The first step in diagnosing ED is to confirm the symptom, since frequently the patient might confuse difficulty to maintain an erection with premature ejaculation or other sexual dysfunctions. It is important to establish the duration of the symptom (onset), as well as its severity and frequency (once, always, situational) to help confirm the dysfunction and help identify the diagnosis. The interviewer should use clear and simple language and make the patient feel as comfortable as possible to discuss his situation. Language too technical and distant will jeopardize the patient’s understanding and expression. Frequently, the patient needs permission to talk about ED with his physician, since he may think his doctor could feel uncomfortable with the discussion. This is easy to overcome by allowing the patient to discuss the issue, asking direct questions about the patient’s sex life.

Historytaking should follow a formula allowing the interviewer to identify the different risks and predisposing factors, with the intention to act on each of them with a clear therapeutic purpose. Also, a thorough review of the patient’s current medications is mandatory to rule out etiology and potential treatment contraindications.One important aspect to explore during the interview is the patient and partner’s degree of knowledge regarding the normal sexuality changes with aging, such as the progressive decrease of testosterone levels. This decrease may be due to a lower number of Leydig cells, a decrease of the LH peaks, an impaired tissue perfusion, and/or an increase of the serum sexhormone binding globulin (SHBG).

The concept that sexual dysfunctions are a part of the normal sexual changes accompanying aging is a common myth. It is important to explain to the patient that while the sexual responses may change with aging, they do not disappear. There are many reports supporting the concept of a continuing sexual interest and activity in the elderly, which could represent even a larger proportion of subjects if non-coital sexual activity were considered. The Massachusetts Male Aging Study showed a clear relationship of ED with age and reported a prevalence of ED as 52% of men over 50 years old. A decrease of sexual interest with age may reflect a hormonal imbalance. Also, there may be an adrenergic over-sensibility or hyperactivity, and a decrease of penile smooth muscle resulting in a lower intensity arousal phase, thus translating into difficulty to obtain and maintain an erection.

The ejaculatory volume and orgasmic intensity is lower, and with a decrease of ejaculatory contractions, the detumescence phase is faster and the refractory period is longer. These changes need to be discussed with the patients as they often result in a lower sexual frequency, a longer time needed to achieve a rigid erection, a need of a greater stimulus to obtain a similar response, lower penetration rigidity, lower ejaculatory volume, and faster detumescence. It is also important to discuss the normal physiologic changes which occur in their female partner, such as the physical and psychological changes occurring during menopause and female sexual dysfunction.

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Posted on 24-07-2012
Filed Under (ED Treatment) by admin

If relevant data (e.g. standard deviations) were not reported adequately, we attempted to calculate the needed parameters. Trials that did not report complete numerical information for relevant efficacy/harms outcomes (i.e., arm-specific mean endpoint or change in score, standard deviation, or standard error, proportion of patients with an outcome at followup) could not be incorporated in the meta-analyses. Trial reports presenting measures of variability (e.g. standard deviation) only graphically (i.e., no numerical data were available) were not pooled. Online Mexican Pharmacy

We calculated standard deviations from standard errors or 95 percent confidence intervals.

For continuous outcomes (e.g. mean endpoint/change in the total score of IIEF), the absolute difference between treatment-specific means and corresponding standard deviations were ascertained for each individual study. A generic inverse variance method was used to calculate the response outcomes and corresponding 95 percent confidence intervals for the combined treatment groups.

For dichotomous outcomes (e.g. improvement in erection GAQ), studies were grouped by type of treatment and dose to minimize clinical heterogeneity. The intent-to-treat group or number enrolled at the time of study was used for analyses and, when this information was unavailable, we used the number provided in the report.

Pooled relative risks with corresponding 95 percent confidence intervals were generated.

The DerSimonian and Laird random-effects model was used to obtain combined estimates across the studies. The degree of statistical heterogeneity was evaluated by using a chi-square test and the I2 statistic. An I2 of less than 25 percent is consistent with low heterogeneity; 25 to 50 percent with moderate heterogeneity; and over 50 percent with high heterogeneity. When statistically significant heterogeneity was identified, it was explored through subgroup and sensitivity analyses when appropriate. Sources of heterogeneity include reporting and methodological quality (e.g. methods for randomization, adequacy of allocation concealment, blinding, washout period for crossover trials, data analysis) as well as clinical heterogeneity (e.g. study population, dosing of therapeutic agent, duration of followup). Estimates from the heterogeneous groups must be interpreted with caution, especially when small numbers of trials are included.

We also performed a series of subgroup analyses to explore the consistency of the results.

The meta-analyses are presented as forest plots. Publication bias was explored through funnel plots (Figures D1-16, Appendix D) by plotting the relative measures of effect (relative risk) versus a measure of precision of the estimate (1/standard error). The visual asymmetry in funnel plots maybe be suggestive of publication bias, although other potential causes for asymmetry exist. The degree of funnel plot asymmetry was measured using the Egger regression test.

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