Defining failed induction of labor

BACKGROUND: While there are well-accepted standards for the diagnosis of arrested active-phase labor, the definition of a "failed" induction of labor remains less certain. One approach to diagnosing a failed induction is based on the duration of the latent phase. However, a standard for the minimum duration that the latent phase of a labor induction should continue, absent acute maternal or fetal indications for cesarean delivery, remains lacking. OBJECTIVE: The objective of this study was to determine the frequency of adverse maternal and perinatal outcomes as a function of the duration of the latent phase among nulliparous women undergoing labor induction. METHODS: This study is based on data from an obstetric cohort of women delivering at 25 U.S. hospitals from 2008-2011. Nulliparous women who had a term singleton gestation in the cephalic presentation were eligible for this analysis if they underwent a labor induction. Consistent with prior studies, the latent phase was determined to begin once cervical ripening had ended, oxytocin was initiated and rupture of membranes (ROM) had occurred, and was determined to end once 5 cm dilation was achieved. The frequencies of cesarean delivery, as well as of adverse maternal (e.g., cesarean delivery, postpartum hemorrhage, chorioamnionitis) and perinatal outcomes (e.g., a composite frequency of either seizures, sepsis, bone or nerve injury, encephalopathy, or death), were compared as a function of the duration of the latent phase (analyzed with time both as a continuous measure and categorized in 3-hour increments). RESULTS: A total of 10,677 women were available for analysis. In the vast majority (96.4%) of women, the active phase had been reached by 15 hours. The longer the duration of a woman's latent phase, the greater her chance of ultimately undergoing a cesarean delivery (P<0.001, for time both as a continuous and categorical independent variable), although more than forty percent of women whose latent phase lasted for 18 or more hours still had a vaginal delivery. Several maternal morbidities, such as postpartum hemorrhage (P < 0.001) and chorioamnionitis (P < 0.001), increased in frequency as the length of latent phase increased. Conversely, the frequencies of most adverse perinatal outcomes were statistically stable over time. CONCLUSION: The large majority of women undergoing labor induction will have entered the active phase by 15 hours after oxytocin has started and rupture of membranes has occurred. Maternal adverse outcomes become statistically more frequent with greater time in the latent phase, although the absolute increase in frequency is relatively small. These data suggest that cesarean delivery should not be undertaken during the latent phase prior to at least 15 hours after oxytocin and rupture of membranes have occurred. The decision to continue labor beyond this point should be individualized, and may take into account factors such as other evidence of labor progress

Preterm neonatal morbidity and mortality by gestational age: a contemporary cohort

Although preterm birth less than 37 weeks gestation is the leading cause of neonatal morbidity and mortality in the United States, the majority of data regarding preterm neonatal outcomes come from older studies, and many reports have been limited to only very preterm neonates. Delineation of neonatal outcomes by delivery gestational age is needed to further clarify the continuum of mortality and morbidity frequencies among preterm neonates

Ocean FAIR Data Services

Well-founded data management systems are of vital importance for ocean observing systems as they ensure that essential data are not only collected but also retained and made accessible for analysis and application by current and future users. Effective data management requires collaboration across activities including observations, metadata and data assembly, quality assurance and control (QA/QC), and data publication that enables local and interoperable discovery and access and secures archiving that guarantees long-term preservation. To achieve this, data should be findable, accessible, interoperable, and reusable (FAIR). Here, we outline how these principles apply to ocean data and illustrate them with a few examples. In recent decades, ocean data managers, in close collaboration with international organizations, have played an active role in the improvement of environmental data standardization, accessibility, and interoperability through different projects, enhancing access to observation data at all stages of the data life cycle and fostering the development of integrated services targeted to research, regulatory, and operational users. As ocean observing systems evolve and an increasing number of autonomous platforms and sensors are deployed, the volume and variety of data increase dramatically. For instance, there are more than 70 data catalogs that contain metadata records for the polar oceans, a situation that makes comprehensive data discovery beyond the capacity of most researchers. To better serve research, operational, and commercial users, more efficient turnaround of quality data in known formats and made available through Web services is necessary. In particular, automation of data workflows will be critical to reduce friction throughout the data value chain. Adhering to the FAIR principles with free, timely, and unrestricted access to ocean observation data is beneficial for the originators, has obvious benefits for users, and is an essential foundation for the development of new services made possible with big data technologies

