What Factors Predict Adverse Discharge Disposition in Patients Older Than 60 Years Undergoing Lower-extremity Surgery? The Adverse Discharge in Older Patients after Lower-extremity Surgery (ADELES) Risk Score

被引:22
|
作者
Schaefer, Maximilian S. [1 ,2 ,3 ]
Hammer, Maximilian [1 ,2 ]
Platzbecker, Katharina [1 ,2 ]
Santer, Peter [1 ,2 ,4 ]
Grabitz, Stephanie D. [1 ,2 ]
Murugappan, Kadhiresan R. [1 ,2 ]
Houle, Tim [2 ,4 ]
Barnett, Sheila [1 ,2 ]
Rodriguez, Edward K. [2 ,5 ]
Eikermann, Matthias [1 ,2 ,6 ]
机构
[1] Beth Israel Deaconess Med Ctr, Dept Anesthesia Crit Care & Pain Med, 330 Brookline Ave, Boston, MA 02215 USA
[2] Harvard Med Sch, Boston, MA 02115 USA
[3] Duesseldorf Univ Hosp, Dept Anesthesiol, Dusseldorf, Germany
[4] Massachusetts Gen Hosp, Dept Anesthesia Crit Care & Pain Med, Boston, MA 02114 USA
[5] Beth Israel Deaconess Med Ctr, Dept Orthoped Surg, Boston, MA 02215 USA
[6] Essen Duisburg Univ, Med Fac, Klin Anaesthesiol & Intens Therapie, Essen, Germany
关键词
MODIFIED FRAILTY INDEX; HIP FRACTURE; POSTOPERATIVE MORTALITY; AMERICAN-COLLEGE; NURSING-HOME; VALIDATION; CARE; DISPARITIES; MORBIDITY; ASSOCIATION;
D O I
10.1097/CORR.0000000000001532
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
Background Adverse discharge disposition, which is discharge to a long-term nursing home or skilled nursing facility is frequent and devastating in older patients after lower-extremity orthopaedic surgery. Predicting individual patient risk allows for preventive interventions to address modifiable risk factors and helps managing expectations. Despite a variety of risk prediction tools for perioperative morbidity in older patients, there is no tool available to predict successful recovery of a patient's ability to live independently in this highly vulnerable population. Questions/purposes In this study, we asked: (1) What factors predict adverse discharge disposition in patients older than 60 years after lower-extremity surgery? (2) Can a prediction instrument incorporating these factors be applied to another patient population with reasonable accuracy? (3) How does the instrument compare with other predictions scores that account for frailty, comorbidities, or procedural risk alone? Methods In this retrospective study at two competing New England university hospitals and Level 1 trauma centers with 673 and 1017 beds, respectively; 83% (19,961 of 24,095) of patients 60 years or older undergoing lowerextremity orthopaedic surgery were included. In all, 5% (1316 of 24,095) patients not living at home and 12% (2797 of 24,095) patients with missing data were excluded. All patients were living at home before surgery. The mean age was 72 +/- 9 years, 60% (11,981 of 19,961) patients were female, 21% (4155 of 19,961) underwent fracture care, and 34% (6882 of 19,961) underwent elective joint replacements. Candidate predictors were tested in a multivariable logistic regression model for adverse discharge disposition in a development cohort of all 14,123 patients from the first hospital, and then included in a prediction instrument that was validated in all 5838 patients from the second hospital by calculating the area under the receiver operating characteristics curve (ROC-AUC).Thirty-eight percent (5360 of 14,262) of patients in the development cohort and 37% (2184 of 5910) of patients in the validation cohort had adverse discharge disposition. Score performance in predicting adverse discharge disposition was then compared with prediction scores considering frailty (modified Frailty Index-5 or mFI-5), comorbidities (Charlson Comorbidity Index or CCI), and procedural risks (Procedural Severity Scores for Morbidity and Mortality or PSS). Results After controlling for potential confounders like BMI, cardiac, renal and pulmonary disease, we found that the most prominent factors were age older than 90 years (10 points), hip or knee surgery (7 or 8 points), fracture management (6 points), dementia (5 points), unmarried status (3 points), federally provided insurance (2 points), and low estimated household income based on ZIP code (1 point). Higher score values indicate a higher risk of adverse discharge disposition. The score comprised 19 variables, including socioeconomic characteristics, surgical management, and comorbidities with a cutoff value of >= 23 points. Score performance yielded an ROC-AUC of 0.85 (95% confidence interval 0.84 to 0.85) in the development and 0.72 (95% CI 0.71 to 0.73) in the independent validation cohort, indicating excellent and good discriminative ability. Performance of the instrument in predicting adverse discharge in the validation cohort was superior to the mFI-5, CCI, and PSS (ROC-AUC 0.72 versus 0.58, 0.57, and 0.57, respectively). Conclusion The Adverse Discharge in Older Patients after Lower Extremity Surgery (ADELES) score predicts adverse discharge disposition after lower-extremity surgery, reflecting loss of the ability to live independently. Its discriminative ability is better than instruments that consider frailty, comorbidities, or procedural risk alone. The ADELES score identifies modifiable risk factors, including general anesthesia and prolonged preoperative hospitalization, and should be used to streamline patient and family expectation management and improve shared decision making Future studies need to evaluate the score in community hospitals and in institutions with different rates of adverse discharge disposition and lower income. A non-commercial calculator can be accessed at www.adeles-score.org.
引用
收藏
页码:546 / 557
页数:12
相关论文
共 5 条
  • [1] CORR Insights®: What Factors Predict Adverse Discharge Disposition in Patients Older Than 60 Years Undergoing Lower-extremity Surgery? The Adverse Discharge in Older Patients after Lower-extremity Surgery (ADELES) Risk Score
    Bernstein, David N.
    CLINICAL ORTHOPAEDICS AND RELATED RESEARCH, 2021, 479 (03) : 558 - 560
  • [2] The Effect of Height on Adverse Short-Term Outcomes After Lower-Extremity Bypass Surgery in Patients with Diabetes Mellitus
    Kaur, Kushkaran
    Cornell, Rhonda S.
    Oresanya, Lawrence
    Meyr, Andrew J.
    JOURNAL OF THE AMERICAN PODIATRIC MEDICAL ASSOCIATION, 2024, 114 (04)
  • [3] Predictive model for surgical site infection risk after surgery for high-energy lower-extremity fractures: Development of the Risk of Infection in Orthopedic Trauma Surgery Score
    Paryavi, Ebrahim
    Stall, Alec
    Gupta, Rishi
    Scharfstein, Daniel O.
    Castillo, Renan C.
    Zadnik, Mary
    Hui, Emily
    O'Toole, Robert V.
    JOURNAL OF TRAUMA AND ACUTE CARE SURGERY, 2013, 74 (06) : 1521 - 1527
  • [4] Hospital Frailty Risk Score predicts adverse events in older patients with hip fractures after surgery: Analysis of a nationwide inpatient database in Japan
    Shimizu, Akio
    Maeda, Keisuke
    Fujishima, Ichiro
    Kayashita, Jun
    Mori, Naoharu
    Okada, Kiwako
    Uno, Chiharu
    Shimizu, Miho
    Momosaki, Ryo
    ARCHIVES OF GERONTOLOGY AND GERIATRICS, 2022, 98
  • [5] Risk Factors Analysis and Nomogram Conduction for Major Adverse Events After Lumbar Fusion Surgery in Older Patients: A Prospective Cohort Study
    Wang, Shuaikang
    Wang, Qijun
    Wang, Peng
    Zhou, Yaru
    Lu, Shibao
    WORLD NEUROSURGERY, 2025, 193 : 663 - 674