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Prognostic nomogram for risk of mortality after hip fracture surgery in geriatrics

Open AccessPublished:January 18, 2022DOI:https://doi.org/10.1016/j.injury.2022.01.029

      Highlights

      • Age, CCI, serum albumin, sodium, and hemoglobin are five identified risk variables for mortality after hip fracture surgery in geriatrics.
      • The novel nomogram established with them for stratifying the mortality risk after hip fracture surgery in geriatrics had good accuracy and usefulness.
      • External validation is warranted to confirm the performance of this nomogram.

      Abstract

      Purpose

      Hip fracture is a significant public health problem, with associated high morbidity and mortality. Orthopedic surgeons are concerned to improve prognosis and stratify mortality risk after hip fracture surgery. This study established a nomogram that combines the Charlson Comorbidity Index (CCI) with specific laboratory parameters to predict mortality risk after hip fracture surgery in geriatrics.

      Methods

      The records of consecutive patients who underwent hip fracture surgery from January 2015 through May 2020 at one medical center were reviewed for perioperative factors and mortality. Patients with age ≥ 70 years who were diagnosed with intertrochanteric or femoral neck fractures were included. Patients who were diagnosed with pathological fracture, received only conservative treatment or lost to follow-up were excluded. A multivariate Cox proportional hazards regression model was used to identify risk factors. A nomogram was established with R software and evaluated using concordance (C)-index, area under receiver operating characteristic (AUC), calibration curves, and decision curve analysis (DCA).

      Results

      In total, 454 patients were included with a mean age of 81.6 years. The mean follow-up and one-year mortality rate were 37.2 months and 10.4%, respectively. Five identified risk variables for mortality after hip fracture surgery in geriatrics comprised age (HR 1.05, 95% CI 1.01-1.08; P = 0.003), CCI (HR 1.38, 95% CI 1.24-1.54; P = 0.000), albumin (HR 1.78, 95% CI 1.31-2.43; P = 0.000), sodium (HR 1.59, 95% CI 1.18-2.15; P = 0.002) and hemoglobin (HR 1.46, 95% CI 1.07-2.00; P = 0.02). A nomogram was proposed and evaluated, showing a C-index of 0.76 ± 0.02. The AUCs for 6-month, 1-year, and 3-year mortality predictions were 0.83, 0.79, and 0.77, respectively. The calibration curve and DCA showed good discrimination and clinical usefulness.

      Conclusion

      This novel nomogram for stratifying the mortality risk after hip fracture surgery in geriatrics incorporated age, CCI, serum albumin, sodium, and hemoglobin. Internal validation indicated that the model has good accuracy and usefulness. This nomogram had improved convenience and precision compared with other models. External validation is warranted to confirm its performance.

      Keywords

      Abbreviations:

      ASA (American society of anesthesiologists), AUC (area under receiver operating characteristic), CCI (Charlson comorbidity index), C-index (concordance index), DCA (decision curve analysis), E-PASS (estimation of physiologic ability and surgical stress), HR (hazard ratio), NA (not applicable), NHFS (Nottingham hip fracture score), NLR (neutrophil-to-lymphocyte ratio), O-POSSUM (orthopedic physiologic and operative severity score for the enumeration of mortality and morbidity), ROC (receiver operating characteristic), SCr (serum creatinine)