Shading Response of Solanaceous and Amaranthaceous Weeds in Soybean

The ability of emerged seedlings of apple of Peru [Nicandra physalodes (L.) Gaertn], cutleaf groundcherry (Physalis angulata L.), eastern black nightshade (Solanum ptycanthum Dunal), and two biotypes of Palmer amaranth [Amaranthus palmeri (S.) Wats.] to withstand canopy shading under 25- and 45-cm soybean [Glycine max (L.) Merr.] height was investigated in the greenhouse. Weeds and soybean were grown in separate pots to prevent competition for water and nutrients and to eliminate the possibility of chemical interactions through allelopathy. Weed dry weight was reduced 40 to 81% when planted with the 45-cm-tall soybean but no more than 14% when planted with 25-cm-tall soybean. Cutleaf groundcherry and eastern black nightshade biomass were affected less by soybean than Palmer amaranth biotypes and apple of Peru when grown with 45-cm soybean but weed biomass reduction did not differ among weed species in the soybean 25-cm shade

Influence of Distance from Source and Height Above Canopy on Palmer Amaranth Pollen Distribution

The spread of glyphosate-resistant Palmer amaranth (Amaranthus palmeri S. Wats) germplasm through pollination makes managing this weed challenging. The objective of this study was to determine Palmer amaranth pollen dispersal under prevailing field conditions at various heights above cotton (Gossypium hirsutum L.) or soybean [Glycine max (L.) Merr.] canopies within 50 m of pollen-source plants. On four days in 2008 and 15 days in 2009, Palmer amaranth pollen was collected in a compass rose array of traps at the top of the crop canopy or 1, 2, or 3 m above the canopy at distances of 1, 2, 10, 25, and 50 m from a densely planted pollen source. Pollen was found at the outermost extremities of the trap array (50 m laterally and 3 m above the crop canopy) indicating that Palmer amaranth pollen dispersion likely extend beyond the area considered in this study. Eighty-two percent of pollen captured was within 2 m of the source while 5 to 7% was captured 10 to 50 m from the source. Seventy-five percent of pollen was captured at canopy level (0.75 m above soil surface) with 10% or less at 1, 2, and 3 m above the canopy. Data did not consistently correlate with relative humidity, dew point, ambient temperature, prevailing wind direction, or wind speed

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

Impacts of multiple stressors on freshwater biota across spatial scales and ecosystems

Climate and land-use change drive a suite of stressors that shape ecosystems and interact to yield complex ecological responses (that is, additive, antagonistic and synergistic effects). We know little about the spatial scales relevant for the outcomes of such interactions and little about effect sizes. These knowledge gaps need to be filled to underpin future land management decisions or climate mitigation interventions for protecting and restoring freshwater ecosystems. This study combines data across scales from 33 mesocosm experiments with those from 14 river basins and 22 cross-basin studies in Europe, producing 174 combinations of paired-stressor effects on a biological response variable. Generalized linear models showed that only one of the two stressors had a significant effect in 39% of the analysed cases, 28% of the paired-stressor combinations resulted in additive effects and 33% resulted in interactive (antagonistic, synergistic, opposing or reversal) effects. For lakes, the frequencies of additive and interactive effects were similar for all spatial scales addressed, while for rivers these frequencies increased with scale. Nutrient enrichment was the overriding stressor for lakes, with effects generally exceeding those of secondary stressors. For rivers, the effects of nutrient enrichment were dependent on the specific stressor combination and biological response variable. These results vindicate the traditional focus of lake restoration and management on nutrient stress, while highlighting that river management requires more bespoke management solutions

A randomized, double-blind, placebo-controlled trial of antidepressants in Parkinson disease

OBJECTIVE: To evaluate the efficacy and safety of a selective serotonin reuptake inhibitor (SSRI) and a serotonin and norepinephrine reuptake inhibitor (SNRI) in the treatment of depression in Parkinson disease (PD). METHODS: A total of 115 subjects with PD were enrolled at 20 sites. Subjects were randomized to receive an SSRI (paroxetine; n = 42), an SNRI (venlafaxine extended release [XR]; n = 34), or placebo (n = 39). Subjects met DSM-IV criteria for a depressive disorder, or operationally defined subsyndromal depression, and scored >12 on the first 17 items of the Hamilton Rating Scale for Depression (HAM-D). Subjects were followed for 12 weeks (6-week dosage adjustment, 6-week maintenance). Maximum daily dosages were 40 mg for paroxetine and 225 mg for venlafaxine XR. The primary outcome measure was change in the HAM-D score from baseline to week 12. RESULTS: Treatment effects (relative to placebo), expressed as mean 12-week reductions in HAM-D score, were 6.2 points (97.5% confidence interval [CI] 2.2 to 10.3, p = 0.0007) in the paroxetine group and 4.2 points (97.5% CI 0.1 to 8.4, p = 0.02) in the venlafaxine XR group. No treatment effects were seen on motor function. CONCLUSIONS: Both paroxetine and venlafaxine XR significantly improved depression in subjects with PD. Both medications were generally safe and well tolerated and did not worsen motor function. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that paroxetine and venlafaxine XR are effective in treating depression in patients with PD