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. 2024 Dec 19:12:e18753.
doi: 10.7717/peerj.18753. eCollection 2024.

A novel model based on clinical and computed tomography (CT) indices to predict the risk factors of postoperative major complications in patients undergoing pancreaticoduodenectomy

Jiaqi Wang #  1 , Kangjing Xu #  1 , Changsheng Zhou  2 , Xinbo Wang  1 , Junbo Zuo  3 , Chenghao Zeng  1 , Pinwen Zhou  1 , Xuejin Gao  1 , Li Zhang  1 , Xinying Wang  1
Affiliations

A novel model based on clinical and computed tomography (CT) indices to predict the risk factors of postoperative major complications in patients undergoing pancreaticoduodenectomy

Jiaqi Wang et al. PeerJ. .

Abstract

Background: Postoperative complications are prone to occur in patients after radical pancreaticoduodenectomy (PD). This study aimed to construct and validate a model for predicting postoperative major complications in patients after PD.

Methods: The clinical data of 360 patients who underwent PD were retrospectively collected from two centers between January 2019 and December 2023. Visceral adipose volume (VAV) and subcutaneous adipose volume (SAV) were measured using three-dimensional (3D) computed tomography (CT) reconstruction. According to the Clavien-Dindo classification system, the postoperative complications were graded. Subsequently, a predictive model was constructed based on the results of least absolute shrinkage and selection operator (LASSO) multivariate logistic regression analysis and stepwise (stepAIC) selection. The nomogram was internally validated by the training and test cohort. The discriminatory ability and clinical utility of the nomogram were evaluated by area under the receiver operating characteristic (ROC) curve (AUC), calibration curve, and decision curve analysis (DCA).

Results: The major complications occurred in 13.3% (n = 48) of patients after PD. The nomogram revealed that high VAV/SAV, high system inflammation response index (SIRI), high triglyceride glucose-body mass index (TyG-BMI), low prognostic nutritional index (PNI) and CA199 ≥ 37 were independent risk factors for major complications. The C-index of this model was 0.854 (95%CI [0.800-0.907]), showing excellent discrimination. The calibration curve demonstrated satisfactory concordance between nomogram predictions and actual observations. The DCA curve indicated the substantial clinical utility of the nomogram.

Conclusion: The model based on clinical and CT indices demonstrates good predictive performance and clinical benefit for major complications in patients undergoing PD.

Keywords: Pancreaticoduodenectomy; Postoperative complications; Predictive model; Three-dimensional CT reconstruction.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1. 3D CT reconstruction to analyze the L3 adipose and muscle tissue.
(A) Analysis results of patient’s adipose and muscle tissue. (B) Axial slice reformation of a preoperative CT scan at the L3 level. (C) Sagittal reformation at the L3 level of the same patient. (D) Coronal plane reformation at the L3 level of the same patient.
Figure 2
Figure 2. Nomogram to predict the probability of major complications after PD.
Figure 3
Figure 3. The ROC curve of the predictive model for major complications after PD.
Figure 4
Figure 4. The calibration curve of the nomogram for predicting the probability of major complications (bootstrap = 1,000 repetitions).
Figure 5
Figure 5. DCA curves of the prediction model to predict the probability of major complications.
See this image and copyright information in PMC

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