Consistent with our previous review , several domains of GA are associated with adverse outcomes .
BACKGROUND Our previous systematic review of geriatric assessment ( GA ) in oncology included a literature search up to November 2010 .
However , the quickly evolving field warranted an up date .
Aims of this review : ( i ) provide an overview of all GA instruments developed and /or in use in the oncology setting ; ( ii ) evaluate effectiveness of GA in predicting/modifying outcomes ( e.g. treatment decision impact , treatment toxicity , mortality , use of care ) .
Frailty predicts increased hospital and six-month healthcare cost following colorectal surgery in older adults.
BACKGROUND The purpose of this study was to determine the relationship of frailty and 6-month postoperative costs . METHODS Subjects aged ≥ 65 years undergoing elective colorectal operations were enrolled in a prospect i ve observational study . Frailty was assessed by a vali date d measure of function , cognition , nutrition , comorbidity burden , and geriatric syndromes . Frailty was quantified by summing the number of positive characteristics in each subject . RESULTS Sixty subjects ( mean age , 75 ± 8 years ) were studied . Inpatient mortality was 2 % ( n = 1 ) . Overall , 40 % of subjects ( n = 24 ) were considered nonfrail , 22 % ( n = 13 ) were prefrail , and 38 % ( n = 22 ) were frail . With advancing frailty , hospital costs increased ( P < .001 ) and costs from discharge to 6-months increased ( P < .001 ) . Higher degrees of frailty were related to increased rates of discharge institutionalization ( P < .001 ) and 30-day readmission ( P = .044 ) . CONCLUSIONS A simple , brief preoperative frailty assessment accurately forecasts increased surgical hospital costs and postdischarge to 6-month healthcare costs after colorectal operations in older adults
Consistent with our previous review , several domains of GA are associated with adverse outcomes .
BACKGROUND Our previous systematic review of geriatric assessment ( GA ) in oncology included a literature search up to November 2010 .
However , the quickly evolving field warranted an up date .
Aims of this review : ( i ) provide an overview of all GA instruments developed and /or in use in the oncology setting ; ( ii ) evaluate effectiveness of GA in predicting/modifying outcomes ( e.g. treatment decision impact , treatment toxicity , mortality , use of care ) .