Use of Urinary Pregnanediol 3-glucuronide to Confirm Ovulation

Objective Urinary hormonal markers may assist in increasing the efficacy of Fertility Awareness Based Methods (FABM). This study uses urinary pregnanediol-3a-glucuronide (PDG) testing to more accurately identify the infertile phase of the menstrual cycle in the setting of FABM. Methods Secondary analysis of an observational and simulation study, multicentre, European study. The study includes 107 women and tracks daily first morning urine (FMU), observed the changes in cervical mucus discharge, and ultrasonography to identify the day of ovulation over 326 menstrual cycles. The following three scenarios were tested: (A) use of the daily pregnandiol-3a-glucuronide (PDG) test alone; (B) use of the PDG test after the first positive urine luteinizing hormone (LH) kit result; (C) use of the PDG test after the disappearance of fertile type mucus. Two models were used: (1) one day of PDG positivity; or (2) waiting for three days of PDG positivity before declaring infertility. Results After the first positivity of a LH test or the end of fertile mucus, three consecutive days of PDG testing over a threshold of 5 μg/mL resulted in a 100% specificity for ovulation confirmation. They were respectively associated an identification of an average of 6.1 and 7.6 recognized infertile days. Conclusions The results demonstrate a clinical scenario with 100% specificity for ovulation confirmation and provide the theoretical background for a future development of a competitive lateral flow assay for the detection of PDG in the urine

Potential impact of multiple interventions on HIV incidence in a hyperendemic region in Western Kenya : a modelling study

Background: Multiple prevention interventions, including early antiretroviral therapy initiation, may reduce HIV incidence in hyperendemic settings. Our aim was to predict the short-term impact of various single and combined interventions on HIV spreading in the adult population of Ndhiwa subcounty (Nyanza Province, Kenya). Methods: A mathematical model was used with data on adults (15-59 years) from the Ndhiwa HIV Impact in Population Survey to compare the impacts on HIV prevalence, HIV incidence rate, and population viral load suppression of various interventions. These interventions included: improving the cascade of care (use of three guidelines), increasing voluntary medical male circumcision (VMMC), and implementing pre-exposure prophylaxis (PrEP) use among HIV-uninfected women. Results: After four years, improving separately the cascade of care under the WHO 2013 guidelines and under the treat-all strategy would reduce the overall HIV incidence rate by 46 and 58 %, respectively, vs. the baseline rate, and by 35 and 49 %, respectively, vs. the implementation of the current Kenyan guidelines. With conservative and optimistic scenarios, VMMC and PrEP would reduce the HIV incidence rate by 15-25 % and 22-28 % vs. the baseline, respectively. Combining the WHO 2013 guidelines with VMMC would reduce the HIV incidence rate by 35-56 % and combining the treat-all strategy with VMMC would reduce it by 49-65 %. Combining the WHO 2013 guidelines, VMMC, and PrEP would reduce the HIV incidence rate by 46-67 %. Conclusions: The impacts of the WHO 2013 guidelines and the treat-all strategy were relatively close; their implementation is desirable to reduce HIV spread. Combining several strategies is promising in adult populations of hyperendemic areas but requires regular, reliable, and costly monitoring

Confirmation of ovulation from urinary progesterone analysis: assessment of two automated assay platforms

Urinary concentrations of the major progesterone (P4) metabolite pregnanediol-3-glucuronide (PDG) are used to confirm ovulation. We aimed to determine whether automated immunoassay of urinary P4 was as efficacious as PDG to confirm ovulation. Daily urine samples from 20 cycles in 14 healthy women in whom ovulation was dated by ultrasound, and serial weekly samples from 21 women in whom ovulation was unknown were analysed. Daily samples were assayed by two automated P4 immunoassays (Roche Cobas and Abbott Architect) and PDG ELISA. Serial samples were assayed for P4 by Architect and PDG by ELISA. In women with detailed monitoring of ovulation, median (95% CI) luteal phase increase was greatest for PDG, 427% (261–661), 278% (187–354) for P4 Architect and least for P4 Cobas, 146% (130–191), p 0.92). In serial samples classified as (an)ovulatory by PDG, P4 Architect gave ROC AUC 0.95 (95% CI 0.89 to 1.01), with sensitivity and specificity for confirmation of ovulation of 0.90 and 0.91 at a cutoff of 1.67 μmol/mol. Automated P4 may potentially be as efficacious as PDG ELISA but research from a range of clinical settings is required

