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Journal of Peking University (Health Sciences) ›› 2024, Vol. 56 ›› Issue (5): 874-883. doi: 10.19723/j.issn.1671-167X.2024.05.019

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Construction and validation of a nomogram for predicting in-hospital postoperative heart failure in elderly patients with hip fracture

Yuanmei LIU, Yicheng FU, Jingxin HAO, Fuchun ZHANG, Huilin LIU*()   

  1. Department of Geriatrics, Peking University Third Hospital, Beijing 100191, China
  • Received:2024-01-18 Online:2024-10-18 Published:2024-10-16
  • Contact: Huilin LIU E-mail:0563178481@bjmu.edu.cn
  • Supported by:
    Supported by the Chronic Disease Prevention and Health Education Research Project(BJMB0012023024006);the Key Clinical Program of Peking University Third Hospital(BYSYDL2021022)

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Abstract:

Objective: To construct and validate a nomogram for prediction of in-hospital postoperative heart failure (PHF) in elderly patients with hip fracture. Methods: This was a retrospective cohort study. The patients aged ≥65 years undergoing hip fracture surgery in Peking University Third Hospital from July 2015 to December 2023 were enrolled. The patients admitted from July 2015 to December 2021 were divided into a development cohort, and the others admitted from January 2022 to December 2023 in to a validation cohort. The patients ' clinical data were collected from the electronic medical record system. Univariate and multivariate Logistic regression were employed to screen the predictors for PHF in the patients. The R software was used to construct a nomogram. Internal and external validation were performed by the Bootstrap method. The discriminatory ability of the model was determined by the area under the receiver operating characteristic curve (AUC). The calibration was evaluated by the calibration plot and Hosmer-Lemeshow goodness-of-fit test. Decision curve analysis (DCA) was performed to assess the clinical utility. Results: In the study, 944 patients were eventually enrolled in the development cohort, and 469 were in the validation cohort. A total of 54 (5.7%) patients developed PHF in the deve-lopment cohort, and 18 (3.8%) patients had PHF in the validation cohort. Compared with those from non-PHF group, the patients from PHF group were older, had higher prevalence of heart disease, hypertension and pulmonary disease, had poorer American Society of Anesthesiologists (ASA) classification (Ⅲ-Ⅳ), presented with lower preoperative hemoglobin level, lower left ventricular ejection fraction, higher preoperative serum creatinine, received hip arthroplasty and general anesthesia more frequently. Multivariate Logistic regression analysis showed that age (OR=1.071, 95%CI: 1.019-1.127, P=0.008), history of heart disease (OR=5.360, 95%CI: 2.808-10.234, P < 0.001), preoperative hemoglobin level (OR=0.979, 95%CI: 0.960-0.999, P=0.041), preoperative serum creatinine (OR=1.007, 95%CI: 1.001-1.013, P=0.015), hip arthroplasty (OR=2.513, 95%CI: 1.259-5.019, P=0.009), and general anesthesia (OR=2.024, 95%CI: 1.053-3.890, P=0.034) were the independent predictors for PHF in elderly patients with hip fracture. Four preoperative predictors were incorporated to construct a preoperative nomogram for PHF in the patients. The AUC values of the nomogram in internal and external validation were 0.818 (95%CI: 0.768-0.868) and 0.873 (95%CI: 0.805-0.929), indicating its good accuracy. The calibration plots and Hosmer-Lemeshow goodness-of-fit test (internal validation: χ2=9.958, P=0.354; external validation: χ2=5.477, P=0.791) showed its satisfactory calibration. Clinical usefulness of the nomogram was confirmed by decision curve analysis. Conclusion: An easy-to-use nomogram for prediction of in-hospital PHF in elderly patients with hip fracture is well developed. This preoperative risk assessment tool can effectively identify patients at high risk of PHF and may be useful for perioperative management optimization.

Key words: Elderly, Hip fracture, Heart failure, Nomograms

CLC Number: 

  • R541.6

Figure 1

Flowchart of the study design"

Table 1

Comparison of baseline characteristics and outcome between the development cohort and validation cohort"