      Introduction

      Hip fracture is a significant public health problem worldwide, due to the high epidemiology in geriatrics and aging of the global population [
      • Marks R.
      Hip fracture epidemiological trends, outcomes, and risk factors.
      ]. An estimated 2.6 million individuals will suffer a hip fracture by the year 2025, and 7 to 21 million by 2050[
      • Gullberg B.
      • Johnell O.
      • Kanis J.A.
      World-wide projections for hip fracture.
      ]. The morbidity associated with hip fracture is high, with 30 to 50% of patients losing functional independence, and mortality is such that it has been called the last fracture of life [
      • Sing C.W.
      • Lin T.C.
      • Bartholomew S.
      • et al.
      Global epidemiology of hip fractures: a study protocol using a common analytical platform among multiple countries.
      ]. Within one year after hip fracture surgery mortality is as high as 30% (21% in the United States, and 17.9% in Asia) [
      • Downey C.
      • Kelly M.
      • Quinlan J.F.
      Changing trends in the mortality rate at 1-year post hip fracture - a systematic review.
      ]. Thus, a major concern of orthopedic surgeons is methods to improve prognosis and stratify and reduce the associated risk after hip fracture surgery.
      Many models have incorporated various risk factors to predict the risk of mortality after hip fracture surgery. These risk factors included age, gender, comorbidities, American Society of Anesthesiologists (ASA) score, and other biomarkers. Orthopedic Physiologic and Operative Severity Score for the Enumeration of Mortality and Morbidity (O-POSSUM), Charlson Comorbidity Index (CCI), Nottingham Hip Fracture Score (NHFS), Estimation of Physiologic Ability and Surgical Stress (E-PASS), and others [
      • Nia A.
      • Popp D.
      • Thalmann G.
      • et al.
      Predicting 30-day and 180-day mortality in elderly proximal hip fracture patients: evaluation of 4 risk prediction scores at a level I trauma center.
      • Varady N.H.
      • Gillinov S.M.
      • Yeung C.M.
      • et al.
      The Charlson and Elixhauser scores outperform the american society of anesthesiologists score in assessing 1-year mortality risk after hip fracture surgery.
      ] were common models that had been evaluated for utility and accuracy. Although the areas under the receiver operating characteristic curves (ROC; AUCs) of most models were no less than 0.7, few had been greater than 0.8, which suggests poor performance [
      • Nia A.
      • Popp D.
      • Thalmann G.
      • et al.
      Predicting 30-day and 180-day mortality in elderly proximal hip fracture patients: evaluation of 4 risk prediction scores at a level I trauma center.
      • Varady N.H.
      • Gillinov S.M.
      • Yeung C.M.
      • et al.
      The Charlson and Elixhauser scores outperform the american society of anesthesiologists score in assessing 1-year mortality risk after hip fracture surgery.
      ]. On the other hand, the results of many stable and convenient laboratory tests are closely associated with mortality, including hemoglobin, albumin, and sodium [
      • Ryan G.
      • Nowak L.
      • Melo L.
      • et al.
      Anemia at presentation predicts acute mortality and need for readmission following geriatric hip fracture.
      ,
      • Lizaur-Utrilla A.
      • Gonzalez-Navarro B.
      • Vizcaya-Moreno M.F.
      • Lopez-Prats F.A.
      Altered seric levels of albumin, sodium and parathyroid hormone may predict early mortality following hip fracture surgery in elderly.
      ]. It may be valuable to explore whether applying laboratory results in models that also utilize the CCI or ASA score could improve the predictive accuracy of the model.
      This study constructed a nomogram that combines the CCI score with some special laboratory test results to predict the mortality risk after hip fracture surgery in geriatrics. The nomogram was evaluated at one single center.

      Patients and methods

      Patients and study design

      A cohort of consecutive patients who underwent hip fracture surgery from January 2015 through May 2020 at Peking University First Hospital (Beijing, China) were recruited retrospectively. The inclusion criteria for patients were: (1) patients were diagnosed with intertrochanteric or femoral neck fractures; (2) the ages of the patients were no less than 70 years old; (3) patients received surgery therapy included plate/screw fixation, hemiarthroplasty, or total hip arthroplasty. Patients with any of the following were excluded: pathological fracture; received only conservative treatment; or lost to follow-up.
      The initial search for cases of femoral neck or intertrochanteric fractures in our medical database yielded 658 patients (Fig. 1). Among them, 144, 41, and 15 were excluded for being, respectively, younger than 70 years, lost to follow-up, and duplicated for second hip fracture. No patient was diagnosed with pathological fracture. Ultimately, the records of 454 patients were collected for analysis.
      Fig 1
      Fig. 1Flowchart of screening the recruited patients.

      Data collection

      Basic perioperative demographic (age, gender) and clinic characteristics were collected through the electronic medical record database. Clinic characteristics included ASA score, CCI, preoperative wait time, length of stay, fracture type, anesthesia type, transfusion, and laboratory test results. Specifically, fracture options according to the inclusion criteria were either femoral neck or intertrochanteric fracture. Anesthesia was either general, or combined spinal epidural. The laboratory tests consisted of the following: albumin, sodium, serum creatinine (SCr), hemoglobin, and neutrophil-to-lymphocyte ratio (NLR).
      Serum albumin level was considered normal if >35 g/L. Hypoalbuminemia (low serum albumin) was classified as mild, moderate, or severe (30–35, 25–30, or < 25 g/L, respectively.) A normal sodium level was considered 135–145 mmol/L; hyponatremia was stratified as mild or moderate/severe (130–135, or < 130 mmol/L). The hemoglobin status was classified based on level and gender of the patient, with normal being ≥ 120 g/L and ≥ 110 g/L for men and women, respectively. Anemia (low hemoglobin) was considered mild (men, 120–90 g/L; women, 110–90 g/L), or moderate/severe (both, <90 g/L).

