An evolutionary model of premenstrual syndrome

PMS has existed at least since the beginning of medical writing, and is estimated to affect large proportions of women worldwide. But the etiology remains unknown, diagnostic definition and methods vary tremendously, and treatment is wholly symptom-oriented. This poor state of understanding has been attributed to a lack of theoretical perspective. The current work provides such a theoretical perspective from an evolutionary paradigm. PMS is not evolutionarily adaptive in and of itself. Rather, it is part of a cyclic pattern that results from the cessation of heightened, positive physical and sociobehavioral states that are evolutionarily favored during the fertile phase of the menstrual cycle for some women. When the advantage of these positive states diminishes, they cease, causing relatively lower states that are subjectively experienced as symptoms. In its clinical extreme, this is PMS. However, eons of evolution would result in modern women who are choosy about the conditions under which they reproduce. Thus, women whose conditions suggest a high probability of successful immediate reproduction are expected to experience the heightened, positive states during the fertile phase of the menstrual cycle to attract mates and fertilizations; these women will experience symptoms premenstrually. But women whose conditions suggest a low probability of successful immediate reproduction are expected to experience the heightened, positive states during the premenstruum to retain mates, accrue or maintain resources, and/or otherwise improve their conditions; these women will experience symptoms during the fertile phase of the menstrual cycle ("pseudo-PMS"). In addition, the heightened states are expected to shift in response to changes in conditions throughout women's lives, being expressed at whatever point is most evolutionarily beneficial given current conditions. This suggests that our conceptualization of PMS should be reframed within a facultative (condition-sensitive), evolutionary model. It also generates predictions both within- and between women that should elucidate the syndrome.     

Comparison of low-density lipoprotein cholesterol level calculated using the modified Martin/Hopkins estimation or the Friedewald formula with direct homogeneous assay measured low-density lipoprotein cholesterol

IntroductionLow-density lipoprotein cholesterol (LDL-C) represents the primary lipoprotein target for reducing cardiovascular risk (CV). The aim of our study is to compare the direct and the calculated LDL-C levels in the range below 1.8 mmol/l and 2.6 mmol/l depending on triglycerides, and to evaluate the variation in remnant lipoprotein cholesterol.Material and methodsWe investigated 14 906 lipid profiles from fasting blood samples of Hungarian individuals with triglycerides < 4.5 mmol/l. Total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG) and direct LDL-C were measured by the enzymatic assay. We calculated LDL-C by Friedewald’s formula (F-LDL-C) and by using the new Martin/Hopkins estimation (MH-LDL-C).ResultsFor F-LDL-C below 1.8 mmol/l, MH-LDL-C was 58% between 1.8 and 2.59 mmol/l when TG was in the range 2.3–4.5 mmol/l. For F-LDL-C below 2.6 mmol/l, the MH-LDL-C concordance was 73% in the same TG range (2.3–4.5 mmol/l. If MH-LDL-C was less than 1.8 mmol/l or between 1.8 and 2.59 mmol/l, the difference between non-HDL-C (TC – HDL-C = AC: atherogenic cholesterol) and (MH)LDL-C was less than 0.8 mmol/l in the TG range below 2.3 mmol/l. The remnant lipoprotein cholesterol values were on average 0.5 mmol/l lower by the Martin/Hopkins estimation compared to the Friedewald’s calculation if the TG was above 2.3 mmol/l.ConclusionsThe Friedewald equation tends to underestimate LDL-C levels in very high and high-risk settings. Our analysis supports the conclusion that in Hungarian patients, LDL-C estimation using the Martin/Hopkins formula, which is validated by the beta-quantification method, yields a more accurate LDL-C value than that calculated by the Friedewald formula.