Postoperative Pneumonia in Geriatric Patients With a Hip Fracture: Incidence, Risk Factors and a Predictive Nomogram

Construction and validation of a predictive model for lower extremity deep vein thrombosis after total knee arthroplasty

The aim was to investigate the independent risk factors for lower extremity deep vein thrombosis (DVT) after total knee arthroplasty, and to establish a nomogram prediction model accordingly. Data were collected from total knee replacement patients from January 2022 to December 2023 in our hospital. Unifactorial and multifactorial logistic regression analyses were used to determine the independent risk factors for lower extremity DVT after total knee arthroplasty and to establish the corresponding nomogram. The receiver operating characteristic curves were plotted and the area under the curve was calculated, and the calibration curves and decision curves were plotted to evaluate the model performance. A total of 652 patients with total knee arthroplasty were included in the study, and 142 patients after total knee arthroplasty developed deep veins in the lower extremities, with an incidence rate of 21.78%. After univariate and multivariate logistic regression analyses, a total of 5 variables were identified as independent risk factors for lower extremity DVT after total knee arthroplasty: age > 60 years (OR: 1.70; 95% CI: 1.23-3.91), obesity (OR: 1.51; 95% CI: 1.10-1.96), diabetes mellitus (OR: 1.80; 95% CI: 1.23-2.46), D-dimer > 0.5 mg/L (OR: 1.47; 95% CI: 1.07-1.78), and prolonged postoperative bed rest (OR: 1.64; 95% CI: 1.15-3.44). the nomogram constructed in this study for lower extremity DVT after total knee arthroplasty has good predictive accuracy, which helps physicians to intervene in advance in patients at high risk of lower extremity DVT after total knee arthroplasty.

Incorporating preoperative frailty to assist in early prediction of postoperative pneumonia in elderly patients with hip fractures: an externally validated online interpretable machine learning model

BACKGROUND

This study aims to implement a validated prediction model and application medium for postoperative pneumonia (POP) in elderly patients with hip fractures in order to facilitate individualized intervention by clinicians.

METHODS

Employing clinical data from elderly patients with hip fractures, we derived and externally validated machine learning models for predicting POP. Model derivation utilized a registry from Nanjing First Hospital, and external validation was performed using data from patients at the Fourth Affiliated Hospital of Nanjing Medical University. The derivation cohort was divided into the training set and the testing set. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used for feature screening. We compared the performance of models to select the optimized model and introduced SHapley Additive exPlanations (SHAP) to interpret the model.

RESULTS

The derivation and validation cohorts comprised 498 and 124 patients, with 14.3% and 10.5% POP rates, respectively. Among these models, Categorical boosting (Catboost) demonstrated superior discrimination ability. AUROC was 0.895 (95%CI: 0.841-0.949) and 0.835 (95%CI: 0.740-0.930) on the training and testing sets, respectively. At external validation, the AUROC amounted to 0.894 (95% CI: 0.821-0.966). The SHAP method showed that CRP, the modified five-item frailty index (mFI-5), and ASA body status were among the top three important predicators of POP.

CONCLUSION

Our model's good early prediction ability, combined with the implementation of a network risk calculator based on the Catboost model, was anticipated to effectively distinguish high-risk POP groups, facilitating timely intervention.

Non-linear relationship between preoperative albumin-globulin ratio and postoperative pneumonia in patients with hip fracture

BACKGROUND AND OBJECTIVE

Postoperative pneumonia (POP) is the leading cause of death among patients with hip fractures. Simple and cost-effective markers can be used to assess the risk of these patients. This study aims to investigate the association between POP and preoperative albumin-globulin ratio (AGR) in patients with hip fractures.

METHODS

A retrospective analysis was conducted on data from 1417 hip fracture patients admitted to the Department of Orthopaedics at the hospital. Generalized additive and logistic regression models were used to determine both linear and non-linear associations between preoperative AGR and POP. A two-piece regression model was employed to determine the threshold effect.

