Explainable artificial intelligence model to predict acute critical illness from electronic health records

We developed an explainable artificial intelligence (AI) early warning score (xAI-EWS) system for early detection of acute critical illness. While maintaining a high predictive performance, our system explains to the clinician on which relevant electronic health records (EHRs) data the prediction is grounded. Acute critical illness is often preceded by deterioration of routinely measured clinical parameters, e.g., blood pressure and heart rate. Early clinical prediction is typically based on manually calculated screening metrics that simply weigh these parameters, such as Early Warning Scores (EWS). The predictive performance of EWSs yields a tradeoff between sensitivity and specificity that can lead to negative outcomes for the patient. Previous work on EHR-trained AI systems offers promising results with high levels of predictive performance in relation to the early, real-time prediction of acute critical illness. However, without insight into the complex decisions by such system, clinical translation is hindered. In this letter, we present our xAI-EWS system, which potentiates clinical translation by accompanying a prediction with information on the EHR data explaining it

Should all patients with a culture-negative periprosthetic joint infection be treated with antibiotics?:A multicentre observational study

Aims: The aim of this study was to analyze the prevalence of culture-negative periprosthetic joint infections (PJIs) when adequate methods of culture are used, and to evaluate the outcome in patients who were treated with antibiotics for a culture-negative PJI compared with those in whom antibiotics were withheld. Methods: A multicentre observational study was undertaken: 1,553 acute and 1,556 chronic PJIs, diagnosed between 2013 and 2018, were retrospectively analyzed. Culture-negative PJIs were diagnosed according to the Muskuloskeletal Infection Society (MSIS), International Consensus Meeting (ICM), and European Bone and Joint Society (EBJIS) definitions. The primary outcome was recurrent infection, and the secondary outcome was removal of the prosthetic components for any indication, both during a follow -up period of two years. Results: None of the acute PJIs and 70 of the chronic PJIs (4.7%) were culture-negative; a total of 36 culture-negative PJIs (51%) were treated with antibiotics, particularly those with histological signs of infection. After two years of follow -up, no recurrent infections occurred in patients in whom antibiotics were withheld. The requirement for removal of the components for any indication during follow -up was not significantly different in those who received antibiotics compared with those in whom antibiotics were withheld (7.1% vs 2.9%; p = 0.431). Conclusion: When adequate methods of culture are used, the incidence of culture-negative PJIs is low. In patients with culture-negative PJI, antibiotic treatment can probably be withheld if there are no histological signs of infection. In all other patients, diagnostic efforts should be made to identify the causative microorganism by means of serology or molecular techniques

Use of the prognostic biomarker suPAR in the emergency department improves risk stratification but has no effect on mortality:a cluster-randomized clinical trial (TRIAGE III)

Abstract Background Risk stratification of patients in the emergency department can be strengthened using prognostic biomarkers, but the impact on patient prognosis is unknown. The aim of the TRIAGE III trial was to investigate whether the introduction of the prognostic and nonspecific biomarker: soluble urokinase plasminogen activator receptor (suPAR) for risk stratification in the emergency department reduces mortality in acutely admitted patients. Methods The TRIAGE III trial was a cluster-randomized interventional trial conducted at emergency departments in the Capitol Region of Denmark. Eligible hospitals were required to have an emergency department with an intake of acute medical and surgical patients and no previous access to suPAR measurement. Three emergency departments were randomized; one withdrew shortly after the trial began. The inclusion period was from January through June of 2016 consisting of twelve cluster-periods of 3-weeks alternating between intervention and control and a subsequent follow-up of ten months. Patients were allocated to the intervention if they arrived in interventional periods, where suPAR measurement was routinely analysed at arrival. In the control periods suPAR measurement was not performed. The main outcome was all-cause mortality 10 months after arrival of the last patient in the inclusion period. Secondary outcomes included 30-day mortality. Results The trial enrolled a consecutive cohort of 16,801 acutely admitted patients; all were included in the analyses. The intervention group consisted of 6 cluster periods with 8900 patients and the control group consisted of 6 cluster periods with 7901 patients. After a median follow-up of 362 days, death occurred in 1241 patients (13.9%) in the intervention group and in 1126 patients (14.3%) in the control group. The weighted Cox model found a hazard ratio of 0.97 (95% confidence interval, 0.89 to 1.07; p = 0.57). Analysis of all subgroups and of 30-day all-cause mortality showed similar results. Conclusions The TRIAGE III trial found no effect of introducing the nonspecific and prognostic biomarker suPAR in emergency departments on short- or long-term all-cause mortality among acutely admitted patients. Further research is required to evaluate how prognostic biomarkers can be implemented in routine clinical practice. Trial registration clinicaltrials.gov, NCT02643459. Registered 31 December 2015

Observation of the Rare Decay of the η Meson to Four Muons

A search for the rare η→μ+μ−μ+μ− double-Dalitz decay is performed using a sample of proton-proton collisions, collected by the CMS experiment at the CERN LHC with high-rate muon triggers during 2017 and 2018 and corresponding to an integrated luminosity of 101  fb−1. A signal having a statistical significance well in excess of 5 standard deviations is observed. Using the η→μ+μ− decay as normalization, the branching fraction B(η→μ+μ−μ+μ−)=[5.0±0.8(stat)±0.7(syst)±0.7(B2μ)]×10−9 is measured, where the last term is the uncertainty in the normalization channel branching fraction. This work achieves an improved precision of over 5 orders of magnitude compared to previous results, leading to the first measurement of this branching fraction, which is found to agree with theoretical predictions

Search for new physics in multijet events with at least one photon and large missing transverse momentum in proton-proton collisions at 13 TeV

A search for new physics in final states consisting of at least one photon, multiple jets, and large missing transverse momentum is presented, using proton-proton collision events at a center-of-mass energy of 13 TeV. The data correspond to an integrated luminosity of 137 fb−1, recorded by the CMS experiment at the CERN LHC from 2016 to 2018. The events are divided into mutually exclusive bins characterized by the missing transverse momentum, the number of jets, the number of b-tagged jets, and jets consistent with the presence of hadronically decaying W, Z, or Higgs bosons. The observed data are found to be consistent with the prediction from standard model processes. The results are interpreted in the context of simplified models of pair production of supersymmetric particles via strong and electroweak interactions. Depending on the details of the signal models, gluinos and squarks of masses up to 2.35 and 1.43 TeV, respectively, and electroweakinos of masses up to 1.23 TeV are excluded at 95% confidence level

First measurement of the top quark pair production cross section in proton-proton collisions at s \sqrt{s} = 13.6 TeV

The first measurement of the top quark pair (tt¯) production cross section in proton-proton collisions at s√ = 13.6 TeV is presented. Data recorded with the CMS detector at the CERN LHC in Summer 2022, corresponding to an integrated luminosity of 1.21 fb−1, are analyzed. Events are selected with one or two charged leptons (electrons or muons) and additional jets. A maximum likelihood fit is performed in event categories defined by the number and flavors of the leptons, the number of jets, and the number of jets identified as originating from b quarks. An inclusive tt¯ production cross section of 881 ± 23 (stat + syst) ± 20 (lumi) pb is measured, in agreement with the standard model prediction of 924+32−40 pb