The evidence behind the level of a random urine protein:creatinine in the diagnosis of preeclampsia: A systematic review

Objective. To determine the accuracy of the urine protein:creatinine ratio (pr:cr) in predicting 300 mg of protein in 24-hour urine collection in pregnant patients with suspected preeclampsia. ^ Methods. A systematic review was performed. Articles were identified through electronic databases and the relevant citations were hand searching of textbooks and review articles. Included studies evaluated patients for suspected preeclampsia with a 24-hour urine sample and a pr:cr. Only English language articles were included. The studies that had patients with chronic illness such as chronic hypertension, diabetes mellitus or renal impairment were excluded from the review. Two researchers extracted accuracy data for pr:cr relative to a gold standard of 300 mg of protein in 24-hour sample as well as population and study characteristics. The data was analyzed and summarized in tabular and graphical form. ^ Results. Sixteen studies were identified and only three studies met our inclusion criteria with 510 total patients. The studies evaluated different cut-points for positivity of pr:cr from 130 mg/g to 700 mg/g. Sensitivities and specificities for pr:cr of 130mg/g -150 mg/g were 90-93% and 33-65%, respectively; for a pr:cr of 300 mg/g were 81-95% and 52-80%, respectively; for a pr:cr of 600-700mg/g were 85-87% and 96-97%, respectively. ^ Conclusion. The value of a random pr:cr to exclude pre-eclampsia is limited because even low levels of pr:cr (130-150 mg/g) may miss up to 10% of patients with significant proteinuria. A pr:cr of more than 600 mg/g may obviate a 24-hour collection.^

Estimation of male-to-female ratios of mutation rate in primates and rodents

Haldane (1935) developed a method for estimating the male-to-female ratio of mutation rate ($\alpha$) by using sex-linked recessive genetic disease, but in six different studies using hemophilia A data the estimates of $\alpha$ varied from 1.2 to 29.3. Direct genomic sequencing is a better approach, but it is laborious and not readily applicable to non-human organisms. To study the sex ratios of mutation rate in various mammals, I used an indirect method proposed by Miyata et al. (1987). This method takes advantage of the fact that different chromosomes segregate differently between males and females, and uses the ratios of mutation rate in sequences on different chromosomes to estimate the male-to-female ratio of mutation rate. I sequenced the last intron of ZFX and ZFY genes in 6 species of primates and 2 species of rodents; I also sequenced the partial genomic sequence of the Ube1x and Ube1y genes of mice and rats. The purposes of my study in addition to estimation of $\alpha$'s in different mammalian species, are to test the hypothesis that most mutations are replication dependent and to examine the generation-time effect on $\alpha$. The $\alpha$ value estimated from the ZFX and ZFY introns of the six primate specise is ${\sim}$6. This estimate is the same as an earlier estimate using only 4 species of primates, but the 95% confidence interval has been reduced from (2, 84) to (2, 33). The estimate of $\alpha$ in the rodents obtained from Zfx and Zfy introns is ${\sim}$1.9, and that deriving from Ube1x and Ube1y introns is ${\sim}$2. Both estimates have a 95% confidence interval from 1 to 3. These two estimates are very close to each other, but are only one-third of that of the primates, suggesting a generation-time effect on $\alpha$. An $\alpha$ of 6 in primates and 2 in rodents are close to the estimates of the male-to-female ratio of the number of germ-cell divisions per generation in humans and mice, which are 6 and 2, respectively, assuming the generation time in humans is 20 years and that in mice is 5 months. These findings suggest that errors during germ-cell DNA replication are the primary source of mutation and that $\alpha$ decreases with decreasing length of generation time. ^

Nosocomial infections and their relationship to non-traditional risk factors in a medical intensive care unit

Background. Nosocomial infections are a source of concern for many hospitals in the United States and worldwide. These infections are associated with increased morbidity, mortality and hospital costs. Nosocomial infections occur in ICUs at a rate which is five times greater than those in general wards. Understanding the reasons for the higher rates can ultimately help reduce these infections. The literature has been weak in documenting a direct relationship between nosocomial infections and non-traditional risk factors, such as unit staffing or patient acuity.^ Objective. To examine the relationship, if any, between nosocomial infections and non-traditional risk factors. The potential non-traditional risk factors we studied were the patient acuity (which comprised of the mortality and illness rating of the patient), patient days for patients hospitalized in the ICU, and the patient to nurse ratio.^ Method. We conducted a secondary data analysis on patients hospitalized in the Medical Intensive Care Unit (MICU) of the Memorial Hermann- Texas Medical Center in Houston during the months of March 2008- May 2009. The average monthly values for the patient acuity (mortality and illness Diagnostic Related Group (DRG) scores), patient days for patients hospitalized in the ICU and average patient to nurse ratio were calculated during this time period. Active surveillance of Bloodstream Infections (BSIs), Urinary Tract Infections (UTIs) and Ventilator Associated Pneumonias (VAPs) was performed by Infection Control practitioners, who visited the MICU and performed a personal infection record for each patient. Spearman's rank correlation was performed to determine the relationship between these nosocomial infections and the non-traditional risk factors.^ Results. We found weak negative correlations between BSIs and two measures (illness and mortality DRG). We also found a weak negative correlation between UTI and unit staffing (patient to nurse ratio). The strongest positive correlation was found between illness DRG and mortality DRG, validating our methodology.^ Conclusion. From this analysis, we were able to infer that non-traditional risk factors do not appear to play a significant role in transmission of infection in the units we evaluated.^