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001, pigs P = 0.07). The interaction between light exposure and hair colour was significant in both pigs (P less then 0.01) and cattle (P less then 0.001), so light exposure reduced HCCs in porcine white hair but not black hair. In cattle, light-exposed white hair exhibited lower hair cortisol levels than control white hair or black hair. These results demonstrate that artificial light irradiation degrades hair cortisol or favours its elimination by structural changes of the hair matrix. However, this effect was only detectable in white hair, indicating that the melanin pigments in black hair absorbed radiation, thereby reducing the effects of photodegradation. Compared with other known influencing factors on HCCs, such as age and body region, the influence of light irradiation was relatively low in this in vitro experiment. However, further studies should investigate this influence under real-life animal conditions, such as outdoor and indoor housing.It remains unknown whether dairy cows with more reactive temperament produce more enteric methane (CH4) and are less bioenergetically efficient than the calmer ones. The objectives of this study were (a) to evaluate the relationship between cattle temperament assessed by traditionally used tests with energetic metabolism and enteric CH4 emissions by crossbred dairy cows; (b) to assess how cows' restlessness in respiration chambers affects energetic metabolism and enteric CH4 emissions. Temperament indicators were evaluated for 28 primiparous F1 Holstein-Gyr cows tested singly in the handling corral (entrance time, crush score, flight speed, and flight distance) and during milking (steps, kicks, defecation, rumination, and kick the milking cluster off). Cows' behaviors within respiration chambers were also recorded for each individual kept singly. Digestibility and calorimetry trials were performed to obtain energy partitioning and CH4 measures. Cows with more reactive temperament in milking (the ones that kicd be useful measures to predict animals more prone to metabolic inefficiency, which could negatively affect the sustainability of dairy systems.Hit-and-run crashes not only degrade the morality, but also result in delays of medical services provided to victims. However, class imbalance problem exists as the number of hit-and-run crashes is much smaller than that of non-hit-and-run crashes. The missing label problem also exists in the crash analysis due to reasons like data barrier such that the information hidden in the unlabelled samples has not been effectively utilised. In this paper, a cost-sensitive semi-supervised logistic regression (CS3LR) model is proposed for hit-and-run analysis, in order to tackle class-imbalanced data distribution and missing label problem, based on the crash dataset of Victorian, Australia (2013-2019). By performing label estimation with logistic regression jointly utilising both labelled and unlabelled data with pseudo labels in a well-designed cost-sensitive semi-supervised maximum likelihood framework, the proposed model can obtain an unbiased likelihood parameter for hit-and-run prediction and analysis. Comparing the experimental results of CS3LR model with two logistic regression models and seven machine learning methods, better performance of CS3LR model is demonstrated. The most significant contributing factors to hit-and-run crashes extracted by CS3LR with only 10% labelled data show a high degree of consistency with the true contributing factors obtained by the supervised cost-sensitive logistic regression with complete hit-and-run labels. The effects of class-weighted ratio and hyper-parameter λ on the performance of hit-and-run crash prediction model have also been analysed. The results can further provide recommendations and implications on the policies and counter-measures for preventing hit-and-run collisions and crimes. The methodology proposed in this paper can also be employed to analyse crash data with other types of missing labels, such as crash severity.
To evaluate the findings and compare the diagnostic yield of computed tomography (CT) versus magnetic resonance imaging (MRI) in children with bilateral sensorineural hearing loss (BSNHL).
Multi-institutional retrospective review.
Three tertiary referral centers.
A multi-institutional retrospective chart review was performed in patients under the age of 18 years with BSNHL (diagnosis codes 389.00-389.22) who underwent both CT and MRI from 2010 to 2012. An abnormal imaging finding was defined as an abnormality of the cochleovestibular or central nervous system known to directly correlate with sensorineural hearing loss. Diagnostic yield of CT versus MRI was compared by McNemar's test.
Of 2081 charts reviewed, 313 patients met inclusion criteria. The diagnostic yield of CT and MRI were 25% and 18%, respectively. Approximately one-quarter of patients had an abnormal finding on CT or MRI. The concordance rate was 92%. CT was more likely to yield an abnormal finding versus MRI (p-value=0.0001). The most common findings on CT were cochlear and semicircular canal abnormalities. On MRI, the most common findings were cochlear nerve aplasia/hypoplasia and semicircular canal abnormalities.
This study evaluates and directly compares the diagnostic yield of CT versus MRI for pediatric BSNHL. While both modalities have important and often complementary diagnostic utility, CT had superior diagnostic yield in identifying abnormalities associated with BSNHL.
This study evaluates and directly compares the diagnostic yield of CT versus MRI for pediatric BSNHL. While both modalities have important and often complementary diagnostic utility, CT had superior diagnostic yield in identifying abnormalities associated with BSNHL.
Cannabis use and cannabis use disorders are increasing in prevalence, including among pregnant women. The objective was to evaluate the association of a cannabis-related diagnosis (CRD) in pregnancy and adverse maternal and infant outcomes.
