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Record W4417165600 · doi:10.1093/jsxmed/qdaf320.149

(149) Real-World Effectiveness of Clomiphene Citrate on Total Motile Sperm Count and Endocrine Profile in Idiopathic Male Infertility

2025· article· en· W4417165600 on OpenAlexaff
Carla Roque, Young‐Jin Ko, Ahmed Mousa Almuhanna, Haryana M. Dhillon, Avinash Sarcar, Premal A. Patel

Bibliographic record

VenueThe Journal of Sexual Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsManitoba HealthUniversity of Manitoba
Fundersnot available
KeywordsInfertilityEndocrine systemMale infertilityRetrospective cohort studyPregnancyCohortHormoneSemen analysisSemen

Abstract

fetched live from OpenAlex

Abstract Introduction Infertility affects about 16% of couples worldwide. When evaluating male infertility, clinicians rely on history, physical examination, semen analysis, and targeted hormonal or genetic tests. However, evidence for empiric medical therapy in idiopathic male-factor infertility remains limited. One treatment often used is clomiphene citrate (CC), a selective estrogen-receptor modulator that boosts endogenous gonadotropins and, in turn, spermatogenesis. Objective Our study aims to evaluate the effect of CC on total motile sperm count (TMSC) and overall hormonal profile in infertile men. Methods We conducted a single-center retrospective cohort study of men who underwent CC treatment for primary or secondary infertility. Inclusion criteria were normogonadotropic or hypogonadal men greater than or equal to 18 years old with clinical infertility, defined as the failure to achieve pregnancy after 12 months of regular unprotected intercourse with a healthy partner. Patients were excluded if they had a TMSC >20 million/mL, used exogenous testosterone, had a syndromic disorder, were lost to follow-up, were non-adherent to clomiphene, or lacked post-treatment TMSC data. The primary outcome was the change in TMSC; secondary outcomes were changes in testosterone, FSH, LH, estradiol, and 17-OHP measured before and after CC treatment. Pre- and post-treatment means were compared using paired, two-tailed t-tests. The change in TMSC was evaluated with multivariable linear regression adjusted for age, BMI, and baseline 17-OHP, testosterone, and FSH. Statistical significance was determined by p < 0.05. Results A total of 62 men with a mean age of 35.6 ± 4.6 years (range 25–45) were included in the study. The cohort had a mean BMI of 30.5 ± 6.8 kg/m2, and an average treatment duration of 13.1 ± 6.3 months. Following CC therapy, TMSC increased from 8.4 ± 18.9 to 21.9 ± 43.0 million (p = 0.017). In parallel, 17-OHP rose from 2.8 ± 1.4 to 4.6 ± 2.1 nmol/L, testosterone from 10.0 ± 5.0 to 19.8 ± 7.0 nmol/L, FSH from 6.5 ± 4.7 to 11.3 ± 10.6 IU/L, LH from 4.9 ± 2.5 to 9.7 ± 7.7 IU/L, and estradiol from 90.0 ± 35.6 to 146.1 ± 64.5 pmol/L (all p < 0.001; Table 1). A multiple linear regression found no association between TMSC change and age, BMI, baseline hormone levels, or CC-therapy duration (all p > 0.05; Table 2). Furthermore, Men with primary (n = 47) vs. secondary infertility (n = 15) did not differ in the degree of TMSC or hormonal changes (all p > 0.05), suggesting that the effectiveness of CC therapy is similar across all infertility classifications (Table 3). Conclusions Overall, CC was associated with an approximately 160% rise in TMSC with additional increases in gonadotropins and testosterone. Further, this response was independent of age, BMI, baseline hormone levels, and treatment duration, leaving no clear predictors of benefit. Larger prospective studies are needed to validate these findings and to guide optimal dosing and candidate selection. Disclosure No

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.021
GPT teacher head0.319
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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