Quality improvement program decreases mortality after cardiac surgery

ObjectiveThis study investigated the effects of a quality improvement program and goal-oriented, multidisciplinary protocols on mortality after cardiac surgery.MethodsPatients were divided into two groups: those undergoing surgery (coronary artery bypass grafting, isolated valve surgery, or coronary artery bypass grafting and valve surgery) after establishment of the multidisciplinary quality improvement program (January 2005–December 2006, n = 922) and those undergoing surgery before institution of the program (January 2002–December 2003, n = 1289). Logistic regression and propensity score analysis were used to adjust for imbalances in patients' preoperative characteristics.ResultsOperative mortality was lower in the quality improvement group (2.6% vs 5.0%, P < .01). Unadjusted odds ratio was 0.5 (95% confidence interval 0.3–0.8, P < .01); propensity score–adjusted odds ratio was 0.6 (95% confidence interval 0.4–0.99, P = .04). In multivariable analysis, diabetes (P < .01), chronic renal insufficiency (P = .05), previous cardiovascular operation (P = .04), congestive heart failure (P < .01), unstable angina (P < .01), age older than 75 years (P < .01), prolonged pump time (P < .01), and prolonged operation (P = .05) emerged as independent predictors of higher mortality after cardiac surgery, whereas quality improvement program (P < .01) and male sex (P = .03) were associated with lower mortality. Mortality decline was less pronounced in patients with than without diabetes (P = .04).ConclusionApplication of goal-directed, multidisciplinary protocols and a quality improvement program were associated with lower mortality after cardiac surgery. This decline was less prominent in patients with diabetes, and focused quality improvement protocols may be required for this subset of patients

Testing gravitational-wave searches with numerical relativity waveforms: Results from the first Numerical INJection Analysis (NINJA) project

The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave data analysis communities. The purpose of NINJA is to study the sensitivity of existing gravitational-wave search algorithms using numerically generated waveforms and to foster closer collaboration between the numerical relativity and data analysis communities. We describe the results of the first NINJA analysis which focused on gravitational waveforms from binary black hole coalescence. Ten numerical relativity groups contributed numerical data which were used to generate a set of gravitational-wave signals. These signals were injected into a simulated data set, designed to mimic the response of the Initial LIGO and Virgo gravitational-wave detectors. Nine groups analysed this data using search and parameter-estimation pipelines. Matched filter algorithms, un-modelled-burst searches and Bayesian parameter-estimation and model-selection algorithms were applied to the data. We report the efficiency of these search methods in detecting the numerical waveforms and measuring their parameters. We describe preliminary comparisons between the different search methods and suggest improvements for future NINJA analyses.Comment: 56 pages, 25 figures; various clarifications; accepted to CQ

Genome-wide association analysis implicates dysregulation of immunity genes in chronic lymphocytic leukaemia

Several chronic lymphocytic leukaemia (CLL) susceptibility loci have been reported; however, much of the heritable risk remains unidentified. Here we perform a meta-analysis of six genome-wide association studies, imputed using a merged reference panel of 1,000 Genomes and UK10K data, totalling 6,200 cases and 17,598 controls after replication. We identify nine risk loci at 1p36.11 (rs34676223, P=5.04 × 10−13), 1q42.13 (rs41271473, P=1.06 × 10−10), 4q24 (rs71597109, P=1.37 × 10−10), 4q35.1 (rs57214277, P=3.69 × 10−8), 6p21.31 (rs3800461, P=1.97 × 10−8), 11q23.2 (rs61904987, P=2.64 × 10−11), 18q21.1 (rs1036935, P=3.27 × 10−8), 19p13.3 (rs7254272, P=4.67 × 10−8) and 22q13.33 (rs140522, P=2.70 × 10−9). These new and established risk loci map to areas of active chromatin and show an over-representation of transcription factor binding for the key determinants of B-cell development and immune response

The Far-infrared Polarization Spectrum of ρ Ophiuchi A from HAWC+/SOFIA Observations