Multilevel model to assess sources of variation in follicular growth close to the time of ovulation in women with normal fertility: a multicenter observational study

Mikolajczyk RT, Stanford JB, Ecochard R. Multilevel model to assess sources of variation in follicular growth close to the time of ovulation in women with normal fertility: a multicenter observational study. Reproductive Biology and Endocrinology. 2008;6(1): 61.Background: To assess the amount of variability in ovarian follicular growth rate and maximum follicular diameter related to different centers, women and cycles of the same women in a multicenter observational study of follicular growth. Methods: Secondary analysis of a prospective cohort study from eight centers in Europe. There were 533 ultrasound examinations in 282 cycles of 107 women with normal fertility. A random effects model with center, woman and cycle as hierarchical units of variation was used to analyze mean follicular diameter on days preceding ovulation. Results: Follicular growth did not differ by center. There was homogenous growth across women and cycles, and the maximum follicular diameter before ovulation varied substantially across cycles but not across women. Many (about 40%) women had small maximum follicular diameter on the day before ovulation (<19 mm). Pre-ovulatory cycle length was not related to maximum follicular diameter. Conclusion: In normal fecundity, there is a substantial variation in maximum follicular diameter from cycle to cycle based on variation in the duration of follicular development, but the variation could not be explained by different characteristics of different women. Explanation of variation in follicular growth has to be found on the cycle level

Osmolality and non-structural carbohydrate composition in the secondary phloem of trees across a latitudinal gradient in Europe

Phloem osmolality and its components are involved in basic cell metabolism, cell growth, and in various physiological processes including the ability of living cells to withstand drought and frost. Osmolality and sugar composition responses to environmental stresses have been extensively studied for leaves, but less for the secondary phloem of plant stems and branches. Leaf osmotic concentration and the share of pinitol and raffinose among soluble sugars increase with increasing drought or cold stress, and osmotic concentration is adjusted with osmoregulation. We hypothesize that similar responses occur in the secondary phloem of branches. We collected living bark samples from branches of adult Pinus sylvestris, Picea abies, Betula pendula and Populus tremula trees across Europe, from boreal Northern Finland to Mediterranean Portugal. In all studied species, the observed variation in phloem osmolality was mainly driven by variation in phloem water content, while tissue solute content was rather constant across regions. Osmoregulation, in which osmolality is controlled by variable tissue solute content, was stronger for Betula and Populus in comparison to the evergreen conifers. Osmolality was lowest in mid-latitude region, and from there increased by 37% toward northern Europe and 38% toward southern Europe due to low phloem water content in these regions. The ratio of raffinose to all soluble sugars was negligible at mid-latitudes and increased toward north and south, reflecting its role in cold and drought tolerance. For pinitol, another sugar known for contributing to stress tolerance, no such latitudinal pattern was observed. The proportion of sucrose was remarkably low and that of hexoses (i.e., glucose and fructose) high at mid-latitudes. The ratio of starch to all non-structural carbohydrates increased toward the northern latitudes in agreement with the build-up of osmotically inactive C reservoir that can be converted into soluble sugars during winter acclimation in these cold regions. Present results for the secondary phloem of trees suggest that adjustment with tissue water content plays an important role in osmolality dynamics. Furthermore, trees acclimated to dry and cold climate showed high phloem osmolality and raffinose proportion.Peer reviewe

Tomato: a crop species amenable to improvement by cellular and molecular methods

Tomato is a crop plant with a relatively small DNA content per haploid genome and a well developed genetics. Plant regeneration from explants and protoplasts is feasable which led to the development of efficient transformation procedures. In view of the current data, the isolation of useful mutants at the cellular level probably will be of limited value in the genetic improvement of tomato. Protoplast fusion may lead to novel combinations of organelle and nuclear DNA (cybrids), whereas this technique also provides a means of introducing genetic information from alien species into tomato. Important developments have come from molecular approaches. Following the construction of an RFLP map, these RFLP markers can be used in tomato to tag quantitative traits bred in from related species. Both RFLP's and transposons are in the process of being used to clone desired genes for which no gene products are known. Cloned genes can be introduced and potentially improve specific properties of tomato especially those controlled by single genes. Recent results suggest that, in principle, phenotypic mutants can be created for cloned and characterized genes and will prove their value in further improving the cultivated tomato.

Case-mix and the use of control charts in monitoring mortality rates after coronary artery bypass

BACKGROUND: There is debate about the role of crude mortality rates and case-mix adjusted mortality rates in monitoring the outcomes of treatment. In the context of quality improvement a key purpose of monitoring is to identify special cause variation as this type of variation should be investigated to identify possible causes. This paper investigates agreement between the identification of special cause variation in risk adjusted and observed hospital specific mortality rates after coronary artery bypass grafting in New York hospitals. METHODS: Coronary artery bypass grafting mortality rates between 1994 and 2003 were obtained from the New York State Department of Health's cardiovascular reports for 41 hospitals. Cross-sectional control charts of crude (observed) and risk adjusted mortality rates were produced for each year. Special cause variation was defined as a data point beyond the 99.9% probability limits: hospitals showing special cause variation were identified for each year. Longitudinal control charts of crude (observed) and risk adjusted mortality rates were produced for each hospital with data for all ten years (n = 27). Special cause variation was defined as a data point beyond 99.9% probability limits, two out of three consecutive data points beyond 95% probability limits (two standard deviations from the mean) or a run of five consecutive points on one side of the mean. Years showing special cause variation in mortality were identified for each hospital. Cohen's Kappa was calculated for agreement between special causes identified in crude and risk-adjusted control charts. RESULTS: In cross sectional analysis the Cohen's Kappa was 0.54 (95% confidence interval: 0.28 to 0.78), indicating moderate agreement between the crude and risk-adjusted control charts with sensitivity 0.4 (95% confidence interval 0.17–0.69) and specificity 0.98 (95% confidence interval: 0.95–0.99). In longitudinal analysis, the Cohen's Kappa was 0.61 (95% confidence interval: 0.39 to 0.83) indicating good agreement between the tests with sensitivity 0.63 (95% confidence interval: 0.39–0.82) and specificity 0.98 (95% confidence interval: 0.96 to 0.99). CONCLUSION: There is moderate-good agreement between signals of special cause variation between observed and risk-adjusted mortality. Analysis of observed hospital specific CABG mortality over time and with other hospitals appears to be useful in identifying special causes of variation. Case-mix adjustment may not be essential for longitudinal monitoring of outcomes using control charts

A multiplicative hazard regression model to assess the risk of disease transmission at hospital during community epidemics

<p>Abstract</p> <p>Background</p> <p>During community epidemics, infections may be imported within hospital and transmitted to hospitalized patients. Hospital outbreaks of communicable diseases have been increasingly reported during the last decades and have had significant consequences in terms of patient morbidity, mortality, and associated costs. Quantitative studies are thus needed to estimate the risks of communicable diseases among hospital patients, taking into account the epidemiological process outside, hospital and host-related risk factors of infection and the role of other patients and healthcare workers as sources of infection.</p> <p>Methods</p> <p>We propose a multiplicative hazard regression model to analyze the risk of acquiring a communicable disease by patients at hospital. This model derives from epidemiological data on communicable disease epidemics in the community, hospital ward, patient susceptibility to infection, and exposure of patients to infection at hospital. The model estimates the relative effect of each of these factors on a patient's risk of communicable disease.</p> <p>Results</p> <p>Using individual data on patients and health care workers in a teaching hospital during the 2004-2005 influenza season in Lyon (France), we show the ability of the model to assess the risk of influenza-like illness among hospitalized patients. The significant effects on the risk of influenza-like illness were those of old age, exposure to infectious patients or health care workers, and a stay in a medical care unit.</p> <p>Conclusions</p> <p>The proposed multiplicative hazard regression model could be an interesting epidemiological tool to quantify the risk of communicable disease at hospital during community epidemics and the uncertainty inherent in such quantification. Furthermore, key epidemiological, environmental, host, or exposure factors that influence this risk can be identified.</p

Comparison of Methods to Correct Survival Estimates and Survival Regression Analysis on a Large HIV African Cohort

The evaluation of HIV treatment programs is generally based on an estimation of survival among patients receiving antiretroviral treatment (ART). In large HIV programs, loss to follow-up (LFU) rates remain high despite active patient tracing, which is likely to bias survival estimates and survival regression analyses