      Follow-up

      For follow-up, the recruited patients were contacted by telephone. The minimal follow up duration was 9 months after surgery. If the patient had died before the follow-up time, the date of death was recorded.

      Statistical analysis

      Categorical variables were recorded as numbers, and analyzed using the chi-squared or Fisher's exact test. Continuous variables were recorded as mean ± standard deviation and analyzed using Student's t-test or the Wilcoxon rank-sum test. Survival curves were depicted using the Kaplan-Meier method. The risk factors for mortality after hip fracture surgery were initially identified using a univariate Cox proportional hazards regression model with P < 0.1. The chosen covariates were further analyzed by backward stepwise multivariate Cox proportional hazards regression, and variables with P < 0.05 were considered as final predictors. SPSS 23 for Windows was used in statistical analyses.
      A nomogram was constructed by rms package in R (version 4.1.0) according to the results of the multivariate Cox analysis. The performance of the nomogram was evaluated by concordance index (C-index) and AUC curve over time [
      • Harrell F.E.
      • Califf R.M.
      • Pryor D.B.
      • et al.
      Evaluating the yield of medical tests.
      ]. (The C-index and AUC directly reflect the accuracy of the model—the C-index and AUC rise with the accuracy). After internal validation by bootstrapping, a calibration curve was used to assess the calibration of the nomogram by comparing the actual risk and predicted risk. Based on the net benefit and threshold probabilities, decision curve analysis (DCA) was used to estimate the clinical usefulness of the nomogram.

