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Traditional surveillance of adverse infant outcomes following maternal medication exposures relies on pregnancy exposure registries, which are often underpowered. We characterize the statistical power of TreeScan, a data mining tool, to identify potential signals in the setting of perinatal medication exposures and infant outcomes.We used empirical data to inform background incidence of major congenital malformations and other birth conditions. Statistical power was calculated using two probability models compatible with TreeScan, Bernoulli and Poisson, while varying the sample size, magnitude of the risk increase, and incidence of a specified outcome. We also simulated larger referent to exposure matching ratios when using the Bernoulli model in the setting of fixed N:1 propensity score matching. Finally, we assessed the impact of outcome misclassification on power.The Poisson model demonstrated greater power to detect signals than the Bernoulli model across all scenarios and suggested a sample size of 4,000 exposed pregnancies is needed to detect a twofold increase in risk of a common outcome (approximately 8 per 1,000) with 85% power. Increasing the fixed matching ratio with the Bernoulli model did not reliably increase power. An outcome definition with high sensitivity is expected to have somewhat greater power to detect signals than an outcome definition with high positive predictive value.Use of the Poisson model with an outcome definition that prioritizes sensitivity may be optimal for signal detection. TreeScan is a viable method for surveillance of adverse infant outcomes following maternal medication use.

It is a priority of the US Food and Drug Administration (FDA) to monitor the safety of medications used during pregnancy. Pregnancy exposure registries and cohort studies utilizing electronic health record data are primary sources of information but are limited by small sample sizes and limited outcome assessment. TreeScan™, a statistical data mining tool, can be applied within the FDA Sentinel System to simultaneously identify multiple potential adverse neonatal and infant outcomes after maternal medication exposure.We implemented TreeScan using the Sentinel analytic tools in a cohort of linked live birth deliveries and infants nested in the IBM MarketScan® Research Database. As a case study, we compared first trimester fluoroquinolone use and cephalosporin use. We used the Bernoulli and Poisson TreeScan statistics with compatible propensity score-based study designs for confounding control (matching and stratification) and used multiple propensity score models with various strategies for confounding control to inform best practices. We developed a hierarchical outcome tree including major congenital malformations and outcomes of gestational length and birth weight.1,791 fluoroquinolone-exposed and 8,739 cephalosporin-exposed mother-infant pairs were eligible for analysis. Both TreeScan analysis methods resulted in single alerts that were deemed to be due to uncontrolled confounding or otherwise not warranting follow-up.In this implementation of TreeScan using Sentinel analytic tools, we did not observe any new safety signals for fluoroquinolone use in the first trimester. TreeScan, with tailored or high-dimensional propensity scores for confounding control, is a valuable tool in addition to current safety surveillance methods for medications used during pregnancy. This article is protected by copyright. All rights reserved.

Current algorithms to evaluate gestational age (GA) during pregnancy rely on hospital coding at delivery and are not applicable to non-live births. We developed an algorithm using fertility procedures and fertility tests, without relying on delivery coding, to develop a novel GA algorithm in live-births and stillbirths.Three pregnancy cohorts were identified from 16 health-plans in the Sentinel System: 1) hospital admissions for live-birth, 2) hospital admissions for stillbirth, and 3) medical chart-confirmed stillbirths. Fertility procedures and prenatal tests, recommended within specific GA windows were evaluated for inclusion in our GA algorithm. Our GA algorithm was developed against a validated delivery-based GA algorithm in live-births, implemented within a sample of chart-confirmed stillbirths, and compared to national estimates of GA at stillbirth.Our algorithm, including fertility procedures and 11 prenatal tests, assigned a GA at delivery to 97.9% of live-births and 92.6% of stillbirths. For live-births (n = 4 701 207), it estimated GA within 2 weeks of a reference delivery-based GA algorithm in 82.5% of pregnancies, with a mean difference of 3.7 days. In chart-confirmed stillbirths (n = 49), it estimated GA within 2 weeks of the clinically recorded GA at delivery for 80% of pregnancies, with a mean difference of 11.1 days. Implementation of the algorithm in a cohort of stillbirths (n = 40 484) had an increased percentage of deliveries after 36 weeks compared to national estimates.In a population of primarily commercially-insured pregnant women, fertility procedures and prenatal tests can estimate GA with sufficient sensitivity and accuracy for utility in pregnancy studies.

