Cosmic ray modulation by different types of solar wind disturbances

Context. Solar wind disturbances such as interplanetary coronal mass ejections (ICMEs) and corotating interaction regions (CIRs) cause short-term cosmic ray depressions, generally denoted as Forbush decreases. Aims. We conduct a systematic statistical study of various aspects of Forbush decreases. The analysis provides empirical background for physical interpretations of short-term cosmic ray modulations. Methods. Firstly, we analyzed the effects of different types of solar wind disturbances, and secondly, we focused on the phenomenon of over-recovery (the return of the cosmic ray count to a value higher than the pre-decrease level). The analysis is based on ground-based neutron monitor data and the solar wind data recorded by the Advanced Composition Explorer. The correlations between various cosmic ray depressions and solar wind parameters as well as their statistical significance are analyzed in detail. In addition, we performed a normalized superposed epoch analysis for depressions and magnetic field enhancements. Results. The analysis revealed differences in the relationship between different solar wind disturbances and cosmic ray depression parameters. The amplitude of the depression for ICMEs was found to correlate well with the amplitudes of magnetic field strength and fluctuations, whereas for CIRs we found only the correlation between the amplitude of the depression and the solar wind disturbance dimension proxy vtB. Similar behavior was found for shock and no-shock events, respectively. The CIR/ICME composites show a specific behavior that is a mixture of both ICMEs and CIRs. For all analyzed categories we found that the duration of the depression correlates with the duration of the solar wind disturbance. The analysis of the over-recovery showed that there is no straightforward relationship to either “branching-effect” or geomagnetic effects, therefore we propose a scenario where the “branching-effect” is caused by several factors and is only indirectly related to the over-recovery

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research