Development of brain signal processing interface software for Trackit-LabVIEW

There are many digital electroencephalography (EEG) acquisition systems available nowadays for researchers due to the demand in the brain signal research. The electroencephalography (EEG) acquisition systems varied on the specification, design and prices. One of the ambulatory amplifiers for acquisition is the Trackit from Lifelines Limited. Presently, the Trackit system is only available for clinical applications. In order to integrate from clinical applications to research capabilities, the Trackit has to be interfaced with software that be able to do the electroencephalography (EEG) signals processing. In our project, Lab VIEW is chosen as our software platform. Therefore, we have taken the initiative to developed the software for Trackit-Lab VIEW interfaced. In this paper, we have demonstrated that the acquired electroencephalography (EEG) signals obtained using TrackitLab VIEW software. Example of signal processing application on the raw electroencephalography (EEG) signals was shown in the results section

International Nosocomial Infection Control Consortium report, data summary of 50 countries for 2010-2015: Device-associated module

•We report INICC device-associated module data of 50 countries from 2010-2015.•We collected prospective data from 861,284 patients in 703 ICUs for 3,506,562 days.•DA-HAI rates and bacterial resistance were higher in the INICC ICUs than in CDC-NHSN's.•Device utilization ratio in the INICC ICUs was similar to CDC-NHSN's. Background: We report the results of International Nosocomial Infection Control Consortium (INICC) surveillance study from January 2010-December 2015 in 703 intensive care units (ICUs) in Latin America, Europe, Eastern Mediterranean, Southeast Asia, and Western Pacific. Methods: During the 6-year study period, using Centers for Disease Control and Prevention National Healthcare Safety Network (CDC-NHSN) definitions for device-associated health care-associated infection (DA-HAI), we collected prospective data from 861,284 patients hospitalized in INICC hospital ICUs for an aggregate of 3,506,562 days. Results: Although device use in INICC ICUs was similar to that reported from CDC-NHSN ICUs, DA-HAI rates were higher in the INICC ICUs: in the INICC medical-surgical ICUs, the pooled rate of central line-associated bloodstream infection, 4.1 per 1,000 central line-days, was nearly 5-fold higher than the 0.8 per 1,000 central line-days reported from comparable US ICUs, the overall rate of ventilator-associated pneumonia was also higher, 13.1 versus 0.9 per 1,000 ventilator-days, as was the rate of catheter-associated urinary tract infection, 5.07 versus 1.7 per 1,000 catheter-days. From blood cultures samples, frequencies of resistance of Pseudomonas isolates to amikacin (29.87% vs 10%) and to imipenem (44.3% vs 26.1%), and of Klebsiella pneumoniae isolates to ceftazidime (73.2% vs 28.8%) and to imipenem (43.27% vs 12.8%) were also higher in the INICC ICUs compared with CDC-NHSN ICUs. Conclusions: Although DA-HAIs in INICC ICU patients continue to be higher than the rates reported in CDC-NSHN ICUs representing the developed world, we have observed a significant trend toward the reduction of DA-HAI rates in INICC ICUs as shown in each international report. It is INICC's main goal to continue facilitating education, training, and basic and cost-effective tools and resources, such as standardized forms and an online platform, to tackle this problem effectively and systematically

Measurement of electrons from semileptonic heavy-flavour hadron decays at midrapidity in pp and Pb–Pb collisions at √sNN = 5.02 TeV

The differential invariant yield as a function of transverse momentum (pT) of electrons from semileptonic heavy-flavour hadron decays was measured at midrapidity in central (0–10%), semi-central (30–50%) and peripheral (60–80%) lead–lead (Pb–Pb) collisions at √sNN = 5.02 TeV in the pT intervals 0.5–26 GeV/c (0–10% and 30–50%) and 0.5–10 GeV/c (60–80%). The production cross section in proton–proton (pp) collisions at √s = 5.02 TeV was measured as well in 0.5 < pT < 10 GeV/c and it lies close to the upper band of perturbative QCD calculation uncertainties up to pT = 5 GeV/c and close to the mean value for larger pT. The modification of the electron yield with respect to what is expected for an incoherent superposition of nucleon–nucleon collisions is evaluated by measuring the nuclear modification factor RAA. The measurement of the RAA in different centrality classes allows in-medium energy loss of charm and beauty quarks to be investigated. The RAA shows a suppression with respect to unity at intermediate pT, which increases while moving towards more central collisions. Moreover, the measured RAA is sensitive to the modification of the parton distribution functions (PDF) in nuclei, like nuclear shadowing, which causes a suppression of the heavy-quark production at low pT in heavy-ion collisions at LHC

Multiplicity dependence of K*(892)0 and ϕ(1020) production in pp collisions at t √s=13 TeV

The striking similarities that have been observed between high-multiplicity proton-proton (pp) collisions and heavy-ion collisions can be explored through multiplicity-differential measurements of identified hadrons in pp collisions. With these measurements, it is possible to study mechanisms such as collective flow that determine the shapes of hadron transverse momentum (pT) spectra, to search for possible modifications of the yields of short-lived hadronic resonances due to scattering effects in an extended hadron-gas phase, and to investigate different explanations provided by phenomenological models for enhancement of strangeness production with increasing multiplicity. In this paper, these topics are addressed through measurements of the K∗(892)0 and φ(1020) mesons at midrapidity in pp collisions at √s = 13 TeV as a function of the charged-particle multiplicity. The results include the pT spectra, pT-integrated yields, mean transverse momenta, and the ratios of the yields of these resonances to those of longer-lived hadrons. Comparisons with results from other collision systems and energies, as well as predictions from phenomenological models, are also discussed