We sought to determine whether machine learning and natural language processing (NLP) applied to electronic medical records could improve performance of automated health-care claims-based algorithms to identify anaphylaxis events using data on 516 patients with outpatient, emergency department, or inpatient anaphylaxis diagnosis codes during 2015–2019 in 2 integrated health-care institutions in the Northwest United States. We used one site’s manually reviewed gold-standard outcomes data for model development and the other’s for external validation based on cross-validated area under the receiver operating characteristic curve (AUC), positive predictive value (PPV), and sensitivity. In the development site 154 (64%) of 239 potential events met adjudication criteria for anaphylaxis compared with 180 (65%) of 277 in the validation site. Logistic regression models using only structured claims data achieved a cross-validated AUC of 0.58 (95% CI: 0.54, 0.63). Machine learning improved cross-validated AUC to 0.62 (0.58, 0.66); incorporating NLP-derived covariates further increased cross-validated AUCs to 0.70 (0.66, 0.75) in development and 0.67 (0.63, 0.71) in external validation data. A classification threshold with cross-validated PPV of 79% and cross-validated sensitivity of 66% in development data had cross-validated PPV of 78% and cross-validated sensitivity of 56% in external data. Machine learning and NLP-derived data improved identification of validated anaphylaxis events.

Purpose To develop and validate an International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM)-based algorithm to identify cases of stillbirth using electronic healthcare data. Methods We conducted a retrospective study using claims data from three Data Partners (healthcare systems and insurers) in the Sentinel Distributed Database. Algorithms were developed using ICD-10-CM diagnosis codes to identify potential stillbirths among females aged 12-55 years between July 2016 and June 2018. A random sample of medical charts (N = 169) was identified for chart abstraction and adjudication. Two physician adjudicators reviewed potential cases to determine whether a stillbirth event was definite/probable, the date of the event, and the gestational age at delivery. Positive predictive values (PPVs) were calculated for the algorithms. Among confirmed cases, agreement between the claims data and medical charts was determined for the outcome date and gestational age at stillbirth. Results Of the 110 potential cases identified, adjudicators determined that 54 were stillbirth events. Criteria for the algorithm with the highest PPV (82.5%; 95% CI, 70.9%-91.0%) included the presence of a diagnosis code indicating gestational age ≥ 20 weeks and occurrence of either >1 stillbirth-related code or no other pregnancy outcome code (i.e., livebirth, spontaneous abortion, induced abortion) recorded on the index date. We found ≥90% agreement within 7 days between the claims data and medical charts for both the outcome date and gestational age at stillbirth. Conclusions Our results suggest that electronic healthcare data may be useful for signal detection of medical product exposures potentially associated with stillbirth. This article is protected by copyright. All rights reserved.

Camelina (Camelina sativa [L.] Crtz.) is an oilseed crop of the Brassicaceae family. It represents revived crops, which was reintroduced to contribute in diversification of the used crops. Field trials were set in a total of five different locations across four years in which in Serbia (2015/2016, 2016/2017, 2017/2018, 2018/2019) and in Austria (2016/2017). In all samples, 12 different environments were processed. Analysis of the distributions of environments for oil content, which mirrored protein content, using the PCA analysis, shows a statistical significance of the first two main components, which participated in the phenotypic variation with a larger amount to additive component and with both axes having a statistically significant effect on the interaction. The first two main components jointly explained more than 80% of the variation in two traits. The statistical significance of the remainder is a consequence of an agronomically explicable variation. The genotypes NS Zlatka and NS Slatka, used in this study, come from elite breeding material that is engineered to provide a consistent return to the producer regardless of the amount of money invested in primary agricultural production. Incorporating these varieties into the crop rotation would broaden the range of species available in Balkan agriculture.

