期刊
ANZ JOURNAL OF SURGERY
卷 90, 期 7-8, 页码 1253-1258出版社
WILEY
DOI: 10.1111/ans.15695
关键词
30-day readmission; hospital readmission; patient characteristics; risk factors; total knee arthroplasty; total knee replacement; unplanned readmission
类别
资金
- National Health and Medical Research Council of Australia (NHMRC) Centre for Research Excellence in Total Joint Replacement [APP1116235]
- NHMRC Career Development Fellowship [APP1122526]
- NHMRC Practitioner Fellowship [APP1154203]
Osteoarthritis is a debilitating condition as well as a growing global health problem, and total knee arthroplasty (TKA) is an effective treatment for advanced disease. Unplanned 30-day hospital readmission is an indicator of complications, which is a significant financial burden on healthcare systems. We reviewed the literature to better understand the patient-related factors associated with unplanned 30-day readmission following TKA. MEDLINE and EMBASE were searched for studies reporting on patient-related risk factors for unplanned 30-day readmission following primary or revision TKA for any indication. The impact of specific medical comorbidities on increasing the risk of 30-day readmission following TKA is quite well established. The following comorbidities are strongly associated with readmission: bleeding disorder, diabetes, chronic kidney disease and dialysis, chronic immunosuppressant use and history of cancer. Other significant comorbidities include: dementia; depression; haematological (coagulopathy and anaemia), cardiovascular (atrial fibrillation, cardiovascular disease, coronary artery disease and congestive heart failure), respiratory (chronic obstructive pulmonary disease) and liver diseases; and cerebrovascular accident/transient ischaemic attack (but only in revision TKA patients). The influence of variation in sex, age and body mass index each demonstrate a more complex pattern. A systematic review and meta-analysis is required to quantify the impact of the various patient-related factors on 30-day readmission following TKA. Clinicians can use this information in preoperative decision-making.
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