The role of neutrophil-to-lymphocyte ratio in men with erectile dysfunction-preliminary findings of a real-life cross-sectional study.
Eugenio VentimigliaW CazzanigaF PederzoliN FregoF ChierigoPaolo CapogrossoL BoeriF DehòC AbbateD MorettiL PiemontiF MontorsiAlessia d'ArmaPublished in: Andrology (2018)
The aim of this study was to investigate the role of systemic inflammation by means of the neutrophil-to-lymphocyte ratio (NLR) in men with erectile dysfunction (ED). Complete demographic, clinical, and laboratory data from 279 consecutive men with newly diagnosed ED were analyzed. Health-significant comorbidities were scored with the Charlson Comorbidity Index (CCI). A complete blood count was requested for every man, and the NLR was calculated for every individual. Patients were invited to complete the IIEF questionnaire. Logistic regression models tested the odds (OR, 95% CI) of severe ED (defined as IIEF-EF <11, according to Cappelleri's criteria) after adjusting for age, BMI, comorbidities (CCI >0), metabolic syndrome, NLR, cigarette smoking, and color duplex Doppler ultrasound parameters. Likewise, LNR values were also dichotomized according to the most informative cutoff predicting severe ED using the minimum p value approach. Median [IQR] age of included men was 51 [40-64] years. Of all, 87 (31%) men had severe ED. Men with severe ED were older (median [IQR] age: 61 [47-67] vs. 49 [39-58] years) and had a higher rate of CCI>0 [46/87 (53%) vs. 44/192 (23%) patients]. Thereof, NLR was dichotomized according to the most informative cutoff (NLR>3); patients with severe ED more frequently had NLR>3 as compared to all other ED patients [namely, 18/87 (21%) vs. 13/192 (7%)]. At multivariable logistic regression analysis, NLR>3.0 emerged as an independent predictor (OR [CI] 2.43 [1.06; 5.63]) of severe ED, after accounting for other clinical variables. A NLR>3 increased the risk of having severe ED in our cohort, boosting the already existing evidence linking systemic inflammation to ED. Moreover, this easily obtainable index can be clinically useful in better risk-stratifying patients with ED.
Keyphrases
- emergency department
- newly diagnosed
- end stage renal disease
- early onset
- metabolic syndrome
- ejection fraction
- middle aged
- chronic kidney disease
- magnetic resonance imaging
- healthcare
- prognostic factors
- public health
- mental health
- body mass index
- cardiovascular disease
- adipose tissue
- climate change
- risk assessment
- skeletal muscle
- spinal cord
- machine learning
- human health
- artificial intelligence
- health promotion