Abstract
OBJECTIVE: The prognosis of older adults is strongly influenced by the relation of multifactorial geriatric syndromes (GS) and their health-maintaining counterparts, geriatric resources (GR). The present analysis aimed to identify clusters of comorbidities, GS and GR, and to measure their multidimensional prognostic signature in older patients admitted to different healthcare settings. DESIGN: Pooled secondary analysis of three longitudinal interventional studies with the 3- and 6-month follow-up data collection on mortality and rehospitalisation. SETTING: Inpatients in an internal medicine ward (n=495), inpatients in an ageing medicine ward (n=123) and outpatients from a general practice (n=105). PARTICIPANTS: A total of 734 patients with multimorbidity who aged over 60 years were recruited between August 2016 and July 2020 (mean age 77.8 years, SD 6.2 and 43% female). OUTCOME MEASURES: Comprehensive Geriatric Assessment (CGA), including Cumulative Illness Rating Scale (CIRS), 17 GS and 10 GR, and the CGA-based Multidimensional Prognostic Index (MPI) as a measure of multidimensional prognosis and frailty were assessed. Based on a general linear model and a hierarchical clustering method, clusters of comorbidities, GS and GR were obtained. RESULTS: The study identified five clusters of GR-related GS, namely, psychosocial, iatrogenic, neurovegetative, sensorimotor and fluid dysbalance, along with two clusters related to GR, focusing on independence achievement and requirements- circumstances. Additionally, two clusters were identified pertaining to the CIRS, encompassing sensory-vegetative and heart-kidney morbidity. Patients within the iatrogenic cluster exhibited significantly higher MPI and readmissions during follow-up compared with those outside this cluster (p<0.001). Furthermore, membership in the fluid dysbalance or psychosocial cluster was associated with a significantly increased mortality rate during follow-up (p<0.001). CONCLUSIONS: A feasible combination of GR and GS in clinical routine enables the identification of clusters with clear prognostic relevance, which may improve prognosis through tailored treatment. TRIAL REGISTRATION NUMBERS: DRKS00010606/DRKS00013791/DRKS00017094 MPI_InGAH, DRKS00012820 MPI_NoGeP and DRKS00015996 VNKN.