      Results

      Overall, the study population comprised 454 patients with a mean age of 81.6 years (Table 1). Among them, 274 and 180 had diagnosed femoral neck fracture and intertrochanteric fracture, respectively. The mean follow-up time was 37.2 months, and the one-year mortality rate was 10.4% (Fig. 2).
      Table 1Demographic and clinic characteristics of the included patients.
      n (%) *
      GenderMale125 (27.5)
      Female329 (72.5)
      Age, mean (range), y81.6 (70–98)
      Fracture typeFemoral neck274 (60.4)
      Intertrochanteric180 (39.6)
      Length of stay, d13 ± 8.6
      CCI4167 (36.8)
      5142 (31.3)
      676 (16.7)
      738 (8.4)
      813 (2.9)
      98 (1.8)
      104 (0.9)
      115 (1.1)
      121 (0.2)
      ASA2203 (44.7)
      3225 (49.6)
      426 (5.7)
      Anesthesia typeGeneral120 (73.3)
      Combined spinal epidural333 (26.4)
      Missing data1 (0.2)
      TransfusionYes191 (42.1)
      No263 (57.9)
      Albumin, g/L
      Normal>35344 (75.8)
      HypoalbuminemiaMild, 30–3592 (20.3)
      Moderate, 25–3014 (3.1)
      Severe, <252 (0.4)
      Missing data2 (0.4)
      Sodium, mmol/L
      Normal135–145375 (82.6)
      HyponatremiaMild, 130–13559 (13.0)
      Moderate/severe, < 13018 (4.0)
      Missing data2 (0.4)
      Hemoglobin, g/L
      Normal≥ 120 men; ≥ 110 women327 (72.0)
      AnemiaMild, 120–90 men; 110–90 women98 (21.6)
      Moderate/severe, both genders < 9028 (6.2)
      Missing data1 (0.2)
      SCr, µmol/L92.4 ± 78.8
      NLR8.8 ± 6.7
      * Unless indicated otherwise.
      Fig 2
      Fig. 2Kaplan-Meier survival curves of the included patients after hip fracture surgery.
      The initial screening for the prediction model by univariate Cox regression with P < 0.1 identified several candidate variables including gender, age, CCI, ASA score, transfusion, albumin, sodium, serum creatinine, hemoglobin, and NLR. Multivariate Cox proportional hazards regression identified the following 5 variables that had the strongest association with overall mortality: age; CCI; serum albumin, sodium, and hemoglobin (Table 2).
      Table 2Cox proportional hazards regression of variables for mortality after hip fracture surgery in geriatrics.
      Univariate analysisMultivariate analysis
      PHR (95% CI)PHR (95% CI)
      Gender0.0300.65 (0.45–0.96)0.3270.82 (0.55–1.22)
      Age0.0011.05 (1.02–1.09)0.003 *1.05 (1.01–1.08)
      Fracture type0.2891.22 (0.84–1.78)NANA
      Length of stay0.7911.00 (0.98–1.02)NANA
      CCI0.0001.39 (1.26–1.54)0.000 *1.38 (1.24–1.54)
      ASA0.0011.65 (1.22–2.25)0.4361.14 0.82–1.57 ()
      Anesthesia type0.5471.14 (0.75–1.73)NANA
      Transfusion0.0021.81 (1.25–2.62)0.8670.96 (0.63–1.48)
      Albumin0.0000.85 (0.81–0.89)0.000 *1.78 (1.31–2.43)
      Sodium0.0011.00 (1.00–1.00)0.002 *1.59 (1.18–2.15)
      SCr0.0000.98 (0.97–0.99)0.2751.00 (1.00–1.00)
      Hemoglobin0.0002.05 (1.57–2.67)0.020 *1.46 (1.07–2.00)
      NLR0.8341.01 (0.94–1.08)0.1571.02 (0.99–1.04)
      NA, not applicable; HR, hazard ratio.
      * P < 0.05 with significant difference.
      A new nomogram for predicting the mortality risk after hip fracture surgery in geriatrics was constructed with 5 variables: age, CCI, albumin, sodium, and hemoglobin (Fig. 3). The accuracy of the nomogram was evaluated internally. The C-index of the nomogram was 0.76 ± 0.02. The AUC curve values for predicting mortality at 6 months, 1 year, and 3 years were 0.83, 0.79, and 0.77, respectively (Fig. 4). The C-index and AUC showed that this model had good discrimination and predictive accuracy. There was good consistency between the model's observed and predicted probabilities for overall survival rates at 6 months, 1 year, and 3 years (Fig. 5). The DCA indicated that the nomogram could be a good tool for prediction of overall mortality after hip fracture surgery in geriatric patients (Fig. 6).
      Fig 3
      Fig. 3The nomogram established by identified risk factors for predicting the overall survival rate after hip fracture surgery in geriatrics.
      Fig 4
      Fig. 4The AUC of ROC curve over time of the nomogram. Key: —, mean value; … standard error.
      Fig 5
      Fig. 5The calibration curves of the nomogram for predicting the overall survival rate after hip fracture surgery in geriatrics at (a) 6 months; (b) 1 year; and (c) 3 years.
      Fig 6
      Fig. 6The DCAs. Model-6 and All-6 are the net benefits within 6 months after hip fracture surgery; Model-12 and All-12 are the net benefits within 1 year after hip fracture surgery; Model-36 and All-36 are the net benefits within 3 years after hip fracture surgery.

