Thirty to sixty per cent of older patients experience functional decline after hospitalisation, associated with an increase in dependence, readmission, nursing home placement and mortality. First step in prevention is the identification of patients at risk. The objective of this study is to develop and validate a prediction model to assess the risk of functional decline in older hospitalised patients.
ObjectivesTo establish the prevalence and course of geriatric syndromes from hospital admission up to 3 months postdischarge and to determine the probability to retain geriatric syndromes over the period from discharge until 3 months postdischarge, once they are present at admission.DesignProspective multicenter cohort study conducted between October 2015 and June 2017.Setting and participantsAcutely hospitalized patients aged 70 years and older recruited from internal, cardiology, and geriatric wards of 6 Dutch hospitals.MeasuresCognitive impairment, depressive symptoms, apathy, pain, malnutrition, incontinence, dizziness, fatigue, mobility impairment, functional impairment, fall risk, and fear of falling were assessed at admission, discharge, and 1, 2, and 3 months postdischarge. Generalized estimating equations analysis were performed to analyze the course of syndromes and to determine the probability to retain syndromes.ResultsA total of 401 participants [mean age (standard deviation) 79.7 (6.7)] were included. At admission, a median of 5 geriatric syndromes were present. Most prevalent were fatigue (77.2%), functional impairment (62.3%), apathy (57.5%), mobility impairment (54.6%), and fear of falling (40.6%). At 3 months postdischarge, an average of 3 syndromes were present, of which mobility impairment (52.7%), fatigue (48.1%), and functional impairment (42.5%) were most prevalent. Tracking analysis showed that geriatric syndromes that were present at admission were likely to be retained. The following 6 geriatric syndromes were most likely to stay present postdischarge: mobility impairment, incontinence, cognitive impairment, depressive symptoms, functional impairment, and fear of falling.ImplicationsAcutely hospitalized older adults exhibit a broad spectrum of highly prevalent geriatric syndromes. Moreover, patients are likely to retain symptoms that are present at admission postdischarge. Our study underscores the need to address a wide range of syndromes at admission, the importance of communication on syndromes to the next care provider, and the need for adequate follow-up care and syndrome management postdischarge.
Background:In hospitalized patients with COVID-19, the dosing and timing of corticosteroids vary widely. Low-dose dexamethasone therapy reduces mortality in patients requiring respiratory support, but it remains unclear how to treat patients when this therapy fails. In critically ill patients, high-dose corticosteroids are often administered as salvage late in the disease course, whereas earlier administration may be more beneficial in preventing disease progression. Previous research has revealed that increased levels of various biomarkers are associated with mortality, and whole blood transcriptome sequencing has the ability to identify host factors predisposing to critical illness in patients with COVID-19.Objective:Our goal is to determine the most optimal dosing and timing of corticosteroid therapy and to provide a basis for personalized corticosteroid treatment regimens to reduce morbidity and mortality in hospitalized patients with COVID-19.Methods:This is a retrospective, observational, multicenter study that includes adult patients who were hospitalized due to COVID-19 in the Netherlands. We will use the differences in therapeutic strategies between hospitals (per protocol high-dose corticosteroids or not) over time to determine whether high-dose corticosteroids have an effect on the following outcome measures: mechanical ventilation or high-flow nasal cannula therapy, in-hospital mortality, and 28-day survival. We will also explore biomarker profiles in serum and bronchoalveolar lavage fluid and use whole blood transcriptome analysis to determine factors that influence the relationship between high-dose corticosteroids and outcome. Existing databases that contain routinely collected electronic data during ward and intensive care admissions, as well as existing biobanks, will be used. We will apply longitudinal modeling appropriate for each data structure to answer the research questions at hand.Results:As of April 2023, data have been collected for a total of 1500 patients, with data collection anticipated to be completed by December 2023. We expect the first results to be available in early 2024.Conclusions:This study protocol presents a strategy to investigate the effect of high-dose corticosteroids throughout the entire clinical course of hospitalized patients with COVID-19, from hospital admission to the ward or intensive care unit until hospital discharge. Moreover, our exploration of biomarker and gene expression profiles for targeted corticosteroid therapy represents a first step towards personalized COVID-19 corticosteroid treatment.Trial Registration:ClinicalTrials.gov NCT05403359; https://clinicaltrials.gov/ct2/show/NCT05403359International Registered Report Identifier (IRRID):DERR1-10.2196/48183
MULTIFILE
