Delirium risk in geriatric hip hemi-arthroplasty (DRIGHA): Development and validation of a novel score using a national data

Risk prediction models for postoperative delirium in elderly patients with fragility hip fracture: A systematic review and critical appraisal

BACKGROUND

Elderly patients with fragility hip fracture continue to experience a high rate of postoperative delirium (POD), which has a significant negative impact on prognosis and imposes a huge economic burden. A number of risk prediction models have been developed to detect POD early. However, the risk of bias and clinical applicability of the models remain unclear. The aim of this study was to systematically evaluate risk prediction models for POD.

METHODS

CNKI, WanFang DATA, Vip Database, SinoMed, PubMed, Web of Science, Embase, and the Cochrane Library were searched for studies published by July 2023. The literature was screened independently by two investigators. The Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS) and the Prediction Model Risk of Bias Assessment Tool (PROBAST) were respectively used for data extraction, risk of bias, and applicability assessment.

RESULTS

A total of 16 studies on the construction of POD risk prediction models were included. The area under the ROC curve of the models ranges from 0.670 to 0.957. The most common predictors of POD included age, history of dementia, history of delirium, ASA classification, preoperative waiting time, and preoperative albumin level. All models had a high risk of bias, mainly due to inadequate sample size, inappropriate handling of missing data, a lack of model performance evaluation, and overfitting of the models.

CONCLUSIONS

Overall, risk prediction models for POD in fragility hip fracture patients are still in the development stage. The majority of POD prediction models have substantial bias risks, attributable primarily to poor reporting of analysis and evaluation of model performance. In future research, it is recommended to conduct validation of the models or develop localized prediction models with demonstrated high performance, with the aim of benefiting POD screening.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42023449153.

Prediction models for postoperative delirium in elderly patients with machine-learning algorithms and SHapley Additive exPlanations

Postoperative delirium (POD) is a common and severe complication in elderly patients with hip fractures. Identifying high-risk patients with POD can help improve the outcome of patients with hip fractures. We conducted a retrospective study on elderly patients (≥65 years of age) who underwent orthopedic surgery with hip fracture between January 2014 and August 2019. Conventional logistic regression and five machine-learning algorithms were used to construct prediction models of POD. A nomogram for POD prediction was built with the logistic regression method. The area under the receiver operating characteristic curve (AUC-ROC), accuracy, sensitivity, and precision were calculated to evaluate different models. Feature importance of individuals was interpreted using Shapley Additive Explanations (SHAP). About 797 patients were enrolled in the study, with the incidence of POD at 9.28% (74/797). The age, renal insufficiency, chronic obstructive pulmonary disease (COPD), use of antipsychotics, lactate dehydrogenase (LDH), and C-reactive protein are used to build a nomogram for POD with an AUC of 0.71. The AUCs of five machine-learning models are 0.81 (Random Forest), 0.80 (GBM), 0.68 (AdaBoost), 0.77 (XGBoost), and 0.70 (SVM). The sensitivities of the six models range from 68.8% (logistic regression and SVM) to 91.9% (Random Forest). The precisions of the six machine-learning models range from 18.3% (logistic regression) to 67.8% (SVM). Six prediction models of POD in patients with hip fractures were constructed using logistic regression and five machine-learning algorithms. The application of machine-learning algorithms could provide convenient POD risk stratification to benefit elderly hip fracture patients.

The effect of parecoxib sodium on postoperative delirium in elderly patients with hip arthroplasty

Objective: This study aimed to clarify the effect of parecoxib sodium on the occurrence of postoperative delirium and to investigate its possible mechanism. Methods: A total of 80 patients who underwent elective hip arthroplasty in our hospital between December 2020 and December 2021 were selected and randomly divided into two groups: a parecoxib sodium group (group P, n = 40) and a control group (group C, n = 40). Patients in group P were intravenously injected with 40 mg of parecoxib sodium 30 min before anesthesia and at the end of the surgery. Patients in group C were intravenously injected with the same volume of normal saline at the same time points. The primary endpoint was the incidence of POD, and the secondary endpoints were the levels of inflammatory factors (tumor necrosis factor- α [TNF-α], interleukin [IL]-1β, IL-6, and IL-10), nerve injury-related factors (brain-derived neurotrophic factor [BDNF], S-100β protein, neuron-specific enolase [NSE], and neurofilament light chain [NfL]), and antioxidant factors (heme oxygenase-1 [HO-1]), as well as the Visual Analogue Scale (VAS) and Confusion Assessment Method-Chinese Reversion (CAM-CR) scores. Results: The incidence of POD was 10% in group P and 27.5% in group C. Intergroup comparison revealed that the levels of TNF-α, IL-1β, S-100β, NfL, and NSE were lower, and BDNF was higher, in group P than in group C at each postoperative time point. The levels of IL-6 were lower, and the levels of IL-10 and HO-1 were higher, in group P than in group C at 1 h and 1 day postoperatively (p < 0.05). Three days after surgery, the differences in the levels of IL-6, IL-10, and HO-1 were not statistically significant between the two groups (p > 0.05). The VAS and CAM-CR scores were lower at each postoperative time point in group P than in group C (p < 0.05). Conclusion: Parecoxib sodium could reduce postoperative pain, decrease the plasma levels of inflammatory and nerve injury-related factors, upregulate HO-1 levels, and reduce the incidence of POD. The results of this study suggest that parecoxib sodium may reduce the occurrence of POD through the effects of anti-inflammation, analgesia, and antioxidants.