Variables Development cohort (n=944) Validation cohort (n=469) Z/χ2 P
Age/years 81.0 (74.0, 85.0) 80.0 (72.0, 86.0) -1.198 0.231
Gender 0.897 0.344
    Female 680 (72.0) 349 (74.4)
    Male 264 (28.0) 120 (25.6)
BMI/(kg/m2) 7.575 0.023
     < 18.5 137 (14.5) 44 (9.4)
    18.5-28.0 715 (75.7) 380 (81.0)
    >28.0 92 (9.7) 45 (9.6)
Medical history
    Heart disease 118 (12.5) 43 (9.2) 3.445 0.063
    Diabetes mellitus 265 (28.1) 136 (29.0) 0.132 0.716
    Hypertension 532 (56.4) 276 (58.8) 0.795 0.373
    Cerebrovascular disease 168 (17.8) 88 (18.8) 0.197 0.657
    Pulmonary disease 100 (10.6) 27 (5.8) 8.959 0.003
Type of fracture 8.057 0.018
    Femoral neck fracture 409 (43.3) 195 (41.6)
    Femoral intertrochanteric fracture 446 (47.3) 248 (52.9)
    Femoral subtrochanteric fracture 89 (9.4) 26 (5.5)
Time from injury to surgery/d 4.00 (2.00, 7.00) 4.00 (2.00, 6.00) -0.914 0.361
ASA classification 3.285 0.070
    Ⅰ-Ⅱ 758 (80.3) 357 (76.1)
    Ⅲ-Ⅳ 186 (19.7) 112 (23.9)
Preoperative blood transfusion 1.523 0.217
    <400 mL 888 (94.1) 463 (96.3)
    ≥400 mL 56 (5.9) 18 (3.7)
Preoperative SBP/mmHg 135.0 (125.0, 146.0) 133.0 (124.0, 143.0) -2.015 0.44
Preoperative DBP/mmHg 76.0 (68.0, 80.0) 76.0 (67.8, 80.0) -0.060 0.952
Preoperative heart rate/(beat/min) 76.0 (70.0, 80.0) 75.0 (70.0, 80.0) -2.345 0.019
Preoperative laboratory examinations
    WBC/(×109/L) 9.14 (7.34, 11.18) 9.18 (7.44, 11.40) -0.526 0.599
    HGB/(g/L) 120.00 (108.00, 132.00) 119.00 (105.00, 132.00) -1.162 0.245
    PLT/(×109/L) 194.00 (157.00, 242.00) 190.00 (157.00, 242.00) -0.404 0.686
    ALT/(U/L) 20.00 (16.00, 26.00) 19.00 (15.00, 24.03) -0.785 0.432
    Scr/(μmol/L) 65.00 (54.00, 79.00) 61.00 (53.00, 78.00) -2.310 0.021
    K/(μmol/L) 4.08 (3.80, 4.40) 4.00 (3.75, 4.28) -2.409 0.016
    Na/(μmol/L) 138.70 (136.00, 141.10) 138.00 (135.68, 140.50) -1.705 0.088
    LVEF/% 71.0 (68.0, 73.0) 71.0 (67.0, 73.0) -0.200 0.842
Type of surgery 2.754 0.097
    Internal fixation 690 (73.1) 323 (68.9)
    Arthroplasty 254 (26.9) 146 (31.1)
Type of anesthesia 1.621 0.203
    General anesthesia 211 (22.4) 91 (19.4)
    Regional anesthesia 733 (77.6) 378 (80.6)
Duration of anesthesia/min 122.0 (102.0, 147.0) 127.5 (109.0, 154.0) -2.841 0.004
Duration of surgery/min 63.0 (49.0, 80.0) 61.5 (49.0, 83.3) -0.794 0.427
Intraoperative blood loss/mL 50.0 (50.0, 150.0) 60.0 (50.0, 150.0) -0.980 0.327
Intraoperative fluids infusion/mL 1 100 (1 000, 1 300) 1 100 (1 000, 1 300) -0.479 0.632
Intraoperative blood transfusion 3.176 0.075
     < 400 mL 851 (90.1) 413 (85.9)
    ≥400 mL 93 (9.9) 68 (14.1)
Postoperative heart failure 54 (5.7) 18 (3.8) 2.296 0.130

Table 2

Univariate analysis of factors associating with postoperative heart failure of elderly patients with hip fracture in the development cohort"

