Reliability and responsiveness of measures of pain in people with osteoarthritis of the knee: a psychometric evaluation

PURPOSE: To examine the fit between data from the Short Form McGill Pain Questionnaire (SF-MPQ-2) and the Rasch model, and to explore the reliability and internal responsiveness of measures of pain in people with knee osteoarthritis. METHODS: Participants with knee osteoarthritis completed the SF-MPQ-2, Intermittent and Constant Osteoarthritis Pain questionnaire (ICOAP) and painDETECT. Participants were sent the same questionnaires 3 and 6 months later. RESULTS: Fit to the Rasch model was not achieved for the SF-MPQ-2 Total scale. The Continuous subscale yielded adequate fit statistics after splitting item 10 on uniform DIF for gender, and removing item 9. The Intermittent subscale fit the Rasch model after rescoring items. The Neuropathic subscale had relatively good fit to the model. Test-retest reliability was satisfactory for most scales using both original and Rasch scoring ranging from fair to substantial. Effect sizes ranged from 0.13 to 1.79 indicating good internal responsiveness for most scales. CONCLUSIONS: These findings support the use of ICOAP subscales as reliable and responsive measure of pain in people with knee osteoarthritis. The MPQ-SF-2 subscales found to be acceptable alternatives. Implications for Rehabilitation The McGill Pain Questionnaire short version 2 is not a unidimensional scale in people with knee osteoarthritis, whereas three of the subscales are unidimensional. The McGill Pain Questionnaire short version 2 Affective subscale does not have good measurement properties for people with knee osteoarthritis. The McGill Pain Questionnaire short version 2 and the Intermittent and Constant Osteoarthritis Pain scales can be used to assess change over time. The painDETECT performs better as a screening measure than as an outcome measure

Cardiomyocyte and vascular smooth muscle independent 11β-hydroxysteroid dehydrogenase 1 amplifies infarct expansion, hypertrophy and the development of heart failure following myocardial infarction in male mice

Global deficiency of 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1), an enzyme that regenerates glucocorticoids within cells, promotes angiogenesis, and reduces acute infarct expansion after myocardial infarction (MI), suggesting that 11β-HSD1 activity has an adverse influence on wound healing in the heart after MI. The present study investigated whether 11β-HSD1 deficiency could prevent the development of heart failure after MI and examined whether 11β-HSD1 deficiency in cardiomyocytes and vascular smooth muscle cells confers this protection. Male mice with global deficiency in 11β-HSD1, or with Hsd11b1 disruption in cardiac and vascular smooth muscle (via SM22α-Cre recombinase), underwent coronary artery ligation for induction of MI. Acute injury was equivalent in all groups. However, by 8 weeks after induction of MI, relative to C57Bl/6 wild type, globally 11β-HSD1-deficient mice had reduced infarct size (34.7 ± 2.1% left ventricle [LV] vs 44.0 ± 3.3% LV, P = .02), improved function (ejection fraction, 33.5 ± 2.5% vs 24.7 ± 2.5%, P = .03) and reduced ventricular dilation (LV end-diastolic volume, 0.17 ± 0.01 vs 0.21 ± 0.01 mL, P = .01). This was accompanied by a reduction in hypertrophy, pulmonary edema, and in the expression of genes encoding atrial natriuretic peptide and β-myosin heavy chain. None of these outcomes, nor promotion of periinfarct angiogenesis during infarct repair, were recapitulated when 11β-HSD1 deficiency was restricted to cardiac and vascular smooth muscle. 11β-HSD1 expressed in cells other than cardiomyocytes or vascular smooth muscle limits angiogenesis and promotes infarct expansion with adverse ventricular remodeling after MI. Early pharmacological inhibition of 11β-HSD1 may offer a new therapeutic approach to prevent heart failure associated with ischemic heart disease

Riparian Research and Management: Past, Present, Future: Volume 1

Fifty years ago, riparian habitats were not recognized for their extensive and critical contributions to wildlife and the ecosystem function of watersheds. This changed as riparian values were identified and documented, and the science of riparian ecology developed steadily. Papers in this volume range from the more mesic northwestern United States to the arid Southwest and Mexico. More than two dozen authors—most with decades of experience—review the origins of riparian science in the western United States, document what is currently known about riparian ecosystems, and project future needs. Topics are widespread and include: interactions with fire, climate change, and declining water; impacts from exotic species; unintended consequences of biological control; the role of small mammals; watershed response to beavers; watershed and riparian changes; changes below large dams; water birds of the Colorado River Delta; and terrestrial vertebrates of mesquite bosques. Appendices and references chronicle the field’s literature, authors, “riparian pioneers,” and conferences

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders

Genetic architecture of subcortical brain structures in 38,851 individuals

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five novel loci for intracranial volume and confirmed two known signals. Four of the loci are also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic=0.748), which indicated a similar genetic background and allowed for the identification of four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, Parkinson’s disease, and enriched near genes involved in growth pathways including PI3K–AKT signaling. These findings identify biological underpinnings of intracranial volume and provide genetic support for theories on brain reserve and brain overgrowth