Risk of post-operative cardiovascular event in elderly patients with pre-existing cardiovascular disease who are undergoing hip fracture surgery

Unveiling unique clinical phenotypes of hip fracture patients and the temporal association with cardiovascular events

Cardiovascular events are the leading cause of death among hip fracture patients. This study aims to identify subphenotypes of hip fracture patients and investigate their association with incident cardiovascular events, all-cause mortality, and health service utilisation in Hong Kong and the United Kingdom populations. By the latent class analysis, we show three distinct clusters in the Hong Kong cohort (n = 78,417): Cluster 1 has cerebrovascular and hypertensive diseases, hyperlipidemia, and diabetes; Cluster 2 has congestive heart failure; Cluster 3 consists of relatively healthy patients. Compared to Cluster 3, higher risks of major adverse cardiovascular events are observed in Cluster 1 (hazard ratio 1.97, 95% CI 1.83 to 2.12) and Cluster 2 (hazard ratio 4.06, 95% CI 3.78 to 4.35). Clusters 1 and 2 are also associated with a higher risk of mortality, more unplanned accident and emergency visits and longer hospital stays. Self-controlled case series analysis shows a significantly elevated risk of major adverse cardiovascular events within 60 days post-hip fracture. Similar associations are observed in the United Kingdom cohort (n = 27,948). Pre-existing heart failure is identified as a unique subphenotype associated with poor prognosis after hip fractures.

Characteristics of Postoperative Heart Failure in Older Hip Fractures Patients Combined with Coronary Heart Disease and Construction of a Prediction Model of Nomogram, a Retrospective Cohort Study

Introduction

Older patients combined with coronary heart disease (CHD) develop acute heart failure (AHF) after hip fracture surgery is common, and this study aimed to investigate the risk factors of postoperative AHF in older hip fracture patients and to construct a nomogram prediction model.

Methods

We retrospectively collected older hip fracture patients with CHD who underwent hip fracture surgery at the Third Hospital of Hebei Medical University from January 2017 to December 2021. We divided them into a training set and a validation set. We collected the demographic data, laboratory indicators and imaging examination results. We identified risk factors for postoperative AHF and used R language software to establish a nomogram prediction model, plot ROC curves, calibration curves and DCA decision curves.

Results

We retrospectively collected 1288 older hip fractures patients with CHD. After excluding 214 patients who did not meet the criteria, 1074 patients were included in our research and we divided them into the training set and the validation set. In the training set, a total of 346 (42.8%) patients developing postoperative AHF. Through univariate and multivariate logistic regression analysis, we identified the risk factors for postoperative AHF and constructed a nomogram prediction model. The AUC of the prediction model is 0.778. The correction curve shows that the model has good consistency. The decision curve analysis shows that the model has good clinical practicality.

Conclusion

There were 42.8% older patients combined with CHD develop postoperative AHF. Among them, fracture type, age, anemia at admission, combined with COPD, ASA ≥ 3, and preoperative waiting time >3 days are risk factors for postoperative AHF. We constructed a nomogram prediction model that can effectively predict the risk of postoperative AHF in older hip fracture patients combined with CHD.

Risk Factors of Postoperative Acute Heart Failure in Elderly Patients After Hip Fracture Surgery

