A comparison of three approaches to measuring frailty to determine adverse health outcomes in critically ill patients

Author:

Hao Benchuan12,Chen Tao3,Qin Ji12,Meng Wenwen3,Bai Weimin4,Zhao Libo12,Ou Xianwen5,Liu Hongbin2,Xu Weihao6

Affiliation:

1. Medical School of Chinese PLA , Beijing 100039 , China

2. Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital , Beijing 100039 , China

3. Department of Cardiology, The Sixth Medical Centre, Chinese PLA General Hospital , Beijing 100037 , China

4. Department of Emergency, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, People’s Hospital of Henan University , Zhengzhou 463599 , China

5. College of Information Science & Technology Haikou, Hainan University , Hainan 570100 , China

6. Haikou Cadre's Sanitarium of Hainan Military Region , Haikou 570203 , China

Abstract

Abstract Background studies comparing different frailty measures in intensive care unit settings are lacking. We aimed to compare the frailty index based on physiological and laboratory tests (FI-Lab), modified frailty index (MFI) and hospital frailty risk score (HFRS) to predict short-term outcomes for critically ill patients. Methods we conducted a secondary analysis of data from the Medical Information Mart for Intensive Care IV database. Outcomes of interest included in-hospital mortality and discharge with need for nursing care. Results the primary analysis was conducted with 21,421 eligible critically ill patients. After adjusting for confounding variables, frailty as diagnosed by all three frailty measures was found to be significantly associated with increased in-hospital mortality. In addition, frail patients were more likely to receive further nursing care after being discharged. All three frailty scores could improve the discrimination ability of the initial model generated by baseline characteristics for adverse outcomes. The FI-Lab had the best predictive ability for in-hospital mortality, whereas the HFRS had the best predictive performance for discharge with need for nursing care amongst the three frailty measures. A combination of the FI-Lab with either the HFRS or MFI improved the identification of critically ill patients at increased risk of in-hospital mortality. Conclusions frailty, as assessed by the HFRS, MFI and FI-Lab, was associated with short-term survival and discharge with need for nursing care amongst critically ill patients. The FI-Lab was a better predictor of in-hospital mortality than the HFRS and MFI. Future studies focusing on FI-Lab are warranted.

Funder

Laboratory for Computational Physiology

Massachusetts Institute of Technology

Publisher

Oxford University Press (OUP)

Subject

Geriatrics and Gerontology,Aging,General Medicine

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