Pd52-12 the Impact of Hypertension and Antihypertensives on Semen Quality

Abstract

only 119 (17.8%) were actually hypogonadal according to the Endocrine Society classification criteria. Conversely, 37 (23.7%) out of 156 patients with biochemical hypogonadism would have been overlooked. The overall predictive accuracy, sensibility, and specificity of the ASRM guidelines were 58%, 76%, and 39%, respectively. Our logistic regression-based nomogram, was not quite reliable enough to predict hypogonadism, despite demonstrating a significantly higher predictive accuracy (68%, p<0.001) than ASRM guidelines.CONCLUSIONS: Current findings showed that the ASRM guidelines/recommendations for male infertility work-up may not be suitable for application to Caucasian-European men. As a matter of fact, one out of four hypogonadal men may miss out on a proper endocrine assessment when adhering to the ASRM guidelines/recommendations prompting the EAU guidelines suggestion to have tT assessed in every infertile patients.

Hypertension and Male Fertility

“…Men with hypertension were found to be more likely to have one or more semen abnormalities compared to normotensive men [ 2 ]. Moreover, compared to men without hypertension, men diagnosed with hypertension demonstrated impaired semen parameters [ 15 ]. Hypertensive men had a lower semen volume (2.1 mL vs .…”

“…We then stratified men by individual class of antihypertensive medication [ 15 ]. Several differences were identified between classes of antihypertensives.…”

Considerations for the analysis of longitudinal electronic health records linked to claims data to study the effectiveness and safety of drugs

“…Our search returned 542 unique articles/abstracts, among which nine journal articles and six abstracts were selected. Most of the articles were excluded because they did not investigate drug effectiveness or safety ( n = 350), some for using only EHR ( n = 47) or claims data ( n = 10), some for using both types of datasets without data linkage ( n = 55).…”

“…If not, the researcher will need to supplement the data with EHR. Some example outcomes in this scenario include change in glycosylated hemoglobin (HbA1c), BMI, or blood pressure (BP), smoking cessation, semen volume and sperm concentration, left ventricular ejection fractions assessed by an echocardiogram, or QT interval prolongation assessed by an electrocardiogram. When choosing EHR as the additional source of outcome information, researchers should be mindful of how the information was recorded and how patients with the outcome information recorded in EHR differ from those missing such information.…”

“…Such a comparison would not be fair without taking into account the performance status of the patients, because they noted 75% of the patients had good performance status but only 39% of those with poor performance status received first‐line chemotherapy; they thus had to supplement the claims with EHR to obtain information on performance status . Other commonly used important confounders in the literature that require information from EHR include: vital signs (e.g., blood pressures), BMI, and laboratory values (e.g., HbA1c, low‐density lipoprotein, serum creatinine, etc.). An example of an illustrative clinical question would be the assessment of sulfamethoxazole‐trimethoprim vs. other antibiotics in relation to hyperkalemia with confounding adjustment for baseline potassium and creatinine assessed by laboratory results .…”