Associations of Wellbeing Levels, Changes, and Within-Person Variability With Late-Life All-Cause Mortality Across 12 Years: Contrasting Hedonic vs. Eudaimonic Wellbeing Among Very Old Adults

Advanced old age has been characterized as a biologically highly vulnerable life phase. Biological, morbidity-, and cognitive impairment-related factors play an important role as mortality predictors among very old adults. However, it is largely unknown whether previous findings confirming the role of different wellbeing domains for mortality translate to survival among the oldest-old individuals. Moreover, the distinction established in the wellbeing literature between hedonic and eudaimonic wellbeing as well as the consideration of within-person variability of potentially relevant mortality predictors has not sufficiently been addressed in prior mortality research. In this study, we examined a broad set of hedonic and eudaimonic wellbeing indicators, including their levels, their changes, as well as their within-person variability, as predictors of all-cause mortality in a sample of very old individuals. We used data from the LateLine study, a 7-year longitudinal study based on a sample of n = 124 individuals who were living alone and who were aged 87–97 years (M = 90.6, SD = 2.9) at baseline. Study participants provided up to 16 measurement occasions (mean number of measurement occasions per individual = 5.50, SD = 4.79) between 2009 and 2016. Dates of death were available for 118 individuals (95.2%) who had deceased between 2009 and 2021. We ran longitudinal multilevel structural equation models and specified between-person level differences, within-person long-term linear change trends, as well as the “detrended” within-person variability in three indicators of hedonic (i.e., life satisfaction and positive and negative affect) and four indicators of eudaimonic wellbeing (i.e., purpose in life, autonomy, environmental mastery, and self-acceptance) as all-cause mortality predictors. Controlling for age, gender, education, and physical condition and testing our sets of hedonic and eudaimonic indictors separately in terms of their mortality impact, solely one eudaimonic wellbeing indicator, namely, autonomy, showed significant effects on survival. Surprisingly, autonomy appeared “paradoxically” related with mortality, with high individual levels and intraindividual highly stable perceptions of autonomy being associated with a shorter residual lifetime. Thus, it seems plausible that accepting dependency and changing perceptions of autonomy over time in accordance with objectively remaining capabilities might become adaptive for survival in very old age.

Increased Risk of Poor Clinical Outcome in COVID-19 Patients with Diabetes Mellitus and in-hospital Mortality Predictors: A Retrospective Cohort from a Tertiary Hospital in Indonesia

Aim: To determine association between diabetes in confirmed cases of COVID-19 and intensive care admission and in-hospital mortality, evaluate several laboratory parameters as mortality predictor, and develop predictors of in-hospital mortality among diabetics with COVID-19. Methods: This retrospective cohort recruited all cases of COVID-19 hospitalized in Fatmawati General Hospital during March to October 2020. Inclusion criteria was RT-PCR confirmed cases of COVID-19 who aged 18 years and older while exclusion criteria were incomplete medical record or cannot be found and pregnant women. Results: We enrolled 506 participants to this study with median age of 51 years (IQR:22), female (56.32%), and diabetes (28.46%). Diabetes increased intensive care admission (adjusted OR:6.07;95%CI:3.52-10,43) and in-hospital mortality (adjusted OR:50;95%CI:1.61-3.89). In predicting in-hospital mortality, ferritin and lactate dehydrogenase offered an acceptable discrimination, AUC:0.71 (95%CI: 0.62-0.79) and AUC:0.70 (95%CI: 0.61-0.78), respectively. The optimal cut-off of predicting mortality for ferritin was 786 g/mL and for LDH was 514.94 u/L. Factors include age above 70 years old, RBGs level on admission above 250 mg/dL or below 140 mg/dL, ferritin level above 786 ng/mL, and presence of ARDS increased the odds of mortality among individuals with diabetes. Conclusions: Diabetes increases risk intensive care admission and in hospital mortality in COVID-19. Multivariate analysis showed that older age, RBG on admission, high ferritin level, presence of ARDS increased the odds of mortality among individuals with diabetes.

The profile of lactate, albumin, and lactate/albumin ratio as predictors of mortality in sepsis patients

Background. Oxygenation disturbances in sepsis patients may cause lactate levels increase which is proportional to the severity of the inflammation, followed by decrease in albumin levels. Combination of these two parameters is expected to be predictor of mortality in patients with sepsis. The aim of this study is to investigate the profile of lactate, albumin, and lactate/albumin ratio as mortality predictors in patient with sepsis. Methods. This prospective cohort study was conducted in the ICU of dr. Saiful Anwar Hospital, Malang, from January to May 2019. Subjects were 82 patients with sepsis (SOFA score > 2). Lactate and albumin levels were measured on the first day of hospitalization. Lactate levels were examined by colorimetric method, albumin was examined by BCG method. The instrument used was Cobas 501. Comparation was carried out using the T-Test/Mann–Whitney test. Prediction of mortality risk was done using relative risk (RR) determination. Results. Significant difference was observed in albumin levels between sepsis patients who survived and who died (p = 0.045). No significant differences were observed in lactate levels and lactate/albumin ratio between sepsis patients who survived and who died (p = 0.211, 0.119, respectively). Relative risks were 3.034 for lactate, 3.667 for albumin, and 4.400 for lactate/albumin ratio. Conclusion. In patients with sepsis, albumin level is the best variable in predicting mortality, followed by lactate/albumin ratio and lactate value. Further study that implements repeated measurement of lactate and albumin in 6 and 12 hours is required to better predict the mortality of sepsis patients.

Prognostic value of atrial fibrillation in COVID-19 admitted patients

Introduction/Background COVID-19 is the disease caused by SARS-Cov2. Various prognostic factors have been studied and described. Atrial fibrillation (AF) is an arrhythmia associated with increased complications and mortality in acute situations. The onset of AF in patients hospitalized for COVID-19 could associate a worse prognosis during admission and in the short term. Purpose The objective of this study is to evaluate the adverse events in the population admitted for COVID-19 that develops AF as well as its possible prognostic value. Methods Retrospective, cohort study on 391 patients admitted for COVID-19 in a tertiary hospital. Descriptive and comparative analysis between those with new onset AF versus those who had AF previously in terms of: baseline characteristics, In hospital mortality, bleeding and thrombotic phenomena. Follow-up during three months after discharge. Univariate and multivariate analysis of in-hospital and three-months mortality is also performed. Results 391 patients were included. 21 of them developed AF. These patients are older, more hypertensive and with more history of cardiopathy. At admission, they presented higher mortality (52.4% vs 19.7%; p<0.001) and bleeding (19% vs 8.4%; p<0.001), also compared to those with previous AF (not significant). New onset AF is not an independent predictor of in-hospital mortality, but rather an independent predictor of three-month mortality. In-hospital mortality predictors are: age >70 years, BCRSS scale >2 points, and severe hypotension. Three-month mortality predictors are: high-sensitive T-troponin <50ng/dl, age >70 years, BCRSS scale >2, creatinine >1.5 mg/dl and new-onset AF. Conclusions New onset AF appears in 5,3% of these hospitalized patients, who have greater comorbidity, bleeding and in-hospital mortality as well as three-months mortality. New onset AF is not an independent predictor of in-hospital mortality but rather an independent predictor of mortality during the first three months after discharge FUNDunding Acknowledgement Type of funding sources: None. Table 1 Figure 1. ROC curves