Background: Malnutrition is significantly associated with unfavorable outcomes, but there is little high-level evidence to elucidate the association of malnutrition with losing walking independence (LWI) after hip fracture surgery. This study aimed to assess the association between preoperative nutritional status evaluated by the Controlling Nutritional Status (CONUT) score and walking independence at 180 days postoperatively in Chinese older hip fracture patients. Methods: This prospective cohort study included 1958 eligible cases from the SSIOS database. The restricted cubic spline was used to assess the dose-effect relationship between the CONUT score and the recovery of walking independence. Propensity score matching was performed to balance potential preoperative confounders, and multivariate logistic regression analysis was applied to assess the association between malnutrition and LWI with perioperative factors for further adjustment. Furthermore, inverse probability treatment weighting and sensitivity analyses were performed to test the robustness of the results and the Fine and Gray hazard model was applied to adjust the competing risk of death. Subgroup analyses were used to determine potential population heterogeneity. Results: The authors found a negative relationship between the preoperative CONUT score and recovery of walking independence at 180 days postoperatively, and that moderate-to-severe malnutrition evaluated by the CONUT score was independently associated with a 1.42-fold (95% CI, 1.12–1.80; P=0.004) increased risk of LWI. The results were overall robust. And in the Fine and Gray hazard model, the result was still statistically significant despite the apparent decrease in the risk estimate from 1.42 to 1.21. Furthermore, significant heterogeneities were observed in the subgroups of age, BMI, American Society of Anesthesiologists score, Charlson’s comorbidity index, and surgical delay (P for interaction < 0.05). Conclusion: Preoperative malnutrition is a significant risk factor for LWI after hip fracture surgery, and nutrition screening on admission would generate potential health benefits.

Background Deep vein thrombosis (DVT) is a devastating complication in geriatric patients before hip fracture surgery, and the predictive value of red cell distribution width (RDW) and high-density lipoprotein cholesterol (HDL-C) for DVTs after hip fracture remains to be established. This study aimed to assess the predictive value of RDW, HDL-C, and RDW-to-HDL-C ratio (RHR) in preoperative DVTs screening. Methods We retrospectively analyzed the data of geriatric patients (≥65 years old) admitted for hip fracture surgery between 2015 and 2020. The receiver operating characteristic (ROC) curve and related parameters were used to evaluate the predictive value of the biomarkers. Patients were divided into two groups according to the cutoff value of RHR, and propensity score matching (PSM) and subgroup analyses were performed to assess the true correlations between RHR and DVT. Results Among 2566 eligible patients included, we identified RDW with the area under ROC curve (AUC) of 0.532, cut-off value of 15.89, specificity of 88.2%, sensitivity of 18.2%, HDL-C with AUC of 0.574, cut-off value of 1.20, specificity of 55.6%, sensitivity of 59.3%, and RHR with AUC of 0.578, cut-off value of 13.45, specificity of 71.3%, sensitivity of 43.4%. RHR (>13.45) was independently associated with 1.54-fold risk (95% CI: 1.11–2.14, P=0.011) of DVTs among the post-PSM cohort. And compared with the counterparts, the relative risk of RHR associated with DVT was higher in the subgroups of aged 65–79 years (1.61 vs 1.45), non-hypoproteinemia (2.70 vs 1.29), non-diabetic (1.58 vs 1.41), non-hypertension (2.40 vs 1.06), ASA score I-II (2.38 vs 1.04), and femoral neck fracture (1.70 vs 1.50). Conclusion RDW, HDL-C and RHR were valuable biomarkers in predicting preoperative DVTs in geriatric patients with hip fracture, and RHR would be more efficient in the subgroups of younger age, better medical condition or femoral neck fracture.

Background Hip arthroplasty is in increasing demand with the aging of the world population, and early infections, such as pneumonia, surgical site infection (SSI), and urinary tract infection (UTI), are uncommon but fatal complications following hip arthroplasty. This study aimed to identify preoperative risk factors independently associated with early infections following primary arthroplasty in geriatric hip fracture patients, and to develop a prediction nomogram. Methods Univariate and multivariate logistical analyses were performed to identify the independent risk factors for early infections, which were combined and transformed into a nomogram model. The prediction model was evaluated by using the area under the receiver operating characteristic curve (AUC), Hosmer–Lemeshow test, concordance index (C-index), 1000 bootstrap replications, decision curve analysis (DCA), and calibration curve. Results One thousand eighty-four eligible patients got included and 7 preoperative variables were identified to be independently associated with early infections, including heart disease (odds ratio (OR): 2.17; P: 0.026), cerebrovascular disease (OR: 2.25; P: 0.019), liver disease (OR: 8.99; P: <0.001), time to surgery (OR: 1.10; P: 0.012), hematocrit (44.52; OR: 2.73; P: 0.047), and high-sensitivity C-reactive protein (HCRP; >78.64mg/L; OR: 3.71; P: <0.001). For the nomogram model, AUC was 0.807 (95% confidence interval (CI): 0.742–0.873), the Hosmer-Lemeshow test demonstrated no overfitting (P = 0.522), and C-index was 0.807 (95% CI: 0.742–0.872) with corrected value of 0.784 after 1000 bootstrapping validations. Moreover, the calibration curve and DCA exhibited the tools’ good prediction consistency and clinical practicability. Conclusion Heart disease, cerebrovascular disease, liver disease, time to surgery, hematocrit, PMR, and HCRP were significant preoperative predictors for early infections following primary arthroplasty in elderly hip fracture patients, and the converted nomogram model had strong discriminatory ability and translatability to clinical application.

The fact that most of the patients with preoperative DVTs after calcaneal fractures are asymptomatic brought challenges to the early intervention, and periodic imaging examinations aggravated the financial burden of the patients in preoperative detumescence period. This study aimed to use routine clinical data, obtained from the database of Surgical Site Infection in Orthopaedic Surgery (SSIOS), to construct and validate a nomogram for predicting preoperative DVT risk in patients with isolated calcaneal fracture. The nomogram was established base on 7 predictors independently related to preoperative DVT. The performance of the model was tested by concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA), and the results were furtherly verified internally and externally. 952 patients were enrolled in this study, of which 711 were used as the training set. The AUC of the nomogram was 0.870 in the training set and 0.905 in the validation set. After internal verification, the modified C-index was 0.846. Calibration curve and decision curve analysis both performed well in the training set and validation set. In short, we constructed a nomogram for predicting preoperative DVT risk in patients with isolated calcaneal fracture and verified its accuracy and clinical practicability.