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- W4387457946 abstract "The skeletal muscle mass index (SMI) and skeletal muscle radiodensity (SMD) have shown promise as specific diagnostic indicators for muscle quality. However, the current difficulties in measuring low-SMI (LSMI) and low-SMD (LSMD) limit their use in routine clinical practice, impeding early screening and diagnosis. The objective of this study is to develop a nomogram that incorporates preoperative factors for predicting LSMI and LSMD. A total of 1,692 colorectal cancer patients between 2015 and 2021 were included. The patients were randomly divided into a training cohort (n = 1,353) and a validation cohort (n = 339). Nomogram models were calibrated using the area under the curve (AUC), calibration curves, and the Hosmer-Lemeshow test to assess their predictive ability. Finally, a decision curve was applied to assess the clinical utility. In prediction model for LSMI, Age, BMI, and grip strength were incorporated as variables. For LSMD, Age, gender, BMI, serum hemoglobin level, and grip strength were included as predictors. In the training cohort, the AUC value for LSMI was 0.750 (95% CI: 0.726 - 0.773), while for LSMD it was 0.763 (95% CI: 0.739 - 0.785). The HL test confirmed that both models fit well in both cohorts. Decision curve analysis demonstrated the clinical usefulness of the model. The incorporation of preoperative factors into the nomogram-based prediction model represents a significant advancement in the muscle quality assessment. Its implementation has the potential to early screen patients at risk of LSMI and LSMD." @default.
- W4387457946 created "2023-10-10" @default.
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- W4387457946 date "2023-10-01" @default.
- W4387457946 modified "2023-10-11" @default.
- W4387457946 title "Establishment and validation of novel nomograms to predict muscle quality in colorectal cancer patients" @default.
- W4387457946 doi "https://doi.org/10.1016/j.nut.2023.112256" @default.
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