Prematurity, especially preterm birth (less than 32 weeks' gestation), is common and associated with high rates of both survival and neurodevelopmental disability, especially apparent in cognitive ...spheres. The neuropathological substrate of this disability is now recognized to be related to a variety of dysmaturational disturbances of the brain. These disturbances follow initial brain injury, particularly cerebral white matter injury, and involve many of the extraordinary array of developmental events active in cerebral white and gray matter structures during the premature period. This review delineates these developmental events and the dysmaturational disturbances that occur in premature infants. The cellular mechanisms involved in the genesis of the dysmaturation are emphasized, with particular focus on the preoligodendrocyte. A central role for the diffusely distributed activated microglia and reactive astrocytes in the dysmaturation is now apparent. As these dysmaturational cellular mechanisms appear to occur over a relatively long time window, interventions to prevent or ameliorate the dysmaturation, that is, neurorestorative interventions, seem possible. Such interventions include pharmacologic agents, especially erythropoietin, and particular attention has also been paid to such nutritional factors as quality and source of milk, breastfeeding, polyunsaturated fatty acids, iron, and zinc. Recent studies also suggest a potent role for interventions directed at various experiential factors in the neonatal period and infancy, i.e., provision of optimal auditory and visual exposures, minimization of pain and stress, and a variety of other means of environmental behavioral enrichment, in enhancing brain development.
Summary Brain injury in premature infants is of enormous public health importance because of the large number of such infants who survive with serious neurodevelopmental disability, including major ...cognitive deficits and motor disability. This type of brain injury is generally thought to consist primarily of periventricular leukomalacia (PVL), a distinctive form of cerebral white matter injury. Important new work shows that PVL is frequently accompanied by neuronal/axonal disease, affecting the cerebral white matter, thalamus, basal ganglia, cerebral cortex, brain stem, and cerebellum. This constellation of PVL and neuronal/axonal disease is sufficiently distinctive to be termed “encephalopathy of prematurity”. The thesis of this Review is that the encephalopathy of prematurity is a complex amalgam of primary destructive disease and secondary maturational and trophic disturbances. This Review integrates the fascinating confluence of new insights into both brain injury and brain development during the human premature period.
Selection bias due to loss to follow up represents a threat to the internal validity of estimates derived from cohort studies. Over the past 15 years, stratification-based techniques as well as ...methods such as inverse probability-of-censoring weighted estimation have been more prominently discussed and offered as a means to correct for selection bias. However, unlike correcting for confounding bias using inverse weighting, uptake of inverse probability-of-censoring weighted estimation as well as competing methods has been limited in the applied epidemiologic literature. To motivate greater use of inverse probability-of-censoring weighted estimation and competing methods, we use causal diagrams to describe the sources of selection bias in cohort studies employing a time-to-event framework when the quantity of interest is an absolute measure (e.g., absolute risk, survival function) or relative effect measure (e.g., risk difference, risk ratio). We highlight that whether a given estimate obtained from standard methods is potentially subject to selection bias depends on the causal diagram and the measure. We first broadly describe inverse probability-of-censoring weighted estimation and then give a simple example to demonstrate in detail how inverse probability-of-censoring weighted estimation mitigates selection bias and describe challenges to estimation. We then modify complex, real-world data from the University of North Carolina Center for AIDS Research HIV clinical cohort study and estimate the absolute and relative change in the occurrence of death with and without inverse probability-of-censoring weighted correction using the modified University of North Carolina data. We provide SAS code to aid with implementation of inverse probability-of-censoring weighted techniques.
This Point of View article addresses neonatal encephalopathy (NE) presumably caused by hypoxia–ischemia and the terminology currently in wide use for this disorder. The nonspecific term NE is ...commonly utilized for those infants with the clinical and imaging characteristics of neonatal hypoxic–ischemic encephalopathy (HIE). Multiple magnetic resonance imaging studies of term infants with the clinical setting of presumed hypoxia–ischemia near the time of delivery have delineated a topography of lesions highly correlated with that defined by human neuropathology and by animal models, including primate models, of hypoxia–ischemia. These imaging findings, coupled with clinical features consistent with perinatal hypoxic–ischemic insult(s), warrant the specific designation of neonatal HIE. Ann Neurol 2012;72:156–166
There is interest in using convolutional neural networks (CNNs) to analyze medical imaging to provide computer-aided diagnosis (CAD). Recent work has suggested that image classification CNNs may not ...generalize to new data as well as previously believed. We assessed how well CNNs generalized across three hospital systems for a simulated pneumonia screening task.