RESULTS

The study included 1417 participants, with a mean age of 77.57 (8.53) years and 26.96% (382/1417) male patients. The prevalence of POP was 6.21%. Following full covariate adjustment, each unit increase in AGR was associated with a 79% reduction in the incidence of POP (OR, 0.23; 95% CI: 0.08-0.63; P = 0.0046). The inflection point was found to be 1.33 using a two-piecewise regression model. For each unit increase in AGR on the left side of the inflection point, the incidence of POP decreased by 93% (OR, 0.07; 95%CI: 0.02-0.34; P = 0.0010). However, there was no statistically significant correlation on the right side of the inflection point (OR, 0.84; 95% CI: 0.17-4.10; P = 0.8287).

CONCLUSION

There exists a non-linear association between preoperative AGR and the incidence of POP in elderly hip fracture patients. When AGR is less than 1.33, the incidence of POP is negatively correlated with AGR. However, there is no correlation when AGR is greater than 1.33.

Risk factors for hospital-acquired pneumonia in hip fracture patients: A systematic review and meta-analysis

BACKGROUND

This study aimed to comprehensively assess the prevalence and risk factors for Hospital-acquired pneumonia (HAP) in hip fracture patients by meta-analysis.

METHODS

Systematically searched 4 English databases and 4 Chinese databases from inception until October 20, 2022. All studies involving risk factors of HAP in patients with hip fractures will be considered. Newcastle-Ottawa Scale was used to evaluate the quality of the included studies. The results were presented through Review Manager 5.4 with the pooled odds ratio (OR) and 95% confidence interval.

RESULTS

Of 35 articles included in this study, the incidence of HAP was 8.9%. 43 risk factors for HAP were initially included, 23 were eventually involved in the meta-analysis, and 21 risk factors were significant. Among them, the 4 most frequently mentioned risk factors were as follows: Advanced age (OR 1.07, 95% CI 1.05-1.10), chronic obstructive pulmonary disease (COPD) (OR 3.44, 95% CI 2.83-4.19), time from injury to operation (OR 1.09, 95% CI 1.07-1.12), time from injury to operation ≥ 48 hours (OR 3.59, 95% CI 2.88-4.48), and hypoalbuminemia < 3.5g/dL (OR 2.68, 95% CI 2.15-3.36).

DISCUSSION

Hip fracture patients diagnosed with COPD have a 3.44 times higher risk of HAP compared to the general hip fracture patients. The risk of HAP also increases with age, with patients over 70 having a 2.34-fold higher risk and those over 80 having a 2.98-fold higher risk. These findings highlight the need for tailored preventive measures and timely interventions in vulnerable patient populations. Additionally, hip fracture patients who wait more than 48 hours for surgery have a 3.59-fold higher incidence of HAP. This emphasizes the importance of swift surgical intervention to minimize HAP risk. However, there are limitations to consider in this study, such as heterogeneity in selected studies, inclusion of only factors identified through multivariate logistic regression, and the focus on non-randomized controlled trial studies.

Risk factors for hospital-acquired pneumonia in hip fracture patients: a systematic review and meta-analysis

OBJECTIVE

This study aimed to systematically assess the incidence and risk factors for hospital-acquired pneumonia (HAP) in hip fracture patients by meta-analysis.

METHODS

Systematically searched four English databases (PubMed, EMBASE, The Cochrane Library, and Web Of Science) and four Chinese databases (CNKI, CQVIP, Sinomed, and WAN FANG) from inception until 20 November 2023. All studies involving risk factors of HAP in patients with hip fractures were considered. Newcastle-Ottawa Scale was used to evaluate the quality of the included studies. The results were presented with the pooled odds ratio (OR) and 95% confidence interval (95% CI).

RESULTS

Of 35 articles (337,818 patients) included in this study, the incidence of HAP was 89 per 1000 cases. Twenty-three risk factors were eventually involved in the meta-analysis, and 21 risk factors were significant. Our study has identified four significant risk factors (advanced age, preoperative time, COPD, and hypoalbuminemia) associated with HAP, as follows: Advanced age as a continuous variable (OR 1.07, 95% CI 1.05-1.10), Advanced age > 70 years (OR 2.34, 95% CI 1.77-3.09), Advanced age > 80 years (OR 2.98, 95% CI 2.06-4.31), Chronic obstructive pulmonary disease (COPD) (OR 3.44, 95% CI 2.83-4.19), Time from injury to operation as a continuous variable (OR 1.09, 95% CI 1.07-1.12), Time from injury to operation ≥48 h (OR 3.59, 95% CI 2.88-4.48), Hypoalbuminemia < 3.0 g/dL (OR 3.03, 95% CI 1.93-4.73), and Hypoalbuminemia < 3.5 g/dL (OR 2.68, 95% CI 2.15-3.36). However, it is important to note that all the studies included in our research were retrospective in nature, which introduces certain limitations to the level of evidence and the ability to establish causal inferences.

