Risk Factors Analysis and Nomogram Model Establishment of Hidden Blood Loss in Overweight and Obese Elderly Patients After Total Hip Arthroplasty.

Background: Total hip arthroplasty (THA) has become the first-choice treatment for elderly patients with end-stage hip disease. The high amount of hidden blood loss (HBL) in overweight and obese patients after THA not only affects rapid recovery, but also results in a greater economic burden. We aimed to identify risk factors that contribute to elevated HBL in overweight and obese patients after THA by retrospective analysis, and establish a nomogram prediction model for massive HBL in overweight and obese patients after THA. Methods: A total of 505 overweight and obese patients treated with THA were included and randomly divided into modeling and validation sets according to a 7:3 ratio. The demographic and relevant clinical data of the patients were collected. The independent risk factors affecting HBL after THA in overweight and obese patients were obtained by Pearson, independent sample T-test, and multiple linear regression analyses. R software was used to establish a nomogram prediction model for postoperative HBL, as well as a receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: HBL was 911±438 mL, accounting for 79.5±13.1% of the total perioperative blood loss (1104±468 mL). A multiple linear regression analysis showed that HBL was associated with necrosis of the femoral head, absence of hypertension, longer operative time, higher preoperative erythrocytes, and higher preoperative D-dimer levels. The areas under the ROC curve (AUC) for the modeling and validation sets were 0.751 and 0.736, respectively, while the slope of the calibration curve was close to 1. The DCA curve demonstrated a better net benefit at a risk of HBL ≥1000 ml in both the training and validation groups. Conclusion: HBL was an important component of total blood loss (TBL) after THA in overweight and obese patients. Necrosis of the femoral head, absence of hypertension, longer operative time, higher preoperative erythrocytes, and higher preoperative D-dimer levels were independent risk factors for postoperative HBL in these patients. The predictive model constructed based these data had better discriminatory power and accuracy, and could result in better net benefit for patients.

Galangin ameliorates osteoarthritis progression by attenuating extracellular matrix degradation in chondrocytes via the activation of PRELP expression.

Osteoarthritis (OA) is primarily characterized by progressive degeneration and destruction of articular cartilage. Currently, there is no effective method to treat OA. The metabolic disturbance of cartilage extracellular matrix (ECM) and oxidative stress are critical to promote OA progression. Galangin (Gal) is a small molecule compound that pertains to flavonoids. To determine the protective effect and mechanism of Gal against OA progression, various experiments were performed in vitro and in vivo. In vitro, Gal promoted ECM production and attenuated ECM degradation in human OA chondrocytes. The expression of ECM components from human OA cartilage explants was also stimulated by Gal treatment. As demonstrated from the in vivo study, the intra-articular injection of Gal delayed OA progression in rat models. Moreover, RNA sequencing analysis showed that proline/arginine-rich end leucine repeat protein (PRELP) was a molecular target of Gal activity. Gal inhibited oxidative stress and attenuated ECM degradation by activating PRELP expression. The study demonstrated that Gal could attenuate ECM degradation and ameliorate OA progression, and PRELP may be a potential candidate drug of Gal for treating OA.

Risk Factors Analysis and the Establishment of Nomogram Prediction Model of Hidden Blood Loss After Total Hip Arthroplasty for Femoral Neck Fracture in Elderly Women.

Purpose: To investigate the risk factors of increased hidden blood loss (HBL) after total hip arthroplasty (THA) for femoral neck fracture in elderly women and establish the nomogram prediction model for the guidance to reduce HBL in clinic. Patients and Methods: A total of 206 elderly female patients with femoral neck fracture who underwent THA in Northern Jiangsu People's Hospital from January 2019 to November 2021 were included. The demographic and relevant clinical information of the patients were collected. Pearson, independent sample t-test, multiple linear regression and other statistical methods were used for correlation analysis by SPSS 22.0 statistical software. Moreover, the risk factors of postoperative HBL increase in THA patients were obtained and the nomogram prediction model for the guidance to reduce HBL in clinic was established. Results: HBL was 626 ± 400 mL, accounting for 72.8% ± 18.4% of the perioperative total blood loss (TBL) (799 ± 411 mL), while blood loss of HGB was 15.1±10.4 g/L. Multiple linear regression analysis showed that HBL was associated with lower age (regression coefficient = -9.271, P = 0.010), operative time (regression coefficient = 2.653, P = 0.004), preoperative blood calcium (<2.25 mmol/L) (regression coefficient = 232.492, P < 0.001), hypertension (regression coefficient = 150.352, P = 0.002) and osteoporosis (regression coefficient = 276.072, P < 0.001). R software was used to construct the nomogram prediction model and draw the ROC curve and calibration curve. The area under the curve (AUC) is 0.92 and the slope of calibration curve is close to 1. Conclusion: Based on the five independent risk factors including age, operative time, preoperative blood calcium, hypertension and osteoporosis, the nomogram can predict the risk of HBL after THA for femoral neck fracture in elderly women with favorable differentiation and accuracy.