Early DMO: a predictor of poor outcomes following cataract surgery in diabetic patients. The DICAT-II study

Background: The prospective DIabetes and CATaract Study II (DICAT II) was performed to characterise the risks of cataract surgery to the retinae of patients with early diabetic macular oedema (E-DMO). Methods: DICAT II was a prospective, comparative, multicentre, observational study involving six Italian clinics. Patients were aged 6555 years, had type 1 or 2 diabetes with spectral-domain optical coherence tomography evidence of ESASO classification Early DMO. Group 1 eyes (78 eyes, 78 patients) underwent phacoemulsification-based cataract surgery. Group 2 eyes (65 eyes, 65 patients) had E-DMO and either clear media or had undergone uncomplicated cataract surgery 651 year previously. Central subfield thickness (CST) and best-corrected visual acuity (BCVA) were assessed in both groups. Results: The negative impact of surgery on CST was evident after the first postoperative week; CST peaked during the first month, then rapidly decreased. CST worsening 6510 \ub5m was observed in 63/78 eyes (80.7%) and 29/65 eyes (44.6%) in Groups 1 and 2, respectively (p < 0.0001). CST worsening of 6550 \ub5m was observed in 51 eyes (65.4%) and 10 eyes (15.4%) in Groups 1 and 2, respectively (p < 0.0001). Mean CST worsening was lower in Group 2 than in Group 1 (38.6 \ub1 30.4 \ub5m vs 85.5 \ub1 55.3 \ub5m, p < 0.0001) with a lower BCVA loss (-2.6 \ub1 3.5 letters vs -8.2 \ub1 6.2 letters, p < 0.0001). Higher glycaemic levels and HBA1c levels were significantly associated with the risk of >50 \u3bcm CST worsening in eyes from both groups. Conclusion: Early DMO is associated with poorer outcomes after cataract surgery and requires close pre- and postoperative monitoring

Asthma in patients admitted to emergency department for COVID-19: prevalence and risk of hospitalization

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Development of the CMS detector for the CERN LHC Run 3

International audienceSince the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger

Development of the CMS detector for the CERN LHC Run 3

International audienceSince the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger

Muon identification using multivariate techniques in the CMS experiment in proton-proton collisions at s= \sqrt{s}= 13 TeV

The identification of prompt and isolated muons, as well as muons from heavy-flavour hadron decays, is an important task. We developed two multivariate techniques to provide highly efficient identification for muons with transverse momentum greater than 10 GeV. One provides a continuous variable as an alternative to a cut-based identification selection and offers a better discrimination power against misidentified muons. The other one selects prompt and isolated muons by using isolation requirements to reduce the contamination from nonprompt muons arising in heavy-flavour hadron decays. Both algorithms are developed using 59.7 fb$^{-1}$ of proton-proton collisions data at a centre-of-mass energy of $\sqrt{s}=$ 13 TeV collected in 2018 with the CMS experiment at the CERN LHC.The identification of prompt and isolated muons, as well as muons from heavy-flavour hadron decays, is an important task. We developed two multivariate techniques to provide highly efficient identification for muons with transverse momentum greater than 10\GeV. One provides a continuous variable as an alternative to a cut-based identification selection and offers a better discrimination power against misidentified muons. The other one selects prompt and isolated muons by using isolation requirements to reduce the contamination from nonprompt muons arising in heavy-flavour hadron decays. Both algorithms are developed using 59.7 fb$^{-1}$ of proton-proton collisions data at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV collected in 2018 with the CMS experiment at the CERN LHC

Muon identification using multivariate techniques in the CMS experiment in proton-proton collisions at s\sqrt{s} = 13 TeV

International audienceThe identification of prompt and isolated muons, as well as muons from heavy-flavour hadron decays, is an important task. We developed two multivariate techniques to provide highly efficient identification for muons with transverse momentum greater than 10\GeV. One provides a continuous variable as an alternative to a cut-based identification selection and offers a better discrimination power against misidentified muons. The other one selects prompt and isolated muons by using isolation requirements to reduce the contamination from nonprompt muons arising in heavy-flavour hadron decays. Both algorithms are developed using 59.7 fb$^{-1}$ of proton-proton collisions data at a centre-of-mass energy of $\sqrt{s}$ = 13 TeV collected in 2018 with the CMS experiment at the CERN LHC

Development of the CMS detector for the CERN LHC Run 3

International audienceSince the initial data taking of the CERN LHC, the CMS experiment has undergone substantial upgrades and improvements. This paper discusses the CMS detector as it is configured for the third data-taking period of the CERN LHC, Run 3, which started in 2022. The entire silicon pixel tracking detector was replaced. A new powering system for the superconducting solenoid was installed. The electronics of the hadron calorimeter was upgraded. All the muon electronic systems were upgraded, and new muon detector stations were added, including a gas electron multiplier detector. The precision proton spectrometer was upgraded. The dedicated luminosity detectors and the beam loss monitor were refurbished. Substantial improvements to the trigger, data acquisition, software, and computing systems were also implemented, including a new hybrid CPU/GPU farm for the high-level trigger