Dielectron and heavy-quark production in inelastic and high-multiplicity proton–proton collisions at √s = 13 TeV

The measurement of dielectron production is presented as a function of invariant mass and transverse momentum (pT) at midrapidity (|ye| < 0.8) in proton–proton (pp) collisions at a centre-of-mass energy of √s = 13 TeV. The contributions from light-hadron decays are calculated from their measured cross sections in pp collisions at √s = 7 TeV or 13 TeV. The remaining continuum stems from correlated semileptonic decays of heavy-flavour hadrons. Fitting the data with templates from two different MC event generators, PYTHIA and POWHEG, the charm and beauty cross sections at midrapidity are extracted for the first time at this collision energy: dσcc¯/dy|y=0 = 974 ± 138 (stat.) ± 140 (syst.) ± 214(BR) μb and dσbb¯ /dy|y=0 = 79 ± 14 (stat.) ± 11 (syst.) ± 5(BR) μb using PYTHIA simulations and dσcc¯/dy|y=0 = 1417 ± 184 (stat.) ± 204 (syst.) ± 312(BR) μb and dσbb¯ /dy|y=0 = 48 ± 14 (stat.) ± 7 (syst.) ± 3(BR) μb for POWHEG. These values, whose uncertainties are fully correlated between the two generators, are consistent with extrapolations from lower energies. The different results obtained with POWHEG and PYTHIA imply different kinematic correlations of the heavy-quark pairs in these two generators. Furthermore, comparisons of dielectron spectra in inelastic events and in events collected with a trigger on high charged-particle multiplicities are presented in various pT intervals. The differences are consistent with the already measured scaling of light-hadron and open-charm production at high charged-particle multiplicity as a function of pT. Upper limits for the contribution of virtual direct photons are extracted at 90% confidence level and found to be in agreement with pQCD calculations

Safety and efficacy of non-steroidal anti-inflammatory drugs to reduce ileus after colorectal surgery

Background: Ileus is common after elective colorectal surgery, and is associated with increased adverse events and prolonged hospital stay. The aim was to assess the role of non-steroidal anti-inflammatory drugs (NSAIDs) for reducing ileus after surgery. Methods: A prospective multicentre cohort study was delivered by an international, student- and trainee-led collaborative group. Adult patients undergoing elective colorectal resection between January and April 2018 were included. The primary outcome was time to gastrointestinal recovery, measured using a composite measure of bowel function and tolerance to oral intake. The impact of NSAIDs was explored using Cox regression analyses, including the results of a centre-specific survey of compliance to enhanced recovery principles. Secondary safety outcomes included anastomotic leak rate and acute kidney injury. Results: A total of 4164 patients were included, with a median age of 68 (i.q.r. 57\u201375) years (54\ub79 per cent men). Some 1153 (27\ub77 per cent) received NSAIDs on postoperative days 1\u20133, of whom 1061 (92\ub70 per cent) received non-selective cyclo-oxygenase inhibitors. After adjustment for baseline differences, the mean time to gastrointestinal recovery did not differ significantly between patients who received NSAIDs and those who did not (4\ub76 versus 4\ub78 days; hazard ratio 1\ub704, 95 per cent c.i. 0\ub796 to 1\ub712; P = 0\ub7360). There were no significant differences in anastomotic leak rate (5\ub74 versus 4\ub76 per cent; P = 0\ub7349) or acute kidney injury (14\ub73 versus 13\ub78 per cent; P = 0\ub7666) between the groups. Significantly fewer patients receiving NSAIDs required strong opioid analgesia (35\ub73 versus 56\ub77 per cent; P &lt; 0\ub7001). Conclusion: NSAIDs did not reduce the time for gastrointestinal recovery after colorectal surgery, but they were safe and associated with reduced postoperative opioid requirement

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

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

At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods

By September 2022, more than 600 million cases of SARS-CoV-2 infection have been reported globally, resulting in over 6.5 million deaths. COVID-19 mortality risk estimators are often, however, developed with small unrepresentative samples and with methodological limitations. It is highly important to develop predictive tools for pulmonary embolism (PE) in COVID-19 patients as one of the most severe preventable complications of COVID-19. Early recognition can help provide life-saving targeted anti-coagulation therapy right at admission. Using a dataset of more than 800,000 COVID-19 patients from an international cohort, we propose a cost-sensitive gradient-boosted machine learning model that predicts occurrence of PE and death at admission. Logistic regression, Cox proportional hazards models, and Shapley values were used to identify key predictors for PE and death. Our prediction model had a test AUROC of 75.9% and 74.2%, and sensitivities of 67.5% and 72.7% for PE and all-cause mortality respectively on a highly diverse and held-out test set. The PE prediction model was also evaluated on patients in UK and Spain separately with test results of 74.5% AUROC, 63.5% sensitivity and 78.9% AUROC, 95.7% sensitivity. Age, sex, region of admission, comorbidities (chronic cardiac and pulmonary disease, dementia, diabetes, hypertension, cancer, obesity, smoking), and symptoms (any, confusion, chest pain, fatigue, headache, fever, muscle or joint pain, shortness of breath) were the most important clinical predictors at admission. Age, overall presence of symptoms, shortness of breath, and hypertension were found to be key predictors for PE using our extreme gradient boosted model. This analysis based on the, until now, largest global dataset for this set of problems can inform hospital prioritisation policy and guide long term clinical research and decision-making for COVID-19 patients globally. Our machine learning model developed from an international cohort can serve to better regulate hospital risk prioritisation of at-risk patients. © The Author(s) 2024