We queried an administrative birth cohort of singleton deliveries in California between 2011-2017 linked to maternal and infant hospital discharge records. We classified pregnancies with CRD from International Classification of Disease codes. We identified nicotine and other substance-related diagnoses (SRD) in the same manner. Outcomes of interest included maternal (hypertensive disorders) and infant (prematurity, small for gestational age, NICU admission, major structural malformations) adverse outcomes.
From 3,067,069 pregnancies resulting in live births, 29,112 (1.0 %) had a CRD. CRD was associated with an increased risk of all outcomes studied; the strongest risks observed were for very preterm birth (aRR 1.4, 95 % CI 1.3, 1.6) and small for gestational age (aRR 1.4, 95 % CI 1.3, 1.4). When analyzed with or without co-exposure diagnoses, CRD alone conferred increased risk for all outcomes compared to no use. The strongest effects were seen for CRD with other SRD (preterm birth aRR 2.3, 95 % CI 2.2, 2.5; very preterm birth aRR 2.6, 95 % CI 2.3, 3.0; gastrointestinal malformations aRR 2.0, 95 % CI 1.6, 2.6). The findings were generally robust to unmeasured confounding and misclassification analyses.
CRD in pregnancy was associated with increased risk of adverse maternal and infant outcomes. Providing education and effective treatment for women with a CRD during prenatal care may improve maternal and infant health.
CRD in pregnancy was associated with increased risk of adverse maternal and infant outcomes. Providing education and effective treatment for women with a CRD during prenatal care may improve maternal and infant health.
Availability of medications for opioid use disorder (MOUD) has increased during the past two decades but treatment retention and adherence remain low. This study aimed to measure the impact of out-of-pocket buprenorphine cost on treatment retention and adherence among US commercially insured patients.
Medical payment records from IBM MarketScan were analyzed for 6,439 adults age 18-64 years with commercial insurance who initiated buprenorphine treatment during January 1, 2016 to June 30, 2017. KT 474 ic50 Regression models analyzed the relationship between patients' average daily out-of-pocket buprenorphine cost and buprenorphine retention (at least 80 % days covered by buprenorphine) at three different thresholds (180, 360, and 540 days) and adherence (the number of days of buprenorphine coverage) within each retention threshold. Models controlled for patient demographic and clinical characteristics including age, sex, presence of other substance use disorders, psychiatric and pain diagnoses, and receipt of prescripent levels such costs decrease retention and adherence among commercially insured patients. Efforts to address demand-side barriers could help maximize the health and social benefits of buprenorphine-based MOUD.
National surveys are a leading method for estimating prevalence of substance use and other health-related behaviors. However, when a participant perceives a survey as too time-consuming, there is a higher probability of lower quality responses.
We examined data from the 2018 to 2019 National Survey on Drug Use and Health, a nationally representative sample of non-institutionalized individuals ages ≥12 in the U.S. (N = 112,184). Participants were asked about 13 drug classes on this hour-long survey, and those reporting use of a drug were asked follow-up questions. We estimated prevalence and correlates of participants stating that the survey took too long to complete.
An estimated 9.4 % (95 % CI 8.9-9.8) felt the survey took too long. The more drugs used in the past year, the higher the odds of reporting that the survey took too long. Those reporting use of 8-13 drug classes in particular were at higher odds (aOR = 2.91, 95 % CI 1.44-5.87). More missing responses was associated with higher odds-particularly when ≥5 drug-related questions were skipped (aOR = 3.26, 95 % CI 2.26-4.71). Participants who did not speak any English (aOR = 1.74, 95 % CI 1.31-2.32), have difficulty concentrating (aOR = 1.38, 95 % CI 1.23-1.54), and/or had trouble understanding the interview (aOR = 3.99, 95 % CI 3.51-4.53) were at higher odds, as were those who were older and non-white. Higher education and family income was associated with lower odds.
We identified subgroups of individuals most likely to experience fatigue on a national drug survey. Researchers should recognize that long surveys with extensive follow-up questions may lead to respondent fatigue.
We identified subgroups of individuals most likely to experience fatigue on a national drug survey. Researchers should recognize that long surveys with extensive follow-up questions may lead to respondent fatigue.
To determine how clinicians with a DATA waiver to prescribe buprenorphine for opioid use disorder (OUD) adapted during the COVID-19 pandemic to emergency authorities, including use of telehealth to prescribe buprenorphine, the challenges faced by clinicians, and strategies employed by them to manage patients with OUD.
From June 23, 2020 to August 19, 2020, we conducted an electronic survey of U.S. DATA-waivered clinicians. Descriptive statistics and multivariable logistic regression were used for analysis.
Among 10,238 respondents, 68 % were physicians, 25 % nursing-related providers, and 6% physician assistants; 28 % reported never prescribing or not prescribing in the 12 months prior to the survey. Among the 72 % of clinicians who reported past 12-month buprenorphine prescribing (i.e. active practitioners during the pandemic) 30 % reported their practice setting closed to in-person visits during COVID-19; 33 % reported remote prescribing to new patients without an in-person examination. The strongest predictors of remote buprenorphine prescribing to new patients were prescribing buprenorphine to larger numbers of patients in an average month in the past year and closure of the practice setting during the pandemic; previous experience with remote prescribing to established patients prior to COVID-19 also was a significant predictor.
