Role of Frailty in Prediction of Hospitalized Older Adult Patients Outcomes: A Prospective Study.

Abstract

BACKGROUND/AIM\nFrailty is associated with an increased risk of negative short-term and long-term hospital outcomes. This study aimed to evaluate the role of frailty in predicting readmission, length of stay, and quality of life in the hospitalized older adults.\n\n\nMATERIALS AND METHODS\nThis observational study was conducted at Ziaiyan Hospital, Tehran, Iran. 304 participants (65-85 years), were enrolled through the inclusion criteria from August to December 2019. The Frailty Index (FI) was assessed by the Minimum Data Set-Home Care. Readmission was obtained through telephone interviews. The length of stay was gathered by the patient?s hospital records, and the EuroQol questionnaire was used for assessing the quality of life. Data were collected by a researcher nurse at the admission time, 30, 60, and 90 days after discharge. The logistic regression model and repeated measures ANOVA were employed to analyze the association between frailty and outcomes.\n\n\nRESULTS\nAccording to FI, 102 (33.55%) participants were pre-frail, whereas 35 (11.51%) were frail. In the fully-adjusted model for readmission, the pre-frail participants had a higher risk of readmission at the hospital in comparison with the non-frail and frail groups (OR=1.88, 95% CI =1.90?3.26), and also for GP visits, frail patients showed nearly signi?cant differences (OR =2.45, 95% CI =0.99?6.06) but there were no differences between frail and pre-frail patients in readmissions in the emergency ward. In a fully-adjusted prolonged stay model, pre-frail patients had a higher probability to stay longer in hospital (OR =2.28, 95% CI: 1.24 - 4.18). The fully-adjusted model for QoL showed, frail patients were more prone to the declined levels of QoL in comparison with pre-frail patients (OR =10.77, 95% CI: 3.97 - 29.18).\n\n\nCONCLUSIONS\nThe findings indicated that frailty worsened negative outcomes and declined QoL. Early diagnosis in hospital settings could be beneficial for designing optimal care plans for the frail and pre-frail patients.