Revisiting risk prediction tools for death and end-stage renal disease in older patients with advanced chronic kidney disease: a prospective study.

BACKGROUND: Risk assessment tools for predicting mortality and end-stage renal disease (ESRD) in the elderly with CKD have received growing attention. However, integrating risk equations into a multidimensional approach of elderly with CKD stage 3b-4 is lacking. METHODS: In this prospective observational study, we enrolled CKD stage 3b-4 patients aged ≥ 65 years. Bansal score for predicting mortality risk and Kidney Failure Risk Equation (KFRE) for estimating progression to ESRD were applied. Predicted outcome was compared with actual clinical end-points. All patients underwent comprehensive geriatric assessment (CGA), which is an interdisciplinary multidimensional process for geriatric evaluation and management. RESULTS: Participants (N = 184) were divided into two groups, according to Bansal score: Group 1 (low-risk of death, Bansal score < 7, N = 69) and Group 2 (high-risk of death, Bansal score ≥ 7, N = 115). Group 2 displayed a substantially higher cardiovascular disease burden than Group 1 and was significantly more likely to be depressed and at risk of malnutrition, according to CGA. Thirty-seven patients died, and 16 started dialysis. Group 2 displayed significantly higher all-cause mortality. In the univariable Cox regression, Group 2 had a fourfold increase in the risk of all-cause mortality, as compared with Group 1 (HR = 4.29, 95% CI 1.88-10.26, P < 0.001). Multivariable stepwise Cox analysis showed that Bansal score above 7 remained significantly associated with all-cause mortality (HR = 3.96, 95% CI 1.68-9.29, P < 0.001). Group 2 also displayed higher event rates for dialysis initiation. In Group 1, only four patients started dialysis, and three out of them had a high-risk of progression at baseline, according to KFRE. CONCLUSIONS: Using risk stratification tools and CGA in a population of elderly with advanced CKD, we found that two-thirds of the patients were at high risk of death, malnutrition and depression, with multimorbidity and four times worse probability of survival than those at lower risk of death.

Different aspects of frailty and COVID-19: points to consider in the current pandemic and future ones.

BACKGROUND: Older adults at a higher risk of adverse outcomes and mortality if they get infected with Severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2). These undesired outcomes are because ageing is associated with other conditions like multimorbidity, frailty and disability. This paper describes the impact of frailty on coronavirus disease 2019 (COVID-19) management and outcomes. We also try to point out the role of inflamm-ageing, immunosenescence and reduced microbiota diversity in developing a severe form of COVID-19 and a different response to COVID-19 vaccination among older frail adults. Additionally, we attempt to highlight the impact of frailty on intensive care unit (ICU) outcomes, and hence, the rationale behind using frailty as an exclusion criterion for critical care admission. Similarly, the importance of using a time-saving, validated, sensitive, and user-friendly tool for frailty screening in an acute setting as COVID-19 triage. We performed a narrative review. Publications from 1990 to March 2021 were identified by searching the electronic databases MEDLINE, CINAHL and SCOPUS. Based on this search, we have found that in older frail adults, many mechanisms contribute to the severity of COVID-19, particularly cytokine storm; those mechanisms include lower immunological capacity and status of ongoing chronic inflammation and reduced gut microbiota diversity. Higher degrees of frailty were associated with poor outcomes and higher mortality rates during and after ICU admission. Also, the response to COVID-19 vaccination among frail older adults might differ from the general population regarding effectiveness and side effects. Researches also had shown that there are many tools for identifying frailty in an acute setting that could be used in COVID-19 triage, and before ICU admission, the clinical frailty scale (CFS) was the most recommended tool. CONCLUSION: Older frail adults have a pre-existing immunopathological base that puts them at a higher risk of undesired outcomes and mortality due to COVID-19 and poor response to COVID-19 vaccination. Also, their admission in ICU should depend on their degree of frailty rather than their chronological age, which is better to be screened using the CFS.

The impact of periodontal disease on physical and psychological domains in long-term hemodialysis patients: a cross-sectional study.

PURPOSE: Periodontal disease is a chronic infectious disease. Individuals with end-stage kidney disease (ESKD) experience impaired quality of life (QoL) and low oral health. This is the first comprehensive study which aimed to explore the link between periodontal disease and quality of life, assessed with the Short Form 36-Item Health Survey in hemodialysis patients. METHODS: In total, 101 patients (57 females) with ESKD were recruited from two Romanian dialysis centers. Periodontal disease assessment included the measurement of periodontal disease index, with its three components: the gingival and periodontal index (GP), the bacterial plaque index (PI) and the calculus index (CI). For assessing QoL, we used the Short Form 36-Item Health Survey (SF-36), with its two components: physical component (PCS) and mental component (MCS). RESULTS: The mean age was 52.5 ± 14.3 years. The dialysis vintage was 6.7 ± 5.6 years. According to periodontal status, the mean value of GP was 4.0 ± 1.3, mean PI was 1.8 ± 0.9, and mean CI was 1.3 ± 0.7. Regarding the QoL, the means for PCS and MCS were 38.0 ± 17.3 and 45.0 ± 16.3, respectively. In univariate analysis, the physical and mental components of QoL were significantly associated with the gingival and periodontal index, the bacterial plaque index and the calculus index. In the multivariable linear regression, only the gingival and periodontal index remained significantly associated with physical component (ß = -3.26, p = 0.04, 95% CI -6.39 to -0.13) and mental component (ß = -5.57, p = 0.001, 95% CI -8.74 to -2.41) of QoL. CONCLUSION: Our study shows a high prevalence and severity of periodontal disease. The gingival and periodontal index was associated with low QoL, both on physical and on mental components.