Body Mass Index Combined With Inflammatory Factors Can Better Predict Varicocele

Si Yan Miao1, Wen Rui Wu1, Liang Feng1

  • 1Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, CHN.

Cureus
|October 10, 2024
PubMed

Insights

Varicocele (VC) is often found during infertility diagnosis. Systemic immune-inflammation index (SII) and neutrophil-lymphocyte ratio (NLR) are risk factors, while higher body mass index (BMI) is protective. Combining BMI with SII and NLR improves VC prediction.

Area of Science:

  • Urology
  • Andrology
  • Inflammation Research

Background:

  • Varicocele (VC) is a common cause of male infertility, often asymptomatic and diagnosed late.
  • Early identification of VC is crucial for timely clinical intervention.
  • Understanding risk and protective factors for VC is essential for improved diagnostic strategies.

Purpose of the Study:

  • To identify independent risk and protective factors for varicocele (VC).
  • To evaluate the diagnostic value of these factors, individually and in combination, for predicting VC.
  • To explore the predictive accuracy of body mass index (BMI) combined with inflammatory markers.

Main Methods:

  • Retrospective analysis of clinical data from 423 patients (January 2021-February 2024).
  • Propensity score matching (PSM) to create two comparable groups (VC and non-VC).
  • Multivariate binary logistic regression and Receiver Operating Characteristic (ROC) curve analysis.

Main Results:

  • Systemic immune-inflammation index (SII) and neutrophil-lymphocyte ratio (NLR) were independent risk factors for VC (p<0.05).
  • Higher body mass index (BMI) was an independent protective factor against VC (p<0.05).
  • Combined BMI with inflammatory factors (SII, NLR) significantly improved VC prediction accuracy (87.5%) compared to individual factors.

Conclusions:

  • SII and NLR are significant risk factors for varicocele.
  • BMI serves as a protective factor against varicocele.
  • Combining BMI with SII and NLR offers a more accurate predictive model for varicocele detection.

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