The Pathologic Fracture Mortality Index: A Novel Externally Validated Tool for Predicting 30-day Postoperative Mortality

被引:3
|
作者
Raad, Michael [1 ]
Suresh, Krishna, V [1 ]
Puvanesarajah, Varun [1 ]
Forsberg, Jonathan [1 ]
Morris, Carol [1 ]
Levin, Adam [1 ]
机构
[1] Johns Hopkins Univ, Sch Med, Dept Orthopaed Surg, Baltimore, MD 21205 USA
关键词
MODIFIED FRAILTY INDEX; PROGNOSTIC-FACTORS; OF-LIFE; SURVIVAL; MORBIDITY; SURGERY; QUALITY; DISEASE; CANCER;
D O I
10.5435/JAAOS-D-20-01309
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
Introduction: Current mortality predictive tools, in the setting of completed or impending pathologic fractures, are nonspecific. Clinical decision making and mortality prediction in research would benefit from creation of a high-fidelity scoring system for calculating the risk of 30-day postoperative mortality. The purpose of this study is to develop a validated research and clinical tool that is superior to existing methods in estimating postoperative mortality risk after fixation of pathologic fractures. Methods: One thousand two hundred nineteen patients who underwent fixation for either completed or impending pathologic fractures in the National Surgical Quality Improvement Program (2012 to 2018) database were analyzed. Multivariable logistic regression with diagnostics was used to develop a predictive model in a derivation cohort and then validated in a validation cohort. Area under the curve (AUC) from receiver operator curve analysis was used to assess accuracy. A score was derived and compared with the American Society of Anesthesiologists classification and modified five-component frailty index (mF-I5). The score was validated in an exclusive cohort of patients who underwent fixation for pathologic fractures at a tertiary care center. Results: Of 1,219, a total of 177 (15%) patients did not survive beyond 30 days postoperatively. AUC for our predictive model was 0.76 in the derivation and 0.75 in the validation National Surgical Quality Improvement Program cohorts. The derived Pathologic Fracture Morbidity Index included seven data points: anemia, alkaline phosphatase. 150 U/L, albumin, 3.5 mg/dL, pulmonary disease, recent weight loss, functional dependence, and white blood cell count.12,000. The PFMI (AUC = 0.75) was more accurate than ASA (AUC = 0.60) or mF-5 (AUC = 0.58) (P, 0.01). The AUC for PFMI in predicting 30-day mortality in the exclusive cohort (N = 39) was 0.74. Conclusion: The PFMI is a validated tool that may be used for predicting postoperative 30-day mortality after
引用
收藏
页码:E1264 / E1273
页数:10
相关论文
共 50 条
  • [1] Predicting Risk of 30-day Postoperative Morbidity Using the Pathologic Fracture Mortality Index
    Vankara, Ashish
    Leland, Christopher R.
    Maxson, Ridge
    Raad, Micheal
    Sabharwal, Samir
    Morris, Carol D.
    Levin, Adam S.
    [J]. JOURNAL OF THE AMERICAN ACADEMY OF ORTHOPAEDIC SURGEONS, 2024, 32 (03) : e146 - e155
  • [2] A DEEP LEARNING MODEL FOR PREDICTING 30-DAY POSTOPERATIVE MORTALITY
    Fritz, Bradley A.
    Cui, Zhicheng
    Zhang, Muhan
    He, Yujie
    Chen, Yixin
    Kronzer, Alexander
    Ben Abdallah, Arbi
    King, Christopher R.
    Avidan, Michael
    [J]. ANESTHESIA AND ANALGESIA, 2019, 128 : 601 - 601
  • [3] Predicting 30-day mortality after hip fracture surgery
    Tsang, C.
    Boulton, C.
    Burgon, V.
    Johansen, A.
    Wakeman, R.
    Cromwell, D. A.
    [J]. BONE & JOINT RESEARCH, 2017, 6 (09): : 550 - 556
  • [4] Deep-learning model for predicting 30-day postoperative mortality
    Fritz, Bradley A.
    Cui, Zhicheng
    Zhang, Muhan
    He, Yujie
    Chen, Yixin
    Kronzer, Alex
    Ben Abdallah, Arbi
    King, Christopher R.
    Avidan, Michael S.
    [J]. BRITISH JOURNAL OF ANAESTHESIA, 2019, 123 (05) : 688 - 695
  • [5] Predicting 30-day mortality for palliative radiotherapy
    Witztum, A.
    Wu, S.
    Gennatas, E.
    Valdes, G.
    Solberg, T.
    Braunstein, S.
    [J]. RADIOTHERAPY AND ONCOLOGY, 2019, 133 : S466 - S467
  • [6] A novel, comprehensive tool for predicting 30-day mortality after surgical aortic valve replacement
    Biancari, Fausto
    Rosato, Stefano
    Costa, Giuliano
    Barbanti, Marco
    D'Errigo, Paola
    Tamburino, Corrado
    Cerza, Francesco
    Rosano, Aldo
    Seccareccia, Fulvia
    [J]. EUROPEAN JOURNAL OF CARDIO-THORACIC SURGERY, 2021, 59 (03) : 586 - 592
  • [7] Predicting 30-day mortality after hip fracture: the G4A calibrated prognostic tool
    Harman, Holly
    Walton, Thomas J.
    Chan, Gareth
    Stott, Philip
    Ricketts, David M.
    Rogers, Benedict A.
    [J]. HIP INTERNATIONAL, 2022, 32 (06) : 820 - 825
  • [8] Atrial fibrillation and the risk of 30-day postoperative mortality after hip fracture
    Balani, N.
    Chakladar, A.
    White, S.
    [J]. ANAESTHESIA, 2012, 67 (06) : 686 - 686
  • [9] 30-day mortality after hip fracture surgery: Influence of postoperative factors
    Blanco, Juan F.
    da Casa, Carmen
    Pablos-Hernandez, Carmen
    Gonzalez-Ramirez, Alfonso
    Miguel Julian-Enriquez, Jose
    Diaz-Alvarez, Agustin
    [J]. PLOS ONE, 2021, 16 (02):
  • [10] A prognostic index for 30-day mortality after stroke
    Wang, Y
    Lim, LLY
    Levi, C
    Heller, RF
    Fischer, J
    [J]. JOURNAL OF CLINICAL EPIDEMIOLOGY, 2001, 54 (08) : 766 - 773