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implementers to focus on patients who have these characteristics in order to prevent ART treatment failure.

The systematic review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO), registration number 2019 CRD42019136538.

The systematic review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO), registration number 2019 CRD42019136538.

Children born extremely preterm are at heightened risk for intellectual and social impairment, including Autism Spectrum Disorder (ASD). There is increasing evidence for a key role of the placenta in prenatal developmental programming, suggesting that the placenta may, in part, contribute to origins of neurodevelopmental outcomes.

We examined associations between placental transcriptomic and epigenomic profiles and assessed their ability to predict intellectual and social impairment at age 10years in 379 children from the Extremely Low Gestational Age Newborn (ELGAN) cohort. Assessment of intellectual ability (IQ) and social function was completed with the Differential Ability Scales-II and Social Responsiveness Scale (SRS), respectively. Examining IQ and SRS allows for studying ASD risk beyond the diagnostic criteria, as IQ and SRS are continuous measures strongly correlated with ASD. Genome-wide mRNA, CpG methylation and miRNA were assayeds with the Illumina Hiseq 2500, HTG EdgeSeq miRNA Whole Transcripon of predictive models, though the sample size (N = 49)and the scope of the availableout-sample placentaldataset are limited. Further validation of the models is merited.

Aggregating information from biomarkers within and among molecular data types improves prediction of complex traits like social and intellectual ability in children born extremely preterm, suggesting that traits within the placenta-brain axis may be omnigenic.

Aggregating information from biomarkers within and among molecular data types improves prediction of complex traits like social and intellectual ability in children born extremely preterm, suggesting that traits within the placenta-brain axis may be omnigenic.

Despite existing research on text mining and machine learning for title and abstract screening, the role of machine learning within systematic literature reviews (SLRs) for health technology assessment (HTA) remains unclear given lack of extensive testing and of guidance from HTA agencies. We sought to address two knowledge gaps to extend ML algorithms to provide a reason for exclusion-to align with current practices-and to determine optimal parameter settings for feature-set generation and ML algorithms.

We used abstract and full-text selection data from five large SLRs (n = 3089 to 12,769 abstracts) across a variety of disease areas. Each SLR was split into training and test sets. We developed a multi-step algorithm to categorize each citation into the following categories included; excluded for each PICOS criterion; or unclassified. We used a bag-of-words approach for feature-set generation and compared machine learning algorithms using support vector machines (SVMs), naïve Bayes (NB), and bagged classecisions were used.

ML algorithms can improve the efficiency of the SLR process and the proposed algorithms could reduce the workload of a second reviewer by identifying exclusions with a relevant PICOS reason, thus aligning with HTA guidance. Downsampling can be used to improve study selection, and improvements using full-text exclusions have implications for a learn-as-you-go approach.

ML algorithms can improve the efficiency of the SLR process and the proposed algorithms could reduce the workload of a second reviewer by identifying exclusions with a relevant PICOS reason, thus aligning with HTA guidance. Downsampling can be used to improve study selection, and improvements using full-text exclusions have implications for a learn-as-you-go approach.

Most cardiac surgery patients undergo median sternotomy during open heart surgery. Sternotomy healing is an arduous, very complex, and multifactorial process dependent on many independent factors affecting the sternum and the surrounding soft tissues. Complication rates for median sternotomy range from 0.5 to 5%; however, mortality rates from complications are very variable at 7-80%. Low calcidiol concentration below 80 nmol/L results in calcium absorptive impairment and carries a risk of bone loss, which is considered as a risk factor in the sternotomy healing process. The primary objective of this clinical trial is to compare the incidence of all postoperative sternotomy healing complications in two parallel patient groups administered cholecalciferol or placebo. The secondary objectives are focused on general patient recovery process sternal bone healing grade at the end of the trial, length of hospitalization, number of days spent in the ICU, number of days spent on mechanical lung ventilation, and number of hospital readmissions for sternotomy complications.

This clinical trial is conducted as monocentric, randomized, double-blind, placebo-controlled, with planned enrollment of 600 patients over 4years, approximately 300 in the placebo arm and 300 in the treatment arm. Males and females from 18 to 95 years of age who fulfill the indication criteria for undergoing cardiac surgery with median sternotomy can be included in this clinical trial, if they meet the eligibility criteria.

REINFORCE-D is the first monocentric trial dividing patients into groups based on serum calcidiol levels, and with dosing based on serum calcidiol levels. This trial may help to open up a wider range of postoperative healing issues.

EU Clinical Trials Register, EUDRA CT No 2016-002606-39 . Registered on September 8, 2016.

EU Clinical Trials Register, EUDRA CT No 2016-002606-39 . Indisulam Registered on September 8, 2016.

Burnout is an occupational syndrome that leads to mental health problems, job turnover, and patient safety events. Those caring for critically ill patients are especially susceptible due to high patient mortality, long hours, and regular encounters with trauma and ethical issues. Interventions to prevent burnout in this population are needed. Preliminary studies suggest debriefing sessions may reduce burnout. This study aims to assess whether participation in regular debriefing can prevent burnout in intensive care unit (ICU) clinicians.

A randomized controlled trial will be conducted in two large academic medical centers. Two hundred ICU clinicians will be recruited with target enrollment of 100 physicians and 100 non-physicians (nurses, pharmacists, therapists). Participants must have worked in the ICU for the equivalent of at least 1 full time work week in the preceding 4 weeks. Enrolled subjects will be randomized to virtually attend biweekly debriefing sessions facilitated by a psychotherapist for 3 months or to a control arm without sessions.