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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.
(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.
Aim: To assess the prevalence and severity of periodontitis in patients with moderate chronic kidney disease (CKD) and comparing the results with the self‐reported periodontitis awareness of the study subjects.
Material and methods: The periodontal status of 270 patients with moderate CKD randomly selected from a cohort of 5,217 subjects participating in the prospective observational German Chronic Kidney Disease (GCKD) project was analysed by recording bleeding on probing (BOP), probing pocket depth (PPD) and clinical attachment level (CAL). Furthermore, the awareness of the study subjects of their periodontal conditions was evaluated by a self‐reported questionnaire.
Results: 24.4% of the CKD study patients showed no or only mild signs of periodontal disease, 47.6% displayed moderate and 27% severe periodontitis. Questionnaire data revealed that 62.3% of the study subjects with severe periodontitis were not aware of the presence of the disease, 44.4% denied having received any systematic periodontal therapy so far, although 50% of them indicated to visit their dentist regularly for professional tooth cleanings.
Conclusion: While the clinical study data confirm an increased prevalence of periodontitis in CKD patients, their self‐reported awareness of periodontitis was low.
CD4+ T cell lymphopenia predicts mortality from Pneumocystis pneumonia in kidney transplant patients
(2020)
Background: Pneumocystis jirovecii pneumonia (PcP) remains a life-threatening opportunistic infection after solid organ transplantation, even in the era of Pneumocystis prophylaxis. The association between risk of developing PcP and low CD4+ T cell counts has been well established. However, it is unknown whether lymphopenia in the context of post-renal transplant PcP increases the risk of mortality. Methods: We carried out a retrospective analysis of a cohort of kidney transplant patients with PcP (n = 49) to determine the risk factors for mortality associated with PcP. We correlated clinical and demographic data with the outcome of the disease. For CD4+ T cell counts, we used the Wilcoxon rank sum test for in-hospital mortality and a Cox proportional-hazards regression model for 60-day mortality. Results: In univariate analyses, high CRP, high neutrophils, CD4+ T cell lymphopenia, mechanical ventilation, and high acute kidney injury network stage were associated with in-hospital mortality following presentation with PcP. In a receiver-operator characteristic (ROC) analysis, an optimum cutoff of ≤200 CD4+ T cells/µL predicted in-hospital mortality, CD4+ T cell lymphopenia remained a risk factor in a Cox regression model. Conclusions: Low CD4+ T cell count in kidney transplant recipients is a biomarker for disease severity and a risk factor for in-hospital mortality following presentation with PcP.