Evaluation of falls in older persons in the emergency department during the early Coronavirus-2019 pandemic and pre-pandemic periods.

PURPOSE: This study aimed to investigate the clinical characteristics, outcomes and healthcare costs of older patients presented to the emergency department (ED) with falls in the periods before and during the Coronavirus disease-2019 (COVID-19) pandemic. METHODS: Hospital records one year before and after the onset of the COVID-19 pandemic were retrospectively analyzed through "International Statistical Classification of Diseases-10th Revision" codes. Age, gender, falls, triage classification, length of stay (LOS) in the hospital and the ED, COVID-19 status, Glasgow Coma scale, consultations-comorbidities, injury status, outcomes in the ED, and costs were recorded. RESULTS: The study comprised of 3187 patients aged ≥ 65 years admitted to the ED of a university hospital between March 2019 and 2021. In terms of pre-pandemic and pandemic periods; older patients presenting with falls to the ED, consultations, Charlson Comorbidity Index, and LOS in the ED were lower in the pandemic period, but costs were higher (p = 0.03, p = 0.01, p = 0.01, p = 0.01 and p = 0.02, respectively). Hospitalization/mortality rates were higher in COVID-19 positive patients (77.2%) than in COVID-19 negative patients (4.6%) within the pandemic period and the patients in the pre-pandemic period (22.8%), and the costs, as well (both p = 0.01). CONCLUSION: Though the number of fall-related presentations of older persons to the ED, comorbidity burden, consultations, and the LOS in the ED was lower, direct costs were higher during the pandemic period, particularly for COVID-19 positive older patients admitted to ED with falls than the pre-pandemic period, and those patients were with poorer outcomes.

Performance Evaluation of Machine Learning Algorithms for Sarcopenia Diagnosis in Older Adults.

BACKGROUND: Sarcopenia is a progressive and generalized skeletal muscle disorder. Early diagnosis is necessary to reduce the adverse effects and consequences of sarcopenia, which can help prevent and manage it in a timely manner. The aim of this study was to identify the important risk factors for sarcopenia diagnosis and compare the performance of machine learning (ML) algorithms in the early detection of potential sarcopenia. METHODS: A cross-sectional design was employed for this study, involving 160 participants aged 65 years and over who resided in a community. ML algorithms were applied by selecting 11 features-sex, age, BMI, presence of hypertension, presence of diabetes mellitus, SARC-F score, MNA score, calf circumference (CC), gait speed, handgrip strength (HS), and mid-upper arm circumference (MUAC)-from a pool of 107 clinical variables. The results of the three best-performing algorithms were presented. RESULTS: The highest accuracy values were achieved by the ALL (male + female) model using LightGBM (0.931), random forest (RF; 0.927), and XGBoost (0.922) algorithms. In the female model, the support vector machine (SVM; 0.939), RF (0.923), and k-nearest neighbors (KNN; 0.917) algorithms performed the best. Regarding variable importance in the ALL model, the last HS, sex, BMI, and MUAC variables had the highest values. In the female model, these variables were HS, age, MUAC, and BMI, respectively. CONCLUSIONS: Machine learning algorithms have the ability to extract valuable insights from data structures, enabling accurate predictions for the early detection of sarcopenia. These predictions can assist clinicians in the context of predictive, preventive, and personalized medicine (PPPM).

Predictability of Metabolic Syndrome Diagnosed by Body Mass Index for Cardiovascular Risk in Older Patients Treated with Levothyroxine.

BACKGROUND: We investigated the prevalence and metabolic features of two definitions of meta-bolic syndrome (MS) between older patients with chronic thyroiditis treated with levothyroxine (LT4) and controls. We also assessed the ability of both criteria to predict cardiovascular (CV) risk. METHODS: This cross-sectional, retrospective study included individuals aged ≥60 years who attended a geriatric outpatient clinic between January 2015 and December 2018. The LT4 treatment group was classified as having high or low CV risk based on the Framingham score. RESULTS: This study enrolled 111 patients with chronic thyroiditis treated with LT4 and 131 patients without thyroid disease as the control group. The prevalence of MS according to the World Health Organization (WHO) criteria and American Association of Clinical (AACE) criteria was similar in the LT4 treatment (21.6% and 26.1%, respectively) and the control (30.5% and 34.4%, respectively) groups (p>0.05). While the prevalence of MS and CV risk did not differ significantly between the control and LT4 treatment groups, the prevalence of MS with both definitions was higher among individuals with high CV risk in the LT4 treatment group (p<0.05). For the prediction of CV risk, the sensitivity and specificity of the AACE criteria were higher than those of the WHO criteria in the LT4 treatment group. Conclusions: The prevalence of MS in euthyroid patients treated with LT4 was similar to that of patients without thyroid disease. When the LT4 treatment group was classified based on CV risk, MS was more common in those with a high CV risk.

The Relationship of Balance Disorders with Falling, the Effect of Health Problems, and Social Life on Postural Balance in the Elderly Living in a District in Turkey.

The aim of this study was to determine the prevalence of balance disorders; the effects of sociodemographic, medical, and social conditions on postural balance; and the relationship between balance and falls in elderly individuals. The study design was cross-sectional. A total of 607 community-dwelling elderly individuals with a mean age of 73.99 ± 6.6 years were enrolled after being selected by stratified random sampling. The study was performed as a face-to-face survey in the homes of elderly individuals. Sociodemographic and medical data were obtained from elderly individuals using the Elderly Identification Form. Balance disorders were determined using the Berg Balance Scale (BBS). In this study, the prevalence of balance disorders was found to be 34.3% in the community-dwelling elderly. Older age, physical disability, having four or more chronic illnesses, the presence of incontinence, having a history of falls, not walking regularly, absence of free time activity, and obesity were found to be associated with an increased prevalence of balance disorders. Balance disorders are commonly seen in the elderly and may be triggered by a variety of biological and social factors. It is crucial to develop and implement national health and social policies to eliminate the causes of this problem, as well as to prioritize preventive health services in the ever-increasing elderly population.