      Discussion

      Many models have been designed to predict the mortality risk after hip fracture surgery, but their accuracy and convenience are not satisfactory. To improve their shortcomings, the present novel nomogram model combined certain laboratory tests results with the original CCI. The 5 variables identified through Cox regression as reflecting potential risk were age, CCI, serum albumin, sodium, and hemoglobin levels. These factors were incorporated in a new nomogram, and the model was subjected to internal validation; the C-index was 0.76, and the AUC values for prediction of mortality were 0.83, 0.79, and 0.77, respectively, for 6 months, one year, and 3 years after surgery for hip fracture.
      The CCI, which includes a series of weighted comorbidities to predict 1-year mortality [
      • Charlson M.E.
      • Pompei P.
      • Ales K.L.
      • MacKenzie C.R.
      A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.
      ], well reflects the mortality rate of patients after hip fracture surgery. The ASA score comprises several categories to evaluate a patient's physical status and perioperative risk [
      • Horvath B.
      • Kloesel B.
      • Todd M.M.
      • et al.
      The evolution, current value, and future of the american society of anesthesiologists physical status classification system.
      ]. Together, the CCI and ASA are commonly used tools for risk stratification. According to the present multivariable Cox proportional hazards regression model, the CCI, but not the ASA score, was an independent factor associated with mortality. This is consistent with Varady et al. [
      • Varady N.H.
      • Gillinov S.M.
      • Yeung C.M.
      • et al.
      The Charlson and Elixhauser scores outperform the american society of anesthesiologists score in assessing 1-year mortality risk after hip fracture surgery.
      ], which reported that CCI performed better than the ASA score for evaluating the 1-year mortality risk after hip fracture surgery, though some other studies have disagreed. Quach et al. [
      • Quach L.H.
      • Jayamaha S.
      • Whitehouse S.L.
      • et al.
      Comparison of the Charlson comorbidity index with the ASA score for predicting 12-month mortality in acute hip fracture.
      ] found that the ASA score, rather than either version of the CCI, was independently associated with 12-month mortality. According to Ek et al. [
      • Ek S.
      • Meyer A.C.
      • Hedström M.
      • Modig K.
      Comorbidity and the association with 1-year mortality in hip fracture patients: can the ASA score and the Charlson comorbidity Index be used interchangeably?.
      ], both the ASA and CCI had a similar stepwise association with 1-year mortality in patients with hip fracture. The follow-up duration in these studies [
      • Quach L.H.
      • Jayamaha S.
      • Whitehouse S.L.
      • et al.
      Comparison of the Charlson comorbidity index with the ASA score for predicting 12-month mortality in acute hip fracture.
      ,
      • Ek S.
      • Meyer A.C.
      • Hedström M.
      • Modig K.
      Comorbidity and the association with 1-year mortality in hip fracture patients: can the ASA score and the Charlson comorbidity Index be used interchangeably?.
      ] was limited to one year after surgery and shorter compared with our study. The ASA score is proposed to optimize perioperative care, while CCI is used to measure the burden of specific comorbidity and prognosis of diseases. This might be the cause of the difference.
      The present analysis chose the CCI, rather than ASA score, as an important predictor in the nomogram model. Yet, as a single factor to predict the mortality risk of patients with hip fracture, the CCI did not perform well. Varady et al. [
      • Varady N.H.
      • Gillinov S.M.
      • Yeung C.M.
      • et al.
      The Charlson and Elixhauser scores outperform the american society of anesthesiologists score in assessing 1-year mortality risk after hip fracture surgery.
      ] reported an AUC value of 0.769 (95% CI 0.739-0.800) for CCI for predicting the 1-year mortality risk. Karres et al [
      • Karres J.
      • Heesakkers N.A.
      • Ultee J.M.
      • Vrouenraets B.C.
      Predicting 30-day mortality following hip fracture surgery: evaluation of six risk prediction models.
      ]. found that the CCI had low power of prediction, with an AUC of 0.71 (0.65–0.77) to predict 30-day mortality. To improve the predictive power, more factors might be combined with the CCI.
      The present study found that serum albumin, sodium, and hemoglobin, which are easily accessible and convenient laboratory tests, reflected well the risk of mortality of patients after hip fracture surgery. This is consistent with previous studies. A meta-analysis [
      • Li S.
      • Zhang J.
      • Zheng H.
      • et al.
      Prognostic role of serum albumin, total lymphocyte count, and mini nutritional assessment on outcomes after geriatric hip fracture surgery: a meta-analysis and systematic review.
      ] showed that low serum albumin was an independent predictor for overall mortality risk after hip fracture surgery in geriatrics. Sim et al. [
      • Sim S.D.
      • Sim Y.E.
      • Tay K.
      • et al.
      Preoperative hypoalbuminemia: poor functional outcomes and quality of life after hip fracture surgery.
      ] found that low serum albumin (≤ 35 g/L) was not uncommon in geriatrics with hip fracture, and was associated with slower recovery and low quality of life after surgery. Ayus et al. [
      • Ayus J.C.
      • Fuentes N.
      • Go A.S.
      • et al.
      Chronicity of uncorrected hyponatremia and clinical outcomes in older patients undergoing hip fracture repair.