Variables Non-PHF group (n=890) PHF group (n=54) Z/χ2 P
Age/years 81.0 (74.0, 85.0) 83.0 (80.0, 88.0) -3.739 < 0.001
Gender 0.431 0.512
    Female 639 (71.8) 41 (75.9)
    Male 251 (28.2) 13 (24.1)
BMI/(kg/m2) 1.065 0.587
     < 18.5 131 (14.7) 6 (11.1)
    18.5-28.0 674 (75.7) 41 (75.9)
    >28.0 85 (9.6) 7 (13.0)
Medical history
    Heart disease 91 (10.2) 27 (50.0) 73.641 < 0.001
    Diabetes mellitus 247 (27.8) 18 (33.3) 0.785 0.376
    Hypertension 494 (55.5) 38 (70.4) 4.547 0.032
    Cerebrovascular disease 157 (17.6) 11 (20.4) 0.259 0.611
    Pulmonary disease 87 (9.8) 13 (24.1) 10.990 0.001
Type of fracture 3.534 0.171
    Femoral neck fracture 387 (43.5) 22 (40.7)
    Femoral intertrochanteric fracture 423 (47.5) 23 (42.6)
    Femoral subtrochanteric fracture 80 (9.0) 9 (16.7)
Time from injury to surgery/d 4.00 (2.00, 7.00) 4.00 (3.00, 7.25) -1.283 0.200
ASA classification 37.416 < 0.001
    Ⅰ-Ⅱ 732 (82.2) 26 (48.1)
    Ⅲ-Ⅳ 158 (17.8) 28 (51.9)
Preoperative blood transfusion 1.857 0.173
     < 400 mL 840 (94.4) 48 (88.9)
    ≥400 mL 50 (5.6) 6 (11.1)
Preoperative SBP/mmHg 135.0 (125.0, 146.0) 135.0 (125.0, 151.0) -0.144 0.885
Preoperative DBP/mmHg 76.0 (68.0, 80.0) 72.0 (68.0, 80.5) -0.977 0.329
Preoperative heart rate/(beat/min) 76.0 (70.0, 80.0) 78.0 (69.8, 85.8) -0.979 0.327
Preoperative laboratory examinations
    WBC/(×109/L) 9.06 (7.28, 11.13) 9.75 (7.92, 12.93) -1.869 0.062
    HGB/(g/L) 121.00 (108.00, 132.00) 111.50 (98.75, 126.00) -3.074 0.002
    PLT/(×109/L) 194.00 (156.00, 240.00) 202.00 (170.00, 285.00) -1.869 0.062
    ALT/(U/L) 20.00 (16.00, 26.00) 18.00 (13.00, 23.00) -1.119 0.263
    Scr/(μmol/L) 64.00 (54.00, 78.00) 79.00 (58.00, 109.00) -4.281 < 0.001
    K/(μmol/L) 4.08 (3.80, 4.38) 4.21 (3.88, 4.52) -1.844 0.065
    Na/(μmol/L) 138.80 (136.10, 141.12) 137.40 (134.98, 140.58) -1.913 0.056
    LVEF/% 71.0 (68.0, 73.0) 69.0 (65.8, 72.3) -2.255 0.024
Type of surgery 5.574 0.028
    Internal fixation 658 (73.9) 32 (59.3)
    Arthroplasty 232 (26.1) 22 (40.7)
Type of anesthesia 7.117 0.008
    General anesthesia 191 (21.5) 20 (37.0)
    Regional anesthesia 699 (78.5) 34 (63.0)
Duration of anesthesia/min 121.5 (101.0, 145.3) 123.0 (103.8, 158.3) -1.520 0.128
Duration of surgery/min 63.0 (49.0, 80.0) 64.5 (49.0, 83.3) -0.325 0.745
Intraoperative blood loss/mL 50.0 (50.0, 150.0) 50.0 (50.0, 150.0) -0.302 0.763
Intraoperative fluids infusion/mL 1 100.0 (1 000.0, 1 300.0) 1 100.0 (1 000.0, 1 312.5) -0.122 0.903
Intraoperative blood transfusion 1.589 0.208
     < 400 mL 805 (90.4) 46 (85.2)
    ≥400 mL 46 (9.6) 8 (14.8)

Table 3

Multivariate Logistic regression analysis of factors associating with postoperative heart failure of elderly patients with hip fracture in the development cohort"

Variables β Wald χ2 OR (95%CI) P
Age 0.069 7.140 1.071 (1.019-1.127) 0.008
Hip arthroplasty 0.922 6.820 2.513 (1.259-5.019) 0.009
General anesthesia 0.705 4.477 2.024 (1.053-3.890) 0.034
History of heart disease 1.679 25.896 5.360 (2.808-10.234) < 0.001
Preoperative hemoglobin -0.021 4.190 0.979 (0.960-0.999) 0.041
Preoperative serum creatinine 0.007 5.907 1.007 (1.001-1.013) 0.015

Figure 2

The nomogram for the prediction of the PHF risk in elderly patients with hip fracture HGB, hemoglobin; Scr, serum creatinine; PHF, postoperative heart failure."

Figure 3

The area under the ROC curve of the nomogram after internal and external validation using the Bootstrap method (resampling=1 000) A, ROC curve after internal validation; B, ROC curve after external validation. ROC, receiver operating characteristic; AUC, area under the curve."

Figure 4

The area under the ROC curve of the nomogram and the predictors in the development cohort HGB, hemoglobin; Scr, serum creatinine; ROC, receiver operating characteristic; AUC, area under the curve."

Figure 5

The area under the ROC curve of the two nomograms in the development and validation cohort A, ROC curves in the development cohort; B, ROC curves in the validation cohort. ModA, the 4-variable nomogram (includes age, history of heart disease, preoperative hemoglobin level, and preoperative serum creatinine); ModB, the 6-variable nomogram (includes the 4 variables in ModA and the predictors of hip arthroplasty and general anesthesia). ROC, receiver operating characteristic; AUC, area under the curve."

Figure 6

Calibration plots of the nomogram after internal and external validation A, calibration plot after internal validation; B, calibration plot after external validation. The black dashed diagonal line indicates the perfect prediction of the ideal model. The blue solid line represents the performance of the nomogram. The red solid line represents the performance of the model after internal and external validation by the Bootstrap method (resampling=1 000). When the solid line is closer to the black dashed line, the prediction accuracy of the nomogram is better."

Figure 7

Decision curve analyses of the nomogram after internal and external validation A, decision curve analysis after internal validation; B, decision curve analysis after external validation. The Y-axis represents the net benefit, and the X-axis represents the threshold probability. The red line represents the nomogram, and the grey and black lines represent the assumption that all and no patients have postoperative heart failure respectively."

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