Infections are leading causes of morbidity and mortality in the advanced aged. Various factors including immunosenescens, comorbid chronic diseases, and alterations in normal physiological organ functions may modify the frequency and severity of infections in elderly patients. Normal body reactions to ensuing infection, such as increased body temperature, may be blunted in those patients causing difficulties in differential diagnosis between infection and other diseases. In severe infections the respiratory and urinary tracts are the most frequently involved systems which may be accompanied by severe sepsis. Bacteremia and sepsis are also associated with indwelling vascular catheters in the elderly who are admitted to the intensive care unit (ICU). Older patients are more vulnerable to the Clostridioides difficile infection, as well. Although the general management of infections in severely ill elderly patients is not different than in younger patients, meticulous care in fluid management and careful individualized optimization in antibiotic therapy, along with the other principals of antimicrobial stewardship are warranted in order to prevent increased mortality caused by infection. Organized team management when treating critically ill elderly patients in the ICU is essential and will reduce the morbidity and mortality due to infection in such patients.

Background The Global Leadership Initiative on Malnutrition (GLIM) has developed new criteria for diagnosing patients with malnutrition. The aims of this study were to investigate the prevalence of malnutrition according to the GLIM criteria, Subjective Global Assessment (SGA), and Nutrition Risk Screening 2002 (NRS‐2002) and their association with long‐term mortality in patients hospitalized for acute illnesses. Methods A retrospective analysis was performed in a sample of 231 patients with different comorbidities hospitalized for acute illnesses in medical or surgical wards. Nutrition status was retrospectively assessed with GLIM criteria using patients’ records at admission in addition to SGA and NRS‐2002. The agreement between the tools was calculated using κ statistics, and the association of malnutrition according to each tool and mortality were analyzed using Cox regression analysis. Results The mean age of the patients was 62.2 ± 18.2 years, and 56.7% were women. The prevalence of malnutrition was 35.9% with GLIM criteria, 37.2% with SGA, and 38% with NRS‐2002. The agreement between tools was good (GLIM‐SGA, κ = 0.804; GLIM–NRS‐2002, κ = 0.784). During a median follow‐up period of 63.2 months, 79 deaths occurred. The sensitivity in predicting 5‐year mortality was 59.49%, 58.23%, and 58.23%, and specificity was 76.32%, 73.68%, and 72.37% for GLIM criteria, SGA, and NRS‐2002, respectively. After adjusting for confounders, GLIM criteria best predicted 5‐year mortality (hazard ratio, 3.09; 95% CI, 1.96–4.86; P < .001). Conclusions Our findings support the effectiveness of GLIM in diagnosing malnutrition and predicting all‐cause mortality among patients hospitalized for acute illnesses.

High prevalence of PIMs and PPOs were found in geriatric patients. Number of medications, female gender, and dependency were associated with PIM. Age, higher scores of Geriatric Depression Scale, DM, and COPD were related with PPOs.

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Background A novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) occurred in China in December 2019 and has spread globally. In this study we aimed to describe the clinical characteristics and outcomes of hospitalized older adults with coronavirus disease 2019 (COVID-19) in Turkey. Methods We retrospectively analyzed the clinical data of hospitalized patients aged ≥ 60 years with confirmed COVID-19 from March 11, 2020, to May 27, 2020 using nationwide health database. Results In this nationwide cohort, a total of 16942 hospitalized older adults with COVID-19 were enrolled, of whom 8635 (51%) were women. Mean age was 71.2 ± 8.5 years, ranging from 60 to 113 years. Mortality rate before and after curfew was statistically different (32.2% vs 17.9%; p & 0.001, respectively). Through multivariate analysis of the causes of death in older patients, we found that male gender, diabetes mellitus, heart failure, chronic kidney disease, dementia, cancer, admission to intensive care unit, computed tomography finding compatible with COVID-19 were all significantly associated with mortality in entire cohort. In addition to abovementioned risk factors, in patients aged between 60-79 years, coronary artery disease, oxygen support need, total number of drugs, and cerebrovascular disease during hospitalization, and in patients 80 years of age and older acute coronary syndrome during hospitalization were also associated with increased risk of mortality. Conclusions In addition to the results of previous studies with smaller sample size, our results confirmed the age-related relationship between specific comorbidities and COVID-19 related mortality.

Background: Sarcopenic obesity (SO) is the coexistence of sarcopenia and obesity in an individual. The present study is designed to define the usefulness of skeletal muscle ultrasonography (US) in the definition of SO. Methods: Eighty-nine participants aged ≥65 whose body mass index (BMI, kg/m 2) was ≥30 were consecutively enrolled in an outpatient clinic of geriatric medicine. All underwent comprehensive geriatric assessment. US measurements were obtained in 6 different muscles consisting of core and limb muscles. We defined SO as the presence of low muscle function (defined by a handgrip strength < 27 kg in males and <16 kg in females) and high BMI (≥30). Results: The median age of the participants was 72 (65-85) years; 81% were female, and 35% (n = 31) had SO. Anthropometric parameters that estimate muscle mass were lower in the sarcopenic group, but estimations of muscle mass with bioelectrical impedance analysis (BIA) did not differ between groups. All US estimations of muscle mass were lower in sarcopenic obese participants, albeit not all significantly. RF muscle cross-sectional area (RF CSA) and abdominal subcutaneous fat thickness were most strongly correlated with grip strength (r = 0.477 and r = −508, respectively). Receiver operating characteristic analysis suggested that the optimum cutoff point of RF CSA for SO was ≤5.22 cm 2 , with 95.8% sensitivity and 46.7% specificity (area under the curve: 0.686). Conclusions: US evaluation of muscle mass may be more accurate than BIA-derived skeletal muscle index assessment for the diagnosis of SO.

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