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

Background 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

Neural Network Using Genetic Algorithm for Magnetic Performance Prediction of Toroidal Wound Cores at 50 Hz

Geometrical and building parameters have a strong influence on magnetic performance of toroidal wound cores made from grain oriented 3% SiFe electrical steel. From a sample of 40 cores with dimensions ranging from 35 to 160 mm outer diameter, 25 to 100 mm inner diameter and JO to 70 mm strip width and a flux density range of 0.1 to 1.7 T have been obtained and used as training data to a generalised feedforward neural network

Thermoluminescence characteristics of Zn(BO2)(2):Ce3+ under beta irradiation

WOS: 000371608500003PubMed ID: 26142459In this study, the thermoluminescence (TL) characteristics of undoped and various Ce3+-doped Zn(BO2)(2) powder samples excited by beta irradiation are reported for the inot signrst time. Zn(BO2)(2):Ce3+ powder samples were prepared by the nitric acid method (NAM) using the starting oxides [zinc oxide (ZnO), boric acid (H3BO3) and doped element oxide (CeO2)]. The formations of the obtained samples were confirmed by an X-ray diffraction study. Dose responses of Ce3+-doped Zn(BO2)(2) samples were investigated after the beta irradiation in the dose range from 143 mGy to 60 Gy. All TL measurements were made on using an automated Riso TL/OSL DA-20 reader. TL emission was detected through a filter pack (Schott BG-39 and Corning 7-59) transmitting between 330 and 480 nm. TL glow curves were obtained using a constant heating rate of 5A degrees C s(-1) from room temperature (RT) to 450A degrees C in an N-2 atmosphere. The dose response and minimum detectable dose (MDD) values of the samples were determined. The dose responses of all the samples tested exhibited a superlinear behaviour. MDD value of 4 % Ce3+-doped Zn(BO2)(2) sample, which shows a high temperature peak at about 230A degrees C, was determined as 96 mGy. MDD values for 1, 2, 3, 5 and 10 % Ce3+-doped Zn(BO2)(2) samples were also determined as 682, 501, 635, 320 and 824 mGy, respectively. The trap parameters of undoped and 4 % Ce3+-doped Zn(BO2)(2) samples were estimated by the computerised glow curve deconvolution method

Magnetocaloric properties of rare-earth-free mn27cr7ni33ge25si8 high-entropy alloy

WOS:000515171200001The magnetic and magnetocaloric properties of a new Mn27Cr7Ni33Ge25Si8 high-entropy alloy (HEA) were investigated. The crystal structure is characterized through multiphase Rietveld refinement of X-ray diffraction data. The structure of the HEA is orthorhombic in the Pnma space group. Arrott plots indicate that the ferromagnetic-paramagnetic phase transition is of second order. The maximum magnetic entropy change is 2.49 J.kg(-1).K-1, among the highest reported for alloys that do not contain rare earth elements.This work was supported by the Commission for Scientific Research Projects of the Bursa Uludag University under Project OUAP(F)-2018/4

Computational modeling of isothermal decay curves of trapping centers in TlGaSeS layered single crystals

This paper presents a new approach based on multilayered perceptrons (MLPs) to compute the isothermal decay curves of trapping centers in undoped TlGaSeS layered crystals. The MLP has been trained by a Genetic Algorithm (GA). The results obtained using the MLP model were tested with an untrained experimental data. The comparison has shown that the proposed model can predict more accurately and easily the isothermal decay curves

Estimation of thermally stimulated current in as grown TlGaSeS layered single crystals by multilayered perceptron neural network

This paper presents an artificial neural network approach to compute thermally stimulated current (TSC) in as-grown T1GaSeS layered single crystals. The experimental data have been obtained from TSC measurements. The network has been trained by a genetic algorithm (GA). The results confirmed that the proposed model could provide an accurate computation of the TSC