Background Cutaneous small vessel vasculitis (CSVV) has been reported after exposure to direct oral anticoagulants (DOACs), such as dabigatran, rivaroxaban, apixaban, and edoxaban. Objective We used the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS) to describe clinical characteristics associated with CSVV among DOAC-exposed patients. Furthermore, we characterized this signal in the Sentinel System to relate the clinical data from the individual FAERS cases to population-based electronic healthcare data. Methods We queried FAERS for all cases of CSVV associated with DOACs from U.S. approval date of each DOAC through March 16, 2018. Within the Sentinel System, we identified incident CSVV cases using ICD-9 and ICD-10 diagnosis codes among adults aged ≥ 30 years who received a DOAC in the prior 90 days between January 1, 2010, and June 30, 2018. We excluded patients with evidence of select autoimmune diagnoses in the 183 days prior to their CSVV diagnoses and reported patient characteristics in the 183-day period prior to CSVV diagnoses. Results In FAERS, we identified 50 cases of CSVV reported with rivaroxaban (n=26), apixaban (n=14), dabigatran (n=9), and edoxaban (n=1). Approximately 50% of the cases reported time to onset within 10 days after DOAC exposure. When specified, the predominant type of CSVV reported was leukocytoclastic vasculitis (n=31), followed by Henoch-Schonlein purpura (n=4). Hospitalization occurred in most of the cases (n=37). Switching of the offending agent after the development of CSVV was reported (n=26). Three rivaroxaban (n=3) cases and one dabigatran case (n=1) reported positive rechallenge. In the Sentinel system, we identified 3659 CSVV cases with prior DOAC exposure, with 85% of events occurring within 10 days. Conclusions The assessment of FAERS cases, combined with the temporal clustering of the Sentinel System cases suggest a possible causal relationship of DOACs and CSVV. Future efforts should characterize the risk of CSVV among the various DOAC users.

The tree-based scan statistic (TreeScan; Martin Kulldorff, Harvard Medical School, Boston, Massachusetts) is a data-mining method that adjusts for multiple testing of correlated hypotheses when screening thousands of potential adverse events for signal identification. Simulation has demonstrated the promise of TreeScan with a propensity score (PS)-matched cohort design. However, it is unclear which variables to include in a PS for applied signal identification studies to simultaneously adjust for confounding across potential outcomes. We selected 4 pairs of medications with well-understood safety profiles. For each pair, we evaluated 5 candidate PSs with different combinations of 1) predefined general covariates (comorbidity, frailty, utilization), 2) empirically selected (data-driven) covariates, and 3) covariates tailored to the drug pair. For each pair, statistical alerting patterns were similar with alternative PSs (≤11 alerts in 7,996 outcomes scanned). Inclusion of covariates tailored to exposure did not appreciably affect screening results. Inclusion of empirically selected covariates can provide better proxy coverage for confounders but can also decrease statistical power. Unlike tailored covariates, empirical and predefined general covariates can be applied “out of the box” for signal identification. The choice of PS depends on the level of concern about residual confounding versus loss of power. Potential signals should be followed by pharmacoepidemiologic assessment where confounding control is tailored to the specific outcome(s) under investigation.

BACKGROUND The US Food and Drug Administration increasingly uses administrative databases to conduct surveillance of medications used during pregnancy. To assess adverse fetal effects, administrative records must be linked between the mother and infant. The Sentinel Initiative's Mother-Infant Linkage Table provides a large cohort of linked deliveries from national, regional, and public insurance claims in the United States for the US Food and Drug Administration to conduct surveillance. OBJECTIVE This study aimed to describe baseline health conditions and prescription medication use during pregnancy in cohorts of women with a live-birth delivery linked and not linked to an infant. STUDY DESIGN Live-birth deliveries in women aged 10 to 54 years with at least 391 days of medical and drug coverage before delivery were identified in the Sentinel Mother-Infant Linkage Table from 2000 to 2019. Two cohorts were created for analysis: deliveries linked to infant records (linked deliveries, n=2,320,805) and deliveries unable to be linked to an infant (not-linked deliveries, n=504,785). Baseline health conditions, pregnancy history, healthcare utilization, and pregnancy conditions were defined using International Classification of Diseases, Ninth Revision, and International Classification of Diseases, Tenth Revision, diagnosis and procedure codes. Medication exposure was identified in a 90-day prepregnancy period and in each trimester. RESULTS Few notable differences were observed between the linked and not-linked deliveries except for maternal age and preterm birth; the not-linked cohort was 3.4 years younger on average and more likely to have a preterm delivery. At baseline among the linked deliveries, the most common conditions were depression and anxiety (5.2% each), acquired hypothyroidism (5.0%), pain conditions (3.9%), and asthma (2.8%). Among linked deliveries, 6.9% had evidence of gestational diabetes mellitus, 3.9% had gestational hypertension, and 4.5% had preeclampsia or eclampsia. The most commonly used medications during pregnancy in the linked deliveries were antibacterials (41.6%) and antiemetics (21.5%); similar medication use patterns were observed in the not-linked cohort. Age trends were observed for some medication groups; anti-infectives, pain medications, and antiemetics were more common in younger mothers, whereas endocrine medications were more common in older mothers. CONCLUSION Similarities between the linked and not-linked cohorts suggested that the ability to link mother and infant records is not influenced by maternal health status. In the linked cohort, the prevalence of specific pregnancy complications and medication use were similar to previously reported national estimates. Some baseline comorbidities, such as obesity and smoking, may be underestimated in the Sentinel Mother-Infant Linkage.

The creation of sunflower hybrids tolerant to tribenuron-methyl enabled the use of wider palette of herbicides to control effectively weeds during the growing season. Moreover, thanks to this tolerance, chemical control of broad-leaves weeds in sunflower, especially Cirsium arvense, is more efficient. The Institute of Field and Vegetable Crops offers four new hybrids tolerant to tribenuron-methyl: NS SUMO SUN, NS SUMO STAR, NS SUMO SjAj and NS SUMO SOL, released in 2016. Hybrids belong to early and medium-early maturity groups; have high yield potential and high oil content. They are adapted for cultivation in different environmental conditions. All hybrids are resistant to broomrape (Orobanche cumana Wallr) races from A-E and have a high level of tolerance to Phomopsis, white rot (Sclerotinia sclorotiorum), rust (Puccinia helianthi) and others. The paper presents the results of seed and oil yield from the official trials of the Department of variety registration within the Ministry of Agriculture and Environmental Protection of the Republic of Serbia. Stvaranjem hibrida suncokreta tolerantnih na sulfonil-ureu tj. tribenuron-metil omogućeno je korišćenje šire palete herbicida za efikasno suzbijanje korova u toku vegetacionog perioda. Zahvaljujući ovoj tolerantnosti znatno je olakšana borba protiv širokolisnih korova, posebno palamide, u usevu suncokreta. U ponudi Instituta za ratarstvo i povrtarstvo su četiri nova hibrida NS SUMO SUN, NS SUMO STAR, NS SUMO SjAj i NS SUMO SOL, registrovanih u 2016. godini. Hibridi priradaju grupi ranih i srednje ranih hibrida suncokreta, pokazuju visok potencijal rodnosti i imaju visok sadržaj ulja u semenu. Prilagođeni su gajenju u različitim agroekološkim uslovima jer imaju široku adaptabilnost na uslove proizvodnje. Svi hibridi imaju otpornost prema volovodu (Orobanche cumana Wallr), rase od A-E i visok stepen tolerantnosti prema Phomopsis-u, beloj truleži (Sclerotinia sclorotiorum), rđi (Puccinia helianthi) i dr. U radu su prikazani rezultati prinosa semena i ulja komisijskih ogleda Odeljenja za priznavanje sorti Ministarstva poljoprivrede i zaštite životne sredine Republike Srbije.

The increased production of oilseed rape (Brassica napus L.) is evident on a global scale, but also in Serbia in the last decade. Rapeseed is used primarily for vegetable oil and processing industry, but also as a source of protein for animal feed and green manure. Following the cultivation of varieties, breeding and cultivation of hybrid rapeseed started in the 1990's, to take advantage of heterosis in F1 generation, while protecting the breeder's rights during seed commercialization. The breeding of hybrid oilseed rape requires high quality starting material (lines with good combining abilities) for introduction of male sterility. Ogura sterility system is primarily used at the Institute of Field and Vegetable Crops, Novi Sad, Serbia. To use this system, separate lines are modified with genes for cytoplasmic male sterility (cms female line - mother line) and restoration of fertility (Rf male lines - father line). In order to maintain the sterility of the mother line it is necessary to produce a maintainer line of cytoplasmic male sterility. Creation of these lines and hybrids at the Institute of Field and Vegetable Crops was successfully monitored with intense use of cytogenetic laboratory methods. The structure and vitality of pollen, including different phases during meiosis were checked so that cms stability was confirmed during the introduction of these genes into different lines. Rapeseed breeding program in Serbia resulted in numerous varieties through collaboration of researchers engaged in breeding and genetics of this plant species. So far, in addition to 12 varieties of winter rapeseed and two varieties of spring rapeseed, a new hybrid of winter rapeseed NS Ras was registered in Serbia. NS Ras is an early-maturing hybrid characterized by high seed yield and oil content. Average yield of NS Ras for two seasons and three sites was 4256 kg ha-1 of seed and 1704 kg ha-1 of oil. Three promising winter rapeseed hybrids are in the process of registration in the Republic of Serbia and one in the EU. While addressing many challenges in breeding, especially resistance to biotic and abiotic stress, in addition to classical breeding, it is necessary to apply the cytogenetic and molecular analysis to increase the efficiency of producing competitive rapeseed genotypes. Porast proizvodnje uljane repice (Brassica napus L.) evidentan je u svetskim razmerama, a poslednje decenije i u Srbiji. Uljana repica se koristi prvenstveno za dobijanje ulja za ishranu i prerađivačku industriju, ali i kao izvor proteina za ishranu domaćih životinja i zelenišno đubrivo. Nakon gajenja sorti počelo se 90-ih godina prošlog veka sa oplemenjivanjem i gajenjem hibrida uljane repice, kako bi se iskoristio efekat heterozisa u F1 generaciji, uz istovremenu zaštitu prava oplemenjivača prilikom prometa semena. U oplemenjivanju hibrida uljane repice neophodno je u kvalitetan početni materijal (linije dobrih kombinacionih sposobnosti) uneti svojstvo muške sterilnosti. U Institutu za ratarstvo i povrtarstvo, Novi Sad koristi se prvenstveno Ogura sistem sterilnosti. Korišćenje ovog sistema obuhvata unošenje citoplazmatske muške sterilnosti (cms linije majke) i gena za restauraciju fertilnosti (Rf linije oca). Da bi se sterilnost linije majke održala neophodno je proizvesti i liniju održivača citoplazmatske muške sterilnosti. Prilikom stvaranja ovih linija, hibrida i u semenskoj proizvodnji u Institutu za ratarstvo i povrtarstvo intenzivno i vrlo uspešno su korišćene citogenetske laboratorijske metode. Analizirana je građa i vitalnost polena, kao i različite faze tokom mejoze i utvrđena stabilnost svojstava prilikom unošenja ovih gena u različite linije. U oplemenjivanju uljane repice u Srbiji postignuti su značajni rezultati kroz saradnju istraživača koji se bave genetikom i oplemenjivanjem ove biljne vrste. Do sada je pored 12 sorti ozime i dve sorte jare repice u Srbiji registrovan hibrid ozime uljane repice NS Ras. NS Ras je ranostasni hibrid koji se odlikuje visokim prinosom zrna i ulja. Prosečan prinos u dve sezone za tri lokaliteta je bio 4256 kg ha-1 semena i 1704 kg ha-1 ulja. Još tri perspektivna ozima hibrida uljane repice nalaze se u postupku registracije u republici Srbiji i jedan u EU. U rešavanju mnogih izazova u oplemenjivanju, prvenstveno otpornosti na biotski i abiotski stres, pored klasičnog oplemenjivanja neophodno je primeniti, citogenetske i molekularne analize za povećanje efikasnosti oplemenjivanja uljane repice.

Serbo-Croatian is a language with a dual system of relative clause formation. By the test of obedience to subjacency, sto and koji relatives are formed by successive cyclic movement, whereas za koga relatives are formed by pronominal linkage. Elicited production and comprehension experiments were conducted with preschool children. We interpret the results as evidence that children initially treat sto relatives as nonmovement relatives, contrary to the facts of the adult grammar. Za koga relatives are mastered by only a small number of children. We discuss our results in the context of the cross-linguistic typology of relative clauses and previous studies of the acquisition of relative clauses, arguing that a nonmovement analysis of relatives is unmarked for relative clause formation (in comparison to wh-question formation) and that a nonmovement analysis may represent a common first stage in the acquisition of relative clauses.

The difference between the two mechanisms for wh-question binding (i.e., sucessive cyclic movement and pronominal binding) is characterized, inter alia, by the presence of island constraints (subjacency effects) in movement but not pronominal constructions. Using experimental data from child and adult speakers of Akan (pronominal binding) and Serbo-Croatian (movement and pronominal binding), it is argued that: 1) Previous experiments on English-speaking children’s knowledge of the block on extraction from within adjuncts do not positively support early use of a movement grammar in English; 2) Apparent sensitivity to movement constraints may arise as a consequence of processing preferences; 3) The evidence to date is nonetheless compatible with movement as the default hypothesis for wh-binding; 4) The parsing preference for non-island locations for a wh-word may have utility for the learner, helping to correct overly permissive grammars.