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(1) Background: The aim of our study was to identify specific risk factors for fatal outcome in critically ill COVID-19 patients. (2) Methods: Our data set consisted of 840 patients enclosed in the LEOSS registry. Using lasso regression for variable selection, a multifactorial logistic regression model was fitted to the response variable survival. Specific risk factors and their odds ratios were derived. A nomogram was developed as a graphical representation of the model. (3) Results: 14 variables were identified as independent factors contributing to the risk of death for critically ill COVID-19 patients: age (OR 1.08, CI 1.06–1.10), cardiovascular disease (OR 1.64, CI 1.06–2.55), pulmonary disease (OR 1.87, CI 1.16–3.03), baseline Statin treatment (0.54, CI 0.33–0.87), oxygen saturation (unit = 1%, OR 0.94, CI 0.92–0.96), leukocytes (unit 1000/μL, OR 1.04, CI 1.01–1.07), lymphocytes (unit 100/μL, OR 0.96, CI 0.94–0.99), platelets (unit 100,000/μL, OR 0.70, CI 0.62–0.80), procalcitonin (unit ng/mL, OR 1.11, CI 1.05–1.18), kidney failure (OR 1.68, CI 1.05–2.70), congestive heart failure (OR 2.62, CI 1.11–6.21), severe liver failure (OR 4.93, CI 1.94–12.52), and a quick SOFA score of 3 (OR 1.78, CI 1.14–2.78). The nomogram graphically displays the importance of these 14 factors for mortality. (4) Conclusions: There are risk factors that are specific to the subpopulation of critically ill COVID-19 patients.
Scores to identify patients at high risk of progression of coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), may become instrumental for clinical decision-making and patient management. We used patient data from the multicentre Lean European Open Survey on SARS-CoV-2-Infected Patients (LEOSS) and applied variable selection to develop a simplified scoring system to identify patients at increased risk of critical illness or death. A total of 1946 patients who tested positive for SARS-CoV-2 were included in the initial analysis and assigned to derivation and validation cohorts (n = 1297 and n = 649, respectively). Stability selection from over 100 baseline predictors for the combined endpoint of progression to the critical phase or COVID-19-related death enabled the development of a simplified score consisting of five predictors: C-reactive protein (CRP), age, clinical disease phase (uncomplicated vs. complicated), serum urea, and D-dimer (abbreviated as CAPS-D score). This score yielded an area under the curve (AUC) of 0.81 (95% confidence interval [CI]: 0.77–0.85) in the validation cohort for predicting the combined endpoint within 7 days of diagnosis and 0.81 (95% CI: 0.77–0.85) during full follow-up. We used an additional prospective cohort of 682 patients, diagnosed largely after the “first wave” of the pandemic to validate the predictive accuracy of the score and observed similar results (AUC for the event within 7 days: 0.83 [95% CI: 0.78–0.87]; for full follow-up: 0.82 [95% CI: 0.78–0.86]). An easily applicable score to calculate the risk of COVID-19 progression to critical illness or death was thus established and validated.
Peri-implantitis: summary and consensus statements of group 3. The 6th EAO Consensus Conference 2021
(2021)
Objective: To evaluate the influence of implant and prosthetic components on peri-implant tissue health. A further aim was to evaluate peri-implant soft-tissue changes following surgical peri-implantitis treatment. Materials and methods: Group discussions based on two systematic reviews (SR) and one critical review (CR) addressed (i) the influence of implant material and surface characteristics on the incidence and progression of peri-implantitis, (ii) implant and restorative design elements and the associated risk for peri-implant diseases, and (iii) peri-implant soft-tissue level changes and patient-reported outcomes following peri-implantitis treatment. Consensus statements, clinical recommendations, and implications for future research were discussed within the group and approved during plenary sessions. Results: Data from preclinical in vivo studies demonstrated significantly greater radiographic bone loss and increased area of inflammatory infiltrate at modified compared to non-modified surface implants. Limited clinical data did not show differences between modified and non-modified implant surfaces in incidence or progression of peri-implantitis (SR). There is some evidence that restricted accessibility for oral hygiene and an emergence angle of >30 combined with a convex emergence profile of the abutment/prosthesis are associated with an increased risk for peri-implantitis (CR). Reconstructive therapy for peri-implantitis resulted in significantly less soft-tissue recession, when compared with access flap. Implantoplasty or the adjunctive use of a barrier membrane had no influence on the extent of peri-implant mucosal recession following peri-implantitis treatment (SR).