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. 2024 Dec 26;29(1):626.
doi: 10.1186/s40001-024-02244-1.

Comprehensive assessment of risk factors and development of novel predictive tools for perioperative hidden blood loss in intertrochanteric femoral fractures: a multivariate retrospective analysis

Linbing Lou #  1   2 , Lei Xu #  3 , Xiaofei Wang  2 , Cunyi Xia  3 , Jihang Dai  1 , Le Hu  4
Affiliations

Comprehensive assessment of risk factors and development of novel predictive tools for perioperative hidden blood loss in intertrochanteric femoral fractures: a multivariate retrospective analysis

Linbing Lou et al. Eur J Med Res. .

Abstract

Objectives: To identify independent risk factors for perioperative hidden blood loss (HBL) in intertrochanteric femoral fractures (ITFs) and to develop a predictive model.

Methods: We enrolled 231 patients with ITFs who underwent proximal femoral nail antirotation (PFNA) surgery at the Orthopedics Department of Northern Jiangsu People's Hospital, Jiangsu Province, China, from January 2021 to December 2023. Hidden blood loss was calculated using the OSTEO formula, and independent risk factors were screened using the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression. A nomogram prediction model was subsequently constructed based on multivariate logistic regression.

Results: The LASSO regression identified eight key predictive factors: sex, body mass index (BMI), Admission serum calcium (mmol/L), American Society of Anesthesiologists (ASA) physical status classification, fracture type (Evans), hypertension, preoperative blood transfusion, and preoperative hemoglobin (HGB, g/L). The nomogram model demonstrated excellent predictive performance in both the training and validation sets, with area under the curve (AUC) values of 0.947 and 0.902, respectively. Calibration curves and decision curve analyses further confirmed the strong agreement between model predictions and actual observations, as well as the net clinical benefit.

Conclusions: The nomogram model facilitates an intuitive and quantitative assessment of the risk of perioperative hidden blood loss in patients with ITFs, providing robust support for clinical decision-making.

Keywords: Hidden blood loss (HBL); Intertrochanteric fractures (ITFs); Nomogram; PFNA.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The present study protocol was reviewed and approved by the Institutional Review Board of Northern Jiangsu People’s Hospital (approval No. 2023ky214). Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Optimize the screening variables by the LASSO regression. A Lasso regression cross-validation plot. B Lasso regression coefficient path plot. C ROC curve analysis of 8 candidate diagnostic indicators
Fig. 2
Fig. 2
Nomogram for predicting the risk factors for perioperative HBL in intertrochanteric femoral fractures
Fig. 3
Fig. 3
ROC curves of the nomogram prediction mode
Fig. 4
Fig. 4
Validation process of the nomogram prediction mode. A Calibration curve of training cohort. B Calibration curve of internal test cohort. C Decision curve analysis of training cohort. D Decision curve analysis of internal test cohort
See this image and copyright information in PMC

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