DISCUSSION

Patients who have suffered hip fractures are at an increased risk of developing postoperative hospital-acquired pneumonia, which can lead to prolonged hospital stays and adverse clinical outcomes. Consequently, the identification of these risk factors offers novel insights and methodologies for healthcare professionals in terms of both prevention and treatment.

TRIAL REGISTRATION

Registration number: INPLASY2022100091.

Construction and validation of a nomogram prediction model for postoperative incisional infection in ankle fractures

The aim was to investigate the independent risk factors for postoperative incisional infection in ankle fractures and to establish a nomogram prediction model accordingly. Data were collected from ankle fracture patients in the Affiliated Hospital of Xinjiang Medical University from January 2018 to December 2022. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors for postoperative incisional infection in ankle fractures and to establish the corresponding nomogram. Receiver operating characteristic curves were plotted and area under the curve was calculated, and calibration curves and decision curve analysis were plotted to evaluate the model performance. A total of 722 patients with ankle fractures were included in the study, and 76 patients developed postoperative incisional infections, with an incidence of 10.53%. After univariate and multivariate logistic regression analysis, a total of 5 variables were identified as independent risk factors for postoperative incisional infection in ankle fractures, namely, age ≥ 60 years (OR, 1.885; 95% CI, 1.156-3.045), having diabetes (OR1.625; 95% CI, 1.095-2.876), open fracture (OR, 5.564; 95% CI, 3.099-9.990), albumin < 35 g/L (OR, 2.618; 95% CI, 1.217-4.215), and operative time ≥ 2 hours (OR, 1.606; 95% CI, 1.077-3.247). The nomogram for postoperative incisional infection after ankle fracture constructed in this study has good predictive accuracy and helps orthopedic surgeons to intervene earlier in patients at high risk of postoperative incisional infection after ankle fracture.

Development and validation of risk prediction nomograms for acute respiratory failure in elderly patients with hip fracture

BACKGROUND

Hip fractures in the elderly often lead to acute respiratory failure, but there is currently no tool to assess the prognosis of such patients. This study aims to develop a risk prediction model for respiratory failure in these patients.

METHODS

A retrospective cross-sectional study was conducted using the Medical Information Mart for Intensive Care (MIMIC)-IV database, incorporating data from 3,266 patients with hip fractures aged over 55 years from 2008 to 2019. Data included demographic information, laboratory indicators, comorbidities, and treatment methods. Patients were divided into a training group (70%) and a validation group (30%). Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select prognostic predictors, and a visualized nomogram model was constructed using multivariate logistic regression analysis. Model performance and clinical applicability were assessed. Statistical analyses were done using R4.2.2, with P < 0.05 deemed significant.

RESULTS

Seven key factors, including age, height, albumin, chloride, pneumonia, acute kidney injury (AKI), and heparin use, were associated with respiratory failure risk. The model demonstrated good performance with area under the curve (AUC) values of 0.77 and 0.73 in the training and validation sets, respectively. The calibration curve showed good agreement, and decision curve analysis (DCA) indicated the model's clinical benefit.

CONCLUSIONS

This risk prediction model can effectively predict respiratory failure in hip fracture patients, assisting clinicians in identifying high-risk individuals and providing evidence-based references for treatment strategies.

