found to be associated, despite a weak negative correlation between IPSS and serum testosterone levels. Nonetheless, with a high prevalence of hypogonadal ageing men, further research regarding serum testosterone measurement among this population may be valuable as part of a multimodal approach to treatment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".