      ] found that nearly 25% of patients with hip fracture suffered from hyponatremia, which was associated with increased post-operative mortality after hip fracture surgery in geriatrics. Ryan et al. [
      • Ryan G.
      • Nowak L.
      • Melo L.
      • et al.
      Anemia at presentation predicts acute mortality and need for readmission following geriatric hip fracture.
      ] found that anemia at admission was associated with greater 30-day postoperative morbidity and mortality in geriatrics with hip fracture. Albumin, sodium, and hemoglobin can be easily tested before surgery, and according to the above studies, their significance is stable and convincing. Thus, albumin, sodium, and hemoglobin were chosen as important predictors in the design of the present nomogram.
      The C-index and AUC value are parameters that indicate the predictive accuracy of a model. The accuracy of prediction for mortality of the present novel nomogram, which combines the CCI with the specified laboratory test results, was good: with a C-index of 0.76, and AUCs at 6 months and 1 and 3 years of 0.83, 0.79, and 0.77, respectively. Other models had been used to stratify the risk of patients with hip fracture [
      • Marufu T.C.
      • Mannings A.
      • Moppett I.K.
      Risk scoring models for predicting peri-operative morbidity and mortality in people with fragility hip fractures: qualitative systematic review.
      ]; the ASA, CCI, NHFS, E-PASS, and O-POSSUM are the most frequently investigated and used. Yet, compared with these models, the nomogram presented here showed a higher C-index and AUC value. The NHFS was designed specifically for patients with hip fracture, with a promising performance in predicting short-term mortality risk: the AUC is 0.72 in patients with hip fracture [
      • Karres J.
      • Heesakkers N.A.
      • Ultee J.M.
      • Vrouenraets B.C.
      Predicting 30-day mortality following hip fracture surgery: evaluation of six risk prediction models.
      ,
      • Marufu T.C.
      • Mannings A.
      • Moppett I.K.
      Risk scoring models for predicting peri-operative morbidity and mortality in people with fragility hip fractures: qualitative systematic review.
      ,
      • Maxwell M.J.
      • Moran C.G.
      • Moppett I.K.
      Development and validation of a preoperative scoring system to predict 30 day mortality in patients undergoing hip fracture surgery.
      ]. Karres et al. [
      • Karres J.
      • Heesakkers N.A.
      • Ultee J.M.
      • Vrouenraets B.C.
      Predicting 30-day mortality following hip fracture surgery: evaluation of six risk prediction models.
      ] assessed the predictive accuracy of 30-day mortality of 6 models (CCI, O-POSSUM, E-PASS, a risk model by Jiang et al., NHFS, and a model by Holt), and determined that none had the AUC necessary for excellent discrimination (i.e., > 0.80). Models developed respectively by Cenzer et al. [
      • Cenzer I.S.
      • Tang V.
      • Boscardin W.J.
      • et al.
      One-year mortality after hip fracture: development and validation of a prognostic index.
      ] and Jiang et al. [
      • Jiang H.X.
      • Majumdar S.R.
      • Dick D.A.
      • et al.
      Development and initial validation of a risk score for predicting in-hospital and 1-year mortality in patients with hip fractures.
      ] to predict one-year mortality had C-indexes of 0.73 and 0.74. Li et al. [
      • Li Y.
      • Chen M.
      • Lv H.
      • et al.
      A novel machine-learning algorithm for predicting mortality risk after hip fracture surgery.
      ] established a new model by machine learning algorithm and achieved an AUC of 0.75 for prediction of 1-year mortality.
      Compared with these models, the present novel nomogram showed a better performance to stratify the mortality risk in geriatrics with hip fracture, and the CCI and albumin, sodium, and hemoglobin can be obtained conveniently and preoperatively. Thus, theoretically, this model could be applied with improved convenience and precision. However, external validation is needed to confirmed its performance before it could be used in clinical practice.
      This study has several limitations. First, although the nomogram performed well as evaluated by internal validation, external validation was not applied. The results warrant external validation, conducted in other clinical centers or with new patient cohorts. In addition, this was a retrospective study and the study period was relatively long, so that some differences regarding perioperative interventions may now exist. Thus, in future a cross-sectional study might be conducted.

      Conclusion

      This study determined that age, CCI, serum albumin, sodium, and hemoglobin were independent risk factors for mortality after hip fracture surgery in geriatrics no younger than 70 years. These parameters are practical and convenient to obtain in a clinical setting, and were incorporated in the novel nomogram designed herein. The model was carefully evaluated and internal validation showed good accuracy and usefulness. This nomogram for predicting the mortality risk after hip fracture surgery in geriatrics warrants confirmation by external validation.

      Declaration of Competing Interest

      The authors declare that they have no conflict of interest.

      Acknowledgment

      The authors thank the doctors in the Department of Orthopedics, Peking University First Hospital for their help and advices in the process of data collection, including Tianyue Zhu, Licheng Wen, Weibing Chai, Hongzhang Lu, Jun Li, Zhenning Liu, Yilin Ye, Daojian Zhang, Xin Yang, and Zhichao Meng.

      Appendix. Supplementary materials

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