Background Postoperative acute heart failure (AHF) in elderly patients after hip fracture surgery is a common complication. Therefore, this study aimed to identify the risk factor of AHF after hip fracture surgery among the older population. Methods This retrospective cohort study was performed on 88 admitted patients whose hip fractures were fixed via internal fixation surgery in a tertiary care hospital in Rawalpindi, Pakistan, from January 2022 to March 2023. Recruitment of patients was made through established inclusion and exclusion criteria. Ethical approval and informed consent were also gained before the data collection. A self-designed form was used to collect data. Data analysis was carried out in the IBM SPSS Statistics for Windows, Version 25 (Released 2017; IBM Corp., Armonk, New York, United States). Both descriptive and inferential statistics were applied to compare the attributes of the patients with AHF and patients without AHF. Multivariate logistic regression was used to evaluate the association between the postoperative AHF and its potential risk factors. Results Out of 88 enrolled patients, 12 (13.64%) had developed postoperative AHF. Age ≥ 65 years (OR = 2.606, 95% CI = 1.035~4.160, p = 0.010), anemia (OR = 3.178, 95% CI = 1.847~5.990, p = 0.029), hypertension (OR = 2.019, 95% CI = 1.110~4.034, p = 0.012), diabetes mellitus (OR = 2.003, 95% CI = 1.115~4.012, p = 0.015), hypoalbuminemia (OR = 2.486, 95% CI = 1.218~4.619, p = 0.030), and operation time ≥ 120 minutes (OR = 1.702, 95% CI = 1.099~2.880, p = 0.018), were the risk factors of postoperative AHF in elderly patients after hip fracture surgery. Conclusions In the study population, the incidence of postoperative heart failure was significant and age ≥ 65 years, anemia, hypertension, diabetes mellitus, hypoalbuminemia, and operation time ≥ 120 were significantly involved in the development of it. Preoperative identification and management of AHF risk factors could lead to the prevention of postoperative complications.

Shape phenotype of thigh fat and muscle and risk of major adverse cardiovascular events after fragility hip fracture

BACKGROUND

Although sarcopenia has been recognized as a predictor of mortality in elderly patients with hip fracture, the association of thigh fat and muscle with cardiovascular (CV) outcome remains unclear. We examined the impact of computed tomography (CT)-derived shape features of thigh fat and muscle on major adverse CV events (MACE) in elderly patients with hip fracture.

METHODS

We conducted a retrospective analysis of consecutive patients aged ≥65 years who presented with hip fracture confirmed on pelvic bone CT scan and underwent hip fracture surgery at our institution from April 2019 to December 2021. The cross-sectional area (CSA) and compactness (CM) of both the muscle and fat at the upper-thigh level were calculated from two-dimensional CT images using AVIEW Research (v1.1.38, Coreline Soft, Co. Ltd, Seoul, South Korea). The shape features of thigh fat and muscle were categorized into four groups based on the combination of CSA and CM: fat CSA (fat area [FA])/fat CM (FCM), muscle CSA (muscle area [MA])/muscle CM (MCM), FA/MCM and MA/FCM. In each of them, subjects were categorized into four subgroups: high CSA/high CM, high CSA/low CM, low CSA/high CM and low CSA/low CM. The primary outcome was MACE after 30 days of surgery, defined as a composite of all-cause death, acute myocardial infarction, stroke or hospitalization for heart failure.

RESULTS

Of 356 patients enrolled (median age, 82 years; 76.7% females), 72 (20.2%) had MACE over a median follow-up of 13.1 months (ranges 5.9-21.0 months). Patients with MACE had a significantly lower median FA (193.7 vs. 226.2 cm2 , P < 0.0001) and FCM (0.443 vs. 0.513, P = 0.001) compared with those without MACE, but no significant differences were found in MA, MCM and FA-MA ratio between the two groups. In a multivariate Cox regression analysis, low FA (<240.1 cm2 ) (adjusted hazard ratio [HR] 2.99, 95% confidence interval [CI] 1.39-6.44, P = 0.005) and low FCM (<0.477) (adjusted HR 2.00, 95% CI 1.10-3.63, P = 0.023) were associated with an increased risk of MACE. Among the shape phenotypes of thigh fat and muscle, the thigh fat phenotype of low FA/low FCM (adjusted HR 3.13, 95% CI 1.81-5.42, P < 0.0001 [reference, high FA/high FCM]) was found to be an independent predictor of MACE.

CONCLUSIONS

In elderly patients with fragility hip fracture, thigh CT-derived measures of FA and FCM may provide useful prognostic information for predicting adverse CV outcomes.