A cross-sectional design with multiple model training cohorts was used to evaluate model generalizability to external sites using split-sample validation. A total of 158,323 chest radiographs were drawn from three institutions: National Institutes of Health Clinical Center (NIH; 112,120 from 30,805 patients), Mount Sinai Hospital (MSH; 42,396 from 12,904 patients), and Indiana University Network for Patient Care (IU; 3,807 from 3,683 patients). These patient populations had an age mean (SD) of 46.9 years (16.6), 63.2 years (16.5), and 49.6 years (17) with a female percentage of 43.5%, 44.8%, and 57.3%, respectively. We assessed individual models using the area under the receiver operating characteristic curve (AUC) for radiographic findings consistent with pneumonia and compared performance on different test sets with DeLong's test. The prevalence of pneumonia was high enough at MSH (34.2%) relative to NIH and IU (1.2% and 1.0%) that merely sorting by hospital system achieved an AUC of 0.861 (95% CI 0.855-0.866) on the joint MSH-NIH dataset. Models trained on data from either NIH or MSH had equivalent performance on IU (P values 0.580 and 0.273, respectively) and inferior performance on data from each other relative to an internal test set (i.e., new data from within the hospital system used for training data; P values both <0.001). The highest internal performance was achieved by combining training and test data from MSH and NIH (AUC 0.931, 95% CI 0.927-0.936), but this model demonstrated significantly lower external performance at IU (AUC 0.815, 95% CI 0.745-0.885, P = 0.001). To test the effect of pooling data from sites with disparate pneumonia prevalence, we used stratified subsampling to generate MSH-NIH cohorts that only differed in disease prevalence between training data sites. When both training data sites had the same pneumonia prevalence, the model performed consistently on external IU data (P = 0.88). When a 10-fold difference in pneumonia rate was introduced between sites, internal test performance improved compared to the balanced model (10× MSH risk P < 0.001; 10× NIH P = 0.002), but this outperformance failed to generalize to IU (MSH 10× P < 0.001; NIH 10× P = 0.027). CNNs were able to directly detect hospital system of a radiograph for 99.95% NIH (22,050/22,062) and 99.98% MSH (8,386/8,388) radiographs. The primary limitation of our approach and the available public data is that we cannot fully assess what other factors might be contributing to hospital system-specific biases.
Pneumonia-screening CNNs achieved better internal than external performance in 3 out of 5 natural comparisons. When models were trained on pooled data from sites with different pneumonia prevalence, they performed better on new pooled data from these sites but not on external data. CNNs robustly identified hospital system and department within a hospital, which can have large differences in disease burden and may confound predictions.
B cells are essential components of the adaptive immune system and have important roles in the pathogenesis of several central nervous system (CNS) diseases. Besides producing antibodies, B cells ...perform other functions, including antigen presentation to T cells, production of proinflammatory cytokines and secretion of anti-inflammatory cytokines that limit immune responses. B cells can contribute to CNS disease either through their actions in the periphery (meaning that they have an 'outside-in' effect on CNS immunopathology) or following their compartmentalization within the CNS. The success of B cell-depleting therapy in patients with multiple sclerosis and CNS diseases with an autoantibody component, such as neuromyelitis optica spectrum disorder and autoimmune encephalitides, has underscored the role of B cells in both cellular and humoral-mediated CNS conditions. Emerging evidence suggests B cells also contribute to the pathogenesis of neurodegenerative diseases, including Alzheimer disease and Parkinson disease. Advancing our understanding of the role of B cells in neuroinflammatory and neurodegenerative diseases could lead to novel therapeutic approaches.
Summary
The challenge‐hindrance model of stress proposes that stressors can be divided into two distinct groups: those that challenge employees and those that hinder employees. This critical review ...seeks to explain the history of the model and its basic tenets, while succinctly summarizing the findings of existing studies based on the model. A thorough search of the stress literature uncovered 32 studies that specifically examined the relationship between challenge and hindrance stressors and important personal/organizational variables. Results were reviewed and analyzed, specifically by describing past meta‐analyses on the model, looking at the overall pattern of results from primary studies, and meta‐analyzing the relationships presented in those papers. This synthesis suggests that although there are some differential relationships of challenge and hindrance stressors with organizational variables (e.g., performance and engagement), the relationships to other key variables, such as counterproductive work behaviors, psychological strains, and physical health, are consistently negative for both challenge and hindrance stressors. Thus, we propose that stress research move away from the current challenge‐hindrance model in favor of other established models and/or a more appraisal‐based approach.
Kratom is a plant with partial opioid agonist effects, and its use has become popular to ameliorate symptoms of opioid withdrawal. However, use has been linked to thousands of poisonings, although ...most have involved use of other drugs. Little is known regarding prevalence and correlates of use in the general U.S. population.
Data were examined from the 2019 National Survey on Drug Use and Health, a nationally representative probability sample of non-institutionalized individuals aged ≥12 years in the U.S. (N=56,136). Prevalence and correlates of past-year kratom use were estimated. Data were analyzed in 2020.
An estimated 0.7% (95% CI=0.6, 0.8) of individuals in the U.S. have used kratom in the past year. Past-year proxy diagnosis of prescription opioid use disorder was associated with increased odds for kratom use (AOR=3.20, 95% CI=1.38, 7.41), with 10.4% (95% CI=6.7, 15.9) of those with use disorder reporting use. Opioid misuse not accompanied with use disorder was not associated with kratom use. Those reporting past-year cannabis use both with (AOR=4.33, 95% CI=2.61, 7.19) and without (AOR=4.57, 95% CI=3.29, 6.35) use disorder and those reporting past-year cocaine use (AOR=1.69, 95% CI=1.06, 2.69) and prescription stimulant misuse (AOR=2.10, 95% CI=1.44, 3.05) not accompanied with use disorder were at higher odds for kratom use.
Kratom use is particularly prevalent among those with prescription opioid use disorder, but it is also prevalent among people who use other drugs. Research is needed to determine reasons for use and potential dangers associated with adding kratom to drug repertoires.