We report on polarimetric maps made with HAWC+/SOFIA toward ρ Oph A, the densest portion of the ρ Ophiuchi molecular complex. We employed HAWC+ bands C (89 μm) and D (154 μm). The slope of the polarization spectrum was investigated by defining the quantity ${{ \mathcal R }}_{{DC}}={p}_{D}/{p}_{C}$, where p C and p D represent polarization degrees in bands C and D, respectively. We find a clear correlation between ${{ \mathcal R }}_{{DC}}$ and the molecular hydrogen column density across the cloud. A positive slope (${{ \mathcal R }}_{{DC}}$ > 1) dominates the lower-density and well-illuminated portions of the cloud, which are heated by the high-mass star Oph S1, whereas a transition to a negative slope (${{ \mathcal R }}_{{DC}}$ < 1) is observed toward the denser and less evenly illuminated cloud core. We interpret the trends as due to a combination of (1) warm grains at the cloud outskirts, which are efficiently aligned by the abundant exposure to radiation from Oph S1, as proposed in the radiative torques theory; and (2) cold grains deep in the cloud core, which are poorly aligned owing to shielding from external radiation. To assess this interpretation, we developed a very simple toy model using a spherically symmetric cloud core based on Herschel data and verified that the predicted variation of ${{ \mathcal R }}_{{DC}}$ is consistent with the observations. This result introduces a new method that can be used to probe the grain alignment efficiency in molecular clouds, based on the analysis of trends in the far-infrared polarization spectrum

The Interleukin 3 Gene (IL3) Contributes to Human Brain Volume Variation by Regulating Proliferation and Survival of Neural Progenitors

One of the most significant evolutionary changes underlying the highly developed cognitive abilities of humans is the greatly enlarged brain volume. In addition to being far greater than in most other species, the volume of the human brain exhibits extensive variation and distinct sexual dimorphism in the general population. However, little is known about the genetic mechanisms underlying normal variation as well as the observed sex difference in human brain volume. Here we show that interleukin-3 (IL3) is strongly associated with brain volume variation in four genetically divergent populations. We identified a sequence polymorphism (rs31480) in the IL3 promoter which alters the expression of IL3 by affecting the binding affinity of transcription factor SP1. Further analysis indicated that IL3 and its receptors are continuously expressed in the developing mouse brain, reaching highest levels at postnatal day 1–4. Furthermore, we found IL3 receptor alpha (IL3RA) was mainly expressed in neural progenitors and neurons, and IL3 could promote proliferation and survival of the neural progenitors. The expression level of IL3 thus played pivotal roles in the expansion and maintenance of the neural progenitor pool and the number of surviving neurons. Moreover, we found that IL3 activated both estrogen receptors, but estrogen didn’t directly regulate the expression of IL3. Our results demonstrate that genetic variation in the IL3 promoter regulates human brain volume and reveals novel roles of IL3 in regulating brain development

Genetically predicted longer telomere length is associated with increased risk of B-cell lymphoma subtypes

Evidence from a small number of studies suggests that longer telomere length measured in peripheral leukocytes is associated with an increased risk of non-Hodgkin lymphoma (NHL). However, these studies may be biased by reverse causation, confounded by unmeasured environmental exposures and might miss time points for which prospective telomere measurement would best reveal a relationship between telomere length and NHL risk. We performed an analysis of genetically inferred telomere length and NHL risk in a study of 10 102 NHL cases of the four most common B-cell histologic types and 9562 controls using a genetic risk score (GRS) comprising nine telomere length-associated single-nucleotide polymorphisms. This approach uses existing genotype data and estimates telomere length by weighing the number of telomere length-associated variant alleles an individual carries with the published change in kb of telomere length. The analysis of the telomere length GRS resulted in an association between longer telomere length and increased NHL risk [four B-cell histologic types combined; odds ratio (OR) = 1.49, 95% CI 1.22–1.82, P-value = 8.5 × 10−5]. Subtype-specific analyses indicated that chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL/SLL) was the principal NHL subtype contributing to this association (OR = 2.60, 95% CI 1.93–3.51, P-value = 4.0 × 10−10). Significant interactions were observed across strata of sex for CLL/SLL and marginal zone lymphoma subtypes as well as age for the follicular lymphoma subtype. Our results indicate that a genetic background that favors longer telomere length may increase NHL risk, particularly risk of CLL/SLL, and are consistent with earlier studies relating longer telomere length with increased NHL risk

Incorporating progesterone receptor expression into the PREDICT breast prognostic model

Background: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).Method: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.Results: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0. 902 for patients with ER-positive tumours (p = 2.3 x 10(-6)) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.Conclusion: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predic-tions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration. (C) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe