Development of Prediction Model for 1-year Mortality after Hip Fracture Surgery
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Purpose: Hip fractures are associated with increased mortality. The identification of risk factors of mortality could improve patient care. The aim of the study was to identify risk factors of mortality after surgery for a hip fracture and construct a mortality model. Materials and Methods: A cohort study was conducted on patients with hip fractures at two institutions. Five hundred and ninety-seven patients with hip fractures that were treated in the tertiary hospital, and another 147 patients that were treated in a secondary hospital. The perioperative data were collected from medical charts and interviews. Functional Assessment Measure score, Short Form-12 and mortality were recorded at 12 months. Patients and surgery variables that were associated with increased mortality were used to develop a mortality model. Results: Mortality for the whole cohort was 19.4% at one year. From the variables tested only age >80 years, American Society of Anesthesiologists category, time to surgery (>48 hours), Charlson comorbidity index, sex, use of anti-coagulants, and body mass index <25 kg/m2 were associated with increased mortality and used to construct the mortality model. The area under the curve for the prediction model was 0.814. Functional outcome at one year was similar to preoperative status, even though their level of physical function dropped after the hip surgery and slowly recovered. Conclusion: The mortality prediction model that was developed in this study calculates the risk of death at one year for patients with hip fractures, is simple, and could detect high risk patients that need special management.
Abstract
Purpose: Hip fractures are associated with increased mortality. The identification of risk factors of mortality could improve patient care. The aim of the study was to identify risk factors of mortality after surgery for a hip fracture and construct a mortality model. Materials and Methods: A cohort study was conducted on patients with hip fractures at two institutions. Five hundred and ninety-seven patients with hip fractures that were treated in the tertiary hospital, and another 147 patients that were treated in a secondary hospital. The perioperative data were collected from medical charts and interviews. Functional Assessment Measure score, Short Form-12 and mortality were recorded at 12 months. Patients and surgery variables that were associated with increased mortality were used to develop a mortality model. Results: Mortality for the whole cohort was 19.4% at one year. From the variables tested only age >80 years, American Society of Anesthesiologists category, time to surgery (>48 hours), Charlson comorbidity index, sex, use of anti-coagulants, and body mass index <25 kg/m2 were associated with increased mortality and used to construct the mortality model. The area under the curve for the prediction model was 0.814. Functional outcome at one year was similar to preoperative status, even though their level of physical function dropped after the hip surgery and slowly recovered. Conclusion: The mortality prediction model that was developed in this study calculates the risk of death at one year for patients with hip fractures, is simple, and could detect high risk patients that need special management.
참고문헌 (38)
- Xu BY, "Predictors of poor functional outcomes and mortality in patients with hip fracture : a systematic review", BMC Musculoskelet Disord, 20, pp.568~ (2019)[DOI]
- Veronese N, "Epidemiology and social costs of hip fracture", Injury, 49, pp.1458~1460 (2018)[DOI]
- Wiles MD, "Nottingham Hip Fracture Score as a predictor of one year mortality in patients undergoing surgical repair of fractured neck of femur", Br J Anaesth, 106, pp.501~504 (2011)[DOI]
- Charlson M, "Validation of a combined comorbidity index", J Clin Epidemiol, 47, pp.1245~1251 (1994)[DOI]
- Mayhew D, "A review of ASA physical status-historical perspectives and modern developments", Anaesthesia, 74, pp.373~379 (2019)[DOI]
- Mattisson L, "Epidemiology, treatment and mortality of trochanteric and subtrochanteric hip fractures : data from the Swedish fracture register", BMC Musculoskelet Disord, 19, pp.369~ (2018)[DOI]
- Peterle VCU, "Osteoporotic hip fracture-comorbidities and factors associated with in-hospital mortality in the elderly : a nine-year cohort study in Brazil", PLoS One, 17, pp.e0272006~ (2022)[DOI]
- Ryan S, "Preoperative hypoalbuminemia predicts poor short-term outcomes for hip fracture surgery", Orthopedics, 41, pp.e789~e796 (2018)[DOI]
- Moja L, "Timing matters in hip fracture surgery : patients operated within 48 hours have better outcomes. A meta-analysis and meta-regression of over 190, 000patients", PLoS One, 7, pp.e46175~ (2012)[DOI]
- Cher EWL, "Comorbidity as the dominant predictor of mortality after hip fracture surgeries", Osteoporos Int, 30, pp.2477~2483 (2019)[DOI]