Construction and validation of a nomogram prediction model for chronic low back pain after PKP for lumbar compression fractures

The aim was to study the independent risk factors for chronic low back pain after lumbar compression fractures undergoing percutaneous kyphoplasty (PKP), and to establish a nomogram prediction model accordingly. Data were collected from patients with lumbar compression fractures from January 2017 to December 2021 at the Affiliated Hospital of Xinjiang Medical University. Univariate and multivariate logistic regression analyses were used to determine the independent risk factors for chronic low back pain after receiving PKP for lumbar compression fractures, and the corresponding nomogram was established. Receiver operating characteristic (ROC) curves were plotted and area under the curve (AUC) was calculated, and calibration curves and decision curve analysis (DCA) were plotted to evaluate the model performance. A total of 792 patients with lumbar compression fractures were included in the study, and 188 patients had chronic postoperative low back pain, with an incidence of 23.74%. After univariate and multivariate logistic regression analysis, a total of 5 variables were identified as independent risk factors for chronic low back pain after undergoing PKP for lumbar compression fractures, namely having diabetes (OR, 1.607; 95% CI, 1.157-3.205), preoperative T value < -2.5 SD (OR, 2.697; 95% CI, 1.417-5.021), multiple lumbar fractures (OR, 1.815; 95% CI, 1.415-3.201), lumbar compression ≥ 50% (OR, 2.854; 95% CI, 1.411-6.524), and bone cement leakage (OR, 2.911; 95% CI, 1.715-6.817). The nomogram for chronic low back pain after PKP for lumbar compression fractures constructed in this study has good predictive accuracy and helps orthopedic surgeons to intervene earlier in patients at high risk of chronic low back pain after undergoing PKP for lumbar compression fractures.

Association between admission hyperglycemia and postoperative pneumonia in geriatric patients with hip fractures

BACKGROUND

Admission hyperglycemia is a common phenomenon in the early stages of injury. This study aimed to determine the relationship between admission hyperglycemia and postoperative pneumonia in geriatric patients with hip fractures.

METHODS

A total of 600 geriatric patients admitted to Dandong Central Hospital with hip fractures were included. Patients were divided into four groups based on quartiles of admission blood glucose levels: Q1- Q4. Multivariable logistic regression and propensity score-matched analyses were conducted to calculate adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for postoperative pneumonia. Receiver operating characteristic (ROC) curves were used to determine the cut-off value of admission hyperglycemia for predicting postoperative pneumonia.

RESULTS

The incidence of postoperative pneumonia was significantly higher among hyperglycemic patients than those with normal glucose levels (OR = 2.090, 95% CI: 1.135-3.846, p = 0.016). Admission hyperglycemia showed moderate predictive power, with an area under the ROC curve of 0.803. Furthermore, propensity score-matched analyses demonstrated that patients in the Q3 (OR = 4.250, 95% CI: 1.361-13.272, p = 0.013) and Q4 (OR = 4.667, 95% CI: 1.251-17.405, p = 0.022) quartiles had a significantly higher risk of postoperative pneumonia compared to patients in the Q1 quartile.

CONCLUSIONS

Admission hyperglycemia in elderly hip fracture patients increases the risk of postoperative pneumonia. This biomarker can aid clinical assessment and perioperative management.

Machine learning algorithms to predict risk of postoperative pneumonia in elderly with hip fracture

BACKGROUND

Hip fracture (HF) is one of the most common fractures in the elderly and is significantly associated with high mortality and unfavorable prognosis. Postoperative pneumonia (POP), the most common postoperative complication of HF, can seriously affect patient prognosis and increase the burden on the healthcare system. The aim of this study was to develop machine learning models for identifying elderly patients at high risk of pneumonia after hip fracture surgery.

METHODS

From May 2016 to November 2022, patients admitted to a single central hospital for HF served as the study population. We extracted data that could be collected within 24 h of patient admission. The dataset was divided into training and validation sets according to 70:30. Based on the screened risk factors, prediction models were developed using seven machine learning algorithms, namely CART, GBM, KNN, LR, NNet, RF, and XGBoost, and their performance was evaluated.

RESULTS

Eight hundred five patients were finally included in the analysis and 75 (9.3%) patients suffered from POP. Age, CI, COPD, WBC, HB, GLU, STB, GLOB, Ka+ which are used as features to build machine learning models. By evaluating the model's AUC value, accuracy, sensitivity, specificity, Kappa value, MCC value, Brier score value, calibration curve, and DCA curve, the model constructed by XGBoost algorithm has the best and near-perfect performance.

CONCLUSION

The machine learning model we created is ideal for detecting elderly patients at high risk of POP after HF at an early stage.