Development and Internal Validation of a Nomogram for Predicting Postoperative Cardiac Events in Elderly Hip Fracture Patients

Purpose

Postoperative cardiac events (PCEs) are among the main adverse events after hip fracture surgery in the elderly. Existing cardiac risk assessment tools have some limitations and are not specifically designed for elderly patients undergoing hip fracture surgery. This study aimed to develop and internally validate a nomogram for prediction of PCEs in these patients.

Patients and Methods

We performed a retrospective study of 992 patients aged ≥65 years undergoing hip fracture surgery in our hospital from July 2015 to December 2021. Patients' demographics and clinical data were collected. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select predictors, and multivariate logistic regression was employed to construct a nomogram. Internal validation was performed by bootstrapping. The discriminatory ability of the model was determined by the area under the receiver operating characteristic curve (AUC). The calibration and clinical utility of the model were assessed. The predictive power and clinical benefit of the nomogram were compared with the Revised Cardiac Risk Index (RCRI).

Results

The nomogram was constructed including seven variables: general anesthesia, the American Society of Anesthesiologists (ASA) classification, history of heart failure, history of severe arrhythmia, history of coronary artery disease, preoperative platelet count, and serum creatinine. The nomogram had an excellent predictive ability (AUC = 0.875, 95% confidence interval [CI]: 0.828-0.918). Satisfactory calibration was shown by calibration plots and the Hosmer-Lemeshow goodness-of-fit test (P = 0.520). Clinical usefulness was confirmed by decision curve analysis and clinical impact curve. The predictive power and clinical utility of the nomogram were superior to RCRI.

Conclusion

We developed an easy-to-use nomogram for prediction of PCEs in elderly hip fracture patients. This prediction model could effectively identify patients at high risk of PCEs and may be useful for perioperative management optimization.

The elderly in the post-anesthesia care unit

It is increasingly conceivable that elderly patients will be treated in perioperative settings as the world's population shifts toward an older age distribution. They are more prone to a variety of unfavorable outcomes as a consequence of the physiological changes that accompany aging and the coexistence of multiple medical conditions. Postoperative complications in elderly patients are linked to a large increase in morbidity and mortality and the burden placed on the healthcare system. Our goal is to determine how elderly patients' recovery after anesthesia differs from that of younger patients. In addition, we will discuss the main postoperative complications experienced by elderly patients and the measures that are utilized to limit the risk of these complications developing.

Analysis of Cardiac Events and the Subsequent Impact for Geriatric Patients Undergoing Hip Fracture Surgeries

Perioperative complications, particularly cardiac events, compromised surgical outcomes for geriatric patients. This retrospective study intended to investigate the occurrence and subsequent impact of cardiac events for geriatric patients undergoing hip fracture surgeries. We collected 607 patients undergoing hip fracture surgeries from January 2017 to December 2022 that received transthoracic echocardiography (TTE) pre-operatively to screen for cardiac abnormalities. Except for demographic characteristics, the researchers recorded fracture type, surgical method, American Society of Anesthesiologists (ASA) class, anesthesia type, perioperative cardiac events, and in-hospital mortality. Statistical analysis was performed using SPSS 22.0 statistics software. Throughout the whole course of the study, 16 postoperative cardiac events occurred. The cardiac events included ten arrhythmias, three acute myocardial infarctions, two heart failures, and one sudden death. Notably, 12 of 16 patients with cardiac events presented with abnormal findings on TTE, except 15 of them had a history of cardiac disease. This study disclosed 93.7% of cardiac events developed in patients with a history of cardiovascular disease. Among patients that experienced cardiac events, 75% of patients had abnormal echocardiographic findings. Pre-operative transthoracic echocardiography deserves a recommendation for geriatric patients with histories of cardiac diseases undergoing hip fracture surgeries to detect the risk of developing cardiac events earlier.