- Smith T, "Pre-operative indicators for mortality following hip fracture surgery : a systematic review and meta-analysis", Age Ageing, 43, pp.464~471 (2014)[DOI]
- Hall K, "Overview of functional assessment scales in brain injury rehabilitation", NeuroRehabilitation, 2, pp.98~113 (1992)[DOI]
- Ware JE Jr, "The MOS 36-item short-form health survey(SF-36). I. Conceptual framework and item selection", Med Care, 30, pp.473~483 (1992)
- Kontodimopoulos N, "Validity of SF-12 summary scores in a Greek general population", Health Qual Life Outcomes, 5, pp.55~ (2007)[DOI]
- Danford NC, "Debate update : surgery after 48hours of admission for geriatric hip fracture patients is associated with increase in mortality and complication rate : a study of 27, 058 patients using the national trauma data bank", J Orthop Trauma, 35, pp.535~541 (2021)[DOI]
- Rosso F, "Prognostic factors for mortality after hip fracture : operation within 48 hours is mandatory", Injury, 4, pp.S91~S97 (2016)[DOI]
- Modig K, ""Obesity Paradox"holds true for patients with hip fracture : a registry-based cohort study", J Bone Joint Surg Am, 101, pp.888~895 (2019)[DOI]
- Tahir M, "The phenomenon of"obesity paradox"in neck of femur fractures", Pak J Med Sci, 36, pp.1079~1083 (2020)[DOI]
- Dowsey MM, "Body mass index is associated with allcause mortality after THA and TKA", Clin Orthop Relat Res, 476, pp.1139~1148 (2018)[DOI]
- Evans JT, "Obesity and revision surgery, mortality, and patient-reported outcomes after primary knee replacement surgery in the National Joint Registry : a UK cohort study", PLoS Med, 18, pp.e1003704~ (2021)[DOI]
- Ma L, "Obesity paradox among patients undergoing total knee arthroplasty : a retrospective cohort study", BMC Surg, 22, pp.373~ (2022)[DOI]
- Sarabia-Cobo CM, "Variables to predict mortality in hip fractures in patients over 65 years of age : a study on the role of anticoagulation as a risk factor", J Trauma Nurs, 24, pp.326~334 (2017)[DOI]
- Arshi A, "Blood transfusion rates and predictors following geriatric hip fracture surgery", Hip Int, 31, pp.272~279 (2021)[DOI]
- Okike K, "Effect of surgeon and hospital volume on morbidity and mortality after hip fracture", J Bone Joint Surg Am, 99, pp.1547~1553 (2017)[DOI]
- Singh JA, "Hospital volume and surgical outcomes after elective hip", knee arthroplasty : a risk-adjusted analysis of a large regional database, 2011, pp.63, 2531~2539
- Malik AT, "The impact of surgeon volume and hospital volume on postoperative mortality and morbidity after hip fractures : a systematic review", Int J Surg, 54(Pt B), pp.316~327 (2018)[DOI]
- Thorne G, "Performance of the Nottingham Hip Fracture Score and Clinical Frailty Scale as predictors of short and long-term outcomes : a dual-centre 3-year observational study of hip fracture patients", J Bone Miner Metab, 39, pp.494~500 (2021)[DOI]
- Bliemel C, "Pre-fracture quality of life predicts 1-year survival in elderly patients with hip fracture-development of a new scoring system", Osteoporos Int, 27, pp.1979~1987 (2016)[DOI]
- Cenzer IS, "One-year mortality after hip fracture : development and validation of a prognostic index", J Am Geriatr Soc, 64, pp.1863~1868 (2016)[DOI]
- Elliott J, "Predicting survival after treatment for fracture of the proximal femur and the effect of delays to surgery", J Clin Epidemiol, 56, pp.788~795 (2003)[DOI]
- Jiang HX, "Development and initial validation of a risk score for predicting in-hospital and 1-year mortality in patients with hip fractures", J Bone Miner Res, 20, pp.494~500 (2005)[DOI]
- Menéndez-Colino R, "Development of a new comprehensive preoperative risk score for predicting 1-year mortality in patients with hip fracture : the HULP-HF score. Comparison with 3 other risk prediction models", Hip Int, 31, pp.804~811 (2021)[DOI]
- Ekinci M, "C-reactive protein level, admission to intensive care unit, and high American Society of Anesthesiologists score affect early and late postoperative mortality in geriatric patients with hip fracture", Hip Pelvis, 33, pp.200~210 (2021)[DOI]
- van Baalen B, "Reliability and sensitivity to change of measurement instruments used in a traumatic brain injury population", Clin Rehabil, 20, pp.686~700 (2006)[DOI]
- Clement ND, "The minimal clinically important difference in the Oxford knee score and Short Form 12 score after total knee arthroplasty", Knee Surg Sports Traumatol Arthrosc, 22, pp.1933~1939 (2014)[DOI]
- Jacquet C, "Evaluation of the"Minimal Clinically Important Difference"(MCID)of the KOOS, KSS and SF-12 scores after open-wedge high tibial osteotomy", Knee Surg Sports Traumatol Arthrosc, 29, pp.820~826 (2021)[DOI]
- Díaz-Arribas MJ, "Minimal clinically important difference in quality of life for patients with low back pain", Spine(Phila Pa 1976), 42, pp.1908~1916 (2017)[DOI]
- Fong DYT, "The English and Chinese language versions of the Short Form 12-item Health Survey are equivalent", Health Qual Life Outcomes, 19, pp.14~ (2021)[DOI]