Background. The prognostic value of the neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) in patients with COVID-19 is rarely described in older adults. We aimed to estimate the prognostic value of NLR and PLR, determining the mortality of adults over 60 years of age hospitalized for COVID-19 in three hospitals in Peru from March to May 2020. Methods. We performed a secondary analysis of data from a retrospective cohort carried out in Lambayeque, Peru, from March 18 to May 13, 2020. Older adults hospitalized for COVID-19 were included. The outcome variable was in-hospital mortality by all causes, while the exposure variable was the NLR and PLR (categorized in tertiles and numerically, performing a logarithmic transformation). We included sociodemographic variables, comorbidities, vital functions, laboratory markers, and treatment received during hospital stay. We evaluated the association between NLR and PLR using the hazard ratio (HR) in a Cox regression model. We estimated HR with their respective 95% confidence intervals (95% CI). We estimated cumulative/dynamic time-dependent ROC curves and reported area under the curve ROC (AUC-ROC) for 15-, 30-, and 60-day mortality with their respective simultaneous confidence intervals (confidence bands (CB)). Also, we estimated an optimal cut-off point based on the maximally selected rank statistics. Results. A total of 262 hospitalized older adults were analyzed, 71.8% ( n = 188 ) of whom were male with a median age of 70 years (interquartile range: 65-78). The mean NLR and PLR were 16.8 (95% CI: 14.9-18.7; SD: 15.5) and 50.3 (95% CI: 44.6-55.9; SD: 46.3), respectively. The mortality rate was 68.7% (95% CI: 62.7-74.3). The adjusted Cox regression analysis showed that the high NLR ( adjusted   HR   aHR = 2.12 ; 95% CI: 1.43-3.14) and PLR ( aHR = 1.90 ; 95% CI: 1.30-2.79) tertiles were associated with a higher risk of mortality. The maximum AUC-ROC values at 60 days of follow-up for NLR and PLR were 0.713 (95%CB: 0.627-0.800) and 0.697 (95%CB: 0.583-0.754), respectively. Conclusions. The NLR and PLR are predictors of higher risk of mortality, and these results suggest that both could be reliable and practical markers for the identification of older adults at high risk of mortality by COVID-19. NLR and PLR have prognostic value, with an AUC greater than 0.5; however, by themselves, they are weak prognostic markers. It is important to carry out future studies incorporating these two markers into preexisting models or designing new ones considering them.

ObjectiveTo evaluate the role of cognitive frailty and its components as risk factors of mortality in older adults of the Centro Médico Naval (CEMENA) in Callao, Peru during 2010-2015.MethodsWe performed a secondary analysis of data from a prospective cohort that included older adults (60 years and older) treated at the CEMENA Geriatrics service between 2010–2015. Frailty was defined as the presence of three or more criteria of the modified Fried Phenotype. Cognitive impairment was assessed using the Peruvian version of the Mini Mental State Examination (MMSE), considering a score <21 as cognitive impairment. Cognitive frailty was defined as the coexistence of both. In addition, we included sociodemographic characteristics, medical and personal history, as well as the functional evaluation of each participant.ResultsWe included 1,390 older adults (mean follow-up: 2.2 years), with a mean age of 78.5 ± 8.6 years and 59.6% (n = 828) were male. Cognitive frailty was identified in 11.3% (n = 157) and 9.9% (n = 138) died during follow-up. We found that cognitive frailty in older adults (aHR = 3.57; 95%CI: 2.33–5.49), as well as its components, such as sedentary behavior and cognitive impairment (aHR = 7.05; 95%CI: 4.46–11.13), weakness and cognitive impairment (aHR = 6.99; 95%CI: 4.41–11.06), and exhaustion and cognitive impairment (aHR = 4.51; 95%CI: 3.11–6.54) were associated with a higher risk of mortality.ConclusionCognitive frailty and its components were associated with a higher risk of mortality in older adults. It is necessary to develop longitudinal studies with a longer follow-up and that allow evaluating the effect of interventions in this vulnerable group of patients to limit adverse health outcomes, including increased mortality.

Objectives We aimed to evaluate the role of SARC-F and SARC-CalF scores as risk factors for mortality in adults over 60 years of age with cancer of the Centro Médico Naval (CEMENA) in Callao, Peru during 2012–2015. Methods We performed a secondary analysis of data from a prospective cohort carried out from September 2012 to February 2013 in the Geriatrics Department of CEMENA. The outcome variable was mortality at two years of follow-up, while the exposure variable was the risk of sarcopenia assessed using the SARC-F and SARC-CalF scales. We carried out Cox proportional-hazards models to assess the role of SARC-F and SARC-CalF scores as risk factors for mortality. We estimated crude (cHR) and adjusted (aHR) hazard ratios (HR) with their respective 95% confidence intervals (95%CI). Likewise, we calculated the area under the curve (AUC) of both exposure variables in relation to mortality. Results We analyzed data from 922 elderly men with cancer; 43.1% (n=397) were between 60 and 70 years old. 21.5% (n=198) and 45.7% (n=421) were at risk of sarcopenia according to SARC-F and SARC-CalF, respectively, while the incidence of mortality was 22.9% (n=211). In the adjusted Cox regression model, we found that the risk of sarcopenia measured by SARC-F (aHR=2.51; 95%CI: 1.40–2.77) and SARC-CalF (aHR=2.04; 95%CI: 1.55–4.02) was associated with a higher risk of death in older men with cancer. In the diagnostic performance analysis, we found that the AUC for mortality prediction was 0.71 (95%CI: 0.68–0.75) for SARC-F and 0.80 (95%CI: 0.78–0.82) for SARC-CalF. Conclusions The risk of sarcopenia evaluated by SARC-F and SARC-CalF scores was associated with an increased risk of mortality in older men with cancer. Both scales proved to be useful and accessible instruments for the identification of groups at risk of mortality. Electronic Supplementary Material Supplementary material is available in the online version of this article at 10.1007/s12603-022-1844-2.