Adaptive Risk Modeling: Improving Risk Assessment of Geriatric Hip Fracture Patients Throughout their Hospitalization

INTRODUCTION

The purpose of this study was twofold: 1. To assess how adaptive modeling, accounting for development of inpatient complications, affects the predictive capacity of the risk tool to predict inpatient mortality for a cohort of geriatric hip fracture patients. 2. To compare how risk triaging of secondary outcomes is affected by adaptive modeling. We hypothesize that adaptive modeling will improve the predictive capacity of the model and improve the ability to risk triage secondary outcomes.

METHODS

Between October 2014-August 2021, 2421 patients >55 years old treated for hip fracture obtained through low-energy mechanisms were analyzed for demographics, injury details and hospital quality measures. The baseline Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) tool for hip fractures (STTGMA_HIP) was calculated in the emergency department setting. A new mortality risk score (STTGMA_{HIP_ADPTV}) was created including inpatient complications. Each models' predictive ability was compared using DeLong's test. Patients were grouped into quartiles based on their respective STTGMA_{HIP_ADPTV} and comparative analyses were conducted.

RESULTS

AUROC comparison demonstrated STTGMA_{HIP_ADPTV} significantly improved the predictive capacity for inpatient mortality compared to STTGMA_HIP (p < 0.01). STTGMA_{HIP_ADPTV} correctly triaged 80% and 64% of high-risk patients with inpatient and 30-day mortality compared to 64% and 57% for STTGMA_HIP. STTGMA_{HIP_ADPTV} quartile stratification demonstrated that the highest risk cohort had the worst mortality outcomes and hospital quality measures. Patients whose risk classification changed from minimal risk using STTGMA_HIP to high risk using STTGMA_{HIP_ADPTV} experienced the highest rate of mortality, readmission, ICU admission, with longer lengths of stay and higher hospital costs.

DISCUSSION

Adaptive modeling accounting for inpatient complications improves the predictive capacity and risk triaging of the STTGMA_HIP tool. Real-time modulation of a patient's mortality risk profile can inform their requisite level of medical management to improve the quality and value of care as patients progress through their index hospitalization. STTGMA_{HIP_ADPTV} can better identify patients at risk for developing complications whose mortality and readmission risk profile increase significantly, allowing their new risk classification to inform higher levels of care. While this may increase length of stay and total costs, it may improve outcomes in both the short and long-term.

LEVEL OF EVIDENCE

III.

Association between radiotherapy and risk of death from cardiovascular diseases in lung and bronchus cancer

Background

Radiotherapy plays an important role in the treatment of lung cancer. However, radiation-related deaths from cardiovascular disease (CVD) are a concern in these patients, and few studies have examined CVD-related death associated with lung cancer. We aimed to evaluate the risk of CVD-related death after radiotherapy in patients with lung and bronchus cancer.

Methods

Data were extracted from the surveillance, epidemiology, and end results database. Propensity score matching (PSM) was applied to reduce possible bias between patients who received radiotherapy and those who did not. The Kaplan-Meier method was used to estimate cardiovascular-specific survival (CVSS), and the log-rank test was used to compare CVSS between the radiotherapy and no radiotherapy groups. Cox proportional hazards regression analysis was performed to estimate the hazard ratio (HR) of CVD-related death.

Results

A total of 225,570 patients with lung and bronchus cancer were included, and 201,282 patients remained after PSM. Radiotherapy was identified as an independent risk factor for CVSS among patients with lung and bronchus cancer before PSM (HR: 1.18, P < 0.001) and after PSM (HR: 1.18, P < 0.001). Patients treated with radiotherapy had a significantly worse CVSS than those who did not receive radiotherapy before PSM (25-year CVSS: 49.9 vs. 56.4%, P = 0.002) and after PSM (25-year CVSS: 48.4 vs. 56.7%, P < 0.001). Radiotherapy was associated with more deaths from heart disease before PSM (81.9 vs. 77.2%, P < 0.001) and after PSM (83.0 vs. 78.7%, P < 0.001).

Conclusion

Radiotherapy is associated with an increased risk of CVD-related death, especially death from heart disease, in patients with lung and bronchus cancer. More efforts are needed to monitor cardiovascular health after radiotherapy.