Relationship between preoperative red blood cell distribution width and postoperative pneumonia in elderly patients with hip fracture: a retrospective cohort study

OBJECTIVE

The relationship between the preoperative red blood cell distribution width and postoperative pneumonia in elderly patients with hip fractures remains unclear. This study investigated whether the preoperative red blood cell distribution width was associated with postoperative pneumonia in elderly patients with hip fractures.

METHODS

Clinical data of patients with hip fractures in the Department of orthopedics of a hospital from January 2012 to December 2021 were retrospectively analyzed. A generalized additive model was used to identify both linear and nonlinear relationships between red blood cell distribution width and postoperative pneumonia. A two-piecewise linear regression model was used to calculate the saturation effect. Subgroup analyses were performed using stratified logistic regression.

RESULTS

This study included a total of 1444 patients. The incidence of postoperative pneumonia was 6.30% (91/1444), the mean age of the patients was 77.55 ± 8.75 years, and 73.06% of them (1055/1444) were female. After full adjustment for covariates, the preoperative red blood cell distribution width showed a nonlinear relationship with postoperative pneumonia. The two-piecewise regression model showed an inflection point at 14.3%. On the left side of the inflection point, the incidence of postoperative pneumonia increased by 61% for every 1% increase in red blood cell distribution width (OR: 1.61, 95% CI 1.13-2.31, P = 0.0089). The effect size was not statistically significant on the right side of the inflection point (OR: 0.83, 95% CI 0.61-1.12, P = 0.2171).

CONCLUSION

The relationship between preoperative red blood cell distribution width and incidence or postoperative pneumonia was nonlinear in elderly patients with hip fractures. The incidence of postoperative pneumonia was positively correlated with red blood cell distribution width when it was < 14.3%. A saturation effect was observed when the red blood cell distribution width reached 14.3%.

What are Risk Factors of Postoperative Pneumonia in Geriatric Individuals after Hip Fracture Surgery: A Systematic Review and Meta-Analysis

Postoperative pneumonia (POP) is a common postoperative complication. Negative consequences associated with POP included prolonged hospital length of stay, more frequent intensive care unit (ICU) stays, and a higher rate of sepsis, readmission, and mortality. This meta-analysis aimed to assess the incidence and risk factors associated with POP after hip fracture surgery in elderly patients. PubMed, Web of Science, and Cochrane Library were searched (up to March 31, 2022). All studies on the risk factors for POP after hip fracture surgery in elderly patients, published in English, were reviewed. The qualities of the included studies were assessed using the Newcastle-Ottawa Scale. Data were pooled, and a meta-analysis was performed. Ten studies, including 12,084 geriatric patients undergoing hip fracture surgery, were included. Of these 12,084 patients, POP occurred in 809 patients. The results indicated that age (mean difference [MD] = 4.95, 95% confidence interval [CI]: 3.22-6.69), male (odds ratio [OR] = 1.41, 95% CI: 1.02-1.93), the American Society of Anaesthesiologists classification ≥3 (OR = 3.48, 95% CI: 1.87-6.47), dependent functional status (OR = 5.23, 95% CI: 2.18-12.54, P = 0.0002), smoking (OR = 1.33, 95% CI: 1.07-1.65), chronic obstructive pulmonary disease (OR = 3.76, 95% CI: 2.07-6.81), diabetes mellitus (OR = 1.19, 95% CI: 1.01-1.40), coronary heart disease (OR = 1.74, 95% CI: 1.23-2.46), arrhythmia (OR = 1.47, 95% CI: 1.01-2.14), cerebrovascular disease (OR = 1.88, 95% CI: 1.56-2.27), dementia (OR = 2.36, 95% CI: 1.04-5.36), chronic renal failure (OR = 1.85, 95% CI: 1.29-2.67), hip arthroplasty (OR = 1.30, 95% CI: 1.08-1.56), delayed surgery (OR = 6.40, 95% CI: 3.00-13.68), preoperative creatinine (MD = 5.32, 95% CI: 0.55-10.08), and preoperative serum albumin (MD = -3.01, 95% CI: -4.21 - -1.80) were risk factors for POP. Related prophylactic measures should be provided in geriatric patients with the above-mentioned risk factors to prevent POP after hip fracture surgery.